Monitoring of Wildlife Using Unmanned Aerial Vehicle (UAV) With Machine Learning

The use of unmanned aerial vehicles allows the countries that use them to significantly reduce the loss of manpower and equipment during the combat mission and at the same time significantly increase the effectiveness of the use of high-precision and conventional means of destruction. The greatest experience in the use of unmanned aerial vehicles was acquired by countries that are actually advanced in terms of military technology (in particular, the USA, Israel, Turkey, etc.), which took an active part in armed conflicts in the Middle East, the North Caucasus, etc. In addition, in modern conditions, the threat of uncontrolled spread of the use of unmanned aerial vehicles of a light class, which can be used for the purpose of carrying out terrorist acts on important state and military facilities, is growing. Unmanned aerial vehicles have become so important to success on the battlefield that they are sometimes used by the military to destroy enemy drones. In addition, it is with the help of unmanned aerial vehicles that one side receives the coordinates of military targets and command posts of the opposite side, which are subsequently destroyed by accurate artillery strikes. In the article, based on the analysis of modern wars and armed conflicts, combat experience and features of the use of unmanned aerial vehicles of the armed forces of the russian federation, an analysis of unmanned aerial vehicles for typical tasks, in particular, conducting reconnaissance, adjusting fire, striking and electronic warfare, was carried out. In particular, the conducted analysis indicates a tendency to increase the scale of use of unmanned aerial vehicles by the armed forces of the russian federation in conditions of a full-scale armed conflict (not excluded due to the end of stocks of high-precision missiles), in contrast to the experience of the combat use of individual unmanned aerial vehicles in the East of the country and the expansion of the range of tasks.

The conducted SWOT analysis made it possible to develop problematic issues that are proposed during the operation of unmanned aerial vehicles, proposals were made for the creation of a mobile complex of the use of unmanned aerial vehicles based on the chassis of a truck. Formulation of the problem. During hostilities, unmanned aerial vehicles (UAVs) were widely used. The massive use of the latest robotic (automated) weapons and military equipment on the battlefield is changing the nature of units' actions. Currently, almost every combat unit has a UAV application group. The high efficiency of their use is confirmed by high results on the battlefield. The security and defense forces of Ukraine are armed with dozens of types of UAVs for various purposes and with various capabilities for lifting cargo and carrying explosives. The use of UAV combat units in the field. Launches of lethal vehicles are carried out by hand or with the help of launch devices. With this mobile application group, the BPLA, although it is at a distance from the line of the next combat encounter, does not have sufficient security and protection from enemy fire. Preparation for use, maintenance of UAVs and charging of batteries in stationary conditions the day before, which reduces the efficiency of actions.The deployment of mobile groups of UAV operators is carried out on vehicles that are available to the military unit at the time, and which are not adapted for the high-quality performance of the combat mission by the group. UAV operators and equipment are not protected from exposure to low ambient temperatures and have no protection from small arms and shrapnel damage. Time indicators of deployment on the terrain of the complex for launching UAVs and folding after the completion of a combat mission need improvement. Analysis of recent research and publications. Scientific studies on improving the actions of units equipped with UAVs were carried out in the National Guard even before the beginning of the full-scale invasion of the Russian Federation. For example, in [1-2], data are given regarding the need for intelligence information and the development of a rational procedure for the use of intelligence unmanned aerial vehicles. In [3], the methodological apparatus for researching the problems of using information technologies and telecommunication systems in the process of military management is presented. The purpose of the article is to justify the need to create a mobile complex for the use of unmanned aerial vehicles based on a truck chassis. Provide recommendations on the creation of a mobile complex for the use of unmanned aerial vehicles.

Rapid growth of mechanization of all agricultural work cannot completely reduce human participation, so agricultural automation is extremely important. In terms of automation, this study highlights crucial role of UAVs in accurate and intelligent agriculture. In the article, possibilities of using unmanned aerial vehicles (UAVs) in agriculture are conisred. Advantages of using UAVs in comparison with traditional methods are described, as well as prospects for the development of this direction in the agricultural sector are highlighted. Of course, using of unmanned aerial vehicles is widespread in many countries of the world, and results of research in this direction, despite short period of implementation of this technology, are presented in numerous scientific publications. The volume of the global market for Unmanned Aircraft Systems is constantly increasing, and Ukraine, given high development of the aircraft industry, can become one of the leading manufacturers of integrated solutions and services to meet the ever-growing needs of this market. Ukraine has potential to use unmanned aerial vehicles in agriculture in terms of technical, economic and human resources. UAVs can provide clear, high-resolution images for commercial use, including agriculture. However, at present, the area of increasing the activity of multi-rotor UAVs for agricultural needs is not sufficiently studied. Many scientific works of domestic and foreign authors are devoted to the use of UAVs in agriculture. Nevertheless, today, the full list of works that can be performed with the help of UAVs, in particular in agriculture (agronomy), has not yet been determined. Using unmanned aerial vehicles in agriculture is the innovation for Ukraine, since UAVs were primarily used for military needs and only after military tests began to be widely used in agriculture. An important section of research on ways to improve the functionality of UAVs in the agricultural sector is to improve ways to control UAVs when using these advanced technologies as machine learning and the Internet of things. The analysis of the most effective ways to increase the activity of UAVs in agriculture is carried out and it is stated that evelopment of UAVs with new capabilities and improvement of their sensor base are the main ways of their modernization. It is noted that addition of new sensors that provide more accurate information about the state of crops will allow farmers to monitor and care for plants as efficiently as possible.

In the 21 st century, unmanned systems (especially unmanned aerial vehicles) will play a dominant role in the operational fields. Thanks to the technological developments witnessed in many fields, the use of unmanned aerial vehicles for military purposes is becoming easier. Looking at the operations carried out over the last 25 years, it can be seen that most were conducted in residential areas, where and techniques, tactics and equipment with asymmetric effects will make significant differences. In addition to this, the more loss of life in operations, the more governments come under pressure from the public. Taking these factors into consideration, it is believed that unmanned aerial vehicles, which can be used to increase dominance in operations and prevent loss of life, will be used more often and more effectively in the future. It is also believed that unmanned aerial vehicles will be used as assault media in both residential areas and in other operational environments in order to take advantage of the high level asymmetric effect.

The appearance in widespread use of unmanned aerial vehicles, both multi-rotor and wing-carrying aircraft, revealed the possibility of their use in the activities of the State Emergency Service of Ukraine. They can be used for emergency reconnaissance, aerial surveying, search operations, aviation chemical work related to the circulation of hazardous substances, monitoring of territories and objects, transmission of radio signals, delivery to the site of emergencies various types of payload, conducting alerting, lighting emergency situations and direct firefighting. Therefore, the issue of using unmanned aerial vehicles in the activities of the State Emergency Service of Ukraine is relevant. In essence, the use of an unmanned aerial vehicle is reduced to two main types of work - observation or work around a point object or movement over long distances to ensure work on the earth's surface. It is clear that the technical characteristics of the unmanned aerial vehicle determines its suitability for use in the relevant types of work. One of these characteristics is the range of radio communication, the busiest channel of which is real-time video communication, which is essential for most assigned tasks. The article attempts to estimate the range of video data transmission by radio for the most common models of multi-rotor unmanned aerial vehicles of mass production and video data transmission systems that can be used optionally. To this end, we analyze the characteristics of video transmission systems, factors that affect the quality of video communication and others. Existing mass-produced models are best suited to work around a point object. Their use for long-distance flights will be limited by the range of video data transmission. By overcoming this situation, the authors see the use of unified unmanned aerial vehicles equipping them with optional video transmission systems.

Editorial: Welcome to <i>Wildlife Letters</i>

In recent years, low-altitude and low-volume plant protection operations using unmanned aerial vehicle (UAV) sprayer developed rapidly in China with the advantages of high efficiency, labour saving, high safety, high terrain adaptability, high flexibility, water and chemicals saving, and high intelligence. With the UAV application technology in field crops is becoming more and more mature, aerial spraying operations in orchards are promising and in the ascendant, but a high risk of UAV spray drift is appearing due to high working height and fine droplets sprayed in slope orchards, highlighting the necessity of the study on the spray drift characteristics of UAV chemicals application for fruit trees. Therefore, based on previous research, a novel type of measuring method of spray drift for UAV chemicals application in orchard was proposed in this study and an artificial orchard test stand (vineyard) and 3 airborne drift frame collectors were designed and built, and a set of field drift test bench was firstly used to collect aerial spray drift droplets at different downwind distances, together with ground drift collectors and canopy deposition collectors. An airborne drift index (ADX) of UAV’s spray was initially applied for quantitative analysis to compare spray drift characteristics of different models of unmanned aircrafts and variable operation parameters. Fluorescence tracer Pyranine water solution was prepared at the concentration of 0.1% as the spray liquid. Four typical types of plant protection UAV (a single-rotor oil-powered helicopter, a 6-rotor motor drone and two models of 8-rotor motor drones) equipped with conventional hollow cone nozzle ‘TR 80-0067’ and air-induction anti-drift nozzle ‘IDK 120-015’were tested in the artificial vineyard, and results of canopy deposition distribution, ground sediment drift, near-ground drift, and airborne drift were obtained and analysed, and different sampling collectors for spray drift were evaluated and compared. The results showed that: Under the environmental conditions that the nominal crosswind speed was 2.4-3.6 m/s, the temperature was 29.8-34.3 ℃ and relative humidity was 10.7%-30.6%, at the flight height of 1.5 m (3.5 m from the ground) and the speed of 2.0 m/s the air-induction nozzle IDK can significantly reduce the level of downwind spray drift of UAV, optimize the uniformity of deposition distribution and increase the effective utilization rate of chemicals; There was no significant difference in the drift characteristics of the 4 types of unmanned aircraft, and the vortex generated by the combination of the rotor’s downwash airflow and the external wind was an important factor on spray drift; Buffer zone of UAV aerial spraying operation in vineyards should be set at at least 15 m; The lower the canopy deposition rate (P 0), the larger the average average drift rate (AADR) and 90% cumulative drift distancex90% of the field drift test bench (P 0), the greater the ADX value (P 0) all indicated the higher spray drift risk, respectively; Both these sampling collectors and their evaluation index could assess the downwind drift characteristics effectively; the relationship between the UAV spray drift rate βdep% and the downwind distance x was described by the exponential function. The results of this study are expected to provide references and data supports for the R&D of UAV dedicated for orchard spraying, the formulation of standards on spray drift field measuring method for UAV orchard operations and the selection of aerial application working parameters in orchards.

&amp;lt;p&amp;gt;Magnetic mapping is commonly used in the academic and industrial sectors for a wide variety of objectives. To comply with a broad range of survey designs, the use of unmanned aerial vehicles (UAVs) has become frequent over the recent years. The majority of existing systems involves a magnetic acquisition equipment and its carrier (an UAV in this context) with no -or very few- connections between the two systems. Terremys is conceiving and optimizing UAVs specifically adapted for geophysical magnetic acquisitions together with the appropriate processing tools, and performs magnetic surveying in challenging environments. Terremys&amp;amp;#8217; &amp;amp;#8220;Q6&amp;amp;#8221; system weights 2.5 kg in air, including UAV &amp;amp; instrumentation, and allows 30 min swarm or individual flights.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Rotary-wing UAVs are found to be the most adaptive systems for a wide range of contexts and constraints (extensive range of flights heights even with steep slopes). They offer more flight flexibility than fixed-wing aircrafts. One of the major problems in the use of rotary-wings UAVs for magnetic mapping is the magnetic field generated by the aircraft itself on the measurements. Towing the magnetic sensor 2 to 5 m under the aircraft reduces data positioning accuracy and decreases the performances of the UAV, which can be critical for high-resolution surveys. To overcome these problems, a deployable 1 m long boom&amp;amp;#160;is rigidly attached to the UAV. The UAV magnetic signal can be divided between 1-the magnetic field of the whole equipment and 2-a low to high frequency magnetic field mostly originating from the motors. The magnetization of the system is the principal source of magnetic noise. It is modelled and corrected by calibration-compensation processes permitted by the use of three-component fluxgate magnetometers. The time-varying noise depends on the motors rotational speed and is minimized by optimizing the UAV components and characteristics along with the boom&amp;amp;#8217;s length.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The final set-up is able to acquire magnetic data with a precision of 1 to 5 nT at any height from 1 to 150 m above ground level. The high-precision magnetic measurements are coupled with a centimetric RTK navigation system to allow for high-resolution surveying. The quality of the obtained data is similar to that obtained with ground or aerial surveys with conventional carriers and matches industrial standards. Moreover, Terremys&amp;amp;#8217; systems merge in real-time data from all the aircraft instruments in order to integrate magnetic measurements, positioning information and all the UAV&amp;amp;#8217;s flight data (full telemetry) into a unique synchronized data file. This opens up many possibilities in terms of QA/QC, data processing and facilitates on-field workflows.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Case studies with diverse designs, flight altitudes and targets are presented to investigate the acquisition performances for different applications, as distinct as network positioning, archaeological prospecting or geological mapping.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The full integration of the magnetic sensor to the drone opens the possibility for implementation additional sensors to the system. The adjoining of other magnetic sensors would allow multi-sensors surveying and increases daily productivity. Diverse geophysical sensors can also be added, such as thermal/infrared cameras, spectrometers, radar/SAR.&amp;lt;/p&amp;gt;

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.

With the advances in computation, sensor, communication and networking technologies, utilization of Unmanned Aerial Vehicles (UAVs) for military and civilian areas has become extremely popular for the last two decades. Since small UAVs are relatively cheap, the focus is changing, and usage of several small UAVs is preferred rather than one large UAV. This change in orientation is dramatic, and it is resulting to develop new networking technologies between UAVs, which can constitute swarm UAV teams for executing specific tasks with different levels of intra and inter vehicle communication especially for coordination and control of the system. Setting up a UAV network not only extends operational scope and range but also enables quick and reliable response time. Because UAVs are highly mobile nodes for networking, setting up an ad-hoc network is a challenging issue, and this networking has some requirements, which differ from traditional networks, mobile ad-hoc networks (MANETs) and vehicular ad-hoc networks (VANETs) in terms of connectivity, routing process, services, applications, etc. In this paper, it is aimed to point out the challenges in the usage of UAVs as mobile nodes in an ad-hoc network and to depict open research issues with analyzing the opportunities and future works.

This paper considers using unmanned aerial vehicles (UAVs) to survey important sites across a city. When the sites are relatively far from the UAVs’ depot, the UAVs may not be able to reach many of the sites. Suppose that a UAV can take public transportation vehicles (PTVs) like a passenger. Then, it may reach a site that is unreachable by flying only. Based on this UAV-PTV scheme, we investigate a task-UAV assignment problem, which assigns a set of surveillance tasks to UAVs. We formulate a mixed-integer linear programming (MILP) problem that minimizes the overall energy consumption of UAVs, subject to that every site is surveyed by a certain number of UAVs during a given time window, and all UAVs successfully return to the depot. Considering that this problem is NP-hard, we present two sub-optimal solutions. The first solution orders the surveillance tasks according to the starting times of their time windows. Then, starting from the earliest one, it assigns the tasks one by one to UAVs. The second solution breaks the tasks into small non-overlapping groups. It then assigns tasks to UAVs group by group. The former solution quickly addresses the assignment problem, but it lacks the overall management of UAV resources. The latter improves this by assigning a group of tasks simultaneously, and it can control the computation complexity by limiting the group size. The comparison with the brute force method shows that the proposed solutions can achieve competitive performance in a reasonable time. Note to Practitioners—Unmanned aerial vehicles (UAVs) have been widely used in surveillance missions. However, one challenge practitioners often meet is the limited flight duration. Commercial UAVs are in general powered by the onboard battery. Due to the restriction of payload, the battery capacity is constrained, which limits the UAVs’ operation time. In this paper, we present the approach exploiting public transportation vehicles (PTVs). In our design, a UAV can take a public transportation vehicles such as buses, trams and trains on the roof and transfer between vehicles when necessary. With this UAV-PTV collaboration scheme, we consider how to efficiently assign surveillance tasks to UAVs. Due to the NP-hardness of the considered problem, two suboptimal algorithms are presented.

Improved Green Anaconda Optimization Algorithm-based Coverage Path Planning Mechanism for heterogeneous unmanned aerial vehicles

Using unmanned aerial vehicles (UAVs) for bridge inspection is becoming increasingly popular due to its ability to improve efficiency and ensure the safety of monitoring personnel. Compared to traditional manual monitoring methods, UAV inspections are a safer and more efficient alternative. This paper examines the impact of meteorological conditions on UAV-based bridge monitoring during specific tasks, with the aim of enhancing the safety of the UAV’s costly components. The wake vortex behind a bridge structure can vary over time due to airflow, which can have a direct impact on the safety of UAV flights. To assess this impact, numerical analysis is conducted based on monitoring requirements specific to different tasks, taking into account wind speed, wind direction, and air temperature. In order to optimize UAV trajectory, it is important to consider the wake vortex intensity and its associated influence region, which can pose a potential danger to UAV flight. Additionally, the analysis should take into account the aerodynamic effects of different types of bridge columns on the wake vortex. An optimization algorithm was utilized to optimize the trajectory of a UAV during bridge inspections within the safe region affected by wind fields. This resulted in the determination of an effective and safe flight path. The study reveals that varying wind speeds have an impact on the safe flight zone of UAVs, even if they are below the operational requirements. Therefore, when monitoring bridges using UAVs, it is important to take into account the influence of meteorological conditions. Furthermore, it was observed that the flight path of UAVs during square cylinder column monitoring is longer and more time-consuming than round cylinder column monitoring. Determining an effective UAV inspection path is crucial for completing bridge monitoring tasks in windy conditions, establishing bridge inspection standards, and developing the Intelligent Bridge Inspection System (IBIS).

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.

The use and applications of unmanned aerial vehicles (UAVs) in geotechnical engineering is rapidly growing, leading to changes in the way that data is acquired, analyzed and processed. UAVs can reach areas previously inaccessible via ground or helicopter, while also being quickly deployed. Cameras are the current standard for data collection and 3D model creation.&#x0D; There are multiple types of UAV’s currently available. Quadcopters can take off and land in spatially constrained areas, but carry a small stabilized camera producing low quality models. Octocopters permit an increased payload, so a higher quality camera can be attached, allowing for increased model accuracy. Flight time is reduced by the additional weight. Fixed wing UAVs create higher quality photogrammetry models, and are commonly deployed over large surface areas. Transport Canada certification must be approved prior to any flights occurring for research or work. A detailed application must be created, including a flight plan and demonstration of prior flight experience.&#x0D; At the White Canyon site in B.C., a Phantom 4 Quadcopter was flown for geotechnical analysis of a complex geometry slope, which has previously been studied for several years. The terrain has occluded the data available from the ground or from permissible helicopter flight paths. Therefore, detailed information from the slope has not been previously available. The process of using a UAV to obtain these data sets, to develop a full 3D model of these areas of the slope is discussed, considering the accuracy and quality of the data available.