Eristalis Research Articles

여성 노인들의 디지털 리터러시 교육 참여 경험을 통한 디지털 기기 활용과 인식 변화에 관한 사례연구

Objectives This study aims to explore, through a qualitative case study method, whether participation in digital literacy education for elderly women leads to changes in their digital device utilization skills and perceptions. Methods For this study, card news creation, drone flying, and coding education were conducted on four elderly women over two 60-minute sessions on September 8 and September 14, 2023. In order to derive the meaning of the change in awareness of the experience of participating in digital literacy education, the participants observed the scenes of the educational site explored from the perspective of an observer, and after the education, the data of individual interviews and additional questions about the experience of participating in this education were analyzed qualitatively over two sessions of about 30 minutes each. Afterwards, the analyzed data were reviewed by experts and the participants to secure the validity of the study. Results The experience of participating in digital literacy education for elderly women gradually reduced their fear of media devices, and the educational experience of using media devices improved their self-confidence. The meaning of the change in digital device use and awareness through the experience of participating in digital literacy education is as follows. ‘First,’ as a ‘change in behavior,’ it created the will to challenge new things, second, as a ‘psychological change,’ it derived the meaning of ‘gratitude through enlightenment and the value of learning,’ and third, as a ‘change in awareness,’ it derived the meaning of ‘self-discovery and improved self-confidence through new experiences.’ Conclusions This study shows that the expansion of information and communication technology and non- face-to-face education using digital devices such as smartphones and computers brings convenience and benefits to the younger generation, but on the other hand, it can cause a sense of isolation and loss in the elderly who are not free to use digital devices. In conclusion, in the future super-aging society, various digital literacy education should be provided so that elderly women can reduce their fear of using digital devices through participation experiences in various digital literacy education and enjoy an active old age. Therefore, it is expected that this study will serve as basic data for digital literacy education related to elderly women.

Quantifying Well Clear Thresholds for UAV in Conjunction with Trajectory Conformity

The rapid advancement of unmanned aerial vehicles (UAVs) has introduced new challenges in overseeing and managing their flight operations due to their diverse flight dynamics and performance metrics. To address these complexities, this study introduces a concept of trajectory conformity aimed at enhancing the supervision and control of UAV flights. Trajectory conformity, from a regulatory perspective, is defined as the distribution of deviations between a UAV’s actual flight path and its intended trajectory, offering a measure of system-wide operational error. The concept of conformity is hoped to simplify and strengthen the monitoring process to ensure conflict-free drone flying. The present work is also concerned with the development of a comprehensive UAV collision risk model grounded in trajectory conformity analysis. The normality and homogeneity of UAV trajectory deviations are validated by evaluating the trajectory data obtained from real-world UAV flights. Well clear thresholds between two UAVs operating in three orthogonal directions within the same airspace have been established by the developed model. The results obtained demonstrate the effectiveness in omni-encounter scenarios, underscoring the potential to strengthen safety measures. The present work is expected to enhance UAV safety systems, such as detect and avoid (DAA) and unmanned aircraft system traffic management (UTM), by enabling real-time collision warnings within predefined safety thresholds, supporting proactive risk mitigation. Furthermore, the model’s versatility allows it to be applied to various UAV operational aspects in future works, including route planning, flight procedure design, airspace capacity assessments, and establishment of separation minima.

End-to-end drone route planning in flexible airspace design

Drone traffic, consisting of anything from small quadcopters for video and photography to large eVTOL transporting people, is expected to grow rapidly as soon as the challenges currently barring urban flights can be solved. One of the main challenges is how to automate authorization while both keeping full control over where and how drones fly over specific areas, and at the same time allowing the operators the freedom they require to successfully provide their services. While restrictions are necessary, being overly restrictive on plans has a negative impact on capacity, safety and efficiency. In this article we propose the combination of no-fly zones and flight grids into design elements for airspace design, to be used only where and when necessary. City planners can use these design elements to make both strategic decisions and real-time updates, and thereby set the rules for an automated system for planning and authorization. We describe the design elements, how to automatically find the optimal end-to-end route between or through these elements, a set of modifications or extension to improve flexibility even more, and demonstrate the efficacy of the approach through example airspace design patterns and by showing the resulting traffic in a drone traffic simulator.

Numerical investigation and performance comparison of UAV propeller with varying duct configuration

PurposeThe purpose of this study is to investigate the effects of propeller thrust with two different duct configurations. Propellers in a quadcopter play an indispensable role in generating the necessary thrust and torque to keep the drone flying and manoeuvring. Based on the specific purpose of the unmanned aerial vehicle, both the altitude and attitude can be varied by the amount of thrust produced.Design/methodology/approachThis paper deals with the generation of three numerical models such as plain rotor, rotor with fixed duct and rotor with rotating duct and the comparison of their amount of generated thrust. The plain rotor numerical analysis was compared with the experimental results. The rotor taken for the analysis was 15 mm*5.5 mm TAROT 650. Thrust was measured for all models at four different angular speeds, such as 2,500 rpm, 4,000 rpm, 5,500 rpm and 7,000 rpm.FindingsDue to the suction pressure gradient on the duct inlet surface, the additional amount of lift is produced, and it is the best way of increasing propulsion efficiency and its aerodynamic performance as it reduces the tip loss at the tip of the propeller. The turbulence model taken for the numerical analysis was k−ε.Originality/valueThe rotating duct is expected to provide additional thrust by the increased upward force due to the rotation of duct. The rotating duct produced the optimal results between the plain model and ducted model. At the highest speed of 7,000 rpm, the ducted propeller produced 24.97 N, and the rotating duct propeller produced 23.89 N, whereas the plain propeller produced 23 N thrust. Nearly 8.6% of the thrust improvement is observed in duct and 3.87% in rotating duct.

ASG-YOLOv5: Improved YOLOv5 unmanned aerial vehicle remote sensing aerial images scenario for small object detection based on attention and spatial gating.

With the accelerated development of the technological power of society, aerial images of drones gradually penetrated various industries. Due to the variable speed of drones, the captured images are shadowed, blurred, and obscured. Second, drones fly at varying altitudes, leading to changing target scales and making it difficult to detect and identify small targets. In order to solve the above problems, an improved ASG-YOLOv5 model is proposed in this paper. Firstly, this research proposes a dynamic contextual attention module, which uses feature scores to dynamically assign feature weights and output feature information through channel dimensions to improve the model's attention to small target feature information and increase the network's ability to extract contextual information; secondly, this research designs a spatial gating filtering multi-directional weighted fusion module, which uses spatial filtering and weighted bidirectional fusion in the multi-scale fusion stage to improve the characterization of weak targets, reduce the interference of redundant information, and better adapt to the detection of weak targets in images under unmanned aerial vehicle remote sensing aerial photography; meanwhile, using Normalized Wasserstein Distance and CIoU regression loss function, the similarity metric value of the regression frame is obtained by modeling the Gaussian distribution of the regression frame, which increases the smoothing of the positional difference of the small targets and solves the problem that the positional deviation of the small targets is very sensitive, so that the model's detection accuracy of the small targets is effectively improved. This paper trains and tests the model on the VisDrone2021 and AI-TOD datasets. This study used the NWPU-RESISC dataset for visual detection validation. The experimental results show that ASG-YOLOv5 has a better detection effect in unmanned aerial vehicle remote sensing aerial images, and the frames per second (FPS) reaches 86, which meets the requirement of real-time small target detection, and it can be better adapted to the detection of the weak and small targets in the aerial image dataset, and ASG-YOLOv5 outperforms many existing target detection methods, and its detection accuracy reaches 21.1% mAP value. The mAP values are improved by 2.9% and 1.4%, respectively, compared with the YOLOv5 model. The project is available at https://github.com/woaini-shw/asg-yolov5.git.

Very Low Level Flight Rules for Manned and Unmanned Aircraft Operations

An analysis of the development of legal regulations regarding unmanned civil aviation leads to the conclusion that the current air traffic rules are among the key issues that require amending. Are drones allowed to fly at any height? Can drones fly freely over a person’s house or garden, several meters above the ground? What is the minimum allowable height for drone flights? The method of study consisted of content analysis of the existing legislation. Current doctrines were confronted with the existing regulations, documents, materials, safety reports, and statistics. The results of the study show that the existing air traffic rules, precisely in the case of aircraft operations performed by manned and unmanned aviation at very low heights, are definitely practical in nature. First, in most countries violations of air traffic rules are prohibited acts subject to criminal penalty. Second, determining the principles of air traffic for air operations is of crucial importance for determining legally permissible interference in property ownership. The urban air mobility is outside the scope of this research.

Drone Technology and it’s Application

Drones were first used by the military, but now they're not just for the army – they're for regular folks too. People started using them in the 2000s, and they're not just for serious stuff like analyzing power system faults. Now, we call them drones, and they're like flying robots. You can use them for all kinds of fun things like taking cool pictures, exploring hard-to- reach places, and even joining drone competitions. They've become a big deal on social media and in business competitions. Lately, smart people are working on making tiny drones that can fly by themselves, especially in indoor spaces. The good news is that the parts that make drones work, like tiny computers, sensors, batteries, and ways for them to talk wirelessly, are getting smaller and cheaper. So, soon, we might see small drones everywhere, doing all sorts of stuff in our daily lives at prices we can all afford. But, as drones become more popular, there are some worries. Imagine if someone used a drone to spy on you in your private space – that's not cool! And when drones fly in busy places like cities and airports, there could be problems. That's why we need rules and checks to make sure things don't go wrong. So, while drones are super cool and fun, we also need to make sure everyone stays safe and feels secure. Keywords--Unmanned Aerial Vehicle, Drone, Drone Features, Technology, Drone usage fields.

Drone-Based Bug Detection in Orchards with Nets: A Novel Orienteering Approach

The use of drones for collecting information and detecting bugs in orchards covered by nets is a challenging problem. The nets help in reducing pest damage, but they also constrain the drone’s flight path, making it longer and more complex. To address this issue, we model the orchard as an aisle-graph, a regular data structure that represents consecutive aisles where trees are arranged in straight lines. The drone flies close to the trees and takes pictures at specific positions for monitoring the presence of bugs, but its energy is limited, so it can only visit a subset of positions. To tackle this challenge, we introduce the Single-drone Orienteering Aisle-graph Problem (SOAP), a variant of the orienteering problem, where likely infested locations are prioritized by assigning them a larger profit. Additionally, the drone’s movements have a cost in terms of energy, and the objective is to plan a drone’s route in the most profitable locations under a given drone’s battery. We show that SOAP can be optimally solved in polynomial time, but for larger orchards/instances, we propose faster approximation and heuristic algorithms. Finally, we evaluate the algorithms on synthetic and real datasets to demonstrate their effectiveness and efficiency.

REDUCTION OF THE RISK OF DAMAGE AT PROJECTILE DEBRIS PROJECTILE EFFECT

Problem statement. The task of assessing the risk of damage to an oil storage facility by debris in the event of a drone explosion is considered. An analysis of the debris movement velocity and the effectiveness of the use of a protective barrier to stop the debris movement in the direction of the oil storage facility is carried out. The purpose of the article. Assessment of the risk of damage to the oil storage wall and the effectiveness of the use of a protective barrier against the throwing action of debris during a drone explosion. Methodology. A numerical model based on the integration of the equation of a material point motion and an empirical model is used to analyze the risk of damage to an oil storage facility when the debris of a drone flies off. The developed numerical model takes into account the initial velocity and size of the debris, the direction of the debris movement, and the height of the debris ejection. On the basis of this numerical model, a computer code was created for conducting a computational experiment. Scientific novelty. An effective mathematical model is developed for analyzing the risk of damage to an oil storage facility from the throwing action of debris generated by a drone explosion. The model makes it possible to determine the effectiveness of using an obstacle to protect an oil storage facility from the throwing action of debris. Practical value. A computer code is developed for calculating the dynamics of the debris movement in the air, which are formed during the explosion of a drone. The use of this code makes it possible to select the rational dimensions of the protective barrier at the industrial site to protect the oil storage from damage. Conclusions. An effective tool for analyzing the risk of damage to an oil storage facility from the throwing action of debris created by a drone explosion is developed. The results of computational experiments are presented.

Thermal Image Tracking for Search and Rescue Missions with a Drone

Infrared thermal imaging is useful for human body recognition for search and rescue (SAR) missions. This paper discusses thermal object tracking for SAR missions with a drone. The entire process consists of object detection and multiple-target tracking. The You-Only-Look-Once (YOLO) detection model is utilized to detect people in thermal videos. Multiple-target tracking is performed via track initialization, maintenance, and termination. Position measurements in two consecutive frames initialize the track. Tracks are maintained using a Kalman filter. A bounding box gating rule is proposed for the measurement-to-track association. This proposed rule is combined with the statistically nearest neighbor association rule to assign measurements to tracks. The track-to-track association selects the fittest track for a track and fuses them. In the experiments, three videos of three hikers simulating being lost in the mountains were captured using a thermal imaging camera on a drone. Capturing was assumed under difficult conditions; the objects are close or occluded, and the drone flies arbitrarily in horizontal and vertical directions. Robust tracking results were obtained in terms of average total track life and average track purity, whereas the average mean track life was shortened in harsh searching environments.

Study on Drone Handover Methods Suitable for Multipath Interference Due to Obstacles

Networks constructed in the sky are known as non-terrestrial networks (NTNs). As an example of an NTN, relay transmission using drones as radio stations enables flexible network construction in the air by performing handovers with ground stations. However, the presence of structures or obstacles in the flight path causes multipath interference; consequently, the propagation environment fluctuates significantly based on the flight. In such a communication environment, it is difficult for a drone to select an optimal ground station for a handover. Moreover, unlike a terrestrial network, the propagation environment of a flying drone is affected by structures and other factors that cause multipaths based on the flight speed and altitude, making the conditions of the propagation environment even more complex. To solve these problems, we propose handover schemes between drones and the ground that consider the multipath interference caused by obstacles. The proposed methods are used to perform handovers based on an optimal threshold of received power considering interference and avoid unnecessary handovers based on the moving speed, which makes the handover seamless. Finally, we develop a simulator that evaluates the cross layer from propagation to upper network protocols in a virtual space, including buildings, evaluate the communication quality of a drone flying in a three-dimensional space, and confirm the effectiveness of the proposed methods as well as the evaluation of the real environment.

Design and Control of Autonomous Flying Excavator

This study presents a drone-based excavation platform prototype with the key objectives of balancing stability during excavation, sensing, and digging the soil pile autonomously without human intervention. The whole platform was first designed in CAD software, and then each part of the excavator assembly was 3D printed by using PLA filament. The physical system was then combined with numerous electronic components and linked to various software applications for a drone to perform autonomous excavations. Pixhawk Orange Cube served as the main controller for the drone, while Nvidia Jetson Nano was used for processing data and controlling the tip of the bucket at a specified location for the autonomous excavator. Two scenarios were considered to validate the functionality of the developed platform. In the first scenario, the drone flies independently to a construction site, lands, senses the soil, excavates it, and then travels to another location specified by the mission to deposit the soil.

A framework for the optimal deployment of police drones based on street-level crime risk

Drones are increasingly adopted for policing in many countries, as they can aid police officers to detect hazards and respond to incidents with timely and low-cost services. However, the planning and deployment of police drones are subject to several challenges, including the proper distance metric for drone flying and the risk-based location optimisation of drone base stations. This study proposes a new framework that enables the optimal deployment of police drones to address crime risk issues on urban street networks. This risk-based decision framework takes into account three potential distance metrics that regulate and shape the flying routes of drones, which in turn affects the optimal location of drone base stations. In addition, this framework takes into account the major risk constraints of flying drones in urban areas, including domestic privacy and elevation. The proposed risk-based decision framework is validated using the real case study of Liverpool with historical crime data and street network layouts. The findings contribute to the operations and management of police drones in urban areas and shift the paradigm of policing drones towards a risk-based regime.

The golden native drone fly (Eristalinus punctulatus) is an effective hybrid carrot pollinator that lives within Australian crop agroecosystems

Abstract Native insect flower visitors can be important contributors to crop pollination, yet little is known of their pollination abilities and the resources (habitat) they need to be supported within crop agroecosystems. Here, we compared the abundance and pollination abilities of the golden drone fly (Eristalinus punctulatus) to the European honey bee (Apis mellifera) in hybrid carrot crop fields known to produce variable seed yields in regional New South Wales, Australia. We further observed the egg‐laying behaviours of female golden drone flies at a commercial berry orchard to provide insight into the habitat needs of this species. In hybrid carrot crop fields, golden drone flies were far less abundant flower visitors than European honey bees; however, these flies deposited more carrot pollen grains on average (8.21 ± 3.04 SE) onto carrot flowers than European honey bees (3.45 ± 1.06 SE). Both insects also deposited pollen onto a similar number of carrot flowers (pollinated) per visit (about 2 out of 18). Golden drone flies were observed laying eggs within masses of discarded red raspberry plant roots and soil (root balls) at a commercial berry orchard. The natural habitat utilised by these flies, as well as their egg‐laying behaviours, were described for the first time. Our results indicate that golden drone flies are effective pollinators of hybrid carrot crop plants. The habitat that these flies utilised to lay eggs (discarded plants and water) is cheap and commonly found in crop agroecosystems. Therefore, we recommend placing this low‐cost habitat within, or nearby, crop fields as a potential management practice to support the lifecycle needs of golden drone flies and other non‐bee pollinators.

Image background assessment as a novel technique for insect microhabitat identification

Habitat fragmentation under increased urbanisation, industrial agriculture and land clearing, are changing the way insects occupy habitat. Some species are highly adaptable and may occupy urbanised areas, utilising anthropogenic microhabitat-scale features. Other species are dependent on natural elements of their habitats, having to locate small regions of natural microhabitat within increasingly hostile landscapes. Consequently, humans are encountering insects in new settings. Identifying and analysing insects’ use of natural and anthropogenic microhabitats is therefore important to assess their responses to a changing environment, for instance to improve pollination or manage invasive pests. But such studies are labour-intensive.Traditional studies of insect microhabitat use can now be supplemented by machine learning-based insect image analysis. Typically, research has focused on automatic insect classification, but valuable data appearing in image backgrounds has been ignored. In this research, we analysed the backgrounds of insect images available in the Atlas of Living Australia database to determine the microhabitats in which they were commonly photographed. We analysed the image backgrounds of three globally distributed insect species that are common across Australia: Drone flies (Eristalis tenax), European honey bees (Apis mellifera), and European wasps (Vespula germanica). Image backgrounds were classified broadly as either natural or anthropogenic using computer vision and machine learning tools benchmarked against a manual classification algorithm.Our automated image background classification achieved 97.4% accuracy when compared against manual classification. Mis-classifications were scarce, usually less than 1%, and primarily for backgrounds of wood and soil or bare ground. Our results indicate that drone flies and European honey bees were predominantly photographed against natural backgrounds (flies manual classifier 95±3%, automated classifier 94%, bees 89±2%,87%), implying frequent observations by humans in natural microhabitat. European wasps were less frequently photographed against natural backgrounds (70±6%,63%). Within this data set, observations of the wasps in anthropogenic microhabitats were more common than for flies and bees.Our results are aligned with the expectation that the wasps are relatively well-suited to urban environments, and that European honey bees and drone flies utilise natural features of their environment. In general, although biases in data collected without formal protocols limits their application, our new automated approach for image background analysis can provide valuable data about insects’ interactions with humans, our artefacts, and natural features of their environments.

Tricolored Blackbirds’ Reliance on Insects from Dairies

The Tricolored Blackbird has been in a severe population decline due to habitat loss and other factors. It is now heavily dependent on agricultural landscapes such as hay fields for foraging and grain fields for nesting. Dairies are known to provide a concentrated food source throughout the year in the form of grain gleaned from cattle feed. For nesting, however, Tricolored Blackbirds require large quantities of insects for their young. A colony of Tricolored Blackbirds in the San Jacinto Valley, Riverside County, in southern California, fed their young large numbers of house flies from nearby dairy-cattle yards, as well as drone fly larvae from dairy-effluent ponds. At this colony, 67% of the nestlings’ food came from the dairy and another 13% from the adjacent hay fields. Most other insects came from irrigated weedy growth adjacent to wetlands. Such an intense reliance on dairies is risky for the blackbirds as urbanization is displacing the dairy industry in the San Jacinto Valley and many other areas of California. Another potential risk to the blackbirds is the use of pesticides at dairies for fly control. Further research is recommended to determine if this utilization of flies from dairies is widespread in California. Research is also needed to quantify the decrease of insects in drought-stricken landscapes and how this may affect the Tricolored Blackbird’s reproductive success.

Drone Detection using Ultrasonic Sensors for Passive Forward Scattering Radar System

Passive Forward Scattering Radar (PFSR) is a great system that can be used to identify ground moving targets, especially in unsafe areas for reason such as protection and security. Although PFSR can detect any moving target, there are some limitations as PFSR cannot measure height and detect small target such as a drone flying in the sky. A drone is a good device based on the latest technologies, therefore it can also be very dangerous as it can fly in the sky entering prohibited areas that can, for example, breach a border protection system. By developing a system using ultrasonic range sensor interfacing with Raspberry Pi (RPi) and also implementing Internet of Things (IoT) using mobile phone application, which is Telegram, as a security alarm system, this system can integrate with PFSR to be a better system. This project aims to improve the PFSR system with an ultrasonic range sensor remote measuring device. When set up next to the PFSR system, the ultrasonic range sensor has large distance measurement capabilities and use low power to operate. Since ultrasonic range sensors cannot work by themselves, the RPi was used as an operating host that helped to operate and collect data. Then, the data collected was saved into Comma Separated Values (CSV) files to be sent to Telegram mobile application later to the user as notification. The data collected from both systems were compared in order to relate that the ultrasonic range sensor system can indeed support the PFSR system. Since the result was obtained and analysis was done successfully, it can be concluded that the system can support the PFSR system, whereby as the drone height (cm) increased, the signal captured in time (sec) decreased. In addition, this system can contribute in many areas such as borders or streets, to detect speed of vehicles or as a traffic surveillance system and for some other reasons such as protection, security and research.

Innate preferences of Eristalis tenax L. (Syrphidae) for flower colour, size and symmetry are more intricate than the simple additive model

Abstract Plants have evolved complex flowers that differ in visual traits such as colour, size and shape, to attract pollinators. However, pollinators seem to respond differently to individual traits. Our objective was to unravel the effect of individual traits and their interplay in forming pollinator preferences. We measured the preferences of naive drone flies, Eristalis tenax (Syrphidae), for artificial flowers differing in colour, size and flower symmetry, in controlled conditions to untangle the effects of individual traits on pollinator behaviour. Eristalis tenax showed the highest selectivity for colour, followed by size, and only moderate selectivity in relationship to flower symmetry. Flower colour interacted with flower size, in that yellow colour was generally preferred, particularly when the flowers were large in comparison to other forms. Our results suggest that preferences for flower traits are structured, which might suggest that there have been different evolutionary pressures on individual floral traits.

Improvement of ultrasonic sensor-based obstacle avoidance system in drones

Although drone users have received the necessary training, the reflexes of making decisions against a sudden natural event such as wind and avoiding a nearby obstacle may not be sufficient. Therefore, whether drones fly autonomously or under user control, they must sense and act accordingly for an uninterrupted mission. In this study, a drone design and application for obstacle detection and obstacle avoidance were carried out. In the designed drone, Pixhawk was used as the flight control board, ultrasonic sensors were used to detect obstacles, and Arduino Uno was used as a microcontroller to obtain avoidance commands. The sensors used in obstacle detection and their performance are the most decisive factors in achieving the targeted goal. Because obstacle detection sensors are affected by electrical noises, the success of detecting obstacles decreases. For this reason, first of all, the integration of these sensors into the system was investigated and the drone was developed accordingly. Then, an algorithm was developed using a software filtering method both to minimize communication instabilities and to increase the clarity of detection. Finally, the ability to evade obstacles both while the drone is suspended in the air and while it is in motion has been investigated. In the experiments carried out, it was found that the drone was able to successfully avoid obstacles up to a flight speed of 3.94 m/s.

Mango Fruit Fly Trap Detection Using Different Wireless Communications

Fruit flies cause production losses in mango orchards affecting fruit quality. A National Campaign against Fruit Flies (NCFF) evaluates farm status using the fruit flies per trap per day index (FTD). Traps with attractant are installed manually within orchards in Mexico, but counting the flies trapped every week requires excessive numbers of trained personal. Electronic traps (e-traps) use sensors to monitor fruit fly population, saving labor and obtaining the real-time orchard infestation. The objective of this work was to acquire an image within a e-trap at 17:00 when an insect was detected and binarize the information in real-time to count the number of flies. Each e-trap was implemented with a polyethylene PET bottle screwed to a tap containing an ESP32-CAM camera. E-traps from several hectares of mango trees were sampled and transmitted through WSN wireless sensor networks. This original system presents a star topology network within each hectare with the long range LoRa transceiver at the central tower. It receives the fly count from five e-traps and finally transmits data to the house tower end point. Another contribution of this research was the use of a DJI mini2 for acquiring the e-trap data, and the 8-ha flight took 15 min and 35 s. This period can be reduced if the drone flies higher.