Use Of Drones Research Articles

Violation of the Airspace of Countries by Unmanned Aerial Vehicles (Drones) from the Perspective of International Law

Objective: to illustrate the challenges to international law and the shortcomings of current regulation caused by the rapid development of drone technology, by the example of using unmanned aerial vehicles (drones) in airspace.Methods: the study is based primarily on a set of methods for interpreting the provisions of international law, which allow analyzing the provisions in the field of using unmanned aerial vehicles (drones). Results: based on international air law and humanitarian law, the article examines the issues of unmanned aerial vehicles (drones) using airspace. The main sources of law in this area are analyzed, including the provisions of international air law, especially the Paris, Madrid, Havana and Chicago Conventions. An attempt is made to answer the questions arising from the development of unmanned technologies as to which rules of international law apply to their use and whether existing international law is capable of responding effectively to them. The article shows the current understanding of the legal status of airspace over the territory of a state. The author puts forward the question whether the sphere of unmanned aerial vehicles, automatic and autonomous weapons, which combines scientific and military achievements with new technologies, is exceptional. In this regard, the problem of using unmanned aerial vehicles as a universal weapon in international conflicts is touched upon. A conclusion is made that the use of intelligent, guided and robotic weapons capable of automatic decision-making, such as drones, requires the revision of existing conventions or the establishment of new legal standards for these weapons. It is proposed to consider such drones as military aircraft of a special type.Scientific novelty: international legal responsibility of states for the military use of drones has not received an unambiguous assessment in the doctrine. However, much in this issue depends on the legal interpretation of the most important international legal categories. Further development of this issue is directly related to the issues of international responsibility and the concept of state sovereignty over airspace.Practical significance: the development of unmanned aviation at the present stage demonstrates the imperfection of the existing legal framework, which is designed to regulate these relations. With regard to the study of the global trend in the current international law, the identification of the shortcomings in the provisions of the latter is important primarily for their further modernization, taking into account modern scientific achievements and the development of the concept of a state sovereignty over its airspace.

Impact of prior experience and gender on cognitive load during initial drone use

The purpose of this demonstration study was to determine the effect of prior experiences and gender on cognitive demands at the initial educational technology experience. The task of drone operation was selected as a novel educational technological tool and videogame use was determined to be a tangential prior experience. Through the framework of embodied cognition, the NASA Task Load Index was used to measure cognitive demand. Practicing middle- and high-school science teachers were recruited to participate in this study. Participants operated drones at three instances over two weeks. An additional challenging task was also presented. A mixed ANOVA suggested a significant interaction between videogame use and time: F(2, 28) = 3.77, p<\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p<$$\\end{document} 0.05. A significant interaction between gender and time was also observed: F(2, 29) = 3.72, p<\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p<$$\\end{document} 0.05. For both prior experience and gender, the differences were observed at the first instance of drone operation and not at subsequent trials. Results suggest prior experience and gender may only affect cognitive load at the initial experience and leveling of cognitive load occurs with continued practice. These findings can support an educator’s planning for drone-based activities and help to mitigate the stigma of gender differences regarding technology use. Additionally, these findings support the need to examine and enhance related and transferable skills, such as hand–eye coordination and spatial thinking, to lessen cognitive load at the initial educational experience.

Large-Kernel Central Block Masked Convolution and Channel Attention-Based Reconstruction Network for Anomaly Detection of High-Resolution Hyperspectral Imagery

In recent years, the rapid advancement of drone technology has led to an increasing use of drones equipped with hyperspectral sensors for ground imaging. Hyperspectral data captured via drones offer significantly higher spatial resolution, but this also introduces more complex background details and larger target scales in high-resolution hyperspectral imagery (HRHSI), posing substantial challenges for hyperspectral anomaly detection (HAD). Mainstream reconstruction-based deep learning methods predominantly emphasize spatial local information in hyperspectral images (HSIs), relying on small spatial neighborhoods for reconstruction. As a result, large anomalous targets and background details are often well reconstructed, leading to poor anomaly detection performance, as these targets are not sufficiently distinguished from the background. To address these limitations, we propose a novel HAD network for HRHSI based on large-kernel central block masked convolution and channel attention, termed LKCMCA. Specifically, we first employ the pixel-shuffle technique to reduce the size of anomalous targets without losing image information. Next, we design a large-kernel central block masked convolution to make the network pay more attention to the surrounding background information, enabling better fusion of the information between adjacent bands. This, coupled with an efficient channel attention mechanism, allows the network to capture deeper spectral features, enhancing the reconstruction of the background while suppressing anomalous targets. Furthermore, we introduce an adaptive loss function by down-weighting anomalous pixels based on the mean absolute error. This loss function is specifically designed to suppress the reconstruction of potentially anomalous pixels during network training, allowing our model to be considered an excellent background reconstruction network. By leveraging reconstruction error, the model effectively highlights anomalous targets. Meanwhile, we produced four benchmark datasets specifically for HAD tasks using existing HRHSI data, addressing the current shortage of HRHSI datasets in the HAD field. Extensive experiments demonstrate that our LKCMCA method achieves superior detection performance, outperforming ten state-of-the-art HAD methods on all datasets.

Vision-Based Drone Detection in Complex Environments: A Survey

The frequent illegal use of drones poses a serious threat to public security and property. Counter-drones are crucial tools. The prerequisite for an effective counter-drone is to detect drones accurately. With the rapid advancements in computer vision, vision-based drone detection methods have emerged as a hot topic of research. However, current reviews of vision-based drone detection are less focused on algorithmic summarization and analysis. For this reason, this survey aims to comprehensively review the latest methods for vision-based drone detection in complex environments, with the goal of providing a more thorough reference and guidance for related research. We first explore the imaging and drone characteristics in complex environments and summarize the main challenges of visual UAV detection. Then, we summarize the existing solutions for the main challenges. Finally, we systematically organize and introduce the commonly used datasets and evaluation metrics and conduct experiment comparisons based on the representative methods. We not only reveal the current development status of visual UAV detection but also analyze the deficiencies in current research. On this basis, we further look forward to future research directions and possible breakthroughs, with a view to providing useful insights for further research and development in related fields.

DRONES IN WARFARE: NIGERIA'S ADOPTION OF TECHNOLOGY IN FIGHTING INSECURITY

Rapid technological advancements have driven the increasing complexity of warfare, positioning unmanned aerial vehicles (UAVs), or drones, at the forefront of military operations globally. This study examines Nigeria's adoption of drone technology in its fight against insurgencies, banditry, and communal violence. As part of its evolving security strategy, Nigeria has integrated drones into its military operations to enhance intelligence gathering, surveillance, and precision strikes. Despite the operational benefits, the use of drones raises ethical concerns, especially related to civilian casualties, and poses challenges due to limited transparency and regulatory oversight. The study employed a systematic literature review (SLR), drawing on secondary data sources and reports that address the role, effectiveness, and challenges of drones in Nigeria's defense strategies. Key findings highlight that Nigeria's military, particularly the Air Force, has successfully deployed both indigenous and foreign-acquired drones, such as the Amebo, Gulma, and Chinese CH-4, to bolster its intelligence and combat operations. However, the lack of a robust legal framework and the need for improved training and data processing infrastructure hinder the full realization of drone technology's potential. Based on the findings, the study recommends enhancing Nigeria's regulatory framework to ensure ethical drone deployment, investing in indigenous UAV development, and improving inter-agency coordination for more efficient use of drone capabilities. These steps are crucial to ensuring that drones can effectively contribute to Nigeria's national security while minimizing the associated risks.

Comparison of classical and drone based hard-target methodologies applied to scanning lidar for offshore wind

Abstract Hard target testing is a crucial part of the commissioning process of scanning lidar measurement systems. The correct alignment of the scan head and understanding of the pointing accuracy is crucial to reducing uncertainties in wind speed measurements by scanning lidar especially in dual-scanning configuration. This paper presents a comparison between traditional hard targeting technique and the use of drone based hard targets. A procedure is presented to minimise measurement error and hence increase confidence in the pointing accuracy.

ANTI-DRONE TECHNOLOGY

This work provides an overview of the growing use of drones in both civilian and military domains, highlighting the associated risks to public safety and privacy. It discusses the development of counter-drone systems to mitigate these risks, focusing on detection, tracking, classification, and neutralization technologies. Various sensors such as passive radar, acoustic sensors, electro-optical and infrared sensors, radiofrequency analyzers, active radar, and LiDAR are detailed, along with algorithms for data fusion. Mitigation strategies include soft kill methods like spoofing and jamming, as well as hard kill approaches such as projectiles and directed energy weapons. Keywords: counter-UAS; drone threat; unmanned aircraft system; malicious drone

Application of Building Information Modelling in Construction and Demolition Waste Management: Systematic Review and Future Trends Supported by a Conceptual Framework

The architecture, engineering, construction, and operations industry faces an urgent need to enhance construction and demolition waste management in urban areas, driven by increasing demolition and construction activities and a desire to align with sustainable practices and the circular economy principles. To address this need, a systematic literature review on the building information modelling methodology was conducted, employing a structured protocol and specific tools for the analysis of academic studies, based on PRISMA guidelines and StArt software (version 3.4 BETA). Ninety relevant studies published between 1998 and 2024, were analysed and selected from the Web of Science, Scopus, and Engineering Village databases. Findings indicate that China leads in publications with 34%, followed by Brazil (8%) and the United Kingdom (7%). The analysis emphasises the use of drones and LiDAR scanners for precise spatial data, processed by 3D reconstruction tools like Pix4D and FARO As-Built. Revit excels in 3D modelling, providing a robust platform for visualisation and analysis. Visual programming tools such as Dynamo automate processes and optimise material reuse. The study presents a conceptual framework that integrates these technologies with the principles of the circular economy, clarifying the interactions and practical applications that promote the sustainable management of demolition waste from urban buildings and process efficiency. Although the approach promotes material reuse and sustainability, it still faces barriers such as the need for waste segregation at the source, the adaptation of innovative technologies, like the iPhone 15 Pro LiDAR and thermal cameras, as well as associated costs. These factors may limit its adoption in larger-scale projects, particularly due to the increased complexity of buildings.

Enhancing HIV/AIDS and TB medication logistics: A comprehensive approach to global healthcare distribution

The distribution of HIV/AIDS and tuberculosis (TB) medications is critical to the success of global healthcare initiatives, particularly in regions with limited infrastructure and resources. This review examines the logistical challenges hindering the efficient delivery of these life-saving medications, including supply chain inefficiencies, poor infrastructure, and geographical barriers. It also explores innovative approaches to optimizing logistics, such as the use of blockchain, drones, and artificial intelligence (AI), alongside public-private partnerships (PPPs) and supportive policy frameworks. These emerging technologies have the potential to enhance the availability and effectiveness of HIV/AIDS and TB treatments by improving supply chain transparency, reducing stockouts, and overcoming transportation challenges in remote areas. The paper further assesses the impact of these logistical improvements on healthcare outcomes, demonstrating how they contribute to improved patient adherence, reduced disease transmission, and cost savings. Finally, recommendations are provided for policymakers, healthcare organizations, and stakeholders to adopt these innovations, and future research directions are proposed to expand these models to other medications and diseases.

Optimizing Swarm UAV Scheduling for Efficiency in Complex Operations and Collision Avoidance

The use of drones or Unmanned Aerial Vehicle (UAVs) has rapidly evolved across various civil, public, and military applications over the past two decades. Military UAVs have long been used for border surveillance, while civilian UAVs can monitor traffic, provide disaster alerts, and deliver medical supplies. Swarm UAVs, inspired by natural animal colonies such as birds and bees, enable complex flight coordination in disaster situations. To optimize operations, the implementation of scheduling methods for swarm drones is crucial. This method involves scheduling flights based on mission priorities, estimated time of arrival, and drone battery conditions. Effective scheduling ensures operational efficiency and flight safety of drones.

Agricultural spray drone deposition, Part 2: Operational height and nozzle influence pattern uniformity, drift, and weed control

Abstract Agricultural spray drone (ASD) use in managed turfgrass has been given limited attention in the scientific literature. Further, deposition patterns of ASD spray have been obscured in previous research by ambient wind, crop canopy interference, and limited sampling resolution. Using a continuous sampling method involving blue colorant and water sprayed over white Kraft paper that was assessed via digital image analysis of stain objects and referenced spectrophotometric analysis of extractant, deposition metrics were estimated across a 29.3-m transect perpendicular to an ASD or ground sprayer spray swath. The ASD applies very fine droplets that are highly concentrated with herbicide, similar to ultra-low volume treatments, that improved smooth crabgrass [Digitaria ischemum (Schreb.) Schreb. ex Muhl.] control compared to a ground sprayer when the ASD was operated at 2 m above the turf. Unfortunately, these very fine droplets also drift, leading to four times greater droplet density at distance of almost 12 m away from the targeted spray swath following an operational height of 10 m compared to that at 2 m. As ASD operational height increases, drift and effective swath width at 30% coefficient of variation uniformity increases while effective application rate, total deposition, and D. ischemum control by quinclorac herbicide decreased. Total deposition decreased 6% for each m increase in ASD operational height, likely due to evaporation. The potential losses due to evaporation is a serious consideration for ASD use that has received little attention in the scientific literature. Our data suggest that ASD operational height should be as low as possible, but modification of spray systems may be needed to improve homogeneity of spray pattern.

Review of the application of drones for smart cities

AbstractIn an area of increasing digitalisation and rapid technological development, information management is becoming essential for the effective functioning of modern organisations and cities. One of the new trends is the gradual expansion and use of drones in parts of the smart cities concept. In security, drones are used to protect public order, monitor traffic in cities and municipalities, and control sub‐activities falling under the competence of police forces. In rescue work, drones allow us to efficiently and quickly manage accidental emergencies in hard‐to‐reach areas. At the same time, in the transport sector, drones have become an important component for the efficient delivery of parcels, reducing overall costs and time savings. This paper systematically overviews the importance of drones in various fields such as security, transportation, rescue operations or parcel delivery. Drones are becoming key elements for public order, crisis management and enhancing the quality of life of citizens in smart cities due to their capabilities of rapid response, monitoring hard‐to‐reach locations and autonomous data collection. Particular attention is then paid to comparing the use of drones in the Czech Republic and abroad and their benefits in the field of innovative technologies that help improve the safety and efficiency of urban services. The article also analyses the technical specifications of drones and their role in the public and private sectors, considering the legislative framework for their use. Overall, the article offers an overview of how drones contribute to integrating modern technologies into the daily functioning of smart cities and improving residents' quality of life.

TRANSFORMATION OF DIGITAL INNOVATION IN EDUCATION IN THE POST-COVID ERA: AN EXPLORATION CENTERED ON DRONES AND VIRTUAL REALITY

The relevance of this study is underscored by the significant shifts in traditional methods of teaching software disciplines in the post-COVID era. The widespread adoption of remote learning and integrating innovative technologies have necessitated re-evaluating educational practices. This study aims to explore the impact of modern innovative technologies on the effectiveness of education and the quality of learning in the post-COVID period. The primary method employed in this study was a survey, through which questions related to the use of drones and virtual reality (VR) technologies in the educational process were posed to students and educators. The results obtained during this study indicate a high level of acceptance by modern students and their educators of the role of drones and VR technologies in the educational environment of contemporary educational institutions. Participants in the surveys positively assessed the transformation trends of innovative technologies in the educational environment, which applies to almost all groups of students and educators without exception, regardless of their specialties. Respondents highlighted multiple positive effects of integrating drones and VR technologies into the educational space of educational institutions, including a high level of comfort when using these technical devices, improvement in the perception of educational material, and enhancement of the quality of mastering software disciplines. Both educators and students positively view the emerging prospects of practical use of drones and VR technologies in educational institutions' educational space, particularly in the post-COVID period and beyond.

Perspectives on drone journalism in Turkiye: Journalists' views on the use of drones

The subject of this study is the role of drone journalism as a new field within journalism. Drone journalism has emerged due to the rapid development of new communication technologies, making it crucial to define the role of drone technology in journalism. This study aims to investigate journalists' perspectives on drone technology and its effects on their professional lives. The research examines how journalists use drone technology, its contributions to their journalistic processes, and the challenges they face in detail. A qualitative paradigm was adopted for this study, and data were collected through semi-structured interviews within a phenomenological design. The data obtained were analyzed using thematic analysis with MAXQDA qualitative data analysis software. Due to resource and time constraints, the study was limited to 11 journalists working in Türkiye. The findings indicate that the use of drones in journalism is perceived positively for facilitating access, providing bird's-eye view imagery, enhancing aesthetic visuals, reducing physical and material risks in the news-gathering process, increasing the attractiveness of news, promoting objective journalism, and creating new employment opportunities. However, the findings also reveal concerns regarding the violation of personal data protection, privacy, and the boundaries between public and private domains. As a result of these findings, it can be concluded that there are debates about the meaning and use of drone journalism in the industry and that theoretical, practical and legal advances are needed. This study has limitations in terms of research methodology, sampling technique and size. Future research could be improved with new studies that are larger in scale and focus specifically on female drone journalists.

Drone-based warehouse inventory management of perishables

Warehouse inventory management is a complex process. When inventory includes perishables, the complexity of these processes is compounded with additional requirements such as appropriate ambient storage conditions and placement of one type of perishables (e.g., bananas) far away from another type of perishables (e.g., strawberries). With perishables spending a significant amount of time post-harvest in warehouses, appropriate management of warehouse inventory is necessary to reduce wastage due to spoilage. Drone-based warehouse inventory management is gaining popularity as seen in the increasing number of firms in this space as well as the number of research publications. RFID tags have been widely used for inventory management for more than two decades. While drones have been successfully used in warehouses with non-perishables, RFID and drone use in warehouses with perishables has not witnessed its fair share as evidenced by the lack of publications in this general area. This paper is a step in the direction to address this void in published literature. We consider object-level RFID tags and drones to automate warehouse inventory management of perishables. Results from our analytical model and simulation analysis indicate that such warehouse automation is beneficial to both the warehouse operators and their customers.

The use of drones for studying the behaviour of mammals

Since the advent and wide use of unmanned aerial vehicles (UAVs), they have been increasingly useful in monitoring the abundance, distribution and behaviour of terrestrial and aquatic animals. At present, this technique is actively applied to mammal research. The diversity and relative availability of drones allows for a variety of research tasks to be achieved. The use of UAVs has its advantages and disadvantages, these being discussed in the present review. The study examines the advantages of using UAVs in comparison to other methods, identifies new research opportunities opened up by drones, and emphasizes the advantages of modern analytical tools. The technical limitations of UAVs and the problem of the negative impact of this technique on mammals are discussed. The need to minimize the disturbance of animals during such research is emphasized. In addition, the work summarizes the experience of using UAVs in the studies on Russia’s theriofauna.

Spatial and temporal variation of marine megafauna off coastal beaches of south-eastern Queensland, Australia

Context Coastal beach environments provide habitats for marine megafauna, including turtles, rays, marine mammals and sharks. However, accessing these variable energy zones has been difficult for researchers by using traditional methods. Aims This study used drone-based aerial surveys to assess spatio-temporal variation of marine megafauna across south-eastern Queensland, Australia. Methods Drones were operated at five south-eastern Queensland beaches. Megafauna sightings and key variables including location, month and turbidity were analysed to assess variation across locations. Key results Overall, 3815 individual megafauna were detected from 3273 flights. There were significant differences in the composition of megafauna assemblages throughout the year and among beaches, with megafaunal sightings in &gt;80% of flights conducted off North Stradbroke Island. Conclusions Strong temporal presence was found that is congruent with other studies examining seasonality. This supports the use of drones to provide ecological data for many hard-to-study megafauna species and help inform long-term sustainable management of coastal ecosystems. Implications Results indicated that environmental conditions can influence the probability of sighting marine megafauna during aerial surveys.

Presentación del Volumen 5 Número 3 - Octubre 2024 - enero 2025

Latest issue of Volume 5 of the journal, which highlights aspects of national security, reaffirming that in Peru there are multiple dimensions of the national reality in which risk scenarios develop. The national peculiarity lies in the increase of problems –in the internal sphere– that affect national security and development, which leads to maintaining the diversity of studies and research that highlight the interdependence of security and development, but does not neglect the analysis of the advance of war, as the case of the use of drones, mercenaries and nuclear plants in the conflict between the Russian Federation and Ukraine. In the anniversary month of CAEN-EPG, its important role in benefiting proposals to optimize our national security, overcoming the adversaries of the Homeland, is highlighted.

Enhancing Satellite Link Security Against Drone Eavesdropping Through Cooperative Communication

ABSTRACTIntegrated satellite terrestrial networks (ISTNs) are emerging as a promising next‐generation communication technology, for example, B5G and 6G, with low‐earth orbit (LEO) satellites playing a growing role. However, the complex and unique characteristics of ISTNs make them more susceptible to cyberattacks. Recently, the use of drones for public and private services has increased the risk of eavesdropping on LEO satellite links. Such scenario presents an extremely challenging environment due to dynamic nature of LEO satellite and drone along with atmospheric attenuation at sub‐THz frequencies. This study proposes a novel adaptive power‐bandwidth cooperative scheme designed to mitigate the likelihood of eavesdropping attacks on LEO satellite links communicating with a ground station when a drone is within the line of sight. The mathematical algorithm dynamically adapts the resources to maximize the normalized secrecy capacity in this challenging scenario while maintaining a reasonable signal‐to‐noise ratio (SNR) at the legitimate receiver. The adaptive scheme involves strategic cooperation with a nearby terrestrial third party to amplify and forward the satellite signal to the ground station receiver. The simulation results demonstrate the effectiveness of the proposed algorithm, showing significant improvements (&gt; 70%) compared to the non‐adaptive scheme over a wide range of elevation angles.

On the Possibilities and Significance of Unmanned Aerial Vehicles for the Pre- Hospital Stage of Medical Care

Unmanned aerial vehicles are an important force in search and rescue operations. They help reduce the time needed to search for and provide assistance to the wounded, sick and injured who are located at a large territorial distance and in hard-to-reach places. With the help of computer “vision” and sensors such as noise sensing, binary sensing, vibration and thermal sensing, drones are able to search for living patients not only in the sea, high in the mountains and in mines, but also buried under the rubble of buildings and structures. Such devices demonstrate advantages in emergency and urgent delivery of medical resuscitation and other medical equipment, medicines, blood products and organs for transplantation to patients, especially those in remote locations. With the help of drones, it is possible to effectively sort patients in case of mass sanitary losses, carry out disinfection and remotely monitor the health status of patients with highly contagious infectious diseases and other pathological conditions, as well as reduce the time for providing other medical and humanitarian services to the population. It is obvious that the use of drones requires further study of their promising capabilities, especially in the actual conditions of emergency medical services.