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      스마트 홈 사용자를 위한 라이다, 영상, 오디오 센서를 이용한 인공지능 이상징후 탐지 알고리즘 = Intelligent Abnormal Situation Event Detections for Smart Home Users Using Lidar, Vision, and Audio Sensors

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      https://www.riss.kr/link?id=A107774764

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      다국어 초록 (Multilingual Abstract)

      Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.
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      Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at hom...

      Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

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      참고문헌 (Reference)

      1 정주호, "이상 징후 탐지를 위한 영상, 소리, 활동 패턴 기반 지능형 패턴 인식 알고리즘" 한국컴퓨터정보학회 24 (24): 59-66, 2019

      2 Joseph Redmon, "You Only Look Once: Unified, Real-Time Object Detection"

      3 R. Bardeli, "Uninformed Abnormal Event Detection on Audio" 1-4, 2012

      4 Serhan Cosar, "Toward Abnormal Trajectory and Event Detection in Video Surveillance" Institute of Electrical and Electronics Engineers (IEEE) 27 (27): 683-695, 2017

      5 Korea Mutual-aid News, "The soaring rise of elderly lonely deaths, Urgent need for a social safety net"

      6 He, Kaiming, "Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition, Lecture Notes in Computer Science"

      7 Dan Jia, "Self-Supervised Person Detection in 2D Range Data using a Calibrated Camera"

      8 Ross Girshick, "Rich feature hierarchies for accurate object detection and semantic segmentation"

      9 Tslil, Or, "Representing and updating objects' identities in semantic SLAM" 1-7, 2020

      10 Huy Phan, "Improved Audio Scene Classification Based on Label-Tree Embeddings and Convolutional Neural Networks" Institute of Electrical and Electronics Engineers (IEEE) 25 (25): 1278-1290, 2017

      1 정주호, "이상 징후 탐지를 위한 영상, 소리, 활동 패턴 기반 지능형 패턴 인식 알고리즘" 한국컴퓨터정보학회 24 (24): 59-66, 2019

      2 Joseph Redmon, "You Only Look Once: Unified, Real-Time Object Detection"

      3 R. Bardeli, "Uninformed Abnormal Event Detection on Audio" 1-4, 2012

      4 Serhan Cosar, "Toward Abnormal Trajectory and Event Detection in Video Surveillance" Institute of Electrical and Electronics Engineers (IEEE) 27 (27): 683-695, 2017

      5 Korea Mutual-aid News, "The soaring rise of elderly lonely deaths, Urgent need for a social safety net"

      6 He, Kaiming, "Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition, Lecture Notes in Computer Science"

      7 Dan Jia, "Self-Supervised Person Detection in 2D Range Data using a Calibrated Camera"

      8 Ross Girshick, "Rich feature hierarchies for accurate object detection and semantic segmentation"

      9 Tslil, Or, "Representing and updating objects' identities in semantic SLAM" 1-7, 2020

      10 Huy Phan, "Improved Audio Scene Classification Based on Label-Tree Embeddings and Convolutional Neural Networks" Institute of Electrical and Electronics Engineers (IEEE) 25 (25): 1278-1290, 2017

      11 The Science Times, "How has your lifestyle changed since COVID-19?"

      12 Ross Girshick, "Fast R-CNN" 2015

      13 C. Premebida, "Exploiting LIDAR-based features on pedestrian detection in urban scenarios" 1-6, 2009

      14 Z. Ma, "Device-Free, Activity During Daily Life, Recognition Using a Low-Cost Lidar" 1-6, 2018

      15 M. Przybyła, "Detection and tracking of 2D geometric obstacles from LRF data" 135-141, 2017

      16 L. Vuegen, "An MFCC GMM approach for event detection and classification" 2013

      17 Xilin Yu, "An Investigation into Audio Features and DTW Algorithms for Infant Cry Classification" 54 (54): 54-59, 2019

      18 Yonhapnews, "AI speaker saved for the elderly living alone"

      19 Csaba Benedek, "3D people surveillance on range data sequences of a rotating Lidar" Elsevier BV 50 : 149-158, 2014

      20 The Statistics Korea, "2020 Statistics show single-person households"

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
      2021-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2018-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2015-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2013-11-05 학술지명변경 외국어명 : Journal of Korean Society for Internet Information -> Journal of Internet Computing and Services KCI등재
      2011-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2006-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2005-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2003-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.55 0.55 0.63
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.64 0.6 0.85 0.03
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