JournalTOCs

Drone Systems and Applications
Number of Followers: 1

This is an Open Access Journal

Open Access journal
ISSN (Online) 2564-4939
Published by NRC Research Press

[19 journals]

Note of appreciation
- Pages: i - i
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page i-i, January 2024.
  
  Citation: Drone Systems and Applications
  PubDate: 2024-01-09T08:00:00Z
  DOI: 10.1139/dsa-2023-0074
  Issue No: Vol. 12 (2024)
A methodological approach to rock art survey and recording via drone. The
application to the Rock Art of the Mediterranean Basin of the Iberian
Peninsula assemblage
- Authors: Francisco Javier Molina Hernández, Virginia Barciela González, Juan F. Ruiz López, Ximo Martorell Briz
  Pages: 1 - 18
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-18, January 2024.
  The significant advancement in drone technology has led to increased usage across different scientific domains. In the field of archaeology, drones became increasingly popular a decade ago, primarily for photogrammetric documentation or aerial photography. Since then, researchers have experimented with new applications, notably utilizing LiDAR imagery to enhance archaeological surveying. In this context, one of the latest applications involves surveying open-air rock art shelters in inaccessible locations to search for prehistoric rock art imagery. The current study involves refining the methodology used for this purpose in the territory of UNESCO’s World Heritage List property Rock Art of the Mediterranean Basin of the Iberian Peninsula, utilizing a DJI Mavic 3 drone, which represents a significant improvement over previous models. On the other hand, it highlights the potential for its utilization in conservation studies and managing human activity in their environments, considering the threats to which these sites are currently exposed.
  Citation: Drone Systems and Applications
  PubDate: 2024-07-02T07:00:00Z
  DOI: 10.1139/dsa-2023-0134
  Issue No: Vol. 12 (2024)
Modifying a mini drone for remote drug delivery for wildlife medicine
- Authors: Marnoch Yindee, Patcharapol Khumngoen, Wallaya Manatchaiworakul, Tuempong Wongtawan
  Pages: 1 - 6
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-6, January 2024.
  Remote drug delivery is an essential tool for administering medication to wildlife. However, the conventional method, the dart gun, has limitations in terms of injection distance, posing risks for operators. This study aimed to modify a mini drone equipped with a dart syringe and delivery system for use with large wildlife. A commercial mini drone was modified to release a syringe dart using a vertical gravity-based delivery system. The performance of the drone and delivery system was evaluated based on accuracy to the target and penetration ability through pig skin. The evaluation compared a dart with or without a plastic shell, with tests conducted both indoors and outdoors. The results indicated that the higher the drone’s flight, the more the dart tended to deviate from the target. In outdoor tests, a syringe dart without a shell showed greater accuracy than a dart with a shell. Regarding penetration ability, only a dart without a shell had a 100% success rate at a maximum height of 5 m, with an overall statistical difference (P = 0.01). In conclusion, this study represents the first scientific validation of using mini drones for remote drug injections that could be used in large wildlife medicine.
  Citation: Drone Systems and Applications
  PubDate: 2024-06-26T07:00:00Z
  DOI: 10.1139/dsa-2024-0015
  Issue No: Vol. 12 (2024)
A systematic review on metaheuristic approaches for autonomous path
planning of unmanned aerial vehicles
- Authors: Sameer Agrawal, Bhumeshwar K. Patle, Sudarshan Sanap
  Pages: 1 - 28
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-28, January 2024.
  In the path planning of UAVs, autonomous decision-making and control are challenging tasks in the uncertain 3D environment consisting of static and dynamic obstacles. Hence, the selection of appropriate path-planning approaches is essential. In the proposed work, we have considered the meta-heuristic approaches only for an in-depth review. Metaheuristic approaches have been remarkably known for solving complex problems, optimal solutions, and lesser computational complexity compared to deterministic approaches that produce an inefficient solution. An in-depth review has been made by considering the approaches used for path planning, their advantages, disadvantages, applications, the type of time domain (offline or online), type of environment (simulation or real time), hybridization with other approaches, single or multiple UAV system, and obstacle handled (static or dynamic). It is observed that current meta-heuristic methods face constraints like inadequate convergence rates, entrapment in local optima, and complex operations, necessitating continuous development of novel approaches. Implementation of path-planning approaches are very much limited to simulation study over experimental analysis. Hybrid algorithms emerge as a potential solution for tackling these hurdles and optimizing UAV navigation, particularly in dynamic environments involving multiple UAVs. The paper highlights key research gaps, trends, along with prospects in the field of research.
  Citation: Drone Systems and Applications
  PubDate: 2024-06-06T07:00:00Z
  DOI: 10.1139/dsa-2023-0093
  Issue No: Vol. 12 (2024)
Multi-sensor data fusion for autonomous flight of unmanned aerial vehicles
in complex flight environments
- Authors: Kun Yue
  Pages: 1 - 12
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-12, January 2024.
  The flight environment of unmanned aerial vehicles faces various challenges. To effectively navigate and perform tasks, they need to effectively integrate multiple sensors. This study applies the adaptive weighted average method, combined with data from global positioning system, inertial measurement unit, three-dimensional optical detection and ranging, and uses linear Kalman filtering to smooth the merged velocity data. High-order B-spline curves for route planning and applying flight constraint formulas to better adapt are used to the dynamics of unmanned aerial vehicles. The research results indicated that the improved adaptive weighting algorithm had high comprehensive performance for multi-sensor data fusion, with the highest accuracy, robustness, real-time performance, and consistency of 94.2%, 93.7%, 100%, and 95.6%, respectively. The flight path lengths planned by the A* algorithm and higher-order B-spline curve were 15.7 and 16.3 m, respectively, and the flight time was 8.2 and 7.1 s, respectively. The flight path planned by higher-order B-spline curve was further away from obstacles. The use of adaptive weighted fusion and linear Kalman filtering facilitates the fusion of multi-sensor data, and autonomous flight routes planned using high-order B-spline curves can also meet the needs of unmanned aerial vehicle flight in complex flight environments.
  Citation: Drone Systems and Applications
  PubDate: 2024-06-05T07:00:00Z
  DOI: 10.1139/dsa-2024-0005
  Issue No: Vol. 12 (2024)
Thermal-based gender recognition using drones: advancing biometric
recognition in challenging outdoor environments
- Authors: Kateřina Příhodová, Jakub Jech
  Pages: 1 - 9
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-9, January 2024.
  While biometric recognition typically uses features such as face, fingerprint, and iris to identify individuals, this study focuses on utilising specific characteristics to identify gender. The aim of this article is to propose a procedure for gender recognition under specific conditions. The specific condition addressed is outdoor area monitoring, which presents challenges such as varying lighting conditions and limited camera placement options. To tackle this, a proposed procedure utilises thermal images captured by the drone equipped with a thermal camera. The advantage of thermal images is their independence from ambient light conditions. The captured images are resized and processed using convolutional neural networks (CNNs) (AlexNet, VGG-16, VGG-19) for feature extraction and binary classification. A freely available database of thermal face images is used for training the CNNs, while a own created dataset of thermal images obtained by the drone is used for testing. The findings indicate that the optimised CNNs achieve classification accuracies of 82.4% (VGG-16), 82.9% (AlexNet), and 85.5% (VGG-19). The original contribution of this study lies in demonstrating the suitability of face thermal images obtained through drones for gender recognition purposes.
  Citation: Drone Systems and Applications
  PubDate: 2024-05-30T07:00:00Z
  DOI: 10.1139/dsa-2023-0075
  Issue No: Vol. 12 (2024)
Towards drone-based magnetometer measurements for archaeological
prospection in challenging terrain
- Authors: Volkmar Schmidt, Joris Coolen, Thomas Fritsch, Stefan Klingen
  Pages: 1 - 15
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-15, January 2024.
  While airborne magnetometry has been used for geological surveys for decades, magnetic surveys for archaeological prospection are almost exclusively ground-based, as the detection of archaeological features requires higher spatial resolution and close proximity between sensor and object. However, the recent development of drones and magnetic sensors allows for low-altitude drone-based surveys, which are an interesting alternative for magnetic prospection of challenging areas, where vegetation, difficult terrain, access restrictions, or safety concerns hamper ground-based surveys. In this paper, we present test measurements in challenging areas in Germany and Switzerland, which demonstrate the potential as well as technical and practical concerns of drone-based magnetometry for archaeological prospection. We used a miniature total-field magnetometer, which was tethered to an octocopter drone. Although it is preferable to fly the sensor close to the ground where anomalies show the highest values, we could also detect magnetic anomalies in altitudes up to few metres above ground. Flights at different altitudes show the decay and widening of the anomalies with height. Drone-based magnetic measurements in rough and vegetated terrain require careful flight planning based on a high-resolution surface model. Further development is needed to improve positioning accuracy of the tethered magnetometer and to improve heading error correction.
  Citation: Drone Systems and Applications
  PubDate: 2024-05-29T07:00:00Z
  DOI: 10.1139/dsa-2023-0128
  Issue No: Vol. 12 (2024)
A critical theory of the drone in archaeology: on space, epistemology, and
automation
- Authors: Daniel Carvalho
  Pages: 1 - 7
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-7, January 2024.
  This article seeks to establish a theoretical framework surrounding the drone and its use in archaeology. More than just a tool, this vehicle has revolutionized not only the practice of the discipline but also the way archaeologists approach their object of study. To highlight its theoretical components, we have established a dialog with the philosophy of technology and the archaeological dimension, to understand the implications and impositions that the drone implies for the activities of archaeologists. Passing through the verticalization of the gaze, the machinic rhythms and choreographies, and, finally, the theme of automation, we understand that the theory of the drone in archaeology is fertile ground for a critique of how technique shapes the discipline.
  Citation: Drone Systems and Applications
  PubDate: 2024-05-13T07:00:00Z
  DOI: 10.1139/dsa-2023-0142
  Issue No: Vol. 12 (2024)
Precision pest control using purpose-built uncrewed aerial system (UAS)
technology and a novel bait pod system
- Authors: Craig G. Morley, Philip Solaris, Greg O. Quinn, Kathryn E. Ross, Bruce J. Peterson
  Pages: 1 - 13
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-13, January 2024.
  Controlling invasive species is imperative due to their significant roles in spreading diseases, preying on threatened species, and diminishing biodiversity. Crewed aircraft are proficient at dispersing toxic bait across vast expanses to combat small pest mammals such as possums and rats. However, their utility diminishes significantly in small, remote areas typified by rugged terrain due to impracticality and prohibitive costs. Similarly, while ground control operations are effective in compact, easily reachable locations, they encounter formidable obstacles like costly labour expenses, safety hazards, and the peril of worker injuries while navigating treacherous landscapes. An innovative approach to address these limitations is to use uncrewed aerial systems that are unhampered by the terrain to deploy bait at precise locations. Our team engineered a purpose-built system designed specifically for deploying bait using innovative bait pods. Two field trials were conducted in New Zealand to validate our systems’ efficacy, assessing deployment precision and accuracy against predefined ground targets. While the initial trial yielded mixed results, significant improvements were observed in the subsequent trial, featuring enhancements to the bait pod design. The median deployment accuracy achieved was 1.91 m from the target (n = 63), with no statistically significant difference in deployment accuracy between open and forested areas (p = 0.76). This advanced system permits the precise placement of bait pods to any location, facilitating effective pest control within complex landscapes, challenging terrain, and dense vegetation. With its smart functionality and adaptability, this system can be utilised across various aircraft and autopilot systems to ensure maximum accuracy and efficiency in delivering bait pods for pest control operations. Therefore, this innovative tool possesses tremendous potential for managing small mammalian invasive species, particularly in specialised environments such as reserves, gullies, and islands, complementing existing pest control strategies to expedite the restoration of ecosystems and safeguard biodiversity.
  Citation: Drone Systems and Applications
  PubDate: 2024-05-02T07:00:00Z
  DOI: 10.1139/dsa-2023-0104
  Issue No: Vol. 12 (2024)
Network analysis of decentralized fault-tolerant UAV swarm coordination in
critical missions
- Authors: Indu Chandran, Kizheppatt Vipin
  Pages: 1 - 15
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-15, January 2024.
  Unmanned aerial vehicles (UAVs) have gained prominence across various sectors for their versatile applications. While their advantages are evident, addressing concerns associated with their deployment is essential to ensure reliability. This study presents an innovative approach for coordinating a group of UAVs in aerial survey missions. The decentralized strategy presented in this article allow UAVs to self-organize into linear formation, optimize their coverage paths, and adapt to agent failures, thereby ensuring efficient and adaptive mission execution. The strategy has been tested and validated on two different platforms: the inter-UAV communication performance is evaluated on NS-3 simulator to measure metrices such as packet delivery ratio, throughput, delay, and routing overhead within the UAV swarms, while mission efficiency and fault tolerance is analyzed on robot operating system framework, and visualized on Gazebo simulator with real-time parameters. Through experimental results, we show that, after proper tuning of control parameters, the approach succeeds in flock formation with high level of fault tolerance, offering higher efficiency in terms of mission time, transmission delay, packet delivery rate, and control overhead, when compared to the benchmark approaches.
  Citation: Drone Systems and Applications
  PubDate: 2024-05-01T07:00:00Z
  DOI: 10.1139/dsa-2023-0101
  Issue No: Vol. 12 (2024)
Drone-based mixed reality: enhancing visualization for large-scale outdoor
simulations with dynamic viewpoint adaptation using vision-based pose
estimation methods
- Authors: Airi Kinoshita, Tomohiro Fukuda, Nobuyoshi Yabuki
  Pages: 1 - 19
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-19, January 2024.
  In recent years, there has been a growing interest in the integration of drones across diverse sectors, particularly within architecture, engineering, and construction (AEC). The amalgamation of drones with mixed reality (MR) stands out as a promising avenue. Proposed applications include the comparison of design and actual objects, as well as landscape simulation in urban design. A previous study successfully developed a drone-viewpoint MR system with low model dependence, leveraging general drones and methods. However, the alignment between the real and virtual worlds was contingent on predefined flight routes, limiting adaptability during MR execution. This study introduces a new model-independent drone viewpoint MR system that integrates two vision-based attitude estimation methods, enabling execution on arbitrary flight paths. Evaluation of the prototype for system latency and alignment accuracy revealed an overall latency of 3.5 s. The alignment accuracy, assessed using intersection over union, demonstrated performance equal to or surpassing the previous system. While this paper does not showcase MR content for practical use, the research lays the groundwork for advancing drone applications in the AEC field. The proposed system offers versatility for MR applications across various stages, from design to maintenance.
  Citation: Drone Systems and Applications
  PubDate: 2024-04-29T07:00:00Z
  DOI: 10.1139/dsa-2023-0135
  Issue No: Vol. 12 (2024)
Terra-22: an aerial soil sampling in densely compacted agricultural fields
- Authors: Hugo B. Klopfenstein, Alexis Lussier Desbiens
  Pages: 1 - 14
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-14, January 2024.
  Soil sampling is used in agriculture to monitor fields and plan fertilizer application. This task is typically performed manually, but ground robots have recently been introduced. However, ground robots are often slow and heavy, which contributes to soil compaction. Fast-flying drones could provide an interesting alternative to ground robots. However, drones are severely limited in their payload and in the forces that they can apply to the soil. This paper presents the Terra-22, the first airborne system capable of sampling densely compacted agricultural soils. To do so, many challenges were addressed, including the development of (i) a high-power density drilling system that outperforms typical brushed DC gear motor by 39%, (ii) a drill design that is 48% lighter than traditional steel auger drills and that keeps cross-contamination under 4%, and (iii) a drill penetration rate controller that reduces the torque requirement by 33% and the axial force requirement by eight folds when compared to a constant penetration speed controller. Outdoor soil sampling tests in a corn field (sandy loam soil, compaction between 0.8 and 2 MPa) demonstrated a 94% success rate on flat terrain and a sampling duration under one minute.
  Citation: Drone Systems and Applications
  PubDate: 2024-04-15T07:00:00Z
  DOI: 10.1139/dsa-2023-0010
  Issue No: Vol. 12 (2024)
UAV avionics safety, certification, accidents, redundancy, integrity, and
reliability: a comprehensive review and future trends
- Authors: Devon Wanner, Hashim A. Hashim, Siddhant Srivastava, Alex Steinhauer
  Pages: 1 - 23
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-23, January 2024.
  This paper underscores the significance of safety and reliability in the realm of unmanned aerial vehicle (UAV) technologies, and how regulations play a pivotal role in ensuring their responsible use. We have analyzed safety incidents and trends both in Canada and globally, noting a decline in incidents attributed to enhanced regulations. Our comparative analysis of different UAV technologies identified batteries as the most reliable power supply, Global Navigation Satellite System as the most effective navigation system, and light detection and ranging as the optimal optical sensor due to regulatory compliance and system redundancies. We also examined the regulatory framework in Canada, comparing it with the risk-based approach of the European Union Aviation Safety Agency and the efforts of Joint Authorities for Rule-making on Unmanned Systems towards global harmonization. Furthermore, we highlighted emerging trends in automation and flight control technologies, with a focus on European regulations shaping UAV automation trends. In conclusion, by adhering to best practices from other regulatory bodies, embracing emerging trends, and adopting a risk-based approach, Canada can promote the growth of the UAV industry while ensuring safety and reliability in UAV technologies.
  Citation: Drone Systems and Applications
  PubDate: 2024-04-10T07:00:00Z
  DOI: 10.1139/dsa-2023-0091
  Issue No: Vol. 12 (2024)
Using drones to measure the status of cavity-nesting raptors
- Authors: David M. Bird, Christina Petalas, Paul Pace, Kyle H. Elliott
  Pages: 1 - 7
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-7, January 2024.
  Many wildlife species, including hole-nesting raptors, occupy cavities that are challenging or unsafe for observers to examine. We conducted field tests using an inexpensive, off-the-shelf camera attached to an affordable commercial drone to assess the reproductive success of American kestrels (Falco sparverius), a small, cavity-nesting raptor. Specifically, we developed a system that consisted of (1) a wireless mini camera transmitting images to an observer’s phone and (2) a Mini-Mavic 2 drone controlled through direct line-of-sight piloting. Following successful preliminary flights involving chicken eggs and other inanimate objects, we field-tested the system in two kestrel nest boxes in the wild. The system accurately recorded the contents of all nest boxes during the trials, provided the wind speed remained below approximately 2.5 m/s (5 knots). However, wind speeds at this level were observed only 40% of the days in our study area during kestrel breeding, which limited the surveying opportunities. Our system offers a promising method for surveying wildlife inhabiting inaccessible cavities.
  Citation: Drone Systems and Applications
  PubDate: 2024-03-19T07:00:00Z
  DOI: 10.1139/dsa-2023-0121
  Issue No: Vol. 12 (2024)
Optimising camera and flight settings for ultrafine resolution mapping of
artificial night-time lights using an unoccupied aerial system
- Authors: Dipendra Bhattarai, Arko Lucieer
  Pages: 1 - 11
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-11, January 2024.
  Light pollution from artificial night-time lights (ANTLs) is a global health, economic, and environmental issue. Remote sensing and unoccupied aerial systems (UASs) provide efficient and cost-effective ways to study ANTL spatial patterns and dynamics over large areas. With ultrahigh-resolution images that can identify individual light sources, UAS offers more detailed image than satellite imagery. However, standardisation and optimisation of camera and flight settings during the acquisition ANTL UAS images is lacking. The aim of this paper is to determine the camera and flight settings to capture high-quality ANTL using a DJI Matrice 300 RTK aircraft with a Zenmuse P1 camera. It emphasises the importance of selecting appropriate camera settings for high-quality ANTL images, which can benefit future research. Results show significant image quality gains when camera and flight settings are chosen appropriately in relation to the lighting conditions. We present three experiments demonstrating a range of camera settings, and we provide practical recommendations for high-quality night-time image collection. The optimal camera settings were determined to be an exposure time of 0.0166 s, ISO of 25600, and aperture of 2.97. This experiment produced outstanding results, with 85% of images having a blur extent below 0.40.
  Citation: Drone Systems and Applications
  PubDate: 2024-03-19T07:00:00Z
  DOI: 10.1139/dsa-2023-0086
  Issue No: Vol. 12 (2024)
An assessment of survey techniques using unmanned aerial vehicles to
monitor Nile crocodiles (Crocodylus niloticus)
- Authors: Debbie Jewitt, Rickert Van Der Westhuisen, Adrian J. Armstrong
  Pages: 1 - 7
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-7, January 2024.
  Monitored populations of the Nile crocodile Crocodylus niloticus at the southern end of its distribution, in the KwaZulu-Natal province of South Africa, are largely in decline. Trophy hunting of wild Nile crocodiles is only permitted at Pongolapoort Dam in the province, and monitoring of this population is required to enable the setting of annual hunting quotas. The aims of this study were to determine the feasibility of using drones to count and measure Nile crocodiles in the inlet to the dam and evaluate the utility of photomosaics, individual photographs, and videos for this purpose. A total of 16.5 km of shoreline was surveyed and 183 sub-adult and adult crocodiles observed, averaging 10.74 crocodiles per kilometer. The use of drones was cost-effective compared to traditional survey methods even though a higher number of person hours were required for data collection and processing. We recommend that drones be used to acquire video footage, supplemented by photomosaics in areas where large aggregations of crocodiles occur, to regularly monitor this crocodile population.
  Citation: Drone Systems and Applications
  PubDate: 2024-03-14T07:00:00Z
  DOI: 10.1139/dsa-2023-0124
  Issue No: Vol. 12 (2024)
Seasonal Phragmites australis classification in Long Point National
Wildlife Area wetlands using a remotely piloted aircraft system and random
forest machine learning
- Authors: Morgan Hrynyk, Amir Behnamian, Sarah Banks, Zhaohua Chen, Taylor Harmer, Patrick Kirby, Lori White, Jon Pasher, Jason Duffe
  Pages: 1 - 13
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-13, January 2024.
  This study produced a high-accuracy remotely piloted aircraft system (RPAS) imagery classification method for identifying the invasive reed Phragmites australis (Cav.) Trin. Ex Steud subsp. australis using random forest (RF) machine learning. RPAS imagery was collected in the spring and fall of 2019 using a fixed-wing RPAS equipped with a visible spectrum camera (eBee X, S.O.D.A. 3D; senseFly) in Long Point, Ontario, Canada. Imagery was used to produce separate early and late season classifications and a bi-temporal classification which used imagery from both dates. The overall accuracy achieved for each was 97%, 96%, and 91%, respectively. Digital surface models (DSMs) were the most important variable for identifying Phragmites in all classifications due to their greater height when compared to surrounding herbaceous vegetation. The bi-temporal classification, which utilized change in DSM value during the growing season, resulted in an estimated 47.8% new growth of Phragmites and appeared to capture sparse growth better than traditional classification differencing alone. This study highlights the promising use of high-resolution DSMs produced from RPAS imagery to classify invasive Phragmites and monitor within-year patch expansions.
  Citation: Drone Systems and Applications
  PubDate: 2024-03-13T07:00:00Z
  DOI: 10.1139/dsa-2023-0082
  Issue No: Vol. 12 (2024)
Malicious UAV detection using various modalities
- Authors: Safaa Dafrallah, Moulay Akhloufi
  Pages: 1 - 18
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-18, January 2024.
  Unmanned aerial vehicles, also known as drones, have seen increasing interest in recent years. This surge of interest is based on technological advancements, enhanced performance, affordability, and their large array of applications. Despite their utility in various applications, drones could also be used for malicious intent. The increasing concern regarding malicious drones triggers the use of various technologies and countermeasures, including drone detection and counter-drone systems. In this paper, we raise concerns about the malicious use of drone systems by providing a brief description of the major security threats. We also present the architecture of unmanned aerial systems, drone types, and their communication methods. We provide an in-depth overview of various drone detection techniques including vision-based, radio-frequency-based, and audio-based techniques, and discuss recent studies that address this issue using machine learning and deep learning models. We highlight the importance of using a hybrid approach for more accurate results.
  Citation: Drone Systems and Applications
  PubDate: 2024-03-12T07:00:00Z
  DOI: 10.1139/dsa-2023-0049
  Issue No: Vol. 12 (2024)
Review of autonomous outdoor blimps and their applications
- Authors: Shantanu S. Bhat, Sreenatha G. Anavatti, Matthew Garratt, Sridhar Ravi
  Pages: 1 - 21
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-21, January 2024.
  Autonomous blimps have potential applications in surveillance, monitoring, and advertising. Due to their lower payload capacities and possible unstable flight profile, small blimps have been mostly used in indoor applications. However, recent advancements in their design and control have increased the prospects of deploying them for outdoor applications. This study presents a literature review of various aspects that encompass the unique elements of blimps’ design and operations followed by a discussion on the modern applications. The review focuses on advancements made in the fundamental attributes of blimps, including design, propulsion, navigation, and control. The review reveals that recent successes in using blimps for various missions, where heavier-than-air platforms have been usually used, highlight the potential for blimps to offer a lightweight and low-risk alternative. The relatively stable operation of blimps in low winds and longer-duration hovering capability can make them a preferred platform for rescue, source localization, and space applications. However, their stability in extreme environments is a challenge, in addition to their lower mobility and problems in accurately predicting control parameters. Thus, this review concludes with an overview of blimps’ futuristic applications of miniature blimps and recommendations to address the challenges in using them in real-world missions.
  Citation: Drone Systems and Applications
  PubDate: 2024-03-06T08:00:00Z
  DOI: 10.1139/dsa-2023-0052
  Issue No: Vol. 12 (2024)
Direct drive or slider-crank' Comparing motor-actuated flapping-wing
micro aerial vehicles
- Authors: Moonsoo Park, Ali Abolfathi
  Pages: 1 - 8
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-8, January 2024.
  For flapping-wing micro aerial vehicles, the common approach to converting the rotational motion of a DC motor to the reciprocal flapping motion is using a slider-crank mechanism. However, frictional losses in sliders and rotational joints can hinder the performance of such a system. An alternative is a direct drive system where the wings are directly connected to a DC motor that has been driven by an AC signal. These two approaches are compared in this paper, to evaluate their performances and assess which one provides a better solution for flapping-wing micro drones. The electromechanical model of the two systems is used in this paper to compare their performances. System parameters for both types of drones were derived through a multi-variable optimisation process using the same DC motor. The comparisons are made in terms of input power requirement, aerodynamic power, system efficiency, and lift. The direct drive model can generate about 16% higher average lift at 5 V with 50% lower input electrical power. It has 29% larger aerodynamic power and the system efficiency is 16.0% higher than that of the slider-crank model.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-28T08:00:00Z
  DOI: 10.1139/dsa-2023-0026
  Issue No: Vol. 12 (2024)
Multi-UAV networks for disaster monitoring: challenges and opportunities
from a network perspective
- Authors: Indu Chandran, Kizheppatt Vipin
  Pages: 1 - 28
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-28, January 2024.
  Disasters, whether natural or man-made, demand rapid and comprehensive responses. Unmanned aerial vehicles (UAVs), or drones, have become essential in disaster scenarios, serving as crucial communication relays in areas with compromised infrastructure. They establish temporary networks, aiding coordination among emergency responders and facilitating timely assistance to survivors. Recent advancements in sensing technology have transformed emergency response by combining the collaborative power of these networks with real-time data processing. However, challenges remain to consider these networks for disaster monitoring applications, particularly in deployment strategies, data processing, routing, and security. Extensive research is crucial to refine ad hoc networking solutions, enhancing the agility and effectiveness of these systems. This article explores various aspects, including network architecture, formation strategies, communication protocols, and security concerns in multi-UAV networks for disaster monitoring. It also examines the potential of enabling technologies like edge computing and artificial intelligence to bolster network performance and security. Further, the article provides a detailed overview of the key challenges and open issues, outlining various research prospects in the evolving field of multi-UAV networks for disaster response.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-27T08:00:00Z
  DOI: 10.1139/dsa-2023-0079
  Issue No: Vol. 12 (2024)
Drone noise differs by flight maneuver and model: implications for animal
surveys
- Authors: Erin N. Macke, Landon R. Jones, Raymond B. Iglay, Jared A. Elmore
  Pages: 1 - 5
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-5, January 2024.
  Drones are becoming a common tool for animal monitoring; however, sound emitted from drones may disturb animals and bias survey results. Understanding noise levels produced by different flight maneuvers, altitudes (i.e., above ground level (AGL)), and drone models could mitigate animal disturbance during surveys. We measured maximum sound (dB) emitted during three flight maneuvers (hovering, flyover, and turning) among eight AGLs (15–120 m) and two vertical maneuvers (ascending and descending) for four commercially available quadcopter drone models (DJI Matrice 300, Matrice 200, Phantom 3, and Autel Evo II), accounting for wind speed and comparing to ambient (background) noise. Ascending, descending, and hovering produced more noise compared to flyover and turning maneuvers. One large drone (Matrice 200, 4.7 kg) produced more noise than the two smaller drones (Evo II, 1.2 kg and Phantom 3, 1.1 kg). However, the largest drone (Matrice 300, 6.4 kg) produced noise similar to smaller models and was the quietest among all models from 75 to 120 m AGL, providing potential size advantages with less noise disturbance. Our results indicate that flights consisting of flyover and turning maneuvers likely cause less noise disturbance than surveys with prolonged hovering over animals.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-21T08:00:00Z
  DOI: 10.1139/dsa-2023-0054
  Issue No: Vol. 12 (2024)
AI-based landing zone detection for vertical takeoff and land LiDAR
localization and mapping pipelines
- Authors: Narmada M. Balasooriya, Oscar De Silva, Awantha Jayasiri, George K.I. Mann
  Pages: 1 - 19
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-19, January 2024.
  This work describes a deep learning-based autonomous landing zone identification module for a vertical takeoff and landing vehicle. The proposed module is developed using LiDAR point cloud data and can be integrated into a visual LiDAR odometry and mapping pipeline implemented in the vehicle. “ConvPoint,” the top-performing neural network architecture in an online point cloud segmentation benchmark leaderboard at the time of writing, was chosen as the reference architecture. Semantic labeling of the datasets was done using the terrain geometry characteristics and manual adjustment of labels through visual observation. Point clouds captured by the Memorial University and online point cloud datasets were used to transfer-learn the neural network model and to evaluate the accuracy-runtime trade-off for the proposed pipeline. The selected neural network model generated accuracy values of 89.7% and 92.1% on two selected datasets, while it computed 3940.15 points per second and 3633.85 points per second to predict landing zone labels, respectively. Hyperparameter tuning was carried out to obtain a higher throughput with an update rate of 1 Hz for the landing zone map of the point cloud inputs from the visual LiDAR odometry and mapping pipeline. The proposed system is validated by evaluating its performance on three variations of point clouds. The results validate the accuracy-runtime trade-off of the proposed system and show that further optimization can improve performance.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-12T08:00:00Z
  DOI: 10.1139/dsa-2022-0038
  Issue No: Vol. 12 (2024)
Cloud-based mathematical models for self-organizing swarms of UAVs: design
and analysis
- Authors: Suren Poghosyan, Vahagn Poghosyan, Sergey Abrahamyan, Artyom Lazyan, Hrachya Astsatryan, Yeghisabet Alaverdyan, Karen Eguiazarian
  Pages: 1 - 12
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-12, January 2024.
  Unmanned aerial vehicle (UAV) swarms have gained significant attention for their potential applications in various fields. The effective coordination and control of UAV swarms require the development of robust mathematical models that can capture their complex dynamics. The paper introduces mathematical models and relevant paradigms based on the design and analysis of self-organizing swarms of UAVs. The logical and technological construction of the model relies on the theorems developed by authors for obtaining full information exchange during the swarm quasi-random walk. The suggested rotor-router model interprets the discrete-time walk accompanied by the deterministic evolution of configurations of rotors randomly placed on the vertices of the swarm graph. The recommended optimal and fault-tolerant gossip/broadcast schemes support the resilience of swarm to internal failures and external attacks, and cryptographic protocols approve the security. The proposed cloud network topology serves as the implementation framework for the model, encompassing various connectivity options to ensure the expected behavior of the UAV swarms.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-09T08:00:00Z
  DOI: 10.1139/dsa-2023-0039
  Issue No: Vol. 12 (2024)
Investigating archaeological remains at Stracciacappe, Rome: comparing
traditional sources with UAV-based multispectral, thermal and
microtopographic analysis
- Authors: Gabriele Ciccone
  Pages: 1 - 16
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-16, January 2024.
  This study investigates the applicability of drone technology in examining Stracciacappe, a minor archaeological site through low-altitude aerial photography. Using multispectral and thermal sensors mounted on DJI Phantom Multispectral and DJI Mavic Enterprise Advanced drones, several flight missions were conducted in November 2020, May 2021, and April 2022. The effectiveness of analyzing multispectral and thermal raw images was limited by the area’s irregular vegetation, which hindered the clear detection of archaeological anomalies. However, microtopographic analysis employing various visualization techniques revealed significant traces, aligning with the site’s description found in numerous documentary sources. This includes the identification of two distinct areas within the castrum: the elevated cassarum and the burgus, along with potential traces of defensive structures within these areas. Drone analysis delineated a cassarum comprising a tower, palatium, and defensive walls, while the burgus seemed devoid of buildings, supporting the notion of a village primarily constructed with perishable materials. Thus, the study highlights the importance of using diverse sensor-based drone analyses to enhance archaeological investigations at minor sites.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-09T08:00:00Z
  DOI: 10.1139/dsa-2023-0114
  Issue No: Vol. 12 (2024)
An analysis of trends in UAV swarm implementations in current research:
simulation versus hardware
- Authors: Abhishek Phadke, F. Antonio Medrano, Chandra N. Sekharan, Tianxing Chu
  Pages: 1 - 10
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-10, January 2024.
  In the fast-evolving field of uncrewed aerial vehicle (UAV) swarm research, there is a growing emphasis on validating results through simulation rather than hands-on hardware experiments. This article delves into this shift, focusing on fundamental research questions on whether simulation tests verify results with hardware experiments, if they mention reasons for not using hardware, and if they provide plans for future implementation using hardware. By examining relevant trends, this study aims to be among the first to address the question of whether the advancements in simulation platforms and disruption modeling have reduced the perceived need for real-world hardware-based tests to verify performance metrics. Supported by data from articles spanning a decade, this report examines global trends in UAV swarm research and experimentation. Variables such as the country, swarm size, and implementation method are reviewed to reveal current trends in how UAV swarm research is conducted and validated. It is concluded that the increase in the simulation-only deployments used by UAV swarm researchers is being readily accepted by the academic community, viewing it as a viable solution to avoid regulations on the UAV industry as well as a reflection on the advanced simulation and modeling methods being developed to support them.
  Citation: Drone Systems and Applications
  PubDate: 2024-02-09T08:00:00Z
  DOI: 10.1139/dsa-2023-0099
  Issue No: Vol. 12 (2024)
Assessing wind impact on semi-autonomous drone landings for in-contact
power-line inspection
- Authors: Étienne Gendron, Marc-Antoine Leclerc, Samuel Hovington, Étienne Perron, David Rancourt, Alexis Lussier-Desbiens, Philippe Hamelin, Alexandre Girard
  Pages: 1 - 16
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-16, January 2024.
  In recent years, the use of inspection drones has become increasingly popular for high-voltage electric cable inspections due to their efficiency, cost-effectiveness, and ability to access hard-to-reach areas. However, safely landing drones on power lines, especially under windy conditions, remains a significant challenge. This study introduces a semi-autonomous control scheme for landing on an electrical line with the NADILE drone (an experimental drone based on original LineDrone key features for inspection of power lines) and assesses the operating envelope under various wind conditions. A Monte Carlo method is employed to analyze the success probability of landing given initial drone states. The system’s performance is assessed by testing two landing strategies, adjusting controller parameters, and considering four different levels of wind intensity. The results show that a two-stage landing strategy offers higher probabilities of landing success and gives insight regarding the best controller parameters and the maximum wind level for which the system is robust. Finally, an experimental demonstration of the system landing autonomously on a power line is presented.
  Citation: Drone Systems and Applications
  PubDate: 2024-01-04T08:00:00Z
  DOI: 10.1139/dsa-2023-0036
  Issue No: Vol. 12 (2024)
Czech society and drones: experience, norms, and concerns
- Authors: Sarah Komasová
  Pages: 1 - 14
  Abstract: Drone Systems and Applications, Volume 12, Issue , Page 1-14, January 2024.
  Understanding societal acceptance of drones is key to their operational incorporation to flight space. For this reason, this study measures experience, norms, and concerns related to drone operation on a quota representative sample of the Czech public and provides an overview of the situation. It finds out that a majority of Czechs already has some level of personal experience with drones and that Czechs are quite confident about high quality of drones’ performance in regard to manoeuvrability, video recording, or low noise levels. Despite these, more legislative regulations and their stronger enforcement are favoured by the majority. Public acceptance of a particular type of flight operations is then highly dependent on the operators’ institutional background. Operations by police and firefighters are supported significantly more. Finally, it is shown that privacy is the driving concern compared to safety or noise in the Czech Republic. Given these, it seems reasonable to focus further communication with the public about this issue, particularly on the introduction of technological capabilities, societal effects of drone operation, and the current legislative framework related to privacy rights and new technologies rather than on promoting drone operation safety.
  Citation: Drone Systems and Applications
  PubDate: 2024-01-03T08:00:00Z
  DOI: 10.1139/dsa-2023-0065
  Issue No: Vol. 12 (2024)

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