• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.4
• /
• pp.1-10
• /
• 2019

Unmanned aerial vehicle(UAV) can acquire images with lower cost than conventional manned aircraft and commercial satellites. It has the advantage of acquiring high-resolution aerial images covering in the field area more than 50 ha. The purposes of this study is to develop the rice grain yield distribution using UAV. In order to develop a technology for estimating the rice yield using UAV images, time series UAV aerial images were taken at the paddy fields and the data were compared with the rice yield of the harvesting area for two rice varieties(Singdongjin, Dongjinchal). Correlations between the vegetation indices and rice yield were ranged from 0.8 to 0.95 in booting period. Accordingly, rice yield was estimated using UAV-derived vegetation indices($R^2=0.70$ in Sindongjin, $R^2=0.92$ in Donjinchal). It means that the rice yield estimation using UAV imagery can provide less cost and higher accuracy than other methods using combine with yield monitoring system and satellite imagery. In the future, it will be necessary to study a variety of information convergence and integration systems such as image, weather, and soil for efficient use of these information, along with research on preparing management practice work standards such as pest control and nutrient use based on UAV image information.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1083-1094
• /
• 2021

In order to monitor nuclear activity in inaccessible areas, it is necessary to establish a methodology to analyze changesin nuclear activity-related objects using high-resolution satellite images. However, traditional object detection and change detection techniques using satellite images have difficulties in applying detection results to various fields because effects of seasons and weather at the time of image acquisition. Therefore, in this paper, an object of interest was detected in a satellite image using a deep learning model, and object changes in the satellite image were analyzed based on object detection results. An initial training of the deep learning model was performed using an open dataset for object detection, and additional training dataset for the region of interest were generated and applied to transfer learning. After detecting objects by multitemporal and multisensory satellite images, we tried to detect changes in objects in the images by using them. In the experiments, it was confirmed that the object detection results of various satellite images can be directly used for change detection for nuclear activity-related monitoring in inaccessible areas.

• Journal of Korean Society on Water Environment
• /
• v.28 no.1
• /
• pp.137-147
• /
• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.

• Journal of Sensor Science and Technology
• /
• v.10 no.3
• /
• pp.187-195
• /
• 2001

A wireless telemetry measurement system, using ISFETs, was developed for environmental monitoring applications, industrial processes, medical treatments and so on. This system is composed of the measurement part located at remote site and a personal computer(PC) which control whole instrument process. The measurement part transmits measured data to the PC by RF transceiver, and transmitted data are analyzed and handled in the PC. Proposed system utilizing time division multiplexing for the transmission of 3channel ISFET signal. The measurement part has an identification number(ID) so that the PC controls many measurement parts separately. Experiments were performed using pH-ISFETs, and the implemented system operates well within designed specification and accuracy of 0.1 pH.

• Journal of IKEEE
• /
• v.22 no.3
• /
• pp.645-650
• /
• 2018

IT-based automatic controller that control the temperature and humidity to prevent dew condensation of distributing board was designed and implemented in this paper. The dew condensation temperature was deduced from room temperature and humidity of distributing board. Based on the comparisons between the deduced dew condensation temperature and the temperature of surface condensation, the facilities that can prevent the condensation was implemented to be operated in due order. Also, the remote monitoring module to monitor operation status of controller was implemented using LoRa technique. The performances for controller operation and data transmission were validated from the transmission and operation test for dew condensation prevention. The controller can be put to good use at the facilities that requires the condensation prevention.

• Journal of Advanced Navigation Technology
• /
• v.27 no.5
• /
• pp.635-642
• /
• 2023

With the development of artificial intelligence technology, drones are evolving beyond simple remote control tools into intelligent drones that perform missions autonomously. The importance of drones is gradually gaining attention due to the use of drones in overseas military conflicts and the analysis of the future operational environment in Korea. AMAD is proposed for the rapid development of intelligent drones. In order to develop intelligent software based on AMAD, an integrated development environment (IDE) that supports users with functions such as debugging, performance evaluation, and monitoring is essential. In this paper, we define the concepts of the development environment required for intelligent software development and describe the results of reflecting them in the design of the IDE and AMAD's agents, SVI and MPD, which are interfaced with the IDE.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_1
• /
• pp.907-917
• /
• 2019

Recently, the demand for high-resolution satellite images increases in many fields such as land monitoring and terrain analysis. Therefore, the need for geometric correction is increasing. As an automatic precision geometric correction method, there is a method of automatically extracting the GCP by matching between the GCP Chip and the satellite image. For automatic precision geometric correction, the success rate of matching GCP Chip and satellite image is important. Therefore, it is important to evaluate the matching performance of the manufactured GCP Chip. In order to evaluate the matching performance of GCP Chips, a total of 3,812 GCP Chips in South Korea were used as experimental data. The GCP Chip matching results of KOMPSAT-3A and Google Map showed similar matching results. Therefore, we determined that Google Map satellite imagery could replace high-resolution satellite imagery. Also, presented a method using center point and error radius of Google Map to reduce the time required to verify matching performance. As a result, it is best to set the optimum error radius to 8.5m. Evaluated the matching performance of GCP Chips in South Korea using Google Maps. And verified matching result using presented method. As a result, the GCP Chip s in South Korea had a matching success rate of about 94%. Also, the main matching failure factors were analyzed by matching failure GCP Chips. As a result, Except for GCP Chips that need to be remanufactured, the remaining GCP Chips can be used for the automatic geometric correction of satellite images.

• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.4
• /
• pp.193-204
• /
• 2007

As the scale of broadcasting systems gets bigger and the functionality of broadcasting devices becomes diverse, networking facilities are being incorporated within recent broadcasting devices. Although networked devices can perform many of the additional functionalities, an effective management becomes a difficult issue. Therefore, it is essential to provide an automated management system for monitoring and controlling distributed broadcasting devices across a network. SNMP (Simple Network Management System) is one of the enabling technologies that we could adopt when we build such a system. However, SNMP-based solution has its limitations. In this paper. we propose the TMS800 system, which is a metadata-based device management system on top of SNMP framework. The system is specifically designed for the management of distributed broadcasting devices. It makes it possible to monitor not only the status of devices, but also the videos in the form of still images. Remote control and real-time notification facilities are also provided.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.121-121
• /
• 2017

오늘날 시장에 유통되는 버섯은 대부분 환경이 조절되는 시설 내부에서 재배된다. 버섯은 다른 식물과 달리 버섯의 종류, 품종 등에 따라 요구되는 환경이 매우 다르다. 특히 대부분의 버섯은 버섯이 생육되는 공간의 온도, 수분, 이산화탄소, 조도 등의 관리가 필수적이다. 버섯의 단위면적당 생산량을 극대화하기 위해서는 이들 버섯이 필요로 하는 환경을 버섯의 생육특성에 따라 적합하게 유지해 주어야만 한다. 현재 대부분의 버섯재배사에는 이들 환경을 컨트롤하는 장치가 설치되어 있고, 이들 시스템의 환경 설정은 농업인이 현장에서 버섯의 상태를 확인 한 후 그때그때 경험에 의해 채득한 정보를 기반으로 환경설정을 하고 있는 실정이다. 이렇다 보니 버섯을 재배하는 기간에는 농업인이 재배사 내부의 환경을 관리하기 위해서 항상 버섯재배사에 머물러야 하고, 재배사의 환경관리 때문에 원거리 또는 장기 출타가 어려운 실정이다. 본 연구에서는 기존에 사람이 버섯재배 현장에서 컨트롤하던 환경관리를 원격에서 컴퓨터 또는 모바일로 구현할 수 있는 시스템을 개발하였다. 시스템에서 모니터링 및 제어하는 환경은 온도, 습도, 이산화탄소, 배기팬 및 입기팬의 가동 등 버섯재배 환경관리에 필요한 모든 요소를 모니터링 및 관리할 수 있도록 하였다. 이들 관리 요소는 인터넷이 연결된 컴퓨터에 접속하여 버섯재배사의 환경을 실시간으로 모니터링 하고 필요에 따라 제어를 할 수 있도록 하였다. 또한 컴퓨터에서 볼 수 있는 환경을 스마트폰을 통해서도 볼 수 있고 또한 제어할 수 있도록 하였다. 그리고 버섯배지를 입상 한 후부터 수확시기까지의 관리 환경을 데이터베이스로 만들어 농민이 버섯배지를 입상하고 데이터베이스와 연동한 제어가 되도록 설정하면 버섯재배사 내부의 환경은 데이터베이스의 정보를 읽어 들여 버섯의 생육단계에 따라 자동으로 내부환경이 제어되도록 하였다. 또한 농업인이 원격에서 버섯재배사 내부 버섯의 생육상황을 모니터링 할 수 있도록 재배사 상부에 CCD 카메라를 달아 실시간으로 버섯의 생육상활을 모니터링 할 수 있도록 구성하였다. 이와 같은 시스템을 사용하면 버섯재배 경험이 없는 농업인도 경험자와 같은 재배관리가 가능하고 원격에서 재배사 내부환경을 모니터링하고 제어 할 수 있기 때문에 농업인이 재배사에 매여 있지않아도 될 것으로 판단된다.

• Journal of Biosystems Engineering
• /
• v.41 no.2
• /
• pp.126-137
• /
• 2016

Purpose: The overall objective of this study was to evaluate the vegetation fraction of soybeans, grown under different cropping conditions using an unmanned aerial vehicle (UAV) equipped with a red, green, and blue (RGB) camera. Methods: Test plots were prepared based on different cropping treatments, i.e., soybean single-cropping, with and without herbicide application and soybean and barley-cover cropping, with and without herbicide application. The UAV flights were manually controlled using a remote flight controller on the ground, with 2.4 GHz radio frequency communication. For image pre-processing, the acquired images were pre-treated and georeferenced using a fisheye distortion removal function, and ground control points were collected using Google Maps. Tarpaulin panels of different colors were used to calibrate the multi-temporal images by converting the RGB digital number values into the RGB reflectance spectrum, utilizing a linear regression method. Excess Green (ExG) vegetation indices for each of the test plots were compared with the M-statistic method in order to quantitatively evaluate the greenness of soybean fields under different cropping systems. Results: The reflectance calibration methods used in the study showed high coefficients of determination, ranging from 0.8 to 0.9, indicating the feasibility of a linear regression fitting method for monitoring multi-temporal RGB images of soybean fields. As expected, the ExG vegetation indices changed according to different soybean growth stages, showing clear differences among the test plots with different cropping treatments in the early season of < 60 days after sowing (DAS). With the M-statistic method, the test plots under different treatments could be discriminated in the early seasons of <41 DAS, showing a value of M > 1. Conclusion: Therefore, multi-temporal images obtained with an UAV and a RGB camera could be applied for quantifying overall vegetation fractions and crop growth status, and this information could contribute to determine proper treatments for the vegetation fraction.