A Lightweight Transmission Line Foreign Object Detection Algorithm Incorporating Adaptive Weight Pooling

The use of unmanned aerial vehicles (UAVs) is becoming increasingly widespread in many areas of human life every year. Not only military, but also civilian use of UAVs in various fields of science, industry, forestry, agronomy, cartography, ecology, and space research is hard to overestimate. For this reason, the use and development of UAVs in various fields remains extremely promising in the near future. Compared to manned vehicles, UAVs have the following advantages: no crew and no need for life support systems, large airfields; lower cost and low expenses for their development, production and operation; better weight and dimensions; high reliability and maneuverability; a wide range of specialized equipment for placement on board. UAVs are being introduced into all spheres of human life, even those where UAVs have no manned alternative. Some models of multicopters are already being used to deliver goods and extinguish fires. UAVs of new designs continue to be developed.In all areas of UAV application, the task of increasing autonomy remains relevant and important. The duration of con-tinuous operation and flight range directly affect the capabilities of the UAV, its ability to perform tasks and efficiency.UAV power consumption depends on the weight of the payload, weather conditions and drone speed. Energy consumption is a critical criterion for a drone to perform its missions and needs to be further studied. Many studies have been conducted to increase flight time by improving energy efficiency or reducing the energy consumed by the drone.Study the influence of battery parameters (capacity and weight) and propeller group (number of propellers and their diameter) on the maximum possible flight duration of UAVs of different masses.The main factors affecting the maximum flight duration of a UAV are considered. A model for calculating the power consumed by the device in the hover mode is presented. The maximum flight duration of a UAV is calculated depending on the battery capacity and weight, the number of propellers, and the diameter of the propellers for vehicles of different masses.It is shown that there is no point in increasing the battery capacity indefinitely, and there is an optimum point that depends on the ratio of the battery mass to the mass of the vehicle. It is also shown that increasing the diameter of the propellers significantly increases the flight time, while increasing their number is not as effective.

Using unmanned aerial vehicles (UAVs) for surveys on thermostatic animals has gained prominence due to their ability to provide practical and precise dynamic censuses, contributing to developing and refining conservation strategies. However, the practical application of UAVs for animal monitoring necessitates the automation of image interpretation to enhance their effectiveness. Based on our past experiences, we present the Sichuan snub-nosed monkey (Rhinopithecus roxellana) as a case study to illustrate the effective use of thermal cameras mounted on UAVs for monitoring monkey populations in Qinling, a region characterized by magnificent biodiversity. We used the local contrast method for a small infrared target detection algorithm to collect the total population size. Through the experimental group, we determined the average optimal grayscale threshold, while the validation group confirmed that this threshold enables automatic detection and counting of target animals in similar datasets. The precision rate obtained from the experiments ranged from 85.14% to 97.60%. Our findings reveal a negative correlation between the minimum average distance between thermal spots and the count of detected individuals, indicating higher interference in images with closer thermal spots. We propose a formula for adjusting primate population estimates based on detection rates obtained from UAV surveys. Our results demonstrate the practical application of UAV-based thermal imagery and automated detection algorithms for primate monitoring, albeit with consideration of environmental factors and the need for data preprocessing. This study contributes to advancing the application of UAV technology in wildlife monitoring, with implications for conservation management and research.

Abstract. The rapid development of unmanned aerial vehicles is a challenge for applied research. Many technologies are developed and then researcher are looking up for their application in different sectors. Therefore, we decided to verify the use of the unmanned aerial vehicle for wood chips pile monitoring. We compared the use of GNSS device and unmanned aerial vehicle for volume estimation of four wood chips piles. We used DJI Phantom 3 Professional with the built-in camera and GNSS device (geoexplorer 6000). We used Agisoft photoscan for processing photos and ArcGIS for processing points. Volumes calculated from pictures were not statistically significantly different from amounts calculated from GNSS data and high correlation between them was found (p = 0.9993). We conclude that the use of unmanned aerial vehicle instead of the GNSS device does not lead to significantly different results. Tthe data collection consumed from almost 12 to 20 times less time with the use of UAV. Additionally, UAV provides documentation trough orthomosaic.

An innovative approach to the process of recording administrative offenses by means of unmanned aerial vehicles will increase the level of organization of road safety, which is one of the urgent tasks of ensuring transport safety in Ukraine. The article investigates the theoretical and practical issues of application of the patented method of fixing road accidents and presents its main advantages in comparison with the existing traditional methods of fixing. Based on the data obtained as a result of aerial photography of an accident site by an unmanned aerial vehicle, the need to improve certain aspects of the patented methods is substantiated. Improving the method of recording road accidents is to use new modern methods and approaches that differ from traditional ones and conditionally divide the overall process into stages of recording. First of all, this is a preparatory stage, which is that an employee of the National Police of Ukraine, which carries out the registration of materials on administrative offenses under Art. 124 of the Administrative code, before the beginning of fixing a road accident with the use of unmanned aerial vehicles is recommended: to receive a conclusion on suitability for controlling an unmanned aerial vehicle from the Central medical flight commission; to undergo professional training in controlling an unmanned aerial vehicle; to get acquainted with the process of recording an accident using an unmanned aerial vehicle; to study in detail the recommendations on the choice of flight altitude during the registration of accidents and parameters related to the use of controlling an unmanned aerial vehicles in different weather conditions. So, in view of the quick and efficient examination of road transport accidents, it is recommended that an official vehicle of a member of the National Police of Ukraine will be equipped with a special complex, which will respond to the criterion "quality – price – technical characteristics". The comparative analysis of two ways of fixing road accidents by means of unmanned aerial vehicles in the form of a table is resulted; their primary advantages and lacks are specified. It is proved that the use of unmanned aerial vehicles is a requirement of today and meets the goal of ensuring transport safety in Ukraine.

The use of unmanned aerial vehicles (UAVs) in the construction industry is swiftly growing worldwide. UAVs are changing the way construction companies do business. Contractors are increasingly using camera-mounted UAVs to monitor the full range of activities. Rapid advances in camera, sensing, aeronautics, battery and autopilot navigation technologies have helped make UAVs affordable, reliable and easy to operate. The US Federal Aviation Administration predicts that UAVs hold tremendous promise and commercial drone sales could increase from 600,000 to 2.7 million over the next four years. On the one hand, UAVs are extremely cost-effective in conducting aerial surveys, worksite surveillance, real-time inspections, and monitoring jobsite safety. On the other hand, with UAV ownership rapidly rising, the number of reported UAV safety, risk, and liability incidents is increasing. With this new technology use in the construction industry, construction companies must be aware of all regulations, legislations, privacy liability, and risks for construction related businesses. Operating a drone or hiring a subcontractor to operate it is not something to do on the spur of the moment. Emphasis and effort should be placed on safety, risk control, training and education. The goal of this paper is to provide construction professionals with timely and pertinent information on UAV use with a focus on risk management based on current industry practice, experience and literature review.

Information acquisition and rescue operation management can be facilitated by the use of unmanned aerial vehicles (UAVs) equipped with cameras and sensors that are capable of aerial photography and acquire important information from disaster-stricken areas. UAV technology is a relatively low-cost, flexible, and safe solution in missions that are difficult for humans or other systems. UAV usage in pre-and post-disaster assessment, response, and management is an active area of research. There are two important technical aspects of UAV applications in disaster situations. The first is the limited communication range. Information acquired and photography produced by UAVs are only transmitted in real-time to the ground control station (GCS) within its communication range. Remote real-time monitoring of distant areas beyond the UAV's communication range is not possible using a single UAV. It is only possible through communication among several UAVs. The second is the relatively short flight time due to limited battery capacity. UAV replacement is required in order to carry out a persistent monitoring mission. In this paper, we propose a new remote real-time monitoring system of a distant disaster area using multiple UAVs. Wireless communications between multiple UAVs constitutes a UAV network in our proposed system. Moreover, the proposed system replaces the UAVs in-flight with standby UAVs according to the remaining energy levels. We compare the performance of the proposed system with an existing UAV system. Our simulation results show that the proposed system can achieve efficient remote real-time monitoring.

Pesticide spray drift and risk assessment using unmanned aerial vehicle (UAV) sprayer and traditional electric knapsack sprayer (EKS).

In the developing world, the trend of using Unmanned Aerial Vehicles (UAVs) is being increased in many fields. These UAVs are now available in many different versions which ranges from children toy to military level combat equipment. Manufacturing companies are mostly mainly paying attention on reducing power consumption, high data transfer rate, less weight and more speed. However, by keeping focus on these features, most of the UAVs manufacturing companies overlook the factor of security and the risk in case of exploitation is ignored. This fact cannot be ignored that an exploited/hacked UAV with malicious intent can cause serious harm to the target in many ways. In the UAVs development, focus on the less computation power, restricted correspondence data transfer capacity, light weight data carrying limit and robustness captivity in UAVs has become a challenge for security practitioners and researchers. UAVs use numerous communication protocols and one among these protocols is Micro Air Vehicle (MAV) link protocol which is reliable as well as efficient. Currently, there are two versions of MAVlink communication protocol called MAVlink1 and MAVlink2. This protocol is used to establish a communication between Ground Control Station and UAV. The second version of this protocol (i.e. MAVlink2) is recent and there is not much data available about the potential exploitable vulnerabilities present in this protocol. This research paper has explored and identified security vulnerabilities in MAVlink2, specifically linked to the communication of UAV and their impact on UAV. The paper has further analyzed MAVlink2 communication protocol in order to exploit the vulnerabilities in the MAVlink2 protocol for hijacking the UAV.

In view of the potentials and benefits of using unmanned aerial vehicles (UAVs) in civil and surveillance applications, such as forest fire monitoring and fighting, earthquake and natural disasters monitoring and sensing etc., the cooperative flight of multiple UAVs has been paid more and more attention. Among the applications of multiple UAVs in cooperative flight, fault-tolerant cooperative localization against global positioning system (GPS) signal loss due to GPS receiver malfunction is one of key techniques for various practical applications. The current research on fault-tolerant cooperative localization of UAVs is mainly based on the distance between UAVs. However, cooperative localization based on the azimuth angles between UAVs has not been generally researched so far. This paper aims to solve the problem of fault-tolerant cooperative localization of UAVs by introducing the azimuth angles between UAVs. Firstly, the basic localization model is established and the formulas of localization in two and three dimensional coordinate systems are derived. Then the optimal reference planes are chosen with the principle of minimum horizontal dilution of positioning (HDOP). Kalman filter is applied to decrease the influence of observation errors on localization. Kalman filter and extended Kalman filter are designed against linear and non-linear systems, respectively. Finally, the simulation results indicate that the cooperative localization based on the azimuth angles achieves high localization accuracy.

CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a key technology for security in smart city environments.This article creates a case where the UAVs with CCTV-cameras fly over the city area for flexible and reliable surveillance services. UAVs should be deployed to cover a large area while minimizing overlapping and shadow areas for a reliable surveillance system. However, the operation of UAVs is subject to high uncertainty, necessitating autonomous recovery systems. This article develops a multiagent deep reinforcement learning-based management scheme for reliable industry surveillance in smart city applications. The core idea this article employs is autonomously replenishing the UAV's deficient network requirements with communications. Via intensive simulations, our proposed algorithm outperforms the state-of-the-art algorithms in terms of surveillance coverage, user support capability, and computational costs.

At present, the method of using unmanned aerial vehicles (UAVs) with traditional navigation equipment for inspection of overhead transmission lines has the limitations of expensive sensors, difficult data processing, and vulnerable to weather and environmental factors, which cannot ensure the safety of UAV and power systems. Therefore, this paper establishes a mathematical model of spatial distribution of transmission lines to study the field strength distribution information around transmission lines. Based on this, research the navigation and positioning algorithm. The data collected by the positioning system are input into the mathematical model to complete the identification, positioning, and safety distance diagnosis of the field source. The detected data and processing results can provide reference for UAV obstacle avoidance navigation and safety warning. The experimental results show that the positioning effect of the positioning navigation algorithm is obvious, and the positioning error is within the range of use error and has good usability and application value.

The article reveals the peculiarities of using unmanned aerial vehicles for reconnaissance in the field in wartime. The article reveals the essence and content of the use of unmanned aerial vehicles for reconnaissance, as well as the conditions and features of their effective use. Study of the possibilities of using unmanned to conduct reconnaissance on the ground in wartime conditions has shown that this technology has great potential to improve operational intelligence and ensuring the safety of military personnel. The advantages of using unmanned aerial vehicles for reconnaissance are obvious. They can quickly and efficiently penetrate enemy territory, collect information territory, collect information and transmit it in real time. This makes it possible to Reduce the risk to the lives of servicemen, as they do not need to go to the front line the front line to conduct reconnaissance. In addition, unmanned aerial vehicles can operate in hazardous environments, such as radioactive contamination or chemicals where humans cannot enter. The use of unmanned aerial vehicles also ensures greater accuracy and objectivity in collecting information. They are equipped with various types of sensors, such as high-resolution cameras, thermal cameras, radars, etc., which provide detailed information about the territory, enemy positions and movements. This significantly improves the quality of intelligence and allows for more informed decisions on further actions. In summary, research has shown that the use of unmanned aerial vehicles for reconnaissance in wartime has significant potential. They can collect information quickly, efficiently and safely, improving operational intelligence and ensuring the safety of soldiers. However, further research and development of new technologies is needed to improve the functionality and safety of unmanned aerial vehicles in warfare.

In this paper, the effective use of flight-time constrained unmanned aerial vehicles (UAVs) as flying base stations that provide wireless service to ground users is investigated. In particular, a novel framework for optimizing the performance of such UAV-based wireless systems in terms of the average number of bits (data service) transmitted to users as well as the UAVs' hover duration (i.e. flight time) is proposed. In the considered model, UAVs hover over a given geographical area to serve ground users that are distributed within the area based on an arbitrary spatial distribution function. In this case, two practical scenarios are considered. In the first scenario, based on the maximum possible hover times of UAVs, the average data service delivered to the users under a fair resource allocation scheme is maximized by finding the optimal cell partitions associated to the UAVs. Using the powerful mathematical framework of optimal transport theory, this cell partitioning problem is proved to be equivalent to a convex optimization problem. Subsequently, a gradient-based algorithm is proposed for optimally partitioning the geographical area based on the users' distribution, hover times, and locations of the UAVs. In the second scenario, given the load requirements of ground users, the minimum average hover time that the UAVs need for completely servicing their ground users is derived. To this end, first, an optimal bandwidth allocation scheme for serving the users is proposed. Then, given this optimal bandwidth allocation, optimal cell partitions associated with the UAVs are derived by exploiting the optimal transport theory. Simulation results show that our proposed cell partitioning approach leads to a significantly higher fairness among the users compared with the classical weighted Voronoi diagram. Furthermore, the results demonstrate that the average hover time of the UAVs can be reduced by 64% by adopting the proposed optimal bandwidth allocation scheme as well as the optimal cell partitioning approach. In addition, our results reveal an inherent tradeoff between the hover time of UAVs and bandwidth efficiency while serving the ground users.

У статті пропонується підхід щодо формалізації знань про процес планування маршруту польоту безпілотного літального апарату на етапі планування повітряної розвідки за допомогою евристичних методів, які є найкращими з точки зору врахування практики, досвіду, інтуїції, знань осіб, що приймають рішення, при веденні повітряної розвідки. Розроблений метод дозволяє формалізувати фактори, що враховують тактичні умови проведення повітряної розвідки, вплив зовнішнього середовища на дальність польоту безпілотного літального апарату у вигляді лінгвістичних і інтервально-оцінюваних параметрів для кожного варіанту, які дозволяють врахувати невизначеність.

Unmanned aerial vehicles (UAVs) are an emerging technology for 3D Earth modelling and mapping. UAVs collect aerial images that are used to generate orthophotos with the assistance of navigation systems such as the Global Positioning System (GPS) and telemetry monitors at the Ground Control Station (GSC) for monitoring and controlling the UAV in autonomous flight. However, precision is critical in UAV photogrammetry mapping (PMg) to present acceptable precision measurements of the captured images that closely related to Ground Sample Distance (GSD) as most survey works are gradually shifting away from conventional surveying equipment such as total station and theodolite which has good precision measurement. This study focuses on the application of UAVs at close-range topography and mapping of land slope. Flight through the slope will vary in terms of flying altitude, affecting the GSD’s value for each slope height. The accuracy of PMg for land slope is subsequently assessed by evaluating the accuracy of slope mapping, particularly the slope height derived from Digital Elevation Model (DEM), Digital Surface Model (DSM) of orthophotos and Global Navigation Satellite System (GNSS) survey. This is due to the fact that most PMg is done on almost exclusively horizontal areas, and the GSD change value acquired remains the same. The purpose of this study is to analyze the accuracy of PMg of land slope by land slope mapping at 100m flight high above ground level. the RMSE recorded for x and y coordinate were (RMSEx = 0.654198cm) and (RMSEy = 0.668516cm) while for elevation error was (RMSEz = 0.512062cm). This study’s output is to help and assist authorities in construction planning, particularly during the cutting and filling process; to determine the precise amount of earth required for construction; and control the cost of earthwork.