• Journal of Apiculture
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• v.33 no.4
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• pp.303-306
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• 2018

Drones of honeybee (Apis mellifera) have been regarded as a useful value only when mating with queen bee. However, the drone pupae have been reported to be nutritionally valuable, and a potential beekeeping product. In this study, drone pupae extracted with 5% acetic acid were used to measure anti-thrombosis related fibrinolytic activity using Strup and Mullertz fibrin plate method. As a result, the drone pupae extract showed higher effect of fibrinolytic activity(clear zone diameter 20.83mm) compared to the human plasmin (clear zone diameter 12.93mm) used as a positive control. It was suggested that the extract of drone pupae can be developed as a functional material helping prevention or treatment of various vascular diseases.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Drive and Control
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• v.20 no.3
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• pp.25-34
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• 2023

In this study, we conducted a research on optimizing the spraying performance of agricultural drones and predicted the spraying performance in various flight conditions using the multi-layer perceptron (MLP). Data was collected using a test device for pesticide spraying performance according to the water sensitive paper (WSP) evaluation. MLP training involved supervised learning to achieve a coefficient of variation (CV), which indicates the degree of uniform spraying. The performance evaluation was conducted using R-squared (R²), the test samples showed an R² of 0.80. The results of this study showed that drone spraying performance can be predicted under various flight environments. In addition, the correlation analysis between flight conditions and predicted spraying performance will be useful for further research on optimizing the spraying performance of agricultural drones.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.531-536
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• 2024

Control drones, which are recently classified as smart agricultural machines in the agricultural field, are striving to build smart control and automatic control systems by combining hardware and software in order to shorten working hours and increase the effectiveness of control in the aging era of rural areas. In this paper, the characteristics of the nozzle dedicated to the control drone were analyzed as a basic study for the establishment of management control and automatic control systems. In order to consider various variables such as the type of various drone models, controller, wind, flight speed, flight altitude, weather conditions, and UAV pesticide types, related studies are needed to be able to present the drug spraying criteria in consideration of the characteristics and versatility of the nozzle. Therefore, to enable the consideration of various variables, flow analysis (CFD) simulation was conducted based on the self-designed nozzle, and the theoretical and experimental values of the droplet distribution were compared and analyzed through water reduction experiments. In the future, we intend to calculate accurate scattering in consideration of various variables according to drone operation and use it in management control and automatic control systems.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.427-435
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• 2023

This study was conducted to evaluate the spraying performance according to the flight conditions of agricultural drones for the development of a variable control system. The analyzed flight conditions comprised six factors: spraying direction, flight speed, altitude, wind speed, wind direction, and rotor rotational speed. The ratio of the area sprayed on the water-sensitive paper was used as the coverage, and the distribution and amount of the coverage were evaluated. The coverage distribution based on the distance from the drone was used to evaluate a spray pattern, and the distribution was expressed as a Gaussian function approximation. In addition, the probability distribution based on coverage was expressed as the cumulative probability via Gamma function approximation to analyze the spraying efficiency in the target area. The results showed that the averaged coverage decreased significantly as the flight speed and wind speed increased, and the wind direction changed the spray pattern without a coverage decrease. This study contributes to the development of a control technique for the precision control system of agricultural drones.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.575-580
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• 2023

This study was prevent the decrease in crop output by insect pests and spraying by application uniformity. A flight level 4 m height and 4-5 m/sec. speed are difficult to maintain with a agricultural drone for aerial application, which has been affected by the methods or environmental factors, such as changes in the wind. Therefore, which can allow a controlled application width and spray rate automatically and verified experimentally using drone. The sprayed particles began to decrease from about 3.75 m on the left and right sides of the spray nozzle. According to the number of particles, the effective spraying width was observed to be about 7.5 m, and it was verified that the proposed spraying system was effective in uniform control system.

• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.70-80
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• 2018

Drones are now widely used in civilian applications such as filming, leisure, agricultural control, monitoring, and the generation of 3D-spatial information, deviating only from military drones. In the field of logistics, prototypes are emerging in the area of logistics transportation, and to develop a future transportation service under the name of a drone tax, each country is introducing its first flight results using its own unique drones. In this paper, we review the domestic and overseas trends of drone delivery service technology, which requires various capabilities such as automatic flight, and review the related core technologies. We then propose the flight capability and road map of a drone delivery service according to the detailed conditions such as the flight area, visibility, and flight method. Additionally, in connection with the postal processing of the Korea Post Office, which would be a main demand for this type of service, we describe a method for realizing a drone delivery service based on the structure, scenario, and deployment of the drone delivery system.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.38-44
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• 2017

Currently, wired gables have been installed or portable storage devices have been installed for data acquisition of flying drone. In this paper, we propose a technology to transmit data wirelessly by sensing information such as battery discharge value, acceleration, and temperature by attaching RF sensor to a drone. The purpose of this paper is to design and develop the monitoring technology of agriculture drone battery usage in real time using RF sensor. In this paper, we propose a monitoring system that can check real time data of battery changed value, temperature, and acceleration during pesticide control activity of agricultural drone.

• Journal of Platform Technology
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• v.10 no.2
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• pp.20-26
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• 2022

Interest and investment in drones that apply the concept of the 4th industrial revolution and ICT convergence advanced technology are continuing. The purpose of drone operation has been widely spread from the initial military use to the use of various industries such as construction, forestry, facilities, and agricultural support. In these industries, the training of pilots who can actually operate drones is increasing centering on the qualification system. However, the detailed standards including the training place, training place, educational environment, and education method for nurturing pilots are ambiguous, so the education through the oral instruction of the training instructor is continuing at the drone training site. In order to solve this problem, this study conducted a study on a dual control platform in which a training instructor could directly intervene in the pilot's flying drone to execute a map in order to improve the quality of synesthesia, which is essential in the field.