• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.497-498
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• 2021

현대사회의 산업 현장에서 기계가 사람들을 대체하면서 작업의 효율을 높이고 있다. 많은 산업 분야에서 사람들을 기계로 대체하고 있는데, 재해 및 사고 현장이나 위험 지역 조사 등에 대한 탐사 활동은 대부분 인력이 차지하고 있으며, 탐사 활동에 참여하는 많은 인력들은 2차, 3차 사고에 쉽게 노출되어 있으며, 그로 인한 인력소모가 심하다. 따라서 우리는 인력 투입 전 사고 및 재난 현장이나 위험 지역에 인력을 투입하기 전 피해를 최소화 하면서 탐사 인력에 대한 안전이 보장된 근무 환경을 개선 시키기 위해서 무인 탐사차량을 생각하게 되었다. 무인 탐사 차량에는 아두이노와 라즈베리파이를 메인으로 삼았고, 현장의 온도와 습도, 화재여부, 가스여부를 측정하기 위한 센서들은 아두이노에 연결하고, 카메라와 라이다센서의 경우 라즈베리파이에 연결을 하였다. 그리고 모든 데이터값은 블루투스와 와이파이 모듈을 통해서 수신받을 수 있게 프로그램을 구성하였다.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.150-161
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• 2018

Recently, unmanned aircraft EM (electromagnetic) survey based on ICT (Information and Communication Technology) has been widely utilized because of the efficiency in regional survey. We performed the theoretical study on the unmanned airship EM system developed by KIGAM (Korea Institute of Geoscience and Mineral resources) as part of the practical application of unmanned aircraft EM survey. Since this system has different configurations of transmitting and receiving loops compared to the conventional aircraft EM systems, a new technique is required for the appropriate interpretation of measured responses. Therefore, we proposed a method to calculate the EM field for the arbitrary shaped transmitter and verified its validity through the comparison with analytic solution for circular loop. In addition, to simulate the magnetic responses by three-dimensionally (3D) distributed anomalies, we have adapted our algorithm to 3D frequency-domain EM modeling algorithm based on the edge-FEM (finite element method). Though the analysis on magnetic field responses from a subsurface anomaly, it was found that the response decreases as the depth of the anomaly increases or the flight altitude increases. Also, it was confirmed that the response became smaller as the resistivity of the anomaly increases. However, a nonlinear trend of the out-of-phase component is shown depending on the depth of the anomaly and the used frequency, that makes it difficult to apply simple analysis based on the mapping of the magnitude of the responses and can cause the non-uniqueness problem in calculating the apparent resistivity. Thus, it is a prerequisite to analyze the appropriate frequency band and flight altitude considering the purpose of the survey and the site conditions when conducting a survey using the unmanned aircraft EM system.

• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.26-37
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• 2022

Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.457-464
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• 2017

The large breeding of algae in rivers has caused the algal bloom and has becoming a serious national problem for the safety of water sources. Therefore, in order to supply stable water resources through securing clean water, it is necessary to develop technology for prevention of water pollution caused by algal bloom. The purpose of this study is to improve the water quality management ability of river by applying the algal bloom detection technique using UAV. Unmanned aerial images were acquired for the Dodong in the middle region of the Nakdong River where algal bloom are frequent. In addition, the phytoplankton concentration was acquired through the sampling of algal bloom and the examination of water quality. Correlation between phytoplankton concentrations and the results of applying the algal bloom index to the Unmanned aerial images showed a strong positive correlation. The remote sensing method suggested in this study is expected to improve the initial response capability of river water pollution.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1209-1216
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• 2020

In this study, we propose a method for detecting coastal surface wastes using an UAV(Unmanned Aerial Vehicle) remote sensing method and an object detection algorithm based on deep learning. An object detection algorithm based on deep neural networks was proposed to detect coastal debris in aerial images. A deep neural network model was trained with image datasets of three classes: PET, Styrofoam, and plastics. And the detection accuracy of each class was compared with Darknet-53. Through this, it was possible to monitor the wastes landing on the shore by type through unmanned aerial vehicles. In the future, if the method proposed in this study is applied, a complete enumeration of the whole beach will be possible. It is believed that it can contribute to increase the efficiency of the marine environment monitoring field.