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![Fig. 4: Countries that have acquired armed UAVs. Source: Adapted from [60]](profile/Vinay-Chamola/publication/344592031/figure/fig3/AS:945323644039168@1602394128646/Countries-that-have-acquired-armed-UAVs-Source-Adapted-from-60_Q320.jpg)
![Fig. 6: Countries that have developed armed UAVs. Source: Adapted from [60]](profile/Vinay-Chamola/publication/344592031/figure/fig5/AS:945323648221185@1602394129154/Countries-that-have-developed-armed-UAVs-Source-Adapted-from-60_Q320.jpg)
Unmanned Aerial Vehicles (UAV) have revolutionized the aircraft industry in this decade. UAVs are now capable of carrying out remote sensing, remote monitoring, courier delivery, and a lot more. A lot of research is happening on making UAVs more robust using energy harvesting techniques to have a better battery lifetime, network performance and to...
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... VTOL refers to vertical takeoff and landing. Figure 2 illustrates various types of UAVs classified based on their wings and rotors and Table II presents an comparison and typical use cases. ...
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... Most of the devel- oped nations have begun utilizing UAVs in their modern agriculture system, photogrammetric and remote sensing. Many countries like, Europe union (Italy, Greece), United Kingdom, sub-Sahara Africa, Asian countries (Israel and China) and Australia have already adopted UAV for various purposes (Chamola et al., 2021). Due to the miniaturization and cost reduction of GPS receivers, inertial navigation systems, computers, and, most importantly, remote sensing sensors, unmanned aerial vehicles (UAVs) or over the past ten years, technologies for remotely piloted aircraft have grown in popularity in Europe and hence adopted by them. ...
In recent years, the agriculture industry has witnessed a significant transformation with the integration of cutting-edge technologies to enhance productivity, efficiency, and sustainability. Among these technologies, sensors have emerged as indispensable tools for monitoring various agricultural parameters and optimizing farming practices. Current advancements and technological improvement in the sector of agriculture requires modern day machineries-drones. Drones technologies proved to save the water, pesticides, and herbicides, maintain the soil fertility also helps to cut excess implication of man power along with increase the output and raise the standard of quality. Robots, artificial intelligence, big data, robotics, and the internet of things are all combined in UAVs. Agricultural UAVs have shown to be quite effective when in use, and they are now extensively employed in many facets of agriculture, such as seed sowing, growth evaluation, and mapping, as well as the application of pesticides and fertilizers. It is becoming essential in the field of agronomical research, they are quite susceptible to variation in soil, climate and alteration to physico-chemical changes. The aim of this paper is to review the usage of Drones, UAVs and remote sensing in agriculture applications. On the basis of literature, we found that a lot of advantages are witnessed in agriculture in using Drone, UAV and remote sensing. This paper summarizes the current state of three technologies for agricultural uses, including crop health monitoring and farm operations like, weed management, evapotranspiration estimation, spraying etc. In order to improve their agricultural production, more farmers should invest in contemporary equipment and technology, according to the research article's conclusion.
... This review is not exclusively about attacks but gives equal weight to prevention and protection mechanisms. A similar work by Chamola et al. [11] emphasizes not only attacks but also prevention through counter-UAV measures. On the other hand, an in-depth study of jamming and MitM attacks, especially spoofing, was conducted. ...
... Jamming the Radio Frequency (RF) communications between the drone and the controller can be used for various purposes, such as preventing reception of control commands, which can crash the drone or trigger landing safety measures (e.g., returning to the starting point). Global Positioning System (GPS) jamming can also be used to interfere with the drone's GPS communications, which is even more effective than RF jamming as the drone is unable to know where it is and return to its controller [11]. One point to note is that jammers can interfere with other devices operating in the same frequency range. ...
Unmanned Aerial Vehicle (UAV)s, also known as drones, are increasingly used in several applications and a variety of cyber attacks can be performed on them using several tools. Some examples of these attacks include breaking the connection between the drone and the controller with deauthentication attacks, discovering a password or cryptographic key used in a communication protocol, gaining control of the drone through command/code injection, and Man-in-the-Middle (MitM) attacks. This paper covers drone attacks by analyzing different components of the drone, including the remote controller and communication protocols. The main purpose is to provide an overview of the possible ways in which cyber attacks can be executed. This analysis concludes that drones, designed for diverse purposes, are vulnerable to a range of cyber attacks. The paper also reviews existing penetration testing methodologies for UAVs, which provide a logical framework for their realization. This review covers the different cyber attack methods and tools used against a UAV, intending to improve defense mechanisms.
... Виклад основного матеріалу Основні групи БПЛА Можна виділити дві основні групи БПЛА: безпілотні літальні апарати з нерухомим крилом (НК) і безпілотники з гвинтокрилом (БГ). Залежно від кількості роторів БГ можна далі розділити на однороторні апарати, трикоптери, квадрокоптери, гексакоптери та октокоптери [4]. Однак для моніторингу забруднення атмосфери, як правило, кращими є невеликі транспортні засоби з чотирма або шістьма роторами [5]. ...
Рівень забруднення атмосферного повітря формується під впливом багатьох факторів, зокрема викидів від об’єктів енергетики, транспорту, промисловості сільського господарства, а також процесів утилізації та очищення стоків. Він також залежить від метеорологічних умов, швидкості розсіювання забруднюючих речовин та їх взаємодії з навколишнім середовищем (фізико-хімічна трансформація, вимивання опадами, поглинання підстилаючою поверхнею), і географічних особливостей місцевості (рельєф, наявність забудови, висота та щільність рослинності). У статті наведено джерела викидів таких забруднювачів повітря, як тверді частинки, чадний газ і діоксид вуглецю, оксиди азоту, аміак, летючі органічні сполуки, озон, діоксид сірки, сірководень, випромінювання, запахи), зазначено загальні методи їх вимірювання. Описано особливості функціонування наземних стаціонарних станцій моніторингу якості повітря. Показано низьку ефективність даних систем для оперативного реагування на швидкоплинні надзвичайні ситуації з хімічним та радіаційним фактором забруднення. Обґрунтовано, що для оперативної оцінки обстановки та отримання необхідних даних під час виникнення таких ситуацій ефективним підходом є застосування систем моніторингу, які базуються на мобільних платформах, а саме БПЛА. Відзначено, що перевагами цих засобів є можливість оперативного потрапляння на місце надзвичайної ситуації в складних умовах (складний рельєф місцевості, наявність важкопрохідної рослинності, руйнація або аварійно-небезпечний стан об’єкту, велика пожежа або вибухи на території об’єкту, бойові дії, важкі метеумови тощо) та швидке отримання необхідних даних для прийняття вчасних ефективних управлінських рішень службами реагування. Описано ефект «змиву», який виникає під БПЛА в результаті швидкого обертання його роторів, що спричиняє порушення розподілу повітря навколо дрона і зменшення концентрації досліджуваних газів в місці розташування мультисенсорної системи. Здійснено аналіз сучасних передових технічних рішень науковців з різних країн світу щодо розміщення датчиків на борту БПЛА для зменшення впливу ефекту «змиву» на точність вимірювання відповідних концентрацій.
... UAVs can currently be classified in several ways. One approach is based on factors such as weight, wing and rotor type, altitude and range, and their specific applications [16]. Another way of classifying UAVs is based on their command and control methods, which can be divided into the following categories [17]: ...
This paper explores the problem of the security of unmanned aerial vehicles (UAV) by introducing the drone security scoring system (D3S). D3S is a security assessment method that analyzes the security of a UAV model by analyzing its components. Penetration tests were carried out to support D3S and identify potential vulnerabilities in UAVs. Specific cyber-attacks, such as deauthentication, flooding, and replay, were executed in an effort to take full control of the UAVs. Eight different UAV models were assessed using D3S, revealing notable variations in performance, both in control communications and video transmission. Security scores ranging from 0.9 to 4.5 out of 5 were obtained, showing significantly divergent security levels.
... 1. Critical Infrastructure. UAVs can attack power plants (Mohsan, Khan, Noor, Ullah, & Alsharif, 2022), oil refineries (Chamola, Pavan, Aayush, Naren, Navneet, & Mohsen, 2021), water treatment facilities, and communication hubs. A successful attack could cause widespread outages, disrupt essential services, or create environmental hazards. ...
... Research in this area can be divided into several main areas: a. announcements and popular science articles in the press (Abott, 2023;Rtx.Com, 2023) -in general, such articles simply confirm the fact of one of the stages of development or testing of weapons systems (Abott, 2023;O'Rourke, 2024), but they often contain a small amount of technical information that does not appear in other sources; b. various publicly available reports of parliaments, ministries of defence and other government agencies of different countries are broadly analytical in nature with sufficient references to scientific review and scientific and practical articles (O'Rourke, 2024); c. scientific review articles (Chamola, Pavan, Aayush, Naren, Navneet, & Mohsen, 2021), as well as scientific (Kim, Choi, & Kwon, 2024;Mohsan, Khan, Noor, Ullah, & Alsharif, 2022) (theoretical, experimental and combined, containing both theoretical and experimental components) articles devoted to the development of individual components of such complexes (Lyu & Zhan, 2022). ...
From the dawn of human history, mankind has always made efforts to create more effective tools for combating other creatures, including fellow people. Thus, the utilisation of different species of animals, the creation of new weapons and other means of human progress have always led to new developments, aimed at emulating, replacing or combating these innovations. The development of unmanned aerial vehicles has prompted the need to develop alternative and innovative countermeasures. These methods may range from the usage of interceptor drones to the application of concentrated energy beams. This paper examines the progress and known uses of laser technology in the context of combating unmanned aerial vehicles. In order to deepen and systematize knowledge about the development of laser applications in the military field, a systematic bibliographic analysis of scientific papers and popular publications on the development of both laser technologies and unmanned aerial vehicles over the past century was conducted. The study focused on developments that were built (at least as a prototype) and tested against various unmanned aerial vehicles. The results were then compared with a number of articles that separately focused on the history, prospects, and current issues in the development of laser weapons and unmanned aerial vehicles. At the same time, due to the fact that laser technology is one of the most rapidly and comprehensively developing areas of scientific progress, it was decided to use a periodic classification model, the main criterion of which was the focus of laser technology development on countering unmanned aerial systems. The issue of determining the cause-and-effect relationship that links the development of unmanned aerial vehicle technologies and designs with the shift in the focus of laser weapons development to counteract them was considered. It is noted that, due to the high requirements for human and financial capital, the direction and pace of development of laser weapons depend not only on technological limitations, but also on the vision of military strategy and possible threats at a given time. As a conclusion, a variant of periodization of the history of the development of laser weapons as a means of combating unmanned aerial vehicles was proposed.
... Recent incidents, such as the drone crash at the White House [3], the disruption caused at Gatwick Airport [4], and the cybersecurity breach of a popular drone manufacturer [5], have highlighted the significance of recognizing and monitoring drones within a specific region. This procedure, known as drone detection (DD), is essential for ensuring safety, privacy, and security. ...
The increasing prevalence of drones has raised significant concerns regarding their potential for misuse in activities such as smuggling, terrorism, and unauthorized access to restricted airspace. Consequently, the development of robust and efficient drone detection systems has become paramount. Traditional detection methods such as radar and acoustic sensors have limitations in detecting small drones and can be costly to implement. This can lead to lower detection rates and increased security breaches and safety concerns. However, prevailing methodologies often falter in achieving real-time detection with requisite precision and efficacy, particularly within complex operational environments. Motivated by the imperative to surmount these challenges, our research endeavors to introduce a pioneering real-time drone detection framework. Our study encapsulates several seminal advancements. Firstly, we proffer a groundbreaking framework that synergizes advanced integration technique based on texture feature extraction and pattern recognition techniques for real-time drone detection to increase accuracy to detect drones in different conditions such as bad weather and low resolution. Secondly, we introduce an intuitive graphical user interface, enhancing the usability and accessibility of the system in real-time scenario. Lastly, through exhaustive evaluation and comparative analysis, we substantiate the superior performance of our framework in terms of accuracy, precision, and real-time detection capabilities compared to conventional DDS methodologies. Its stability and effectiveness render it a compelling solution for security-focused entities, notably those within air force and military systems. Our experimental results reveal a commendable accuracy rate of 97%, affirming the reliability and precision 98% and recall parameter 98% of our framework in accurately identifying and detecting drones, thus surpassing recent models in the field.
... 29 Pistoia 2021. 30 Chamola et al. 2020. 31 Kang et al. 2020. ...
We are living in an era that is marked by the exponential growth of small Unmanned Aircraft Systems (sUAS), therefore the imperative for effective countermeasures against potential threats to public safety, national security, and individual privacy inherent in these airborne apparatus has become increasingly pronounced. Following the foundational exploration of UAS surveillance in the first segment of the Counter-UAS (C-UAS) series, this second instalment shifts its gaze to the pivotal domain of drone neutralisation techniques. Investigating both soft and hard neutralisation methodologies, this study aims to unravel the intricate landscape of strategies devised to legally and securely incapacitate, disrupt, or assume control over sUAS threats. Drawing from a rich tapestry of existing literature and recent research endeavours, this paper embarks on an expedition through a spectrum of neutralisation approaches subjecting the aforementioned methodologies to rigorous scrutiny regarding their efficacy and other implications, in order to contribute substantively to the development of a resilient C-UAS framework. Moreover, this study lays the groundwork for the third part of this C-UAS series, where the author shall unfurl a vision of operation. Besides elucidating the challenges and opportunities inherent in the neutralisation of small drone threats, this study also aims to catalyse collaboration within the research community, dedicated to ensuring the secure coexistence within the airspace system.
... Особливого значення з даного напрямку мала проведена 16 жовтня 2003 р. Генеральна Конференція ЮНЕСКО, якою було визнано Хартію Землі, що визначила основоположні принципи справедливого, сталого і мирного глобального суспільства в XXI ст., наголошуючи на взаємозалежності світу, взаємній відповідальності всіх, як один перед одним, так і перед усім живим та майбутніми поколіннями 4 . За підсумками Конференції ООН зі збалансованого розвитку («Ріо+20»; Бразилія, Ріо-де-Жанейро, червень, 2012 р.) був прийнятий заключний документ «Майбутнє, якого ми прагнемо», яким підтверджено курс (визначений на Всесвітньому Саміті зі збалансованого розвитку у 2002 році) на сталий розвиток і на забезпечення побудови економічно, соціально та екологічно збалансованого майбутнього для планети, для нинішнього і майбутніх поколінь 5 . ...
... Вибір антибіотикотерапії у хірургічних хворих з гнійно-септичними ускладненнями є однією із важливих проблем. Це пов'язано, насамперед, з видовим складом мікрофлори, яка постійно змінюється та її чутливістю до антибіотиків 4 . ...
... У 2020 році Noureddin et al. опублікували систематичний огляд досліджень, в яких вивчали ефективність адеметіоніну для лікування внутрішньопечінкового холестазу (ВПХ) та хронічних захворюваннях печінки. Це був перший систематичний аналіз ефективності SAMe протягом перших тижнів лікування (з 0-го по 8-й тиждень) 4 . ...
The collective monograph is a scientific and practical publication that contains scientific articles by doctors and candidates of sciences, doctors of philosophy and art, graduate students, students, researchers and practitioners from European and other countries. The articles contain
research that reflects current processes and trends in world science.
... In civilian applications, UAVs are helpful in agricultural plant protection, geographic mapping and exploration, electric power inspection, and logistics and transportation [4,5]. In the military field, UAV missions have become increasingly diverse, and the frequency of their use in local conflicts has increased dramatically [6,7]. Owing to their characteristics, such as small radar reflective surfaces, small size, and low heat dissipation, it is difficult to accurately identify and locate small UAVs in complex environments [8][9][10][11][12][13], making it essential to detect and identify low-altitude UAVs effectively. ...
Traditional unmanned aerial vehicle (UAV) detection methods struggle with multi-scale variations during flight, complex backgrounds, and low accuracy, whereas existing deep learning detection methods have high accuracy but high dependence on equipment, making it difficult to detect small UAV targets efficiently. To address the above challenges, this paper proposes an improved lightweight high-precision model, YOLOv8-E (Enhanced YOLOv8), for the fast and accurate detection and identification of small UAVs in complex environments. First, a Sobel filter is introduced to enhance the C2f module to form the C2f-ESCFFM (Edge-Sensitive Cross-Stage Feature Fusion Module) module, which achieves higher computational efficiency and feature representation capacity while preserving detection accuracy as much as possible by fusing the SobelConv branch for edge extraction and the convolution branch to extract spatial information. Second, the neck network is based on the HSFPN (High-level Screening-feature Pyramid Network) architecture, and the CAA (Context Anchor Attention) mechanism is introduced to enhance the semantic parsing of low-level features to form a new CAHS-FPN (Context-Augmented Hierarchical Scale Feature Pyramid Network) network, enabling the fusion of deep and shallow features. This improves the feature representation capability of the model, allowing it to detect targets of different sizes efficiently. Finally, the optimized detail-enhanced convolution (DEConv) technique is introduced into the head network, forming the LSCOD (Lightweight Shared Convolutional Object Detector Head) module, enhancing the generalization ability of the model by integrating a priori information and adopting the strategy of shared convolution. This ensures that the model enhances its localization and classification performance without increasing parameters or computational costs, thus effectively improving the detection performance of small UAV targets. The experimental results show that compared with the baseline model, the YOLOv8-E model achieved (mean average precision at IoU = 0.5) an mAP@0.5 improvement of 6.3%, reaching 98.4%, whereas the model parameter scale was reduced by more than 50%. Overall, YOLOv8-E significantly reduces the demand for computational resources while ensuring high-precision detection.
... The cybersecurity problems of UAVs are being studied in many literature sources. Previous researchers carried out an analysis of attacks on UAVs and countermeasures using anti-UAV techniques (Chamola et al., 2021;Abdullayeva and Ibrahimov, 2022;Abdullayeva and Valikhanli, 2022). Madan, Banik and Bein (2019) proposed a conceptual model of a UAV and demonstrated cyber threats to its separate components. ...
The Unmanned Aerial Vehicles (UAVs) are being actively used in various fields including agriculture, surveillance, scientific research, and delivery. Despite their widespread use, UAVs face significant cybersecurity challenges due to their vulnerabilities as cyber-physical systems. UAVs are vulnerable to cyberattacks, which target cyber or physical elements, the interface between them, wireless connections, or a combination of several components. Given the complexity of securing these systems, this paper provides a comprehensive survey of the current state of UAV cybersecurity. Moreover, different cybersecurity issues of UAVs are analyzed, various features, and functions of UAVs are considered. UAV attack classification scheme is constructed and attacks on various components are accounted for. Also, countermeasures against cyberattacks that target UAVs are discussed. Finally, UAV cyber security datasets for research purposes are indicated, and the remaining open issues in this field are identified.
