Authors:Lorena Chacón, Miguel Chen Chen Austin, Carmen Castaño First page: 405 Abstract: Buildings are among the main reasons for the deterioration of the world environment as they are responsible for a large percentage of CO2 emissions related to energy. For this reason, it is necessary to find solutions to this problem. This research project consists of constructing the metamodel of an urbanization located in Panama, Herrera province. The classification and systematization of its main elements, using the software DesignBuilder and SysML diagrams, were carried out for its subsequent implementation in an optimization analysis that seeks to approach the NZED standard. The main objectives of the optimization are reducing the energy consumption at the lowest possible price while maintaining or improving thermal comfort. In this study, it was possible to reduce electricity consumption to at least 60% of the original value and about 10% of the renewable energy generation capacity by implementing optimization techniques within the retrofit category related to the envelope of the buildings and the occupant’s behavior. Citation: Smart Cities PubDate: 2022-03-26 DOI: 10.3390/smartcities5020023 Issue No:Vol. 5, No. 2 (2022)
Authors:Srinivas Punna, Rupesh Mailugundla, Surender Reddy Salkuti First page: 433 Abstract: This research proposes an enhanced converter for a hybrid energy storage system (HESS) for a multi-input bidirectional DC–DC power converter (MIPC). When batteries are used for energy storage, their charge and discharge rates are low, putting the battery under current stress and shortening its life. Because of their increased power density, supercapacitors (SCs) can react quickly to abrupt fluctuations and solve this problem. SCs, on the other hand, cannot be utilized for storage since they cannot provide power for prolonged periods of time. Batteries and supercapacitors are employed together in HESSs because their opposing characteristics make them an ideal pair for energy storage. An MIPC is used to connect the HESS to the DC microgrid. The MIPC allows for decoupled battery and SC power regulation, as well as energy transfer across storage devices inside the system. A controller has been developed to regulate both HESS charging and discharging operations, making it a unified controller for DC microgrid applications. The proposed model predictive control (MPC) provided better DC grid voltage restoration to step change in PV generation and load demand over the traditional proportional integral (PI) control scheme. The MPC method minimizes current strains, extends battery life and enhances overall system performance in response to a step change in PV power and load demand as well as providing quicker DC grid voltage control. Simulation and experimental data for the proposed controller were created by varying PV generation and load demand, resulting in faster DC link voltage regulation. Citation: Smart Cities PubDate: 2022-03-28 DOI: 10.3390/smartcities5020024 Issue No:Vol. 5, No. 2 (2022)
Authors:Yamuna Kaluarachchi First page: 455 Abstract: Cities are investing in data-driven smart technologies to improve performance and efficiency and to generate a vast amount of data. Finding the opportunities to innovatively use this data help governments and authorities to forecast, respond, and plan for future scenarios. Access to real-time data and information can provide effective services that improve productivity, resulting in environmental, social, and economic benefits. It also assists in the decision-making process and provides opportunities for community engagement and participation by improving digital literacy and culture. This paper aims to review and analyze current practices of data-driven smart applications that contribute to the smooth functioning of urban city systems and the problems they face. The research methodology is qualitative: a systematic and extensive literature review carried out by PRISMA method. Data and information from different case studies carried out globally assisted in the inductive approach. Content analysis identified smart city indicators and related criteria in the case study examples. The study concluded that smart people, smart living, and smart governance methods that have come into practice at a later stage are as important as smart mobility, smart environments, and smart economy measures that were implemented early on, and cities are opening up to new, transparent participatory governance approaches where citizens play a key role. It also illustrates that the current new wave of smart cities with real time data are promoting citizen participation focusing on human, social capital as an essential component in future cities. Citation: Smart Cities PubDate: 2022-03-30 DOI: 10.3390/smartcities5020025 Issue No:Vol. 5, No. 2 (2022)
Authors:Maria Angela Pellegrino, Eftychia Roumelioti, Mauro D’Angelo, Rosella Gennari First page: 475 Abstract: Smart solutions are widespread and diversified. Smart cities and smart objects are example of smart solutions. Their design usually follows certain patterns so that they can detect events and react accordingly. As future citizens, children are expected to interact with them in their daily lives. It is thus crucial to provide children with the tools for understanding, creating, and possibly programming them—in short, designing them. This paper presents a literature review of workshops involving children in designing smart solutions. The review coded a total of 25 papers that met the inclusion criteria. The discussion draws a research agenda using the workshops organized by the authors, the Roobopoli workshops for smart cities and the SNaP workshops for smart objects, as reference. Whereas smart cities and smart objects are usually addressed separately, this paper binds and compares them in order to investigate what, in different settings, enables children to be part of the design of smart solutions. Citation: Smart Cities PubDate: 2022-04-02 DOI: 10.3390/smartcities5020026 Issue No:Vol. 5, No. 2 (2022)
Authors:Andrea Mariscotti First page: 496 Abstract: Electric vehicle (EV) charging represents a relevant electric load with a rapid evolution in terms of number, power rating and distortion, in particular, considering the connection to the low-voltage public grid: available short-circuit power may be limited and particularly susceptible loads may co-exist in the same grid portion. Standards can partially address the problem covering only the harmonic interval, but they necessitate significant extension and improvement in the supraharmonic range. In addition, EV chargers have been observed to violate in some scenarios the applicable harmonic limits, so that the mechanisms of emission and distortion should be better understood and evaluated, including phenomena of mutual influence between EV chargers and with pre-existing grid distortion. Although models can help simulate large-scale scenarios in terms of fundamental frequency phenomena, such as power flow, voltage fluctuation and imbalance, substantial and reliable information can come from experimental results, providing measured harmonic and supraharmonic emissions, accompanied by details on loads mix, grid characteristics and EV charger operating conditions. This work thus defines the applicable constraints in terms of limits and compatibility levels for public and light industrial low-voltage grids, discusses the available experimental results and datasets, analyzing the typical distortion behavior and providing indication of sources of information for further studies. Citation: Smart Cities PubDate: 2022-04-09 DOI: 10.3390/smartcities5020027 Issue No:Vol. 5, No. 2 (2022)
Authors:Matthieu Belarouci First page: 522 Abstract: This article is focusing on the dynamism of the Third Industrial Revolution (TIR) in the region Hauts-de-France between 2013 and 2018. Region Hauts-de-France has been a forerunner in setting up a proactive policy in favour of the TIR. It provides a relevant and suitable context for the identification of TIR activities. We assess the job dynamism of the TIR through the implementation of big data methods for the identification of the firms involved in the TIR activities and the collection of firm microlevel data. We provide evidence of the strong dynamism of the TIR activities in a context of weak regional dynamics. We show that the growth in employment arises mainly from renewable energies, positive energy buildings, circular economy and energy efficiency. Future researches are encouraged to investigate the quality of employment and to question the distinctive characteristics of the firms involved in TIR. Citation: Smart Cities PubDate: 2022-04-09 DOI: 10.3390/smartcities5020028 Issue No:Vol. 5, No. 2 (2022)
Authors:Zaheer Allam, Ayyoob Sharifi First page: 539 Abstract: Mobility is a subject of increasing importance in a time when cities have gained prominence, as they are home to over 56% of the world’s population and generate over 80% of global GDP. Urban planning principles have traditionally been developed to promote urban efficiency and enhance productivity. The emergence of ‘Smart Mobility’ has provided researchers and policy practitioners new ways to understand and plan cities. With rapid urbanization growth and the sustained mobility challenges faced in most global cities, this paper sets forth to understand and map the evolution of the concept of ‘Smart Urban Mobility’ through a bibliometric analysis and science mapping techniques using VOSviewer. In total, 6079 articles were retrieved from the Web of Science database over 5 decades, from 1968 to 2021, and divided into four sub-periods, namely 1968 to 2010, 2011 to 2015, 2016 to 2019, and 2020 to 2021. The paper provides a better understanding of the thematic focus and associated trends of smart mobility beyond technical issues related to Intelligent Transport Systems (ITS), where due to diverse dynamics, such as unprecedented growth and advancement in technologies, attention has extended to incorporating the impacts of the application of different technologies in urban mobility as well as associated fields. This paper further identifies major sources, authors, publications, and countries that have made more contributions to the development of this field. The findings of this study can help researchers better understand the evolution of the subject, and help policymakers make better-informed decisions on investable infrastructures for better mobility outcomes in urban regeneration pursuits and future cities. Citation: Smart Cities PubDate: 2022-04-18 DOI: 10.3390/smartcities5020029 Issue No:Vol. 5, No. 2 (2022)
Authors:Christos Anagnostopoulos, Tahani Aladwani, Ibrahim Alghamdi, Konstantinos Kolomvatsos First page: 562 Abstract: Internet of Things (IoT) applications have led to exploding contextual data for predictive analytics and exploration tasks. Consequently, computationally data-driven tasks at the network edge, such as machine learning models’ training and inference, have become more prevalent. Such tasks require data and resources to be executed at the network edge, while transferring data to Cloud servers negatively affects expected response times and quality of service (QoS). In this paper, we study certain computational offloading techniques in autonomous computing nodes (ANs) at the edge. ANs are distinguished by limited resources that are subject to a variety of constraints that can be violated when executing analytical tasks. In this context, we contribute a task-management mechanism based on approximate fuzzy inference over the popularity of tasks and the percentage of overlapping between the data required by a data-driven task and data available at each AN. Data-driven tasks’ popularity and data availability are fed into a novel two-stages Fuzzy Logic (FL) inference system that determines the probability of either executing tasks locally, offloading them to peer ANs or offloading to Cloud. We showcase that our mechanism efficiently derives such probability per each task, which consequently leads to efficient uncertainty management and optimal actions compared to benchmark models. Citation: Smart Cities PubDate: 2022-04-24 DOI: 10.3390/smartcities5020030 Issue No:Vol. 5, No. 2 (2022)
Authors:Da-Yin Liao First page: 583 Abstract: Modern life is making people infertile. Giving birth later in life is wreaking havoc on our fertility and threatening human survival. Smart cities intend to optimize the quality of life of their citizens by utilizing technology for smarter living. This research first identifies the requirements and business opportunities of using advanced technology for smarter fertility preservation and assisted reproduction in smart cities. A federated blockchain approach is proposed for the alliance of integrated commercial egg banks (ICEBs). In particular, we designed a membership fee rebate (MFR) mechanism that offers incentives for blockchain creations in the egg banking alliance. We formulated the MFR problem into a leader–followers Stackelberg game whose objectives are (1) to maximize the benefits of forming the alliance (the leader) and (2) to maximize the benefits in each ICEB (the follower). We developed an iterative scheme that utilizes mathematical programming techniques to solve the two-level, Stackelberg game problem. With a given set of parameters of the alliance and membership fee function, and the average number of blocks generated for an oocyte, the iterative scheme achieves the optimal solution for the MFR rate per block created . A numerical example demonstrates the feasibility and applicability of the proposed iterative scheme. Numerical results show that it achieves good solutions in adding a small to medium-sized new ICEB to the existing alliance. The proposed federated approach lays the foundation for developing a blockchain-based egg banking platform. Citation: Smart Cities PubDate: 2022-05-03 DOI: 10.3390/smartcities5020031 Issue No:Vol. 5, No. 2 (2022)
Authors:Madis Talmar, A. Georges L. Romme, Rianne Valkenburg First page: 608 Abstract: To address major threats to the sustainability and quality of life in urban settings, many municipalities have started exploring routes toward smarter cities to, for example, lower their energy consumption and carbon footprint. These explorations, in the form of living labs or other pilot projects, often suffer from major problems in scaling up the initial try-outs. In this study, we identify the mechanisms that facilitate the diffusion of smart city solutions, which are developed with public funds but typically lack dedicated resources to spur the diffusion of these solutions within the same municipality as well as toward other municipalities. We introduce the construct of embedded replication potential, defined as the capacity of an original project to be either scaled up locally or replicated elsewhere. Subsequently, empirical findings from a study of smart lighting projects in several municipalities in northwestern Europe serve to develop a checklist-based tool for assessing the embedded replication potential of an initial project. This tool can also be used to assess the replication potential of other smart city projects. Citation: Smart Cities PubDate: 2022-05-03 DOI: 10.3390/smartcities5020032 Issue No:Vol. 5, No. 2 (2022)
Authors:Nouf Aljadani, Tahani Gazdar First page: 633 Abstract: The Smart Grid (SG) aims to cope with the problems of the traditional grid, using renewable power generators. Similarly, SG benefits from the deployment of wireless sensor networks (WSNs) to enhance its aspects by monitoring the physical behavior of the power generators. However, new threats and attacks may arise due to the open nature and large scale of SG where WSNs are deployed. In this paper, we propose a new security architecture for WSNs in SG based on public key infrastructure (PKI). The key idea of the proposed architecture is to distribute the role of the certification authority (CA) among a set of sensor nodes to ensure the availability and scalability of the CA services. To elect this set of sensor nodes, we propose a novel lightweight clustering algorithm for WSNs that relies on the trust metrics of the nodes and their energy levels. The proposed architecture provides many security services such as authentication and confidentiality and mitigates many types of attacks such as Sybil and eavesdropping. Extensive simulations have been conducted using network simulator OMNET++ and Castalia framework to investigate the performance of the clustering algorithm. The results show that almost 100% of the sensors are members of clusters, and even in the presence of malicious nodes, the number of cluster heads remains static which reflects the robustness of the proposed architecture. Citation: Smart Cities PubDate: 2022-05-10 DOI: 10.3390/smartcities5020033 Issue No:Vol. 5, No. 2 (2022)
Authors:Ming-Shiu Sung, Shen-Guan Shih, Yeng-Horng Perng First page: 22 Abstract: Definition and imagination of an ideal city can be traced back to the origin of garden city in UK about 100 years ago. Since then, many different names and topics have been proposed and smart city is the one most recently proposed. Starting from 2000, more and more countries have developed various demonstration projects for the promotion of smart city in order to provide total solution for the promotion of sustainable development and social welfare. In fact, some of them have been successfully carried out. Some researchers in Taiwan argue that the current mechanism by which government subsidies are allocated for smart city demonstration projects warrants improvement. A comprehensive literature review determined that the development potential of smart cities should be prioritized in site selection for such demonstration projects. This study developed an evaluation framework on the basis of multi-criteria evaluation methods to enable the identification of suitable smart city demonstration sites. Evaluation criteria were first identified through the Delphi method. Next, the weights of each criterion were derived through the analytic hierarchy process. Furthermore, the capability of the proposed evaluation model was determined through simulation testing. Four demonstration sites are simulated, they are: Taipower Smart Community, Yinlin Technology University campus, Taichung Creative Cultural Park, and Asian New Bay Area in Kaohsiung, It is expected that the research findings in this thesis can be helpful to the future decision for the demo site selection of smart city. Citation: Smart Cities PubDate: 2022-01-04 DOI: 10.3390/smartcities5010002 Issue No:Vol. 5, No. 1 (2022)
Authors:Hady H. Fayek, Omar H. Abdalla First page: 34 Abstract: Countries around the world are looking forward to fully sustainable energy by the middle of the century to meet Paris climate agreement goals. This paper presents a novel algorithm to optimally operate the Egyptian grid with maximum renewable power generation, minimum voltage deviation and minimum power losses. The optimal operation is performed using Corona Virus Algorithm (CVO). The proposed CVO is compared to the Teaching and Learning-Based Optimization (TLBO) algorithm in terms of voltage deviation, power losses and share of renewable energies. The real demand, solar irradiance and wind speed in typical winter and summer days are considered. The 2020 Egyptian grid model is developed, simulated, and optimized using DIgSILENT software application. The results have proved the effectiveness of the proposed CVO, compared to the TLBO, to operate the grid with the highest share possible of renewables. The paper is a step forward to achieve Egyptian government targets to reach 20% and 42% penetration level of renewable energies by 2022 and 2035, respectively. Citation: Smart Cities PubDate: 2022-01-05 DOI: 10.3390/smartcities5010003 Issue No:Vol. 5, No. 1 (2022)
Authors:Silvia Croce, Stefano Tondini First page: 54 Abstract: In the current scenario of massive urbanization and global climate change, an intelligent monitoring of the environmental variables is becoming fundamental to ensure good living conditions in cities. Indeed, the acquisition of data with high spatiotemporal resolution can enable the assessment of environmental vulnerabilities in urban areas towards the definition of responsive adaptation and mitigation strategies. In this context, the current work presents a two-fold approach based on low-cost cloud-connected sensors for (i) fixed and (ii) mobile monitoring of several environmental parameters. This paper, which focuses on the measurement aspects of the urban micro-climate, describes in detail the hardware and software components of both approaches, and how to exploit them for setting up a field campaign. The methods were tested in the city of Bolzano (Italy), demonstrating their suitability for identifying the spatial variability of the microclimate in relation to the urban morphology, and for highlighting the presence of the urban heat island and estimating its intensity. Citation: Smart Cities PubDate: 2022-01-08 DOI: 10.3390/smartcities5010004 Issue No:Vol. 5, No. 1 (2022)
Authors:Seng Boon Lim, Tan Yigitcanlar First page: 71 Abstract: Participatory governance is widely viewed as an essential element of realizing planned smart cities. Nonetheless, the implementation of e-participation platforms, such as the websites and mobile applications of civic authorities, often offer ambiguous information on how public voices may influence e-decision-making. This study aims to examine the status of participatory governance from the angle of e-participation platforms and from the broader scope of linking e-platforms to a smart city blueprint. In order to achieve this aim, the study focuses on shedding light on the e-governance space given to smart city realization in a developing country context—i.e., Malaysia. The Putrajaya and Petaling Jaya smart cities of Malaysia were selected as the testbeds of the study, which used the multiple case study methodology and multiple data collection designs. The analyses were done through the qualitative observations and quantitative descriptive statistics. The results revealed that both of the investigated smart city cases remained limited in their provision of e-decision-making space. The inefficiency of implementing planned initiatives to link the city blueprints to e-platforms was also evidenced. The study evidenced that the political culture of e-decision-making is undersized in Malaysia, which hinders the achievement of e-democracy in the smart cities’ development. This study has contributed a case report on a developing country’s smart cities, covering the participatory issues from the angle of e-participation and e-platforms. Citation: Smart Cities PubDate: 2022-01-14 DOI: 10.3390/smartcities5010005 Issue No:Vol. 5, No. 1 (2022)
Authors:Aristotelis Ntafalias, Giorgos Papadopoulos, Panagiotis Papadopoulos, Aapo Huovila First page: 90 Abstract: In recent years, the world’s population living in cities has been rapidly increasing. Cities are transforming their infrastructure in a smarter and more efficient way so that sustainable development forms part of their long-term strategy. However, this transformation does not always result in expected benefits due to a variety of factors such as an absence of social acceptance, a lack of holistic design and the development of unilateral interventions. An analysis of the scientific literature related to the evaluation of the impact of smart city actions revealed a gap in the holistic methods for their assessment. To this end, an accurate evaluation of implemented smart solutions focusing on the energy domain is necessary in order to assess the expected and realized impact of each solution. This paper proposes a seven-step methodology for assessing the impact of smart city interventions and presents a use case for the city of Espoo. A number of major findings were the outcome of our research and development work, such as the need for a thorough analysis of the long-term vision of the city, a combined top-down and bottom-up approach and the ongoing cooperation between all stakeholders involved in urban planning and transformation, in which necessary Key Performance Indicators (KPIs) are defined. Citation: Smart Cities PubDate: 2022-01-21 DOI: 10.3390/smartcities5010006 Issue No:Vol. 5, No. 1 (2022)
Authors:Eiko Wataya, Rajib Shaw First page: 108 Abstract: For a smart city, soft or non-physical assets share an important capital component with many impacts in different contexts. They enable a city to deliver and mainstream a people-centered policy in addition to the benefits provided by traditional, hard infrastructure. Soft assets can involve social and human capital, knowledge, participation, and innovative approaches that drive value in the city. However, it is always a challenge for city policy makers to identify and strengthen these soft assets using a systemic approach due to their inherent characteristics. This paper argues that soft assets should be strategically integrated into the development process of smart and resilient cities. Therefore, exploring various approaches to prioritize soft asset consideration would provide helpful guidelines to city policy makers for municipal value creation, and identify where the greatest needs for soft or intangible assets lie. This paper examines how to identify and decide which soft assets should take priority in smart and resilient cities. The findings can assist policy makers in their consideration of an optimal mix and balance of soft assets required in the city to improve living structures for a people-centered approach. Citation: Smart Cities PubDate: 2022-01-26 DOI: 10.3390/smartcities5010007 Issue No:Vol. 5, No. 1 (2022)
Authors:Carsten Frey, Philipp Hertweck, Lucas Richter, Oliver Warweg First page: 133 Abstract: With the vision “Innovation by experiment” the Bauhaus.MobilityLab started in July 2020 as a living lab in the district Brühl of the city Erfurt, Thuringia, Germany. As a unique project, it is coupling the sectors mobility, logistics and energy into a unified living lab. It allows to design, develop and evaluate innovative services to increase the quality of life in the city. Bauhaus.MobilityLab offers access to live smart city data of different domains and provides a set of powerful artificial intelligence (AI) algorithms for data processing, analytics and forecasting. In contrast to existing platforms, its uniqueness is the available and integrated living lab. It allows directly rolling out new smart city services and to evaluate the impact in the real world. This paper describes the implementation of the technical platform supporting the Bauhaus.MobilityLab, realized according to the DIN SPEC 91357 as an open urban platform. It focuses on data sharing based on the concepts of the International Data Spaces and the integration of AI algorithms. The concepts are presented based on examples in the energy domain. Citation: Smart Cities PubDate: 2022-02-07 DOI: 10.3390/smartcities5010009 Issue No:Vol. 5, No. 1 (2022)
Authors:Carles Ferrer-Ortiz, Oriol Marquet, Laia Mojica, Guillem Vich Vich First page: 146 Abstract: Many academics, urban planners and policymakers subscribe to the benefits of implementing the concept of the 15-Minute City (FMC) in metropolises across the globe. Despite the interest raised by the concept, and other variants of chrono-urbanism, to date, only a few studies have evaluated cities from the FMC perspective. Most studies on the subject also lack a proper well-defined methodology that can properly assess FMC conditions. In this context, this study contributes to the development of an appropriate FMC-measuring method by using network analysis for services and activities in the City of Barcelona (Catalonia, northeastern Spain). By using network analyst and basing our analysis on cadastral parcels, this study is able to detail the overall accessibility conditions of the city and its urban social functions based on the FMC perspective. The resulting spatial synthetic index is enhanced with the creation of partial indexes measuring the impact of education, provisioning, entertainment, public and non-motorized transport, and care facilities. The results show that most residents of this dense and compact city live in areas with proximity to services, that can clearly be labeled as FMC, although there are some shortfalls in peripheral areas. Results validate the FMC methodology as a viable method to highlight spatial inequalities at the microscale level, a valuable tool for the development of effective planning policies. Citation: Smart Cities PubDate: 2022-02-11 DOI: 10.3390/smartcities5010010 Issue No:Vol. 5, No. 1 (2022)
Authors:Somdip Dey, Suman Saha, Amit Kumar Singh, Klaus McDonald-Maier First page: 162 Abstract: Food waste is an important social and environmental issue that the current society faces, where one third of the total food produced is wasted or lost every year while more than 820 million people around the world do not have access to adequate food. However, as we move towards a decentralized Web 3.0 enabled smart city, we can utilize cutting edge technologies such as blockchain, artificial intelligence, cloud computing and many more to reduce food waste in different phases of the supply chain. In this paper, we propose SmartNoshWaste—a blockchain based multi-layered framework utilizing cloud computing, QR code and reinforcement learning to reduce food waste. We also evaluate SmartNoshWaste on real world food data collected from the nosh app to show the efficacy of the proposed framework and we are able to reduce food waste by 9.46% in comparison to the originally collected food data based on the experimental evaluation. Citation: Smart Cities PubDate: 2022-02-14 DOI: 10.3390/smartcities5010011 Issue No:Vol. 5, No. 1 (2022)
Authors:Preetham Goli, Kiran Jasthi, Srinivasa Rao Gampa, Debapriya Das, Wajiha Shireen, Pierluigi Siano, Josep M. Guerrero First page: 177 Abstract: In this study, a two-stage methodology based on the energy savings gained by optimal network reconductoring was developed for the sizing and allocation of electric vehicle (EV) charging load at the residential locations in urban distribution systems. During the first stage, the Flower Pollination Algorithm (FPA) was applied to minimize the annual energy losses of the radial distribution system through optimum network reconductoring. A multi-objective function was formulated to minimize investment, peak loss, and annual energy loss costs at different load factors. The results obtained with the flower pollination algorithm were compared with the particle swarm optimization algorithm. In the second stage, a simple heuristic procedure was developed for the sizing and allocation of EV charging load at every node of the distribution system utilizing part of the annual energy savings obtained by optimal network reconductoring. The number of electric cars, electric bikes, and electric scooters that can be charged at every node was computed while maintaining the voltage and branch current constraints. The simulation results were demonstrated on 123 bus and 51 bus radial distribution networks to validate the effectiveness of the proposed methodology. Citation: Smart Cities PubDate: 2022-02-16 DOI: 10.3390/smartcities5010012 Issue No:Vol. 5, No. 1 (2022)
Authors:Giuseppe Musolino, Corrado Rindone, Antonino Vitetta First page: 206 Abstract: Mobility as a Service (MaaS) is the new approach in transportation systems that allows users to use different transport services as a single option, by using digital platforms and with integrated design. In MaaS many actors can be identified: MaaS operators, MaaS companies, MaaS users, citizens, system manager/planner. In order to be able to design the system in an integrated way, it is necessary to identify comprehensive methodologies that make it possible to reach sustainability targets in a context where the decisions to be taken are shared between several operators and affect users and citizens. In this paper, the methods to be adopted for the design of an integrated transport service system have been studied. The main aim of this paper concerns the specification of transport system models for estimating the effects of decision-makers’ actions on MaaS. The consolidated design methodologies of transport networks have been extended in the context of the MaaS. The paper reports a methodology that can be used and describes the main models to be used, which derive from consolidated specifications in the field of transport systems engineering. The methodologies have to be integrated into Intelligent and Communication Technology systems to build the Intelligent Transport System in the MaaS environment. Citation: Smart Cities PubDate: 2022-02-17 DOI: 10.3390/smartcities5010013 Issue No:Vol. 5, No. 1 (2022)
Authors:Jan Mrkos, Robert Basmadjian First page: 223 Abstract: As electric vehicles (EVs) are slowly becoming a common occurrence on roads, commercial EV charging is becoming a standard commercial service. With this development, charging station operators are looking for ways to make their charging services more profitable or allocate the available resources optimally. Dynamic pricing is a proven technique to increase revenue in markets with heterogeneous demand. This paper proposes a Markov Decision Process (MDP)-based approach to revenue- or utilization- maximizing dynamic pricing for charging station operators. We implement the method using a Monte Carlo Tree Search (MCTS) algorithm and evaluate it in simulation using a range of problem instances based on a real-world dataset of EV charging sessions. We show that our approach provides near-optimal pricing decisions in milliseconds for large-scale problems, significantly increasing revenue or utilization over the flat-rate baseline under a range of parameters. Citation: Smart Cities PubDate: 2022-02-27 DOI: 10.3390/smartcities5010014 Issue No:Vol. 5, No. 1 (2022)
Authors:Neil Grigg First page: 241 Abstract: Smart and integrated urban water systems have important roles in advancing smart cities, but their contributions go much further by supplying needed public services and connecting other sectors to meet sustainability goals. Achieving integration and gaining access to financing are obstacles to implementing smart water systems and both are implicit in the economic framework of smart cities. Problems in financing the start-up of smart water systems are reported often. The local and diverse nature of water systems is another barrier because an approach that works in one place may not work in another with different conditions. The paper identifies the challenges posed by the economic framework and provides examples from four cities with diverse characteristics. It outlines pathways to advance implementation of smart water systems by improving control strategies, advancing instrumentation and control technologies, and most of all, to help transform cities by raising customer awareness and trust through reliable and useful water information. Citation: Smart Cities PubDate: 2022-03-02 DOI: 10.3390/smartcities5010015 Issue No:Vol. 5, No. 1 (2022)
Authors:Tiago Fontes, Miguel Arantes, Paulo V. Figueiredo, Paulo Novais First page: 251 Abstract: Urban mobility is a massive issue in the current century, being widely promoted the need of adopting sustainable solutions regarding transportation within large urban centres. The evolution of technologies has democratised smart cities to better plan and manage their mobility solutions, without compromising the social, economic, and environmental impacts. Pursuing the carbon neutrality and the climate agreement goals, soft mobility is one of the most popular emerging methods to provide greener alternatives regarding mobility. Among these transportation modes are the bicycle, which has been widely used in several public systems across the world, one of them being in Lisbon. This article provides a decision support system for bike-sharing docking stations for three council parishes of the city, namely, Parque das Nações, Marvila, and Beato. Taking advantage of clustering methods and GSM data from a telecommunication operator, this study pretends to highlight a novel approach to identify soft mobility hotspots, in specific bike-sharing docking stations, for suited mobility management systems in Lisbon’s city centre. Citation: Smart Cities PubDate: 2022-03-03 DOI: 10.3390/smartcities5010016 Issue No:Vol. 5, No. 1 (2022)
Authors:Stella Manika, Konstantinos Karalidis, Aspa Gospodini First page: 276 Abstract: The economic activities of each city greatly shape and predict their development as well as make them more competitive both locally and globally. In the last two decades, as part of the international economic crisis, Greece has been at the center of changes that have resulted in the closure of thousands of businesses. This significantly affected Greek cities by changing their economic profile and robustness via the spatial distribution of their economic activities. Economic geography, as a sector that examines the geographical distribution of economic activities, is an important methodological base for analysing business locations and urban spatial processes. This paper aims to analyse, through a combination of economic geography theories and spatial analysis methods, the spatial patterns of economic activities and to identify urban areas that are resilient in difficult times of crisis. Thus cities that have the ability, via the proposed analysis/methodological framework, to control and evaluate their economic profile and prospects, can be transformed into smart cities by adopting ad hoc urban renaissance and resilient policies. Citation: Smart Cities PubDate: 2022-03-04 DOI: 10.3390/smartcities5010017 Issue No:Vol. 5, No. 1 (2022)
Authors:Rossella Roversi, Andrea Boeri, Serena Pagliula, Giulia Turci First page: 294 Abstract: Cities are responsible for 65% of energy consumption and for the 70% of CO2 emissions. Incisive actions are fundamental to bring cities towards climate neutrality by 2050 working by and for the citizens. For this reason, the “100 climate-neutral cities Mission” anticipates the target of climate neutrality by 2030. The objective of this paper, developed within the H2020 GRETA project—GReen Energy Transition Actions (GA101022317), is to investigate energy communities and climate city contracts as key interventions to face the ambitious goal of implementing citizens-centered and climate-neutral cities. To achieve this objective, this paper is structured as follows: (1) an updated framework of European and Italian legislation concerning energy communities; (2) an overview of climate city contracts’ definition and key aspects; (3) a selection and analysis of energy communities’ case studies; (4) a description of already developed pilot climate city contracts. The results provide more advanced knowledge about EU energy communities strategies and about the possible contractual agreements that can guarantee commitment between parties and can allow the active participation of citizens in the energy system. The lessons learned contribute to the application in the GRETA Italian case study, whose first participation activities are also described in the paper. Citation: Smart Cities PubDate: 2022-03-06 DOI: 10.3390/smartcities5010018 Issue No:Vol. 5, No. 1 (2022)
Authors:Nasim Nezamoddini, Amirhosein Gholami First page: 318 Abstract: The world is moving toward a new connected world in which millions of intelligent processing devices communicate with each other to provide services in transportation, telecommunication, and power grids in the future’s smart cities. Distributed computing is considered one of the efficient platforms for processing and management of massive amounts of data collected by smart devices. This can be implemented by utilizing multi-agent systems (MASs) with multiple autonomous computational entities by memory and computation capabilities and the possibility of message-passing between them. These systems provide a dynamic and self-adaptive platform for managing distributed large-scale systems, such as the Internet-of-Things (IoTs). Despite, the potential applicability of MASs in smart cities, very few practical systems have been deployed using agent-oriented systems. This research surveys the existing techniques presented in the literature that can be utilized for implementing adaptive multi-agent networks in smart cities. The related literature is categorized based on the steps of designing and controlling these adaptive systems. These steps cover the techniques required to define, monitor, plan, and evaluate the performance of an autonomous MAS. At the end, the challenges and barriers for the utilization of these systems in current smart cities, and insights and directions for future research in this domain, are presented. Citation: Smart Cities PubDate: 2022-03-09 DOI: 10.3390/smartcities5010019 Issue No:Vol. 5, No. 1 (2022)
Authors:Tahani Gazdar, Ohoud Alboqomi, Asmaa Munshi First page: 348 Abstract: Vehicular Ad hoc Networks (VANETs) are one of the pillars of the Internet of Vehicles, they provide plenty of applications ranging from safety to entertainment. Safety applications largely depend on reliable and authentic traffic-related data. However, ensuring the data reliability and authenticity is facing many challenges due mainly to the scalability of VANETs such as the high speed, the long roads, and the open nature of VANETs. This paper addresses these challenges by proposing a decentralized Blockchain-based trust management framework (BC-TMF) aiming to compute trust metrics for vehicles. These trust metrics rely on the authenticity of the messages. Each vehicle assesses the authenticity of the received messages in real-time, calculates a local trust metric for the originator of such messages, then shares it with a miner. Periodically each miner aggregates the received trust metrics into global trust metrics, then packs them in a block. To investigate the efficiency and consistency of the proposed framework, extensive simulations are conducted. The obtained results show that the proposed BC-TMF has an excellent capability in computing accurate trust metrics for vehicles. Besides, it outperforms the existing ones in terms of the accuracy of computed trust metrics, particularly for malicious vehicles. Citation: Smart Cities PubDate: 2022-03-12 DOI: 10.3390/smartcities5010020 Issue No:Vol. 5, No. 1 (2022)
Authors:Anu Singh, Suraj Kumar Singh, Gowhar Meraj, Shruti Kanga, Majid Farooq, Nikola Kranjčić, Bojan Đurin, Sudhanshu First page: 364 Abstract: Property tax is the primary source of revenue for municipal bodies. In India, municipal corporations are facing issues in property tax collection, and the primary reason for it is a lack of count of assessed properties under its jurisdiction. Also, the storage of information on the properties is mainly based on manual efforts, which leads to data redundancy and failure to appropriate tax collection. Geographical Information Systems (GIS) consists of technology, personnel, and resources to create, maintain, visualize, search, and share geospatial data and services. The study has been carried out in the Hauz Khas Ward, South Delhi Municipal Corporation, Delhi. This paper aims to develop a spatial database for property tax management. It includes capturing the building footprint, road, land use such as parks, paved area, drains, and demarcation of boundaries such as locality slums, based on a regular grid net with a cell size of 250 m by 250 m. The generated geospatial database has been finally used to evaluate parameters for property tax calculation. Moreover, this spatial database can be organized as different models for any web-based application for municipal services. This study provides a working example of a GIS-based property tax collection solution for whole of India and other South-Asian countries. Citation: Smart Cities PubDate: 2022-03-16 DOI: 10.3390/smartcities5010021 Issue No:Vol. 5, No. 1 (2022)
Authors:Hafiz Usman Ahmed, Ying Huang, Pan Lu, Raj Bridgelall First page: 382 Abstract: The scientific advancements in the vehicle and infrastructure automation industry are progressively improving nowadays to provide benefits for the end-users in terms of traffic congestion reduction, safety enhancements, stress-free travels, fuel cost savings, and smart parking, etc. The advances in connected, autonomous, and connected autonomous vehicles (CV, AV, and CAV) depend on the continuous technology developments in the advanced driving assistance systems (ADAS). A clear view of the technology developments related to the AVs will give the users insights on the evolution of the technology and predict future research needs. In this paper, firstly, a review is performed on the available ADAS technologies, their functions, and the expected benefits in the context of CVs, AVs, and CAVs such as the sensors deployed on the partial or fully automated vehicles (Radar, LiDAR, etc.), the communication systems for vehicle-to-vehicle and vehicle-to-infrastructure networking, and the adaptive and cooperative adaptive cruise control technology (ACC/CACC). Secondly, for any technologies to be applied in practical AVs related applications, this study also includes a detailed review in the state/federal guidance, legislation, and regulations toward AVs related applications. Last but not least, the impacts of CVs, AVs, and CAVs on traffic are also reviewed to evaluate the potential benefits as the AV related technologies penetrating in the market. Based on the extensive reviews in this paper, the future related research gaps in technology development and impact analysis are also discussed. Citation: Smart Cities PubDate: 2022-03-17 DOI: 10.3390/smartcities5010022 Issue No:Vol. 5, No. 1 (2022)
Authors:Maaria Nuutinen, Eija Kaasinen, Jaana Hyvärinen, Airi Mölsä, Sanni Siltanen First page: 1 Abstract: Buildings shape cities as those cities grow from and nurture people living and working within the built environment. Thus, the conceptualization of smart building should be brought closer to the smart city initiatives that particularly target ensuring and enhancing the sustainability and quality of urban life. In this paper, we propose that a smart building should be interlinked with a smart city surrounding it; it should provide good experiences to its various occupants and it should be in an ongoing state of evolving as an ecosystem, wherein different stakeholders can join to co-produce, co-provide and co-consume services. Smart buildings require a versatile set of smart services based on digital solutions, solutions in the built environment and human activities. We conducted a multiphase collaborative study on new service opportunities guided by a Design Thinking approach. The approach brought people, technology, and business perspectives together and resulted in key service opportunities that have the potential to make the buildings smart and provide enjoyable experience to the occupants who support their living and working activities in smart cities. This paper provides the resulting practical implications as well as proposes future avenues for research. Citation: Smart Cities PubDate: 2021-12-24 DOI: 10.3390/smartcities5010001 Issue No:Vol. 5, No. 1 (2021)
Authors:Konstantinos Tsiamasiotis, Emmanouil Chaniotakis, Moeid Qurashi, Hai Jiang, Constantinos Antoniou First page: 1243 Abstract: Nowadays, the growth of traffic congestion and emissions has led to the emergence of an innovative and sustainable transportation service, called dynamic vanpooling. The main aim of this study is to identify factors affecting the travel behavior of passengers due to the introduction of dynamic vanpooling in the transportation system. A web-based mode choice survey was designed and implemented for this scope. The stated-preference experiments offered respondents binary hypothetical scenarios with an ordered choice between dynamic vanpool and the conventional modes of transport, private car and public transportation. In-vehicle travel time, total travel cost and walking and waiting time or searching time for parking varies across the choice scenarios. An ordered probit model, a multinomial logit model and two binary logit models were specified. The model estimation results indicate that respondents who are aged between 26 and 35 years old, commute with PT or are members of bike-sharing services were significantly more likely to choose dynamic vanpool or PT than private car. Moreover, respondents who are worried about climate change and are willing to spend more for environmentally friendly products are significantly more likely to use dynamic vanpool in comparison with private cars. Finally, to indicate the model estimation results for dynamic vanpool, the value of in-vehicle travel time is found to be 12.2€ per hour (13.4€ for Munich subsample). Citation: Smart Cities PubDate: 2021-09-29 DOI: 10.3390/smartcities4040066 Issue No:Vol. 4, No. 4 (2021)
Authors:Pedro Henrique Ferreira Portugal, Jéssica Freire Moreira, Marcelo dos Santos Póvoas, Carlos Alberto Figueiredo da Silva, André Luis Azevedo Guedes First page: 1259 Abstract: Smart cities are a natural evolution of the concept of sustainable cities. These cities can be analyzed by social, economic, environmental, and technological biases. For this work, we chose the social and economic vision, with a special focus on the poorest and most vulnerable territories of Brazilian cities. These territories in Brazil are called slums, places of poverty but with opportunities for the development of the creative economy with its own brand. Seen by many in a simplistic way, summed up to be geographic spaces of drug circulation dominated by trafficking, Brazilian favelas have been consolidating themselves as a storehouse of innovative minds, a creative territory with multiple and complex cultures. These places today are capable of producing a positive image with potential for market exploitation. Therefore, the objective was to draw a relationship between the creative economy, branding and favelas, considering the concept of smart cities that include products and services from the slums. The present study shows the results of a survey and a bibliographic analysis based on the methodology Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and with parameters that took into account the favela, branding and the creative economy. Thus, we expect that it will be possible to point out ways to accelerate entrepreneurial actions and foster the development of these locations. Citation: Smart Cities PubDate: 2021-09-29 DOI: 10.3390/smartcities4040067 Issue No:Vol. 4, No. 4 (2021)
Authors:Isam Shahrour, Xiongyao Xie First page: 1276 Abstract: This paper presents and discusses the role of the Internet of Things (IoT) and crowdsourcing in constructing smart cities. The literature review shows an important and increasing concern of the scientific community for these three issues and their association as support for urban development. Based on an extensive literature review, the paper first presents the smart city concept, emphasizing smart city architecture and the role of data in smart city solutions. The second part presents the Internet of Things, focusing on IoT technology, the use of IoT in smart city applications, and security. Finally, the paper presents crowdsourcing with particular attention to mobile crowdsourcing and its role in smart cities. The paper shows that IoT and crowdsourcing have a crucial role in two fundamental layers of smart city applications, namely, the data collection and services layers. Since these two layers ensure the connection between the physical and digital worlds, they constitute the central pillars of smart city projects. The literature review also shows that the smart city development still requires stronger cooperation between the smart city technology-centered research, mainly based on the IoT, and the smart city citizens-centered research, mainly based on crowdsourcing. This cooperation could beneficiate in recent developments in the field of crowdsensing that combines IoT and crowdsourcing. Citation: Smart Cities PubDate: 2021-10-01 DOI: 10.3390/smartcities4040068 Issue No:Vol. 4, No. 4 (2021)
Authors:Neda Mashhadi, Isam Shahrour, Nivine Attoue, Jamal El Khattabi, Ammar Aljer First page: 1293 Abstract: This paper presents an investigation of the capacity of machine learning methods (ML) to localize leakage in water distribution systems (WDS). This issue is critical because water leakage causes economic losses, damages to the surrounding infrastructures, and soil contamination. Progress in real-time monitoring of WDS and ML has created new opportunities to develop data-based methods for water leak localization. However, the managers of WDS need recommendations for the selection of the appropriate ML methods as well their practical use for leakage localization. This paper contributes to this issue through an investigation of the capacity of ML methods to localize leakage in WDS. The campus of Lille University was used as support for this research. The paper is presented as follows: First, flow and pressure data were determined using EPANET software; then, the generated data were used to investigate the capacity of six ML methods to localize water leakage. Finally, the results of the investigations were used for leakage localization from offline water flow data. The results showed excellent performance for leakage localization by the artificial neural network, logistic regression, and random forest, but there were low performances for the unsupervised methods because of overlapping clusters. Citation: Smart Cities PubDate: 2021-10-01 DOI: 10.3390/smartcities4040069 Issue No:Vol. 4, No. 4 (2021)
Authors:Daniel Reichenpfader, Sten Hanke First page: 1316 Abstract: Insomnia is the most common sleep disorder worldwide. Its effects generate economic costs in the millions but could be effectively reduced using digitally provisioned cognitive behavioural therapy. However, traditional acquisition and maintenance of the necessary technical infrastructure requires high financial and personnel expenses. Sleep analysis is still mostly done in artificial settings in clinical environments. Nevertheless, innovative IT infrastructure, such as mHealth and cloud service solutions for home monitoring, are available and allow context-aware service provision following the Smart Cities paradigm. This paper aims to conceptualise a digital, cloud-based platform with context-aware data storage that supports diagnosis and therapy of non-organic insomnia. In a first step, requirements needed for a remote diagnosis, therapy, and monitoring system are identified. Then, the software architecture is drafted based on the above mentioned requirements. Lastly, an implementation concept of the software architecture is proposed through selecting and combining eleven cloud computing services. This paper shows how treatment and diagnosis of a common medical issue could be supported effectively and cost-efficiently by utilising state-of-the-art technology. The paper demonstrates the relevance of context-aware data collection and disease understanding as well as the requirements regarding health service provision in a Smart Cities context. In contrast to existing systems, we provide a cloud-based and requirement-driven reference architecture. The applied methodology can be used for the development, design, and evaluation of other remote and context-aware diagnosis and therapy systems. Considerations of additional aspects regarding cost, methods for data analytics as well as general data security and safety are discussed. Citation: Smart Cities PubDate: 2021-10-12 DOI: 10.3390/smartcities4040070 Issue No:Vol. 4, No. 4 (2021)
Authors:Eleonora Sista, Pietro De De Giovanni First page: 1337 Abstract: A large number of smart city logistics projects fail to scale up, remaining a local experimental exercise. This lack of scalability is, in fact, commonly recognized as a major problem. This study aims to determine the key success factors related to the scalability of smart city logistics projects. The process of scaling up, which is articulated as expansion, roll-out, and replication, is defined as the ability of a system to improve its scale by aiming to meet the increasing volume demand. Specifically, this study investigates the scalability intended to be used as expansion and roll-out. A qualitative case study was conducted to fulfill the research purpose. The chosen case study is SMOOTh, a pilot project currently underway in the city of Gothenburg, Sweden, involving a diverse group of companies including Volvo Group and DHL. Semi-structured interviews were conducted with seven of the project’s stakeholders. Through a thematic analysis, four categories and the respective success factors were identified. These were represented by a business model, as well as technical, stakeholder and regulatory factors. The paper concludes with observations and recommendations aimed at the pilot initiatives, adding new perspectives to the upscaling debate. Citation: Smart Cities PubDate: 2021-10-15 DOI: 10.3390/smartcities4040071 Issue No:Vol. 4, No. 4 (2021)
Authors:Davide Carneiro, António Amaral, Mariana Carvalho, Luís Barreto First page: 1366 Abstract: Cities are becoming increasingly complex to manage, as they increase in size and must provide higher living standards for their populations. New technology-based solutions must be developed towards attending this growth and ensuring that it is socially sustainable. This paper puts forward the notion that these solutions must share some properties: they should be anthropocentric, holistic, horizontal, multi-dimensional, multi-modal, and predictive. We propose an architecture in which streaming data sources that characterize the city context are used to feed a real-time graph of the city’s assets and states, as well as to train predictive models that hint into near future states of the city. This allows human decision-makers and automated services to take decisions, both for the present and for the future. To achieve this, multiple data sources about a city were gradually connected to a message broker, that enables increasingly rich decision-support. Results show that it is possible to predict future states of a city, in aspects such as traffic, air pollution, and other ambient variables. The key innovative aspect of this work is that, as opposed to the majority of existing approaches which focus on a real-time view of the city, we also provide insights into the near-future state of the city, thus allowing city services to plan ahead and adapt accordingly. The main goal is to optimize decision-making by anticipating future states of the city and make decisions accordingly. Citation: Smart Cities PubDate: 2021-10-21 DOI: 10.3390/smartcities4040072 Issue No:Vol. 4, No. 4 (2021)
Authors:Katsunobu Sasanuma First page: 1391 Abstract: The number of drivers using parking facilities (parking demand) in downtown Pittsburgh is highly variable throughout business operating hours, which makes an efficient operation of parking facilities challenging and results in congestion around the facilities. In this study, we applied an event-based ordinary least squares (OLS) regression model to the parking data set provided from one of the parking facilities, the Theater Square Garage in downtown Pittsburgh. We demonstrated that our model achieved a high R-squared value during time periods when parking demand is highly variable. Using the model, we revealed the dynamic (time-dependent) impact of theater performances and sports events on parking demand. This dynamic information can help facility managers appropriately adjust their operating settings (e.g., the number of staff and fee structure) during surge or vacant time periods accordingly. This model is applicable to various businesses in downtown areas that have increased customer flow from theater performances and sports events, not only parking garages. Citation: Smart Cities PubDate: 2021-11-08 DOI: 10.3390/smartcities4040073 Issue No:Vol. 4, No. 4 (2021)
Authors:Kaihui Huang, Weijie Luo, Weiwei Zhang, Jinhai Li First page: 1403 Abstract: The rapid expansion of urbanization both in scale and population leads to a series of serious urban diseases, which become a huge obstacle to the healthy and sustainable development of cities. To alleviate these problems and challenges, China launched a smart city construction program in the past decade and has taken the lead in smart city construction in the world. However, there is still a lack of reflection and summary on the practice of smart cities in China. Based on the definition and concept of smart city, this paper points out the internal and external driving factors of China’s smart city development, then summarizes the four major characteristics of China’s smart city construction practice, and explores the main problems existing in the process of China’s smart city construction. Through the reflection and summary, we can facilitate development of smart cities in China, provide useful reference to urban planners and smart city practitioners in other countries and regions, and promote the healthy and sustainable development of cities. Citation: Smart Cities PubDate: 2021-11-09 DOI: 10.3390/smartcities4040074 Issue No:Vol. 4, No. 4 (2021)
Authors:Fernando Martins, Carlos Patrão, Pedro Moura, Aníbal T. de Almeida First page: 1420 Abstract: Nowadays, modeling tools are a crucial part of best practice in the elaboration and implementation of a decarbonization plan in any organization, city, or country. The present review analyzes the different modeling tools available to assess energy systems in smart cities. It creates an updated overview of the modeling tools currently available, showing their capabilities and main potential outputs when considering the energy efficiency objective in the context of smart cities in Europe. A restricted set of 14 tools are identified which optimally fulfill the modeling mission of the energy sector, in a smart city context, for different time horizons. The selection considers the capability to include decarbonization assessments, namely, by considering the flexibility to use different external factors, energy policies, technologies, and mainly the implementation of Article 7 from the Energy Efficiency Directive and the “energy efficiency first” principle defined by the European Commission. The ELECTRE TRI method was used to implement a multi-criteria decision approach for sorting modeling tools, aiming at distributing the various alternatives by previously defined categories, and considering the performance criteria of each alternative modeling tool, the analysis suggests that the best options are the LEAP, MESSAGEix, and oemof tools. Citation: Smart Cities PubDate: 2021-11-16 DOI: 10.3390/smartcities4040075 Issue No:Vol. 4, No. 4 (2021)
Authors:Hugo Algarvio First page: 1437 Abstract: Over the last few decades, the electricity sector has experienced several changes, resulting in different electricity markets (EMs) models and paradigms. In particular, liberalization has led to the establishment of a wholesale market for electricity generation and a retail market for electricity retailing. In competitive EMs, customers can do the following: freely choose their electricity suppliers; invest in variable renewable energy such as solar photovoltaic; become prosumers; or form local alliances such as Citizen Energy Communities (CECs). Trading of electricity can be done in spot and derivatives markets, or by bilateral contracts. This article focuses on CECs. Specifically, it presents how agent-based local consumers can form alliances as CECs, manage their resources, and trade on EMs. It also presents a review of how agent-based systems can model and support the formation and interaction of alliances in the electricity sector. The CEC can trade electricity directly with sellers through private bilateral agreements. During the negotiation of private bilateral contracts, the CEC receives the prices and volumes of their members and according to its negotiation strategy, tries to satisfy the electricity demands of all members and reduce their costs for electricity. Citation: Smart Cities PubDate: 2021-11-27 DOI: 10.3390/smartcities4040076 Issue No:Vol. 4, No. 4 (2021)
Authors:William Hurst, Frida Ruiz Mendoza, Bedir Tekinerdogan First page: 1454 Abstract: The amount of arable land is limited, yet the demand for agricultural food products is increasing. This issue has led to the notion of precision farming, where smart city-based technologies (e.g., Internet of Things, digital twins, artificial intelligence) are employed in combination to cater for increased production with fewer resources. Widely used in manufacturing, augmented reality has demonstrated impactful solutions for information communication, remote monitoring and increased interaction. Yet, the technology has only recently begun to find a footing alongside precision farming solutions, despite the many benefits possible to farmers through augmenting the physical world with digital objects. Therefore, this article reflects on literature discussing current applied solutions within agriculture, where augmented realty has demonstrated a significant impact for monitoring and production. The findings discuss that augmented reality must be coupled with other technologies (e.g., simultaneous localization and mapping algorithms, global positioning systems, and sensors), specifically 9 are identified across 2 application domains (livestock and crop farming) to be beneficial. Attention is also provided on how augmented reality should be employed within agriculture, where related-work examples are drawn from in order to discuss suitable hardware approaches and constraints (e.g., mobility). Citation: Smart Cities PubDate: 2021-12-02 DOI: 10.3390/smartcities4040077 Issue No:Vol. 4, No. 4 (2021)
Authors:Swapnil Sadashiv Shinde, Daniele Tarchi First page: 1469 Abstract: Modern cities require a tighter integration with Information and Communication Technologies (ICT) for bringing new services to the citizens. The Smart City is the revolutionary paradigm aiming at integrating the ICT with the citizen life; among several urban services, transports are one of the most important in modern cities, introducing several challenges to the Smart City paradigm. In order to satisfy the stringent requirements of new vehicular applications and services, Edge Computing (EC) is one of the most promising technologies when integrated into the Vehicular Networks (VNs). EC-enabled VNs can facilitate new latency-critical and data-intensive applications and services. However, ground-based EC platforms (i.e., Road Side Units—RSUs, 5G Base Stations—5G BS) can only serve a reduced number of Vehicular Users (VUs), due to short coverage ranges and resource shortage. In the recent past, several new aerial platforms with integrated EC facilities have been deployed for achieving global connectivity. Such air-based EC platforms can complement the ground-based EC facilities for creating a futuristic VN able to deploy several new applications and services. The goal of this work is to explore the possibility of creating a novel joint air-ground EC platform within a VN architecture for helping VUs with new intelligent applications and services. By exploiting most modern technologies, with particular attention towards network softwarization, vehicular edge computing, and machine learning, we propose here three possible layered air-ground EC-enabled VN scenarios. For each of the discussed scenarios, a list of the possible challenges is considered, as well possible solutions allowing to overcome all or some of the considered challenges. A proper comparison is also done, through the use of tables, where all the proposed scenarios, and the proposed solutions, are discussed. Citation: Smart Cities PubDate: 2021-12-09 DOI: 10.3390/smartcities4040078 Issue No:Vol. 4, No. 4 (2021)
Authors:Nyayu Latifah Husni, Putri Adelia Rahmah Sari, Ade Silvia Handayani, Tresna Dewi, Seyed Amin Hosseini Seno, Wahyu Caesarendra, Adam Glowacz, Krzysztof Oprzędkiewicz, Maciej Sułowicz First page: 1496 Abstract: This paper describes the implementation of real time human activity recognition systems in public areas. The objective of the study is to develop an alarm system to identify people who do not care for their surrounding environment. In this research, the actions recognized are limited to littering activity using two methods, i.e., CNN and CNN-LSTM. The proposed system captures, classifies, and recognizes the activity by using two main components, a namely camera and mini-PC. The proposed system was implemented in two locations, i.e., Sekanak River and the mini garden near the Sekanak market. It was able to recognize the littering activity successfully. Based on the proposed model, the validation results from the prediction of the testing data in simulation show a loss value of 70% and an accuracy value of 56% for CNN of model 8 that used 500 epochs and a loss value of 10.61%, and an accuracy value of 97% for CNN-LSTM that used 100 epochs. For real experiment of CNN model 8, it is obtained 66.7% and 75% success for detecting littering activity at mini garden and Sekanak River respectively, while using CNN-LSTM in real experiment sequentially gives 94.4% and 100% success for mini garden and Sekanak river. Citation: Smart Cities PubDate: 2021-12-13 DOI: 10.3390/smartcities4040079 Issue No:Vol. 4, No. 4 (2021)
Authors: Peoples, Kulkarni, Rabbani, Moore, Zoualfaghari, Ullah First page: 952 Abstract: The full potential of smart cities is not yet realized, and opportunities continue to exist in relation to the business models which govern service provision in cities. In saying this, we make reference to the waste services made available by councils across cities in the United Kingdom (UK). In the UK, smart waste management (SWM) continues to exist as a service trialed across designated cities, and schemes are not yet universally deployed. This therefore exists as a business model which might be improved so that wider roll-out and uptake may be encouraged. In this paper, we present a proposal of how to revise SWM services through integrating the Internet service provider (ISP) into the relationship alongside home and business customers and the city council. The goal of this model is to give customers the opportunity for a more dynamic and flexible service. Furthermore, it will introduce benefits for all parties, in the sense of more satisfied home and business owners, ISPs with a larger customer base and greater profits, and city councils with optimized expenses. We propose that this is achieved using personalized and flexible SLAs. A proof-of-concept model is presented in this paper, through which we demonstrate that the cost to customers can be optimized when they interact with the SWM scheme in the recommended ways. Citation: Smart Cities PubDate: 2021-07-02 DOI: 10.3390/smartcities4030049 Issue No:Vol. 4, No. 3 (2021)
Authors:Javier Parra-Domínguez, Jorge Herrera Santos, Sergio Márquez-Sánchez, Alfonso González-Briones, Fernando De la Prieta First page: 971 Abstract: This article introduces the concern that exists in the wider economic world concerning the developments carried out in Smart Cities. The various studies that have been developed capture the economic approach by focusing on specific economic development theories. This article initially provides a theoretical response to the need for a joint approach to the different economic theories relating to Smart Cities, placing the bases of their development in the circular economy. Subsequently, the paper presents a device-based proposal to validate the sustainability principles indicated in the Smart Economy, focusing exclusively on the areas of health and mobility. As a whole, the work concludes with the need to incorporate sustainability criteria into economic ambition so that technological developments have a place in future Smart Cities. Citation: Smart Cities PubDate: 2021-07-06 DOI: 10.3390/smartcities4030050 Issue No:Vol. 4, No. 3 (2021)
Authors:Junqi Zhao, Boyang Zhou, Jared P. Butler, Randall G. Bock, Joseph P. Portelli, Sven G. Bilén First page: 979 Abstract: Maintaining hand hygiene has been an essential preventive measure for reducing disease transmission in public facilities, particularly during the COVID-19 pandemic. The large number of sanitizer stations deployed within public facilities, such as on university campuses, brings challenges for effective facility management. This paper proposes an IoT sensor network for tracking sanitizer usage in public facilities and supporting facility management using a data-driven approach. Specifically, the system integrates low-cost wireless sensors, LoRaWAN, and cloud-based computing techniques to realize data capture, communication, and analysis. The proposed approach was validated through field experiments in a large building on a university campus to assess the network signal coverage and effectiveness of sensor operation for facility monitoring. The results show that a LoRaWAN created from a single gateway can successfully connect to sensors distributed throughout the entire building, with the sensor nodes recording and transmitting events across the network for further analysis. Overall, this paper demonstrates the potential of leveraging the IoT-based Sanitizer Station Network to track public health mitigation methods in a large facility, which ultimately contributes to reducing the burden of maintaining public health during and post-pandemic. Citation: Smart Cities PubDate: 2021-07-08 DOI: 10.3390/smartcities4030051 Issue No:Vol. 4, No. 3 (2021)
Authors:Li Meng First page: 995 Abstract: The internet of things (IoT) and social media provide information related to disasters that could help businesses to strategically mitigate risks and optimize their supply chain during difficult times. This paper proposes a framework to show how business or supply chain enterprisers can collaborate with community and government in disaster supply chain risk management. Businesses must have an established risk mitigation plan, update it periodically and implement promptly. Community collaboration can build a resilient society, and government should play an important role in leading both financial and non-financial support during natural disasters and pandemic management. The IoT and social media are new mechanisms as a vocal point to enable government, ensuring trustworthiness of information, to provide the community with a means to express needs and feedback, and to assist business services to meet the changeable preferences under risk threats. Social media can be a collaborative effort between all the parties and helps make value added decisions efficiently in supply chain risk management. Citation: Smart Cities PubDate: 2021-07-14 DOI: 10.3390/smartcities4030052 Issue No:Vol. 4, No. 3 (2021)
Authors:S. Vishnu, Jino S. R. Ramson, Samson Senith, Theodoros Anagnostopoulos, Adnan M. Abu-Mahfouz, Xiaozhe Fan, S. Srinivasan, A. Alfred Kirubaraj First page: 1004 Abstract: The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing city processes in real-time. One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact on our society’s health and the environment. The traditional waste management process begins with waste created by city residents and disposed of in garbage bins at the source. Municipal department trucks collect garbage and move it to recycling centers on a fixed schedule. Municipalities and waste management companies fail to keep up with outdoor containers, making it impossible to determine when to clean them or when they are full. This work proposes an IoT-enabled solid waste management system for smart cities to overcome the limitations of the traditional waste management systems. The proposed architecture consists of two types of end sensor nodes: PBLMU (Public Bin Level Monitoring Unit) and HBLMU (Home Bin Level Monitoring Unit), which are used to track bins in public and residential areas, respectively. The PBLMUs and HBLMUs measure the unfilled level of the trash bin and its location data, process it, and transmit it to a central monitoring station for storage and analysis. An intelligent Graphical User Interface (GUI) enables the waste collection authority to view and evaluate the unfilled status of each trash bin. To validate the proposed system architecture, the following significant experiments were conducted: (a) Eight trash bins were equipped with PBLMUs and connected to a LoRaWAN network and another eight trash bins were equipped with HBLMUs and connected to a Wi-Fi network. The trash bins were filled with wastes at different levels and the corresponding unfilled levels of every trash bin were monitored through the intelligent GUI. (b) An experimental setup was arranged to measure the sleep current and active current contributions of a PBLMU to estimate its average current consumption. (c) The life expectancy of a PBLMU was estimated as approximately 70 days under hypothetical conditions. Citation: Smart Cities PubDate: 2021-07-14 DOI: 10.3390/smartcities4030053 Issue No:Vol. 4, No. 3 (2021)
Authors:Wesam Emad Saba, Salwa M. Beheiry, Ghassan Abu-Lebdeh, Mustafa S. AL-Tekreeti First page: 1018 Abstract: Signalized urban intersections are key components of urban transportation networks. They are traditionally viewed and designed as primarily motorized traffic facilities, and thus their physical and operational designs have traditionally aimed at maximizing traffic throughput subject to constraints dictated by vehicular safety requirements and pedestrian crossing needs. Seen from a holistic viewpoint, urban intersections are hubs or effective centers of community activities of which traffic flow is only one. Those hubs have direct and indirect impacts on the overlapping traffic functionalities, the environment, public health, community wellbeing, and the local economy. This study proposes a new rating system, the Holistic Intersection Rating System (HIRS), aimed at appraising signalized intersections from a more inclusive viewpoint. This appraisal covers traffic functionality, sustainability, and public health and community wellbeing. This rating system can be used as a guide to conceive, plan, or design new intersections or revamp existing ones. HIRS rates signalized urban intersections based on the level of use of relevant enabling technologies, and the physical and operational designs that allow those intersections to operate holistically, thus leading to a more human-centric and sustainable operational performance. HIRS was validated using a panel of experts in construction, transportation, and public health. The Relative Importance Index (RII) method was used to weigh the HIRS features. The rating system was piloted on a sample of 20 intersections in different cities in the UAE. The results revealed glaring gaps in services to or the consideration of pedestrians, cyclists, and nearby households. The sample intersections scored a mean of 32% on the public health and community wellbeing section, 37% on the pedestrian subsection, and 15% on the cyclist subsection. Such relatively low scores serve as indicators of areas for improvements, and if mapped to their specific features and their relative weights, specific physical and operations designs and technology integration can be identified as actionable items for inclusion in plans and/or designs. Citation: Smart Cities PubDate: 2021-07-19 DOI: 10.3390/smartcities4030054 Issue No:Vol. 4, No. 3 (2021)
Authors:Amro M. Farid, Asha Viswanath, Reem Al-Junaibi, Deema Allan, Thomas J. T. Van der Van der Wardt First page: 1039 Abstract: Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality. Citation: Smart Cities PubDate: 2021-07-23 DOI: 10.3390/smartcities4030055 Issue No:Vol. 4, No. 3 (2021)
Authors:Franklin Oliveira, Daniel G. Costa, Luciana Lima, Ivanovitch Silva First page: 1058 Abstract: The fast transformation of the urban centers, pushed by the impacts of climatic changes and the dramatic events of the COVID-19 Pandemic, will profoundly influence our daily mobility. This resulted scenario is expected to favor adopting cleaner and flexible modal solutions centered on bicycles and scooters, especially as last-mile options. However, as the use of bicycles has rapidly increased, cyclists have been subject to adverse conditions that may affect their health and safety when cycling in urban areas. Therefore, whereas cities should implement mechanisms to monitor and evaluate adverse conditions in cycling paths, cyclists should have some effective mechanism to visualize the indirect quality of cycling paths, eventually supporting choosing more appropriate routes. Therefore, this article proposes a comprehensive multi-parameter system based on multiple independent subsystems, covering all phases of data collecting, formatting, transmission, and processing related to the monitoring, evaluating, and visualizing the quality of cycling paths in the perspective of adverse conditions that affect cyclist. The formal interactions of all modules are carefully described, as well as implementation and deployment details. Additionally, a case study is considered for a large city in Brazil, demonstrating how the proposed system can be adopted in a real scenario. Citation: Smart Cities PubDate: 2021-07-24 DOI: 10.3390/smartcities4030056 Issue No:Vol. 4, No. 3 (2021)
Authors:Christos Spandonidis, Fotis Giannopoulos, Areti Petsa, Periklis Eleftheridis, Elias Sedikos First page: 1087 Abstract: Based on the constant need for safety and operational cost optimization, the air-cargo industry is continually evolving in the context of Industry 4.0. Used wisely, data can help the industry to provide critical resilience that will allow authorities to take proper measures/actions in response to unexpected disasters and secure societal protection. The “INTELLICONT” project combines state-of-the-art technologies blended with novel solutions to improve the loading/unloading time, the structural status awareness, and the safety and security of the air-cargo related operations (prior to, during, and after the flight), as well as to enhance their capabilities related to the execution of their duties. The suggested system is contextually aligned and harmonized with the existing international and EU regulations. In the present work, the remote monitoring and control system for intelligent aircraft cargo containers have been presented from the software perspective. The intelligent containers integrate three types of sensors, Structural Health Monitoring, fire suppression, and locking status indication. The focus has been given to the design and development of a Human Machine Interface (HMI) capable to visualize all related data for better and safer control of the aircraft cargo. It is shown that the system can contribute to making the air transportations safer, environmentally friendlier, faster and with the lowest possible cost. Citation: Smart Cities PubDate: 2021-07-24 DOI: 10.3390/smartcities4030057 Issue No:Vol. 4, No. 3 (2021)
Authors:Didier Grimaldi, Carly Collins, Sebastian Garcia Acosta First page: 1104 Abstract: Millions of users post comments to TripAdvisor daily, together with a numeric evaluation of their experience using a rating scale of between 1 and 5 stars. At the same time, inspectors dispatched by national and local authorities visit restaurant premises regularly to audit hygiene standards, safe food practices, and overall cleanliness. The purpose of our study is to analyze the use of online-generated reviews (OGRs) as a tool to complement official restaurant inspection procedures. Our case study-based approach, with the help of a Python-based scraping library, consists of collecting OGR data from TripAdvisor and comparing them to extant restaurants’ health inspection reports. Our findings reveal that a correlation does exist between OGRs and national health system scorings. In other words, OGRs were found to provide valid indicators of restaurant quality based on inspection ratings and can thus contribute to the prevention of foodborne illness among citizens in real time. The originality of the paper resides in the use of big data and social network data as a an easily accessible, zero-cost, and complementary tool in disease prevention systems. Incorporated in restaurant management dashboards, it will aid in determining what action plans are necessary to improve quality and customer experience on the premises. Citation: Smart Cities PubDate: 2021-08-02 DOI: 10.3390/smartcities4030058 Issue No:Vol. 4, No. 3 (2021)
Authors:María Verónica Alderete First page: 1113 Abstract: This paper aims to examine the determinants of smart-city commitment across individuals from Bahía Blanca, Argentina. Literature has identified different factors explaining citizens’ commitment to smart cities, such as education, age, labor condition, and other more subjective factors, such as trust and awareness about the smart-city concept. A mediator factor of smart commitment is e-readiness or digital readiness, that is, the level of preparedness to properly exploit internet opportunities such as e-government and e-commerce. To achieve this goal, we used a survey conducted on 97 citizens (followers of the Moderniza Bahía Facebook) from the city of Bahía Blanca, Argentina. By estimating a structural equation model, we found that higher levels of ICT use are associated with higher levels of smart-city commitment and that higher awareness of the smart-city concept is related to higher levels of smart-city commitment. Sociodemographic factors such as age and labor condition also explain ICT use. Citation: Smart Cities PubDate: 2021-08-06 DOI: 10.3390/smartcities4030059 Issue No:Vol. 4, No. 3 (2021)
Authors:Jean-David Collard, Erick Stattner, Panagiotis Gergos First page: 1130 Abstract: Many of us have experienced this when driving in the city, we had to “turn for hours” to find a parking space. To attenuate this drawback, this paper proposes a collaborative parking search strategy based on the reality of a drivers network in which, depending on his/her role at a given time, each one can help the others to find public on-street parking spots. To highlight a situation of parking spot scarcity, we assume the extreme case where there is no free space and the only solution to park is to swap with a parked car that leaves its location. Under this assumption, agent-based modelling and simulations allow to compare the ReadyPark solution with the classical approach that consists, by luck, in taking the place of a nearby car that is leaving its spot. Citation: Smart Cities PubDate: 2021-08-12 DOI: 10.3390/smartcities4030060 Issue No:Vol. 4, No. 3 (2021)
Authors:Fountas Panagiotis, Kouskouras Taxiarxchis, Kranas Georgios, Leandros Maglaras, Mohamed Amine Ferrag First page: 1146 Abstract: Over the years, the digitization of all aspects of life in modern societies is considered an acquired advantage. However, like the terrestrial world, the digital world is not perfect and many dangers and threats are present. In the present work, we conduct a systematic review on the methods of network detection and cyber attacks that can take place in a critical infrastructure. As is shown, the implementation of a system that learns from the system behavior (machine learning), on multiple levels and spots any diversity, is one of the most effective solutions. Citation: Smart Cities PubDate: 2021-08-28 DOI: 10.3390/smartcities4030061 Issue No:Vol. 4, No. 3 (2021)
Authors:Igor Calzada First page: 1158 Abstract: Against the widespread assumption that data are the oil of the 21st century, this article offers an alternative conceptual framework, interpretation, and pathway around data and smart city nexus to subvert surveillance capitalism in light of emerging and further promising practical cases. This article illustrates an open debate in data governance and the data justice field related to current trends and challenges in smart cities, resulting in a new approach advocated for and recently coined by the UN-Habitat programme ‘People-Centred Smart Cities’. Particularly, this feature article sheds light on two intertwined notions that articulate the technopolitical dimension of the ‘People-Centred Smart Cities’ approach: data co-operatives and data sovereignty. Data co-operatives are emerging as a way to share and own data through peer-to-peer (p2p) repositories and data sovereignty is being claimed as a digital right for communities/citizens. Consequently, this feature article aims to open up new research avenues around ‘People-Centred Smart Cities’ approach: First, it elucidates how data co-operatives through data sovereignty could be articulated as long as co-developed with communities connected to the long history and analysis of the various forms of co-operatives (technopolitical dimension). Second, it prospectively anticipates the city–regional dimension encompassing data colonialism and data devolution. Citation: Smart Cities PubDate: 2021-09-05 DOI: 10.3390/smartcities4030062 Issue No:Vol. 4, No. 3 (2021)
Authors:Morteza Azimi Nasab, Mohammad Zand, Mohsen Eskandari, Padmanaban Sanjeevikumar, Pierluigi Siano First page: 1173 Abstract: One of the important aspects of realizing smart cities is developing smart homes/buildings and, from the energy perspective, designing and implementing an efficient smart home area energy management system (HAEMS) is vital. To be effective, the HAEMS should include various electrical appliances as well as local distributed/renewable energy resources and energy storage systems, with the whole system as a microgrid. However, the collecting and processing of the data associated with these appliances/resources are challenging in terms of the required sensors/communication infrastructure and computational burden. Thanks to the internet-of-things and cloud computing technologies, the physical requirements for handling the data have been provided; however, they demand suitable optimization/management schemes. In this article, a HAEMS is developed using cloud services to increase the accuracy and speed of the data processing. A management protocol is proposed that provides an optimal schedule for a day-ahead operation of the electrical equipment of smart residential homes under welfare indicators. The proposed system comprises three layers: (1) sensors associated with the home appliances and generation/storage units, (2) local fog nodes, and (3) a cloud where the information is processed bilaterally with HAEMS and the hourly optimal operation of appliances/generation/storage units is planned. The neural network and genetic algorithm (GA) are used as part of the HAEMS program. The neural network is used to predict the amount of workload corresponding to users’ requests. Improving the load factor and the economic efficiency are considered as the objective function that is optimized using GA. Numerical studies are performed in the MATLAB platform and the results are compared with a conventional method. Citation: Smart Cities PubDate: 2021-09-16 DOI: 10.3390/smartcities4030063 Issue No:Vol. 4, No. 3 (2021)
Authors:Tanweer Alam First page: 1196 Abstract: A smart city is an urbanization region that collects data using several digital and physical devices. The information collected from such devices is used efficiently to manage revenues, resources, and assets, etc., while the information obtained from such devices is utilized to boost performance throughout the city. Cloud-based Internet of Things (IoT) applications could help smart cities that contain information gathered from citizens, devices, homes, and other things. This information is processed and analyzed to monitor and manage transportation networks, electric utilities, resources management, water supply systems, waste management, crime detection, security mechanisms, proficiency, digital library, healthcare facilities, and other opportunities. A cloud service provider offers public cloud services that can update the IoT environment, enabling third-party activities to embed IoT data within electronic devices executing on the IoT. In this paper, the author explored cloud-based IoT applications and their roles in smart cities. Citation: Smart Cities PubDate: 2021-09-17 DOI: 10.3390/smartcities4030064 Issue No:Vol. 4, No. 3 (2021)
Authors:Hafiz Suliman Munawar, Fahim Ullah, Siddra Qayyum, Amirhossein Heravi First page: 1220 Abstract: Floods are one of the most fatal and devastating disasters, instigating an immense loss of human lives and damage to property, infrastructure, and agricultural lands. To cater to this, there is a need to develop and implement real-time flood management systems that could instantly detect flooded regions to initiate relief activities as early as possible. Current imaging systems, relying on satellites, have demonstrated low accuracy and delayed response, making them unreliable and impractical to be used in emergency responses to natural disasters such as flooding. This research employs Unmanned Aerial Vehicles (UAVs) to develop an automated imaging system that can identify inundated areas from aerial images. The Haar cascade classifier was explored in the case study to detect landmarks such as roads and buildings from the aerial images captured by UAVs and identify flooded areas. The extracted landmarks are added to the training dataset that is used to train a deep learning algorithm. Experimental results show that buildings and roads can be detected from the images with 91% and 94% accuracy, respectively. The overall accuracy of 91% is recorded in classifying flooded and non-flooded regions from the input case study images. The system has shown promising results on test images belonging to both pre- and post-flood classes. The flood relief and rescue workers can quickly locate flooded regions and rescue stranded people using this system. Such real-time flood inundation systems will help transform the disaster management systems in line with modern smart cities initiatives. Citation: Smart Cities PubDate: 2021-09-18 DOI: 10.3390/smartcities4030065 Issue No:Vol. 4, No. 3 (2021)
Authors:Abbas Shah Syed, Daniel Sierra-Sosa, Anup Kumar, Adel Elmaghraby First page: 429 Abstract: Internet of Things (IoT) is a system that integrates different devices and technologies, removing the necessity of human intervention. This enables the capacity of having smart (or smarter) cities around the world. By hosting different technologies and allowing interactions between them, the internet of things has spearheaded the development of smart city systems for sustainable living, increased comfort and productivity for citizens. The IoT for Smart Cities has many different domains and draws upon various underlying systems for its operation. In this paper, we provide a holistic coverage of the Internet of Things in Smart Cities. We start by discussing the fundamental components that make up the IoT based Smart City landscape followed by the technologies that enable these domains to exist in terms of architectures utilized, networking technologies used as well as the Artificial Algorithms deployed in IoT based Smart City systems. This is then followed up by a review of the most prevalent practices and applications in various Smart City domains. Lastly, the challenges that deployment of IoT systems for smart cities encounter along with mitigation measures. Citation: Smart Cities PubDate: 2021-03-30 DOI: 10.3390/smartcities4020024 Issue No:Vol. 4, No. 2 (2021)
Authors:Ajibike Eunice Akin-Ponnle, Nuno Borges Carvalho First page: 476 Abstract: The issue of how to power the deployed Internet of Things (IoT) nodes with ubiquitous and long lasting energy in order to ensure uninterruptible optimisation of smart cities is of utmost concern. This among other challenges has continued to gear efforts toward energy harvesting research. With the outbreak of COVID-19 pandemic and the lockdown that nearly paralysed activities of everyday living in many nations of the world, option of human remote interaction to enforce social distancing became imperative. Hence, the world is witnessing a renewed awareness of the importance of IoT devices, as integral components of smart city, especially for the essence of survival in the face of lockdown. Energy harvesting is a possible solution that could enable IoT nodes to scavenge self-sustaining energy from environmental ambient sources. In this paper, we have reviewed most sources within city that energy could be harvested from, as reported by researchers in literature. In addition, we have submitted that energy sources can be application specific, such that, since there are many free sources in the city as presented in this review, energy should be scavenged within close proximity of need for various IoT devices or wireless sensor networks (WSNs), for smart city automation. Citation: Smart Cities PubDate: 2021-04-08 DOI: 10.3390/smartcities4020025 Issue No:Vol. 4, No. 2 (2021)
Authors:Nima Shirzad-Ghaleroudkhani, Mustafa Gül First page: 499 Abstract: This paper develops an enhanced inverse filtering-based methodology for drive-by frequency identification of bridges using smartphones for real-life applications. As the vibration recorded on a vehicle is dominated by vehicle features including suspension system and speed as well as road roughness, inverse filtering aims at suppressing these effects through filtering out vehicle- and road-related features, thus mitigating a few of the significant challenges for the indirect identification of the bridge frequency. In the context of inverse filtering, a novel approach of constructing a database of vehicle vibrations for different speeds is presented to account for the vehicle speed effect on the performance of the method. In addition, an energy-based surface roughness criterion is proposed to consider surface roughness influence on the identification process. The successful performance of the methodology is investigated for different vehicle speeds and surface roughness levels. While most indirect bridge monitoring studies are investigated in numerical and laboratory conditions, this study proves the capability of the proposed methodology for two bridges in a real-life scale. Promising results collected using only a smartphone as the data acquisition device corroborate the fact that the proposed inverse filtering methodology could be employed in a crowdsourced framework for monitoring bridges at a global level in smart cities through a more cost-effective and efficient process. Citation: Smart Cities PubDate: 2021-04-15 DOI: 10.3390/smartcities4020026 Issue No:Vol. 4, No. 2 (2021)
Authors:Donald Bliss, Raymond Garbos, Patrick Kane, Vyacheslav Kharchenko, Thaddeus Kochanski, Andrzej Rucinski First page: 514 Abstract: This paper evaluates the status quo of modern society and identifies the neglect of humanism as the root cause of many of today’s global challenges. Note that “smart cities” are not excluded from this indictment. The “Ptolemaic Universe” offers a means to restore our symbiosis with the environment. The ReSeT model is proposed as a tool to analyze the Ptolemaic Universe. Using ReSeT: Homo Sapiens becomes dependent on AI resulting in Homo Digitalis, with further evolution in concert with AI resulting in Homo Digitus. All of these stages are then analyzed in the context of global trusted dependability (GTD). The wellness domain, provides the design specification framework for Homo Digitus’ human-centered and resilient “smart city” ecosystem. This ultimately leads to a better world of increased wellness for Homo Hominus, with better smart cities emphasizing education and science, promoting wisdom and common sense, and rejecting violence. In summary, humanity has generated diverse social structures with erratic outcomes. On the other hand, technology provides a successful foundation for modern society especially in the Pandemic Era. However, technology’s contributions are generally not publicly acknowledged. The paper concludes with several initiatives designed to establish a trusted and resilient society. Citation: Smart Cities PubDate: 2021-04-20 DOI: 10.3390/smartcities4020027 Issue No:Vol. 4, No. 2 (2021)
Authors:Abu Saleh Md Bakibillah, Yi Feng Paw, Md Abdus Samad Kamal, Susilawati Susilawati, Chee Pin Tan First page: 532 Abstract: Connected and automated vehicle (CAV) technology, along with advanced traffic control systems, cannot ensure congestion-free traffic when the number of vehicles exceeds the road capacity. To address this problem, in this paper, we propose a dynamic ride-sharing system based on incentives (for both passengers and drivers) that incorporates travelers of similar routes and time schedules on short notice. The objective is to reduce the number of private vehicles on urban roads by utilizing the available seats properly. We develop a mobile-cloud architecture-based system that enables real-time ride-sharing. The effectiveness of the proposed system is evaluated through microscopic traffic simulation using Simulation of Urban Mobility (SUMO) considering the traffic flow behavior of a real smart city. Moreover, we develop a lab-scale experimental prototype in the form of Internet of Things (IoT) network. The simulation results show that the proposed system reduces fuel consumption, CO2 and CO emissions, and average waiting time of vehicles significantly, while increasing the vehicle’s average speed. Remarkably, it is found that only 2–10% ride-sharing can improve the overall traffic performance. Citation: Smart Cities PubDate: 2021-04-22 DOI: 10.3390/smartcities4020028 Issue No:Vol. 4, No. 2 (2021)
Authors:Olufemi A. Omitaomu, Haoran Niu First page: 548 Abstract: The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems. Citation: Smart Cities PubDate: 2021-04-22 DOI: 10.3390/smartcities4020029 Issue No:Vol. 4, No. 2 (2021)
Authors:Sven-Volker Rehm, Shane McLoughlin, Giovanni Maccani First page: 569 Abstract: Despite immense efforts to realize diverse visions of the ‘smart city,’ municipalities still face manifold uncertainties of how governance and the tools of governance can best support public and regional value creation for achieving urban sustainability. To this end, Urban Living Labs have become a known enabling mechanism. In this paper, we extend the lab idea and formulate the concept of Urban Experimentation Platform that focuses on developing urban innovation ecosystems for urban sustainability. We use action design research and participant observation across multiple case studies enacting Urban Experimentation Platforms in order to investigate how the tie-in between governance and the local lab’s innovation process unfolds. Our analysis distills three facets that are instrumental in institutionalizing these platforms as resilient organizational models. With the help of the case studies, we illustrate the three facets, concerning issues of urban ecosystem governance, empowering co-creation, and qualifying local innovation. The facets reinforce the roles of digital instruments and digital capabilities for effective urban governance and platform management. We draw some conclusions for future research and formulate policy recommendations for implementing and operating Urban Experimentation Platforms. Citation: Smart Cities PubDate: 2021-04-23 DOI: 10.3390/smartcities4020030 Issue No:Vol. 4, No. 2 (2021)
Authors:Mahdi Fahmideh, Jun Yan, Jun Shen, Davoud Mougouei, Yanlong Zhai, Aakash Ahmad First page: 588 Abstract: The compliance of IoT platforms to quality is paramount to achieve users’ satisfaction. Currently, we do not have a comprehensive set of guidelines to appraise and select the most suitable IoT platform architectures that meet relevant criteria. This paper is a tentative response to this critical knowledge gap where we adopted the design science research approach to develop a novel evaluation framework. Our research, on the one hand, stimulates an unbiased competition among IoT platform providers and, on the other hand, establishes a solid foundation for IoT platform consumers to make informed decisions in this multiplicity. The application of the framework is illustrated in example scenarios. Moreover, lessons learned from applying design science research are shared. Citation: Smart Cities PubDate: 2021-04-28 DOI: 10.3390/smartcities4020031 Issue No:Vol. 4, No. 2 (2021)
Authors:Can Biyik, Zaheer Allam, Gabriele Pieri, Davide Moroni, Muftah O’Fraifer, Eoin O’Connell, Stephan Olariu, Muhammad Khalid First page: 623 Abstract: The Internet of Things (IoT) has come of age, and complex solutions can now be implemented seamlessly within urban governance and management frameworks and processes. For cities, growing rates of car ownership are rendering parking availability a challenge and lowering the quality of life through increased carbon emissions. The development of smart parking solutions is thus necessary to reduce the time spent looking for parking and to reduce greenhouse gas emissions. The principal role of this research paper is to analyze smart parking solutions from a technical perspective, underlining the systems and sensors that are available, as documented in the literature. The review seeks to provide comprehensive insights into the building of smart parking solutions. A holistic survey of the current state of smart parking systems should incorporate the classification of such systems as big vehicular detection technologies. Finally, communication modules are presented with clarity. Citation: Smart Cities PubDate: 2021-04-28 DOI: 10.3390/smartcities4020032 Issue No:Vol. 4, No. 2 (2021)
Authors:Jerker Delsing First page: 643 Abstract: Many smart city applications have been proposed and demonstrated over the years; however, moving to large-scale deployment is still scarce. A contributing factor to this scarcity is the lack of well-established engineering methodologies for large-scale smart city applications. This paper addresses engineering methodologies and tools for large-scale smart city application engineering, implementation, deployment, and evolution. A model-based engineering approach based on IoT, SOA, and SysML is proposed and applied to a smart streetlight application. Engineering considerations for streetlight area enlargement and updated technology generations with additional capabilities are discussed. The proposed model-based engineering approach provides considerable scaling simplifications and opportunities for considerable savings on engineering costs. The model-based engineering approach also provides good documentation that enables technology evolution specifications that support both maintenance and emerging behaviours. Citation: Smart Cities PubDate: 2021-04-30 DOI: 10.3390/smartcities4020033 Issue No:Vol. 4, No. 2 (2021)
Authors:Stephan Olariu First page: 662 Abstract: Under present-day practices, the vehicles on our roadways and city streets are mere spectators that witness traffic-related events without being able to participate in the mitigation of their effect. This paper lays the theoretical foundations of a framework for harnessing the on-board computational resources in vehicles stuck in urban congestion in order to assist transportation agencies with preventing or dissipating congestion through large-scale signal re-timing. Our framework is called VACCS: Vehicular Crowdsourcing for Congestion Support in Smart Cities. What makes this framework unique is that we suggest that in such situations the vehicles have the potential to cooperate with various transportation authorities to solve problems that otherwise would either take an inordinate amount of time to solve or cannot be solved for lack for adequate municipal resources. VACCS offers direct benefits to both the driving public and the Smart City. By developing timing plans that respond to current traffic conditions, overall traffic flow will improve, carbon emissions will be reduced, and economic impacts of congestion on citizens and businesses will be lessened. It is expected that drivers will be willing to donate under-utilized on-board computing resources in their vehicles to develop improved signal timing plans in return for the direct benefits of time savings and reduced fuel consumption costs. VACCS allows the Smart City to dynamically respond to traffic conditions while simultaneously reducing investments in the computational resources that would be required for traditional adaptive traffic signal control systems. Citation: Smart Cities PubDate: 2021-05-01 DOI: 10.3390/smartcities4020034 Issue No:Vol. 4, No. 2 (2021)
Authors:Frank Elberzhager, Patrick Mennig, Svenja Polst, Simon Scherr, Phil Stüpfert First page: 686 Abstract: The digital transformation supports many cities on the way to becoming smarter cities, enabling them to enhance digital processes, care about climate-friendly goals, or improve the quality of life of their citizens. However, such changes usually take place step by step and not in a big-bang approach. In order for the direction of the digital transformation to be defined, it is necessary to know and understand the needs and requirements of all relevant stakeholders who will be affected or are intended to use the new digital solutions. As our environment, a smart city district, is currently under construction, we do not know most of the future stakeholders yet. Therefore, we had to find new ways of eliciting the needs and requirements for digital solutions without knowing, e.g., the citizens who will live in the future district. We show a framework of the procedures we followed, classified into (a) vision and concepts, (b) smart city district digital ecosystem, and (c) dissemination and events. We substantiate the processes with example results and provide a discussion on how we evaluate our solutions with respect to future applicability. Because evaluations are only very limited in our setting right now, we focus on four lead questions to argue why the procedures and results are adequate and share the lessons we learned on this path towards a digital smart city district. Citation: Smart Cities PubDate: 2021-05-13 DOI: 10.3390/smartcities4020035 Issue No:Vol. 4, No. 2 (2021)
Authors:Gregory S. Macfarlane, Christian Hunter, Austin Martinez, Elizabeth Smith First page: 717 Abstract: On-demand microtransit services are frequently seen as an important tool in supporting first and last mile operations surrounding fixed route high frequency transit facilities, but questions remain surrounding who will use these novel services and for what purposes. In November 2019, the Utah Transit Authority launched an on-demand microtransit service in south Salt Lake County in partnership with a private mobility operator. This paper reports the results of an expressed preferences survey of 130 transit riders in the microtransit service area that was collected before and immediately after the service launched. There is not a clear relationship between current transit access mode and expressed willingness to use microtransit, although some responses from new riders indicate the novel service competes most directly with commercial transportation network company operations. The survey responses also reveal younger passengers express a more than expected willingness to use microtransit, middle-aged passengers a less than expected willingness, and older passengers neutral or no expressed opinion. The results suggest additional relationships between household size and transit use frequency, but further research is necessary. The effect of other user characteristics, including income and automobile availability, is less statistically clear and requires further research. Citation: Smart Cities PubDate: 2021-05-14 DOI: 10.3390/smartcities4020036 Issue No:Vol. 4, No. 2 (2021)
Authors:Victor Garcia-Font First page: 728 Abstract: Nowadays, many urban areas are developing projects that are included within the area of smart cities. These systems tend to be highly heterogeneous and involve a large number of different technologies and participants. In general, cities deploy systems to integrate data and to provide protocols to ease interconnectivity between different subsystems. However, this is not enough to build a completely interoperable smart city, where control fully belongs to city administrators and citizens. Currently, in most cases, subsystems tend to be deployed and operated by providers creating silos. Furthermore, citizens, who should be the center of these systems, are often relegated to being just another participant. In this article, we study how smart cities can move towards decentralized and user-centric systems relying on distributed ledger technologies (DLT). For this, we define a conceptual framework that describes the interaction between smart city components, their participants, and the DLT ecosystem. We analyze the trust models that are created between the participants in the most relevant use cases, and we study the suitability of the different DLT types. Citation: Smart Cities PubDate: 2021-05-14 DOI: 10.3390/smartcities4020037 Issue No:Vol. 4, No. 2 (2021)
Authors:Ryan K. Gunawan, Susilawati First page: 746 Abstract: The location placement of pick-up/drop-offs of ride hailing usually only considers spatial distribution within a certain area. Previous studies often mapped out the potential hotspots for pick-up/drop-offs, benefitting the ride-hailing company and not considering the passengers. Therefore, in this study, we incorporated the spatiotemporal distribution of mobility-on-demand on generating pick-up/drop-off location placement using a genetic algorithm considering the walking distance and minimum demand data served within the radius. The data collected are analyzed through the clustering method, and the resulting cluster centers are fed into the location optimization algorithm. The genetic algorithm is used to optimize the location placement with the consideration of the user’s walking distance and demand. The algorithm is able to find an appropriate placement and determine reliable pick-up/drop-off stations within the study area based on observed spatiotemporal demand despite the difference in demand distribution through different time periods. Citation: Smart Cities PubDate: 2021-05-17 DOI: 10.3390/smartcities4020038 Issue No:Vol. 4, No. 2 (2021)
Authors:Emilia Rönkkö, Aulikki Herneoja First page: 767 Abstract: This article addresses the challenges and capability gaps confronted by public administrations concerning digital transformation and the use of novel tools in the context of land use, facilities and urban services planning. The present state of planning and management processes in Finland is introduced and reflected through experimental piloting conducted in two Finnish cities. Participatory action research and design research methodology was utilised to identify the main challenges as well as unravel the possibilities of digital transformation in the context of public services planning. The resulting analysis revealed the critical importance of facilitating integrative policies and coordination when working across knowledge boundaries between administrative domains. The paper contributes to a wider theoretical and conceptual understanding, as it discusses the advantages and feasibility of digital tools as boundary objects for cross-sectoral work in smart, people-centred urban governance. The authors see this direction of research as a fruitful ground for further investigations within the interdisciplinary urban planning research context. Citation: Smart Cities PubDate: 2021-05-17 DOI: 10.3390/smartcities4020039 Issue No:Vol. 4, No. 2 (2021)
Authors:Cristofer Englund, Eren Erdal Aksoy, Fernando Alonso-Fernandez, Martin Daniel Cooney, Sepideh Pashami, Björn Åstrand First page: 783 Abstract: Smart cities and communities (SCC) constitute a new paradigm in urban development. SCC ideate a data-centered society aimed at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with Internet of Things enables data collection and with the help of artificial intelligence (AI) situation awareness can be obtained to feed the SCC actors with enriched knowledge. This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control. Perception, smart traffic control and driver modeling are described along with open research challenges and standardization to help introduce advanced driver assistance systems and automated vehicle functionality in traffic. To fully realize the potential of SCC, to create a holistic view on a city level, availability of data from different stakeholders is necessary. Further, though AI technologies provide accurate predictions and classifications, there is an ambiguity regarding the correctness of their outputs. This can make it difficult for the human operator to trust the system. Today there are no methods that can be used to match function requirements with the level of detail in data annotation in order to train an accurate model. Another challenge related to trust is explainability: models can have difficulty explaining how they came to certain conclusions, so it is difficult for humans to trust them. Citation: Smart Cities PubDate: 2021-05-18 DOI: 10.3390/smartcities4020040 Issue No:Vol. 4, No. 2 (2021)
Authors:Alexandra Medina-Pérez, David Sánchez-Rodríguez, Itziar Alonso-González First page: 803 Abstract: This work aims to monitor air quality in places where humans spend most of their time, such as workplaces and homes. Radon gas is a naturally occurring, colourless, odourless and tasteless gas that accumulates in enclosed spaces. It is a radioactive element produced by the decay of its natural parent elements, uranium and thorium, which is harmful to our respiratory system when inhaled. The Internet of Things (IoT) is the key to the problems of contemporary life; we are witnessing an emerging connected world, and these architectures have the potential by using sensors to take data from the physical world, transfer it over the network and store it for further decision making or action. The proposal of this work is based on a radon sensor connected to an IoT device, the Message Queuing Telemetry Transport protocol (MQTT), the Node-RED for managing data flows and a database management system on a web server. The information collected by the sensor is sent by the IoT device to be processed by Node-RED. The obtained data is stored in a database to be represented on a web server. Therefore, this work includes a case study where the technologies involved in the indoor radon gas monitoring system are presented. It is a way to perform radon gas measurements automatically. The final application would allow: displaying radon concentrations on a map with placemarks and updating the information in real-time. The database could record data from other radon sensors that any user wants to associate with this website. Citation: Smart Cities PubDate: 2021-05-18 DOI: 10.3390/smartcities4020041 Issue No:Vol. 4, No. 2 (2021)
Authors:Luís M. Elvas, Bruno Miguel Mataloto, Ana Lúcia Martins, João C. Ferreira First page: 819 Abstract: The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach. Citation: Smart Cities PubDate: 2021-05-19 DOI: 10.3390/smartcities4020042 Issue No:Vol. 4, No. 2 (2021)
Authors: Algarvio First page: 840 Abstract: Global warming contributes to the worldwide goal of a sustainable carbon-neutral society. Currently, hydroelectric, wind and solar power plants are the most competitive renewable technologies. They are limited to the primary resource availability, but while hydroelectric power plants (HPPs) can have storage capacity but have several geographical limitations, wind and solar power plants have variable renewable energy (VRE) with stochastic profiles, requiring a substantially higher investment when equipped with battery energy storage systems. One of the most affordable solutions to compensate the stochastic behaviour of VRE is the active participation of consumers with demand response capability. Therefore, the role of citizen energy communities (CECs) can be important towards a carbon-neutral society. This work presents the economic and environmental advantages of CECs, by aggregating consumers, prosumers and VRE at the distribution level, considering microgrid trades, but also establishing bilateral agreements with large-scale VRE and HPPs, and participating in electricity markets. Results from the case-study prove the advantages of CECs and self-consumption. Currently, CECs have potential to be carbon-neutral in relation to electricity consumption and reduce consumers’ costs with its variable term until 77%. In the future, electrification may allow CECs to be fully carbon-neutral, if they increase their flexibility portfolio. Citation: Smart Cities PubDate: 2021-05-22 DOI: 10.3390/smartcities4020043 Issue No:Vol. 4, No. 2 (2021)
Authors:Christina Ng, Susilawati Susilawati, Md Abdus Samad Kamal, Irene Chew Mei Leng First page: 864 Abstract: Binary logistic regression has been used to estimate the probability of lane change (LC) in the Cell Transmission Model (CTM). These models remain rigid, as the flexibility to predict LC for different cell size configurations has not been accounted for. This paper introduces a relaxation method to refine the conventional binary logistic LC model using an event-tree approach. The LC probability for increasing cell size and cell length was estimated by expanding the LC probability of a pre-defined model generated from different configurations of speed and density differences. The reliability of the proposed models has been validated with NGSIM trajectory data. The results showed that the models could accurately estimate the probability of LC with a slight difference between the actual LC and predicted LC (95% Confidence Interval). Furthermore, a comparison of prediction performance between the proposed model and the actual observations has verified the model’s prediction ability with an accuracy of 0.69 and Area Under Curve (AUC) value above 0.6. The proposed method was able to accommodate the presence of multiple LCs when cell size changes. This is worthwhile to explore the importance of such consequences in affecting the performance of LC prediction in the CTM model. Citation: Smart Cities PubDate: 2021-05-24 DOI: 10.3390/smartcities4020044 Issue No:Vol. 4, No. 2 (2021)
Authors:Vitor N. Coelho, Thays A. Oliveira, Wellington Tavares, Igor M. Coelho First page: 881 Abstract: This paper introduces state-of-the-art possibilities for using smart contracts capabilities for governance. Assisted by blockchain, the use of these tools can provide a transition that society currently needs due the huge amount of information that reaches citizens. The core mechanism of this study lies within the scope of smart accounts and digital identities. These topics enclose smart cities trends that seek to increase citizens’ participation in the social decision making process, in a transparent way that is usually managed throughout decentralized systems. We define a set of available features that can automatically guide the flow of resources, after the conclusions of voting processes also conducted on trusted environments of distributed ledgers. By presenting innovative ideas and didactically describing the possibilities, we aim to promote awareness of blockchain capabilities among readers, students, decisions makers and, mainly, the younger generation. Citation: Smart Cities PubDate: 2021-05-30 DOI: 10.3390/smartcities4020045 Issue No:Vol. 4, No. 2 (2021)
Authors:Luís Rosa, Fábio Silva, Cesar Analide First page: 894 Abstract: The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches. Citation: Smart Cities PubDate: 2021-06-10 DOI: 10.3390/smartcities4020046 Issue No:Vol. 4, No. 2 (2021)
Authors:Nikos Papadakis, Nikos Koukoulas, Ioannis Christakis, Ilias Stavrakas, Dionisis Kandris First page: 919 Abstract: The risk of theft of goods is certainly an important source of negative influence in human psychology. This article focuses on the development of a scheme that, despite its low cost, acts as a smart antitheft system that achieves small property detection. Specifically, an Internet of Things (IoT)-based participatory platform was developed in order to allow asset-tracking tasks to be crowd-sourced to a community. Stolen objects are traced by using a prototype Bluetooth Low Energy (BLE)-based system, which sends signals, thus becoming a beacon. Once such an item (e.g., a bicycle) is stolen, the owner informs the authorities, which, in turn, broadcast an alert signal to activate the BLE sensor. To trace the asset with the antitheft tag, participants use their GPS-enabled smart phones to scan BLE tags through a specific smartphone client application and report the location of the asset to an operation center so that owners can locate their assets. A stolen item tracking simulator was created to support and optimize the aforementioned tracking process and to produce the best possible outcome, evaluating the impact of different parameters and strategies regarding the selection of how many and which users to activate when searching for a stolen item within a given area. Citation: Smart Cities PubDate: 2021-06-11 DOI: 10.3390/smartcities4020047 Issue No:Vol. 4, No. 2 (2021)
Authors:Nimat Ullah, Michel Klein, Jan Treur First page: 938 Abstract: Behaviour change techniques are considered effective means for changing behaviour, and with an increase in their use the interest in their exact working principles has also expanded. This information is required to make informed choices about when to apply which technique. Computational models that describe human behaviour can be helpful for this. In this paper a few behaviour change techniques have been connected with a computational model of emotion and desire regulation. Simulations have been performed to illustrate the effect of the techniques. The results demonstrate the working mechanisms and feasibility of the techniques used in the model. Citation: Smart Cities PubDate: 2021-06-15 DOI: 10.3390/smartcities4020048 Issue No:Vol. 4, No. 2 (2021)
Authors:Xinyue Ye, Lian Duan, Qiong Peng First page: 204 Abstract: Spatiotemporal prediction of crime is crucial for public safety and smart cities operation. As crime incidents are distributed sparsely across space and time, existing deep-learning methods constrained by coarse spatial scale offer only limited values in prediction of crime density. This paper proposes the use of deep inception-residual networks (DIRNet) to conduct fine-grained, theft-related crime prediction based on non-emergency service request data (311 events). Specifically, it outlines the employment of inception units comprising asymmetrical convolution layers to draw low-level spatiotemporal dependencies hidden in crime events and complaint records in the 311 dataset. Afterward, this paper details how residual units can be applied to capture high-level spatiotemporal features from low-level spatiotemporal dependencies for the final prediction. The effectiveness of the proposed DIRNet is evaluated based on theft-related crime data and 311 data in New York City from 2010 to 2015. The results confirm that the DIRNet obtains an average F1 of 71%, which is better than other prediction models. Citation: Smart Cities PubDate: 2021-01-29 DOI: 10.3390/smartcities4010013 Issue No:Vol. 4, No. 1 (2021)
Authors:Santiago Gomez-Rosero, Miriam A. M. Capretz, Syed Mir First page: 217 Abstract: The development from traditional low voltage grids to smart systems has become extensive and adopted worldwide. Expanding the demand response program to cover the residential sector raises a wide range of challenges. Short term load forecasting for residential consumers in a neighbourhood could lead to a better understanding of low voltage consumption behaviour. Nevertheless, users with similar characteristics can present diversity in consumption patterns. Consequently, transfer learning methods have become a useful tool to tackle differences among residential time series. This paper proposes a method combining evolutionary algorithms for neural architecture search with transfer learning to perform short term load forecasting in a neighbourhood with multiple household load consumption. The approach centres its efforts on neural architecture search using evolutionary algorithms. The neural architecture evolution process retains the patterns of the centre-most house, and later the architecture weights are adjusted for each house in a multihouse set from a neighbourhood. In addition, a sensitivity analysis was conducted to ensure model performance. Experimental results on a large dataset containing hourly load consumption for ten houses in London, Ontario showed that the performance of the proposed approach performs better than the compared techniques. Moreover, the proposed method presents the average accuracy performance of 3.17 points higher than the state-of-the-art LSTM one shot method. Citation: Smart Cities PubDate: 2021-02-01 DOI: 10.3390/smartcities4010014 Issue No:Vol. 4, No. 1 (2021)
Authors:Adrian Tantau, Ana-Maria Iulia Şanta First page: 241 Abstract: In the context of the European Union promoting clean energy, sustainability and better living conditions for its citizens, the development of smarts cities is an initiative supported at the European Union level, in line with the new energy policies of the European Union promoted by the package “Clean Energy for All Europeans”. The concept of smart cities gains increasing importance in the European Union, a fact that is reflected in the project “European Innovation Partnership on Smart Cities and Communities” of the European Commission. Smart cities are a practical example of how the new energy policies shape the lives of the European Union citizens, trying to improve it. As a consequence, new business models arise in big cities, involving the use of technology for better living conditions. These new, technology-based business models are important, as they improve the life quality of the inhabitants, they reduce the climate change impact, and they contribute as well to job creation in the IT-industry, promoting innovation. They have as well a social impact, as they bring experts from energy policies, business, economics, legal and IT together in order to project a new type of city—the smart city. The research hypothesis of the present article is that there is a high acceptance towards the concept of smart cities at the European Union level and that this concept could be implemented with the help of information technology and of artificial intelligence. This way, legal provisions, economic measures and IT-tools work together in order to create synergy effects for better life quality of the citizens of the European Union. The research hypothesis is analyzed by means of the questionnaire as a qualitative research method and is as well assessed by using case studies (e.g., Austria, Finland, Romania). The novelty of the case studies is that the development of smart cities is analyzed due to the new trend towards sustainability in two countries with different living conditions in the European Union. Citation: Smart Cities PubDate: 2021-02-09 DOI: 10.3390/smartcities4010015 Issue No:Vol. 4, No. 1 (2021)
Authors:Mohammed Bin Hariz, Dhaou Said, Hussein T. Mouftah First page: 253 Abstract: This paper focuses on transportation models in smart cities. We propose a new dynamic mobility traffic (DMT) scheme which combines public buses and car ride-sharing. The main objective is to improve transportation by maximizing the riders’ satisfaction based on real-time data exchange between the regional manager, the public buses, the car ride-sharing and the riders. OpenStreetMap and OMNET++ were used to implement a realistic scenario for the proposed model in a city like Ottawa. The DMT scheme was compared to a multi-loading system used for a school bus. Simulations showed that rider satisfaction was enhanced when a suitable combination of transportation modes was used. Additionally, compared to the other scheme, this DMT scheme can reduce the stress level of car ride-sharing and public buses during the day to the minimal level. Citation: Smart Cities PubDate: 2021-02-22 DOI: 10.3390/smartcities4010016 Issue No:Vol. 4, No. 1 (2021)
Authors:Iraklis Rigakis, Ilyas Potamitis, Nicolaos-Alexandros Tatlas, Stelios M. Potirakis, Stavros Ntalampiras First page: 271 Abstract: Is there a wood-feeding insect inside a tree or wooden structure' We investigate several ways of how deep learning approaches can massively scan recordings of vibrations stemming from probed trees to infer their infestation state with wood-boring insects that feed and move inside wood. The recordings come from remotely controlled devices that sample the internal soundscape of trees on a 24/7 basis and wirelessly transmit brief recordings of the registered vibrations to a cloud server. We discuss the different sources of vibrations that can be picked up from trees in urban environments and how deep learning methods can focus on those originating from borers. Our goal is to match the problem of the accelerated—due to global trade and climate change— establishment of invasive xylophagus insects by increasing the capacity of inspection agencies. We aim at introducing permanent, cost-effective, automatic monitoring of trees based on deep learning techniques, in commodity entry points as well as in wild, urban and cultivated areas in order to effect large-scale, sustainable pest-risk analysis and management of wood boring insects such as those from the Cerambycidae family (longhorn beetles). Citation: Smart Cities PubDate: 2021-02-27 DOI: 10.3390/smartcities4010017 Issue No:Vol. 4, No. 1 (2021)
Authors:Ahmed M. Shahat Osman, Ahmed Elragal First page: 286 Abstract: Interest in smart cities (SCs) and big data analytics (BDA) has increased in recent years, revealing the bond between the two fields. An SC is characterized as a complex system of systems involving various stakeholders, from planners to citizens. Within the context of SCs, BDA offers potential as a data-driven decision-making enabler. Although there are abundant articles in the literature addressing BDA as a decision-making enabler in SCs, mainstream research addressing BDA and SCs focuses on either the technical aspects or smartening specific SC domains. A small fraction of these articles addresses the proposition of developing domain-independent BDA frameworks. This paper aims to answer the following research question: how can BDA be used as a data-driven decision-making enabler in SCs' Answering this requires us to also address the traits of domain-independent BDA frameworks in the SC context and the practical considerations in implementing a BDA framework for SCs' decision-making. This paper's main contribution is providing influential design considerations for BDA frameworks based on empirical foundations. These foundations are concluded through a use case of applying a BDA framework in an SC's healthcare setting. The results reveal the ability of the BDA framework to support data-driven decision making in an SC. Citation: Smart Cities PubDate: 2021-02-28 DOI: 10.3390/smartcities4010018 Issue No:Vol. 4, No. 1 (2021)
Authors:Hafiz Usman Ahmed, Ying Huang, Pan Lu First page: 314 Abstract: The platform of a microscopic traffic simulation provides an opportunity to study the driving behavior of vehicles on a roadway system. Compared to traditional conventional cars with human drivers, the car-following behaviors of autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) would be quite different and hence require additional modeling efforts. This paper presents a thorough review of the literature on the car-following models used in prevalent micro-simulation tools for vehicles with both human and robot drivers. Specifically, the car-following logics such as the Wiedemann model and adaptive cruise control technology were reviewed based on the vehicle’s dynamic behavior and driving environments. In addition, some of the more recent “AV-ready (autonomous vehicles ready) tools” in micro-simulation platforms are also discussed in this paper. Citation: Smart Cities PubDate: 2021-03-03 DOI: 10.3390/smartcities4010019 Issue No:Vol. 4, No. 1 (2021)
Authors:Ken Dooley First page: 336 Abstract: The public services in our smart cities should enable our citizens to live sustainable, safe and healthy lifestyles and they should be designed inclusively. This article examines emerging data-driven methods of citizen engagement that promise to deliver effortless engagement and discusses their suitability for the task at hand. Passive participation views citizens as sensors and data mining is used to elicit meaning from the vast amounts of data generated in a city. Direct passive participation has a clear link between the creation and the use of the data whereas indirect passive participation does not require a link between creation and use. The Helsinki city bike share scheme has been selected as a case study to further explore the concept of direct passive participation. The case study shows that passive user generated data is a strong indicator of optimum city bike station sizing relative to the existing methods that are already in use. Indirect passive participation is an important area of development; however, it still needs to be developed further. In the meantime, direct passive participation can be one of the tools used to design inclusive services in a way that is safe and an accurate representation of the citizens’ needs. Citation: Smart Cities PubDate: 2021-03-10 DOI: 10.3390/smartcities4010020 Issue No:Vol. 4, No. 1 (2021)
Authors:Hassan Mehmood, Panos Kostakos, Marta Cortes, Theodoros Anagnostopoulos, Susanna Pirttikangas, Ekaterina Gilman First page: 349 Abstract: Real-world data streams pose a unique challenge to the implementation of machine learning (ML) models and data analysis. A notable problem that has been introduced by the growth of Internet of Things (IoT) deployments across the smart city ecosystem is that the statistical properties of data streams can change over time, resulting in poor prediction performance and ineffective decisions. While concept drift detection methods aim to patch this problem, emerging communication and sensing technologies are generating a massive amount of data, requiring distributed environments to perform computation tasks across smart city administrative domains. In this article, we implement and test a number of state-of-the-art active concept drift detection algorithms for time series analysis within a distributed environment. We use real-world data streams and provide critical analysis of results retrieved. The challenges of implementing concept drift adaptation algorithms, along with their applications in smart cities, are also discussed. Citation: Smart Cities PubDate: 2021-03-14 DOI: 10.3390/smartcities4010021 Issue No:Vol. 4, No. 1 (2021)
Authors:Julio A. Sanguesa, Vicente Torres-Sanz, Piedad Garrido, Francisco J. Martinez, Johann M. Marquez-Barja First page: 372 Abstract: Electric Vehicles (EVs) are gaining momentum due to several factors, including the price reduction as well as the climate and environmental awareness. This paper reviews the advances of EVs regarding battery technology trends, charging methods, as well as new research challenges and open opportunities. More specifically, an analysis of the worldwide market situation of EVs and their future prospects is carried out. Given that one of the fundamental aspects in EVs is the battery, the paper presents a thorough review of the battery technologies—from the Lead-acid batteries to the Lithium-ion. Moreover, we review the different standards that are available for EVs charging process, as well as the power control and battery energy management proposals. Finally, we conclude our work by presenting our vision about what is expected in the near future within this field, as well as the research aspects that are still open for both industry and academic communities. Citation: Smart Cities PubDate: 2021-03-15 DOI: 10.3390/smartcities4010022 Issue No:Vol. 4, No. 1 (2021)
Authors:Robert Basmadjian First page: 405 Abstract: An electric mobility ecosystem, which resembles a human-centred cyber physical (HCP) system, consists of several interacting sub-systems that constantly communicate with each other. Cyber-security of such systems is an important aspect as vulnerability of one sub-system propagates to the entire system, thus putting it into risk. Risk assessment requires modelling of threats and their impacts on the system. Due to lack of available information on all possible threats of a given system, it is generally more convenient to assess the level of vulnerabilities either qualitatively or semi-quantitatively. In this paper, we adopt the common vulnerability scoring system (CVSS) methodology in order to assess semi-quantitatively the vulnerabilities of the communication in electric mobility human-centred cyber physical systems. To this end, we present the most relevant sub-systems, their roles as well as exchanged information. Furthermore, we give the considered threats and corresponding security requirements. Using the CVSS methodology, we then conduct an analysis of vulnerabilities for every pair of communicating sub-systems. Among them, we show that the sub-systems between charging station operator (CSO) and electric vehicle supply equipment (charging box) as well as CSO and electric mobility service provider are the most vulnerable in the end-to-end chain of electric mobility. These results pave the way to system designers to assess the operational security risks, and hence to take the most adequate decisions, when implementing such electric mobility HCP systems. Citation: Smart Cities PubDate: 2021-03-20 DOI: 10.3390/smartcities4010023 Issue No:Vol. 4, No. 1 (2021)
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