• Title/Summary/Keyword: 모바일 서버

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Design and Implementation of Visitor Access Control System using Deep learning Face Recognition (딥러닝 얼굴인식 기술을 활용한 방문자 출입관리 시스템 설계와 구현)

  • Heo, Seok-Yeol;Kim, Kang Min;Lee, Wan-Jik
    • Journal of Digital Convergence
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    • v.19 no.2
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    • pp.245-251
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    • 2021
  • As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

Cat Behavior Pattern Analysis and Disease Prediction System of Home CCTV Images using AI (AI를 이용한 홈CCTV 영상의 반려묘 행동 패턴 분석 및 질병 예측 시스템 연구)

  • Han, Su-yeon;Park, Dea-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.9
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    • pp.1266-1271
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    • 2022
  • Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.