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Territoire en Mouvement     Open Access  
Territories : A Trans-Cultural Journal of Regional Studies     Open Access   (Followers: 1)
Territorio     Full-text available via subscription  
Territorio della Ricerca su Insediamenti e Ambiente. Rivista internazionale di cultura urbanistica     Open Access  
Territorios     Open Access  
Territorios en formación     Open Access  
The Journal of Real Estate Finance and Economics     Hybrid Journal   (Followers: 18)
The Urban Review     Hybrid Journal   (Followers: 18)
Tidsskrift for boligforskning     Open Access  
Tidsskrift for Kortlægning og Arealforvaltning     Open Access  
Town and Regional Planning     Open Access   (Followers: 10)
Town Planning and Architecture     Open Access   (Followers: 10)
Town Planning Review     Hybrid Journal   (Followers: 7)
UPLanD - Journal of Urban Planning, Landscape & environmental Design     Open Access   (Followers: 3)
Urban     Open Access   (Followers: 3)
Urban Affairs Review     Hybrid Journal   (Followers: 17)
URBAN DESIGN International     Hybrid Journal   (Followers: 12)
Urban Ecosystems     Hybrid Journal   (Followers: 11)
Urban Forum     Hybrid Journal   (Followers: 5)
Urban Geography     Hybrid Journal   (Followers: 32)
Urban Governance     Open Access   (Followers: 4)
Urban Land     Free   (Followers: 2)
Urban Planning     Open Access   (Followers: 5)
Urban Planning and Design Research     Open Access   (Followers: 12)
Urban Policy and Research     Hybrid Journal   (Followers: 15)
Urban Studies     Hybrid Journal   (Followers: 65)
Urban Studies Research     Open Access   (Followers: 19)
Urban Transformations     Open Access  
Urban, Planning and Transport Research     Open Access   (Followers: 32)
Urbanisation     Hybrid Journal   (Followers: 1)
Urbano     Open Access  
Vitruvian     Open Access  
Vivienda y Ciudad     Open Access  
WPS Review International on Sustainable Housing and Urban Renewal     Open Access   (Followers: 5)
Yhdyskuntasuunnittelu     Open Access  
ZARCH : Journal of Interdisciplinary Studies in Architecture and Urbanism     Open Access  

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Smart Cities
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ISSN (Online) 2624-6511
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  • Smart Cities, Vol. 5, Pages 1-21: Making a Building Smart with a
           Co-Created and Continuously Evolving Enjoyable Service
           Entity—Insights from a Collaborative Study

    • 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)
  • Smart Cities, Vol. 4, Pages 1243-1258: Identifying and Quantifying Factors
           Determining Dynamic Vanpooling Use

    • 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)
  • Smart Cities, Vol. 4, Pages 1259-1275: The Favela as a Place for the
           Development of Smart Cities in Brazil: Local Needs and New Business

    • 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)
  • Smart Cities, Vol. 4, Pages 1276-1292: Role of Internet of Things (IoT)
           and Crowdsourcing in Smart City Projects

    • 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)
  • Smart Cities, Vol. 4, Pages 1293-1315: Use of Machine Learning for Leak
           Detection and Localization in Water Distribution Systems

    • 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)
  • Smart Cities, Vol. 4, Pages 1316-1336: Requirements and Architecture of a
           Cloud Based Insomnia Therapy and Diagnosis Platform: A Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 1337-1365: Scaling up Smart City Logistics
           Projects: The Case of the Smooth Project

    • 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)
  • Smart Cities, Vol. 4, Pages 1366-1390: An Anthropocentric and Enhanced
           Predictive Approach to Smart City Management

    • 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)
  • Smart Cities, Vol. 4, Pages 1391-1402: Evaluating the Dynamic Impact of
           Theater Performances and Sports Events on Parking Demand in Downtown

    • 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)
  • Smart Cities, Vol. 4, Pages 1403-1419: Characteristics and Problems of
           Smart City Development in China

    • 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)
  • Smart Cities, Vol. 4, Pages 1420-1436: A Review of Energy Modeling Tools
           for Energy Efficiency in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 1437-1453: Management of Local Citizen Energy
           Communities and Bilateral Contracting in Multi-Agent Electricity Markets

    • 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)
  • Smart Cities, Vol. 4, Pages 1454-1468: Augmented Reality in Precision
           Farming: Concepts and Applications

    • 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)
  • Smart Cities, Vol. 4, Pages 1469-1495: Towards a Novel Air–Ground
           Intelligent Platform for Vehicular Networks: Technologies, Scenarios, and

    • 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)
  • Smart Cities, Vol. 4, Pages 1496-1518: Real-Time Littering Activity
           Monitoring Based on Image Classification Method

    • 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)
  • Smart Cities, Vol. 4, Pages 952-973: A Smart City Economy Supported by
           Service Level Agreements: A Conceptual Study into the Waste Management

    • 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)
  • Smart Cities, Vol. 4, Pages 971-978: Technological Developments of
           Mobility in Smart Cities. An Economic Approach

    • 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)
  • Smart Cities, Vol. 4, Pages 979-994: IoT-Based Sanitizer Station Network:
           A Facilities Management Case Study on Monitoring Hand Sanitizer Dispenser

    • 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)
  • Smart Cities, Vol. 4, Pages 995-1003: Using IoT in Supply Chain Risk
           Management, to Enable Collaboration between Business, Community, and

    • 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)
  • Smart Cities, Vol. 4, Pages 1004-1017: IoT-Enabled Solid Waste Management
           in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 1018-1038: A Holistic Intersection Rating
           System (HIRS)—A Novel Methodology to Measure the Holistic Operational
           Performance of Signalized Urban Intersections

    • 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)
  • Smart Cities, Vol. 4, Pages 1039-1057: Electric Vehicle Integration into
           Road Transportation, Intelligent Transportation, and Electric Power
           Systems: An Abu Dhabi Case Study

    • 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)
  • Smart Cities, Vol. 4, Pages 1058-1086: iBikeSafe: A Multi-Parameter System
           for Monitoring, Evaluation and Visualization of Cycling Paths in Smart
           Cities Targeted at Cycling Adverse Conditions

    • 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)
  • Smart Cities, Vol. 4, Pages 1087-1103: A Data-Driven Situational Awareness
           System for Enhanced Air Cargo Operations Emergency Control

    • 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)
  • Smart Cities, Vol. 4, Pages 1104-1112: Dynamic Restaurants Quality Mapping
           Using Online User Reviews

    • 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)
  • Smart Cities, Vol. 4, Pages 1113-1129: Determinants of Smart City
           Commitment among Citizens from a Middle City in Argentina

    • 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)
  • Smart Cities, Vol. 4, Pages 1130-1145: The “ReadyPark” Collaborative
           Parking Search Strategy

    • 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)
  • Smart Cities, Vol. 4, Pages 1146-1157: Intrusion Detection in Critical
           Infrastructures: A Literature Review

    • 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)
  • Smart Cities, Vol. 4, Pages 1158-1172: Data Co-Operatives through Data

    • 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)
  • Smart Cities, Vol. 4, Pages 1173-1195: Optimal Planning of Electrical
           Appliance of Residential Units in a Smart Home Network Using Cloud

    • 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)
  • Smart Cities, Vol. 4, Pages 1196-1219: Cloud-Based IoT Applications and
           Their Roles in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 1220-1243: Application of Deep Learning on
           UAV-Based Aerial Images for Flood Detection

    • 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)
  • Smart Cities, Vol. 4, Pages 429-475: IoT in Smart Cities: A Survey of
           Technologies, Practices and Challenges

    • 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)
  • Smart Cities, Vol. 4, Pages 476-498: Energy Harvesting Mechanisms in a
           Smart City—A Review

    • 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)
  • Smart Cities, Vol. 4, Pages 499-513: An Enhanced Inverse Filtering
           Methodology for Drive-By Frequency Identification of Bridges Using
           Smartphones in Real-Life Conditions

    • 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)
  • Smart Cities, Vol. 4, Pages 514-531: Homo Digitus: Its Dependable and
           Resilient Smart Ecosystem

    • 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)
  • Smart Cities, Vol. 4, Pages 532-547: An Incentive Based Dynamic
           Ride-Sharing System for Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 548-568: Artificial Intelligence Techniques in
           Smart Grid: A Survey

    • 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)
  • Smart Cities, Vol. 4, Pages 569-587: Experimentation Platforms as Bridges
           to Urban Sustainability

    • 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)
  • Smart Cities, Vol. 4, Pages 588-622: A Comprehensive Framework for
           Analyzing IoT Platforms: A Smart City Industrial Experience

    • 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)
  • Smart Cities, Vol. 4, Pages 623-642: Smart Parking Systems: Reviewing the
           Literature, Architecture and Ways Forward

    • 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)
  • Smart Cities, Vol. 4, Pages 643-661: Smart City Solution Engineering

    • 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)
  • Smart Cities, Vol. 4, Pages 662-685: Vehicular Crowdsourcing for
           Congestion Support in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 686-716: Towards a Digital Ecosystem for a
           Smart City District: Procedure, Results, and Lessons Learned

    • 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)
  • Smart Cities, Vol. 4, Pages 717-727: Rider Perceptions of an On-Demand
           Microtransit Service in Salt Lake County, Utah

    • 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)
  • Smart Cities, Vol. 4, Pages 728-745: Conceptual Technological Framework
           for Smart Cities to Move towards Decentralized and User-Centric
           Architectures Using DLT

    • 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)
  • Smart Cities, Vol. 4, Pages 746-766: A Study of Spatiotemporal
           Distribution of Mobility-On-Demand in Generating Pick-Up/Drop-Offs
           Location Placement

    • 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)
  • Smart Cities, Vol. 4, Pages 767-782: Working across Boundaries in Urban
           Land Use and Services Planning—Building Public Sector Capabilities for

    • 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)
  • Smart Cities, Vol. 4, Pages 783-802: AI Perspectives in Smart Cities and
           Communities to Enable Road Vehicle Automation and Smart Traffic Control

    • 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)
  • Smart Cities, Vol. 4, Pages 803-818: An Internet of Thing Architecture
           Based on Message Queuing Telemetry Transport Protocol and Node-RED: A Case
           Study for Monitoring Radon Gas

    • 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)
  • Smart Cities, Vol. 4, Pages 819-839: Disaster Management in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 840-863: The Role of Local Citizen Energy
           Communities in the Road to Carbon-Neutral Power Systems: Outcomes from a
           Case Study in Portugal

    • 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)
  • Smart Cities, Vol. 4, Pages 864-880: Macroscopic Lane Change Model—A
           Flexible Event-Tree-Based Approach for the Prediction of Lane Change on
           Freeway Traffic

    • 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)
  • Smart Cities, Vol. 4, Pages 881-893: Smart Accounts for Decentralized
           Governance on Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 894-918: Mobile Networks and Internet of
           Things Infrastructures to Characterize Smart Human Mobility

    • 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)
  • Smart Cities, Vol. 4, Pages 919-937: An IoT-Based Participatory Antitheft
           System for Public Safety Enhancement in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 938-951: Food Desires, Negative Emotions and
           Behaviour Change Techniques: A Computational Analysis

    • 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)
  • Smart Cities, Vol. 4, Pages 78-92: Smart Data-Driven Policy on Unmanned
           Aircraft Systems (UAS): Analysis of Drone Users in U.S. Cities

    • Authors: Yu-Che Chen, Chenyu Huang
      First page: 78
      Abstract: Realizing the benefits of drones while minimizing public concerns requires development and implementation of drone use policies that are grounded in an understanding of drone users and their behavior. This study aims to contribute to data-driven smart cities by filling our gap in knowledge about city drone users and their compliance behavior. The literature review has identified the main factors affecting drone policy compliance. This study collects data via a national survey of adults on drone behavior and focuses on city drone users. The results show that city drone users are younger with more dispersed educational backgrounds and income distribution than those in the general population. Moreover, civic duty, trust in government, and knowledge about regulatory requirements are motivators for drone users to comply with drone regulation.
      Citation: Smart Cities
      PubDate: 2021-01-07
      DOI: 10.3390/smartcities4010005
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 93-111: Introducing the “15-Minute City”:
           Sustainability, Resilience and Place Identity in Future Post-Pandemic

    • Authors: Carlos Moreno, Zaheer Allam, Didier Chabaud, Catherine Gall, Florent Pratlong
      First page: 93
      Abstract: The socio-economic impacts on cities during the COVID-19 pandemic have been brutal, leading to increasing inequalities and record numbers of unemployment around the world. While cities endure lockdowns in order to ensure decent levels of health, the challenges linked to the unfolding of the pandemic have led to the need for a radical re-think of the city, leading to the re-emergence of a concept, initially proposed in 2016 by Carlos Moreno: the “15-Minute City”. The concept, offering a novel perspective of “chrono-urbanism”, adds to existing thematic of Smart Cities and the rhetoric of building more humane urban fabrics, outlined by Christopher Alexander, and that of building safer, more resilient, sustainable and inclusive cities, as depicted in the Sustainable Development Goal 11 of the United Nations. With the concept gaining ground in popular media and its subsequent adoption at policy level in a number of cities of varying scale and geographies, the present paper sets forth to introduce the concept, its origins, intent and future directions.
      Citation: Smart Cities
      PubDate: 2021-01-08
      DOI: 10.3390/smartcities4010006
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 112-145: Interdependencies of Infrastructure
           Investment Decisions in Multi-Energy Systems—A Sensitivity Analysis for
           Urban Residential Areas

    • Authors: Daniel Then, Johannes Bauer, Tanja M. Kneiske, Martin Braun
      First page: 112
      Abstract: Considering the European Union (EU) climate targets, the heating sector should be decarbonized by 80 to 95% up to 2050. Thus, the macro-trends forecast increasing energy efficiency and focus on the use of renewable gas or the electrification of heat generation. This has implications for the business models of urban electricity and in particular natural gas distribution network operators (DNOs): When the energy demand decreases, a disproportionately long grid is operated, which can cause a rise of grid charges and thus the gas price. This creates a situation in which a self-reinforcing feedback loop starts, which increases the risk of gas grid defection. We present a mixed integer linear optimization model to analyze the interdependencies between the electricity and gas DNOs’ and the building owners’ investment decisions during the transformation path. The results of the investigation in a real grid area are used to validate the simulation setup of a sensitivity analysis of 27 types of building collectives and five grid topologies, which provides a systematic insight into the interrelated system. Therefore, it is possible to identify building and grid configurations that increase the risk of a complete gas grid shutdown and those that should be operated as a flexibility option in a future renewable energy system.
      Citation: Smart Cities
      PubDate: 2021-01-08
      DOI: 10.3390/smartcities4010007
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 146-155: Miniaturized Pervasive Sensors for
           Indoor Health Monitoring in Smart Cities

    • Authors: Marco Carminati, Ganesh R. Sinha, Samrudhi Mohdiwale, Silvia L. Ullo
      First page: 146
      Abstract: Sensors and electronics technologies are pivotal in several fields of science and engineering, especially in automation, industry and environment monitoring. Over the years, there have been continuous changes and advancements in design and miniaturization of sensors with the growth of their application areas. Challenges have arisen in the deployment, fabrication and calibration of modern sensors. Therefore, although the usage of sensors has greatly helped improving the quality of life, especially through their employment in many IoT (Internet of Things) applications, some threats and safety issues still remain unaddressed. In this paper, a brief review focusing on pervasive sensors used for health and indoor environment monitoring is given. Examples of technology advancements in air, water and radioactivity are discussed. This bird’s eye view suggests that solid-state pervasive sensors have become essential parts of all emerging applications related to monitoring of health and safety. Miniaturization, in combination with gamification approaches and machine learning techniques for processing large amounts of captured data, can successfully address and solve many issues of massive deployment. The development paradigm of Smart Cities should include both indoor and outdoor scenarios.
      Citation: Smart Cities
      PubDate: 2021-01-10
      DOI: 10.3390/smartcities4010008
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 156-176: Sustainable and Reliable Information
           and Communication Technology for Resilient Smart Cities

    • Authors: Nikolay Tcholtchev, Ina Schieferdecker
      First page: 156
      Abstract: Information and Communication Technology (ICT) is at the heart of the smart city approach, which constitutes the next level of cities’ and communities’ development across the globe. Thereby, ICT serves as the gluing component enabling different domains to interact with each other and facilitating the management and processing of vast amounts of data and information towards intelligently steering the cities’ infrastructure and processes, engaging the citizens and facilitating new services and applications in various aspects of urban life—e.g., supply chains, mobility, transportation, energy, citizens’ participation, public safety, interactions between citizens and the public administration, water management, parking and many other cases and domains. Hence, given the fundamental role of ICT in cities in the near future, it is of paramount importance to lay the ground for a sustainable and reliable ICT infrastructure, which can enable a city/community to respond in a resilient way to upcoming challenges, whilst increasing the quality of life for its citizens. A structured way of providing and maintaining an open and resilient ICT backbone for a city/community is constituted by the concept of an Open Urban Platform. Therefore, the current article presents the activities and developments necessary to achieve a resilient, standardized smart city, based on Open Urban Platforms (OUP) and the way these serve as a blueprint for each city/community towards the establishment of a sustainable and resilient ICT backbone.
      Citation: Smart Cities
      PubDate: 2021-01-14
      DOI: 10.3390/smartcities4010009
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 177-191: A Predictive Vehicle Ride Sharing
           Recommendation System for Smart Cities Commuting

    • Authors: Theodoros Anagnostopoulos
      First page: 177
      Abstract: Smart Cities (or Cities 2.0) are an evolution in citizen habitation. In such cities, transport commuting is changing rapidly with the proliferation of contemporary vehicular technology. New models of vehicle ride sharing systems are changing the way citizens commute in their daily movement schedule. The use of a private vehicle per single passenger transportation is no longer viable in sustainable Smart Cities (SC) because of the vehicles’ resource allocation and urban pollution. The current research on car ride sharing systems is widely expanding in a range of contemporary technologies, however, without covering a multidisciplinary approach. In this paper, the focus is on performing a multidisciplinary research on car riding systems taking into consideration personalized user mobility behavior by providing next destination prediction as well as a recommender system based on riders’ personalized information. Specifically, it proposes a predictive vehicle ride sharing system for commuting, which has impact on the SC green ecosystem. The adopted system also provides a recommendation to citizens to select the persons they would like to commute with. An Artificial Intelligence (AI)-enabled weighted pattern matching model is used to assess user movement behavior in SC and provide the best predicted recommendation list of commuting users. Citizens are then able to engage a current trip to next destination with the more suitable user provided by the list. An experimented is conducted with real data from the municipality of New Philadelphia, in SC of Athens, Greece, to implement the proposed system and observe certain user movement behavior. The results are promising for the incorporation of the adopted system to other SCs.
      Citation: Smart Cities
      PubDate: 2021-01-27
      DOI: 10.3390/smartcities4010010
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 192-194: Acknowledgment to Reviewers of Smart
           Cities in 2020

    • Authors: Smart Cities Editorial Office Smart Cities Editorial Office
      First page: 192
      Abstract: Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Smart Cities maintains its standards for the high quality of its published papers [...]
      Citation: Smart Cities
      PubDate: 2021-01-27
      DOI: 10.3390/smartcities4010011
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 195-203: Quality Control Methods for Advanced
           Metering Infrastructure Data

    • Authors: Eric Garrison, Joshua New
      First page: 195
      Abstract: While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.
      Citation: Smart Cities
      PubDate: 2021-01-28
      DOI: 10.3390/smartcities4010012
      Issue No: Vol. 4, No. 1 (2021)
  • Smart Cities, Vol. 4, Pages 204-216: Spatiotemporal Prediction of Theft
           Risk with Deep Inception-Residual Networks

    • 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)
  • Smart Cities, Vol. 4, Pages 217-240: Transfer Learning by Similarity
           Centred Architecture Evolution for Multiple Residential Load Forecasting

    • 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)
  • Smart Cities, Vol. 4, Pages 241-252: New Energy Policy Directions in the
           European Union Developing the Concept of Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 253-270: A Dynamic Mobility Traffic Model
           Based on Two Modes of Transport in Smart Cities

    • 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)
  • Smart Cities, Vol. 4, Pages 271-285: TreeVibes: Modern Tools for Global
           Monitoring of Trees for Borers

    • 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)
  • Smart Cities, Vol. 4, Pages 286-313: Smart Cities and Big Data Analytics:
           A Data-Driven Decision-Making Use Case

    • 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)
  • Smart Cities, Vol. 4, Pages 314-335: A Review of Car-Following Models and
           Modeling Tools for Human and Autonomous-Ready Driving Behaviors in

    • 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)
  • Smart Cities, Vol. 4, Pages 336-348: Direct Passive Participation: Aiming

    • 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)
  • Smart Cities, Vol. 4, Pages 349-371: Concept Drift Adaptation Techniques
           in Distributed Environment for Real-World Data Streams

    • 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)
  • Smart Cities, Vol. 4, Pages 372-404: A Review on Electric Vehicles:
           Technologies and Challenges

    • 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)
  • Smart Cities, Vol. 4, Pages 405-428: Communication Vulnerabilities in
           Electric Mobility HCP Systems: A Semi-Quantitative Analysis

    • 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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