• Title/Summary/Keyword: DO 센서

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Quantitative Estimation of Shoreline Changes Using Multi-sensor Datasets: A Case Study for Bangamoeri Beaches (다중센서를 이용한 해안선의 정량적 변화 추정: 방아머리 해빈을 중심으로)

  • Yun, Kong-Hyun;Song, Yeong Sun
    • Korean Journal of Remote Sensing
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    • v.35 no.5_1
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    • pp.693-703
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    • 2019
  • Long-term coastal topographical data is critical for analyzing temporal and spatial changes in shorelines. Especially understanding the change trends is essential for future coastal management. For this research, in the data preparation, we obtained digital aerial images, terrestrial laser scanning data and UAV images in the year of 2009. 2018 and 2019 respectively. Also tidal observation data obtained by the Korea Hydrographic and Oceanographic Agency were used for Bangamoeri beach located in Ansan, Gyeonggi-do. In the process of it, we applied the photogrammetric technique to extract the coastline of 4.40 m from the stereo images of 2009 by stereoscopic viewing. In 2018, digital elevation model was generated by using the raw data obtained from the laser scanner and the corresponding shoreline was semi-automatically extracted. In 2019, a digital elevation model was generated from the drone images to extract the coastline. Finally the change rate of shorelines was calculated using Digital Shoreline Analysis System. Also qualitative analysis was presented.

A Study on the Smart Filter System for External Environment Recognition (외부환경 인식용 스마트 필터 시스템에 대한 연구)

  • Seo, Do-Won;Yoon, Keun-Young
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.2
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    • pp.271-278
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    • 2021
  • This paper is a study on the implementation of smart filter system that recognizes the external environment and automatically removes pollutants according to pollution level. Recently, the occurrence of various pollutants in indoor and outdoor space has adversely affected the human body. Especially, various fine dust generated in the atmosphere becomes worse in closed residential space or office space. Although air pollution can be temporary lowered through ventilation, it is difficult to respond to fine dust changes in real time, and such problems become serious in the space where many people reside, such as at home or industry. Therefore, it is necessary to measure the pollution level of fine dust inside the residential space in real time and to reduce the pollution of indoor ventilation through automatic ventilation with the outside. To improve these problems, this paper proposes the implementation of smart filter system for external environment recognition. The structure of smart filter system that automatically measures air quality inside and outside, removes pollutants, implements the function, and confirms the operability by manufacturing prototypes. Finally, the effectiveness of the smart filter system for solving fine dust problems was examined.

GCP Chip Automatic Extraction of Satellite Imagery Using Interest Point in North Korea (특징점 추출기법을 이용한 접근불능지역의 위성영상 GCP 칩 자동추출)

  • Lee, Kye Dong;Yoon, Jong Seong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.4
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    • pp.211-218
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    • 2019
  • The Ministry of Land, Infrastructure and Transport is planning to launch CAS-500 (Compact Advanced Satellite 500) 1 and 2 in 2019 and 2020. Satellite image information collected through CAS-500 can be used in various fields such as global environmental monitoring, topographic map production, analysis for disaster prevention. In order to utilize in various fields like this, it is important to get the location accuracy of the satellite image. In order to establish the precise geometry of the satellite image, it is necessary to establish a precise sensor model using the GCP (Ground Control Point). In order to utilize various fields, step - by - step automation for orthoimage construction is required. To do this, a database of satellite image GCP chip should be structured systematically. Therefore, in this study, we will analyze various techniques for automatic GCP extraction for precise geometry of satellite images.

An Experimental Study on Cylindrical Countermeasures for Dissipation of Debris Flow Energy (원통형 대책 구조물의 토석류의 에너지 저감 효과에 대한 실험적 연구)

  • Kim, Beom-Jun;Han, Kwang-Do;Kim, Ho-Seop;Choi, Clarence E.;Yune, Chan-Young
    • Journal of the Korean GEO-environmental Society
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    • v.20 no.1
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    • pp.57-65
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    • 2019
  • In this study, to investigate the effect of cylindrical countermeasure on the flow characteristics of debris flow, a series of small-scale tests were conducted using a flume with cylindrical baffles. Various heights and row numbers of installed baffles were considered as a test condition. High speed cameras and laser level sensors were also installed at the top and side of the channel, respectively, to capture the debris flow dynamics before and after baffles. Based on test results, the energy dissipation of debris flow due to baffles was analyzed. Test results showed that baffles can significantly reduce the velocity and flow depth of debris flows. The energy dissipation effect of baffles also increase as the increase of height and row number of baffles.

Development of Membrane Film Pressure Sensor for Hot Roll Laminator (고온 롤 라미네이터용 멤브레인 구조 필름형 압력 센서 개발)

  • Kim, Do-Yeon;Lee, Tae-Kyung;Kang, Pil-Sik
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.6_2
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    • pp.1059-1065
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    • 2020
  • Demand for pressure sensors is increasing in various fields such as machinery, healthcare and medical care. A recent study is being conducted to create sensors that are more sensitive and have longer linear sections based on measurement principles. In this paper, a film-type sensor with a membrane structure was developed to measure the pressure distributed in the axial direction of a hot roll laminator. Performance of sensors was evaluated by resistance and durability according to membrane diameter. The resistance of the membrane sensor varies according to the contact state and contact area of the electrode. Therefore, the membrane diameter selection is important. Experiments showed the most pronounced variation in resistance under pressure at 8 mm in diameter of membrane. Reliability evaluation of sensors was carried out at room temperature and high temperature. The pressure on the sensor was pressurized 1000 times to measure the initial resistance and the resistance after the evaluation to analyze the change. Sensors showed stable results with low resistance changes of 5.15% and 6.27%, respectively. A large area sensor manufactured using the developed sensor also showed reliable results.

Implementation of CNN Model for Classification of Sitting Posture Based on Multiple Pressure Distribution (다중 압력분포 기반의 착석 자세 분류를 위한 CNN 모델 구현)

  • Seo, Ji-Yun;Noh, Yun-Hong;Jeong, Do-Un
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.2
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    • pp.73-78
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    • 2020
  • Musculoskeletal disease is often caused by sitting down for long period's time or by bad posture habits. In order to prevent musculoskeletal disease in daily life, it is the most important to correct the bad sitting posture to the right one through real-time monitoring. In this study, to detect the sitting information of user's without any constraints, we propose posture measurement system based on multi-channel pressure sensor and CNN model for classifying sitting posture types. The proposed CNN model can analyze 5 types of sitting postures based on sitting posture information. For the performance assessment of posture classification CNN model through field test, the accuracy, recall, precision, and F1 of the classification results were checked with 10 subjects. As the experiment results, 99.84% of accuracy, 99.6% of recall, 99.6% of precision, and 99.6% of F1 were verified.

CNN-LSTM Combination Method for Improving Particular Matter Contamination (PM2.5) Prediction Accuracy (미세먼지 예측 성능 개선을 위한 CNN-LSTM 결합 방법)

  • Hwang, Chul-Hyun;Shin, Kwang-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.1
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    • pp.57-64
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    • 2020
  • Recently, due to the proliferation of IoT sensors, the development of big data and artificial intelligence, time series prediction research on fine dust pollution is actively conducted. However, because the data representing fine dust contamination changes rapidly, traditional time series prediction methods do not provide a level of accuracy that can be used in the field. In this paper, we propose a method that reflects the classification results of environmental conditions through CNN when predicting micro dust contamination using LSTM. Although LSTM and CNN are independent, they are integrated into one network through the interface, so this method is easier to understand than the application LSTM. In the verification experiments of the proposed method using Beijing PM2.5 data, the prediction accuracy and predictive power for the timing of change were consistently improved in various experimental cases.

Evaluation of the Location Efficiency of Fine Dust Shelters Considering Vulnerable Population in Seoul (취약계층을 고려한 미세먼지 쉼터 입지 효율성 평가)

  • Lim, Jae Kwon;Lee, Hye Kyung
    • Journal of KIBIM
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    • v.12 no.4
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    • pp.104-115
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    • 2022
  • Fine Dust in Korea has been classified as a social disaster since 2019 due to continuous increase in concentration of Particulate Matter 10(PM 10) and PM 2.5. The fine dust issue has negative physical and mental impacts, especially on vulnerable population including children and the elderly. Seoul metropolitan government have installed fine dust shelters since 2019. However, there is a lack of research that evaluates spatiotemporal distribution of these facilities. Therefore, the first aim of this study is to find the relationship between PM levels and dust scattering construction sites, or air pollutant emission sites through in depth spatial analyses. The second purpose is to analyze the spatial distribution of PM shelters in Seoul, and to evaluate the location efficiency of them. Kernel density, krigging, and network analyses were conducted, and floating population was considered instead of census data for this research. The reults of network analysis based on the road system showed that Yangcheon-gu, Songpa-gu, Seongbuk-gu, and Dobong-gu were found to need additional fine dust shelters. Also, the results from analyzing the floating population that includes children and the elderly showed that Songpa-gu, Seodaemun-gu, Gangdong-gu, Seocho-gu, and Dongdaemun-gu need more placements of find dust shelters. The results of this study are expected to provide implications for urban planners to enhance find dust shelter placement in urban areas, and vulnerable population issues would be considered in many ways.

Study on Utilization of Sleep Measurement Data for Practice of Sleep Hygiene (수면위생 실행을 위한 수면 측정 데이터 활용 방안 연구)

  • Lee, Hee-Young;Park, Do-Sung;Lee, Jei;Jung, Won-Hyeong;Kim, Jung-Yi
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.663-668
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    • 2022
  • As the number of people who experience sleep disorders is increasily growing, users' desire to improve their sleep quality has also increased. Acoordingly, the 'Sleeptech' market is showing a steady growth. This study designs and proposes a system after consideration of existing related research that can help modern people overcome sleep disorders, which is based on the necessity for customized sleep hygien service. This system analyzes user's sleep data collected through smartphone built-in sensors to calculate sleep patterns, provides customized sleep hygiene-based solutions to users through collaborative filtering, and provides an environment suitable for sleep through the automatic control of IoT devices. This method of using sleep data is expected to contribute to the improvement of the quality of life of modern people suffering from sleep disorders, which results from expansion to Sleeptech market as well as improvement of users' sleep habits.

Development of an AI-based Waterside Environment and Suspended Solids Detection Algorithm for the Use of Water Resource Satellite (수자원위성 활용을 위한 AI기반 수변환경 및 부유물 탐지 알고리즘 개발)

  • Jung Ho Im;Kyung Hwa Cho;Seon Young Park;Jae Se Lee;Duk Won Bae;Do Hyuck Kwon;Seok Min Hong;Byeong Cheol Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.4-4
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    • 2023
  • C-band SAR 센서를 탑재한 수자원위성은 한반도 수자원 모니터링을 위해 개발되어 2025년 발사가 계획되어 있으며, 수변환경 및 부유물 탐지 및 다양한 활용이 기대되고 있다. 그 중 수변환경은 수변 생태계 안정성을 유지하는 역할을 담당하여 이에 대한 모니터링은 중요하다. s현장 관측 기반 탐지 방법과 비교하여 위성 원격탐사는 광범위한 지역을 반복적으로 관측하여, 연속적인 수변환경 및 부유물 정보를 제공할 수 있다. 이러한 특성에 기반하여 다양한 다중분광 및 SAR (Synthetic Aperture Radar) 위성 원격탐사 자료를 바탕으로 수변환경 및 부유물의 탐지 연구가 이루어졌다. 특히 단일 영상만을 사용하는 기법에 비해 다중분광 및 SAR 영상을 융합하여 높은 정확도를 보인 바 있다. 초기 연구에서는 임계값 알고리즘 또는 현장관측 기반의 부유물 농도와 위성 자료간의 선형관계를 분석하는 단순한 알고리즘이 주를 이루었으나, 최근에는 RF, CNN 등 보다 복잡하고 다양한 인공지능 알고리즘이 적용되어 높은 정확도로 해당 문제들을 해결하고 있다. 본 연구에서는 수자원위성 활용을 위해 인공지능 기반 수변환경 및 부유물 탐지 알고리즘을 개발하고자 한다. 수자원위성의 대체 자료로 유럽우주국의 Sentinel-1 A/B 위성의 C-band SAR 영상을 이용하였으며, 보조자료로 Sentinel-2 다중분광 영상을 이용하였다. 개발된 알고리즘은 수자원 관리를 위한 환경변화 탐지에 유용한 정보로 활용될 수 있을 것으로 기대된다.

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