• Journal of Korean Society of Rural Planning
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• v.23 no.1
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• pp.21-29
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• 2017

The purpose of this study is to analyze the accuracy of cultivated crop database in agricultural farm business using UAV(Unmanned Aerial Vehicle) and field survey over Daesso-myeon, Umsung-gun, Chungbuk. When comparing with agricultural farm business and cadastral maps, Daeso-myeon crop field shows 29.8%(2,030 parcels out of 6,822 parcels) is either mismatched or missing. It covers almost 19.3%($3.4km^2$ of $17.6km^2$) of total farmland. In order to solve these problems, it is necessary to prepare a multifaceted plan including cadastral map. Comparative analysis of the cultivated crop registered in the agricultural farm business and the field survey agreed only in 3,622 parcels in total 6,822 parcels whereas 3200 parcels disagree. Among these disagreed parcels 2,030(29.8%) have been confirmed as unregistered farm business entity. Accuracy of cultivated crop registered in agricultural farm business agreed in 75.6% cases. Especially the paddy field registration is more accurate that other crops. These discrepancies can lead to false payment in agricultural farm business. For exploration and analysis of regional resources, UAV images can be used together with farm business management database and cadastral map to get a clearer grasp over on-site resources and conditions.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.209-216
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• 2024

Land shrimp farms can control the growth environment more stably than coastal ones, making them advantageous for high-quality, large-scale production. In order to maintain an optimal shrimp growth environment, various factors such as water circulation, maintaining appropriate water temperature, oxygen supply, and feed supply must be managed. In particular, failure to properly manage water quality can lead to the death of shrimp, making it difficult to have people stationed at the farm 24 hours a day to continuously manage them. In this paper, to solve this problem, we design an integrated monitoring system for land farms that can be operated with minimal manpower. The proposed design plan uses IoT technology to collect real-time images of land farms, pump status, water quality data, and energy usage and transmit them to the server. Through web interfaces and smartphone apps, administrators can check the status of the farm stored on the server anytime, anywhere in real time and take necessary measures. Therefore, it is possible to significantly reduce field work hours without the need for managers to reside in the farm.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.12a
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• pp.23-29
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• 1999

• Agricultural and Biosystems Engineering
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• v.2 no.2
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• pp.69-74
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• 2001

Detection of operation lines in farm works, object recognition and obstacle avoidance are essential pre-requisite technologies for unmanned agricultural machinery. A CCD camera, which has been largely used for these functions, is expensive and has difficulty in real-time signal processing. In this study, a laser range sensor was selected as the guiding vision for unmanned agricultural machinery such as a tractor. To achieve this capability, algorithms for distance measurement, signal filtering, object recognition, and obstacle avoidance were developed. Computer simulations were carried out to evaluate performance of the algorithms. Experiments were also conducted with various materials and shapes, Laser beam lost its intensity for poor reflective materials, resulting in less range value than actual, so a compensation technique was considered to be necessary. Object detection system was fabricated on an agricultural tractor and the performance was evaluated. As test result for obstacle detection and avoidance in field, to detect and avoid obstacle for path finding with guiding system for unmanned agricultural machinery was enable.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.2
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• pp.96-103
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• 2011

Rotor grip is used as a component of rotor system in unmanned helicopter. Instead of usual machining, hot forging process has been considered to improve its proof stress against repeated loading conditions and crash in the farm-field. Die design and forming analysis have been performed according to the conditions such as billet volume, flash, cavity filling, and the distribution of damage during the forming by using FE analysis. In the results of analysis, the possibility of structural failure in the model has not been found because its maximum effective stress is much lower than yield strength of the titanium alloy. In the forging die design, flash has been allowed because of low production in the industrial field. Preform design was studied by using FE-analysis, and its optimal dimension was obtained in the hot forging of rotor grip with titanium alloy.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.412-418
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• 2011

The scale of wind turbines has continuously increased over the last decade. Especially, the rapid growth of the rotor diameter has brought about the increase of the tower height and the load on the rotor blade, as can be seen in the case of a 5MW class wind turbine with 126m rotor diameter. This trend means the increasing possibility of system failure. In addition to that, it is impossible for human operators to stay and manage all the turbines in the case of a large-scale wind farm. For these reasons, the operation and maintenance technology is getting more importance. In this paper, we present an unmanned remote monitoring system for MW class wind turbines and its application to YeungHeung wind test bed.

• Journal of Practical Agriculture & Fisheries Research
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• v.10 no.1
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• pp.43-58
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• 2008

This research was conducted to determine the alternative tool of chemical spray for rice cultivation using the unmanned helicopter(Yamaha, R-Max Type 2G-remote controlled system) at farmer's field in Korea. The unmanned helicopter tested was introduced form Japan. In Korea the application of chemicals by machine sprayer for pest management in rice cultivation has been ordinarily used at the farmer's level. However, it involved a relatively high cost and laborious for the small scale of cultivation per farm household. Farm population has been highly decreased to 7.5% in 2002 and the population is expected to rapidly reduce by 3.5% in 2012. In Japan, pest control depending on unmanned helicopter has been increased by leaps and bounds. This was due in part to the materialization of the low-cost production technology under agricultural policy and demand environmentally friendly farm products. The practicability of the unmanned helicopter in terms of super efficiency and effectiveness has been proven, and the farmers have understood that the unmanned helicopter is indispensable in the future farming system that they visualized. Also, the unmanned helicopter has been applied to rice, wheat, soybean, vegetables, fruit trees, pine trees for spraying chemicals and/or fertilizers in Japan Effect of disease control by unmanned helicopter was partially approved against rice blast and sheath blight. However, the result was not satisfactory due to the weather conditions and cultural practices. The spray density was also determined in this experiment at 0, 15, 30, and 60cm height from the paddy soil surface and there was 968 spots at 0cm, 1,560 spots at 15cm, 1,923 spots at 30cm, and 2,999 spots at 60cm height. However, no significant difference was found among the treatments. At the same time, there was no phytotoxicity observed under the chemical stray using this unmanned helicopter, nor the rice plant itself was damaged by the wind during the operation.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.591-597
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• 1996

To straighten the path that farm machinery follows in paddy fields, it is necessary to measure and evaluate the tracks that these machines leave behind. However, there are no known methods for making such measurements and evaluations since it is difficult to accurately trace the paths that the machine make in paddy fields. Therefore, a measuring system has been developed which can accurately recored the path of a farm machinery in a field by measuring the horizontal straight-line distance from the side of the field to the machine. This system consists of a track subsystem on the machine and a range finder system. A measuring appraratus is installed on a flatcar which runs on rails over 50 m long at the side of the filed. The track subsystem uses a CCD camera to track the movement of the machine in the field which is following a lengthwise path. The range finder subsystem measures the distance that the measuring apparatus has traveled on the rails and the distance from the app ratus to the machine in the field. This system makes it possible to record the path that the machine travels. Even though differences in traveling distance arise between the measuring apparatus and the farm machine, these differences are detected by image processing , which allows the machine in the field to be located accurately. The short(0.05 second) time required for image processing is enough to follow an object . In the present study, this system was able to measure the path that a moving tractor makes. Even though a lag of up to 0.4 meters occurred, this system did not miss its target during operation of the track subsystem. Thus the path measuring system developed here is able to record vehicle paths automatically by following the movement of vehicles in the field and measuring the distance to them. It is expected to come into use in such applications as unmanned moving vehicle tests.