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http://dx.doi.org/10.6109/jkiice.2022.26.8.1130

Escape Route Prediction and Tracking System using Artificial Intelligence  

Yang, Bum-Suk (Department of Convergence Engineering, Hoseo Graduate School of Venture)
Park, Dea-Woo (Department of Convergence Engineering, Hoseo Graduate School of Venture)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.8, 2022 , pp. 1130-1135 More about this Journal
Abstract
In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office has built a control center for CCTV control and is performing 24-hour CCTV video control for the safety of citizens. Seoul Metropolitan Government is building a smart city integrated platform that is safe for citizens by providing CCTV images of the ward office to enable rapid response to emergency/emergency situations by signing an MOU with related organizations. In this paper, when an incident occurs at the Seoul Metropolitan Government Office, the escape route is predicted by discriminating people and vehicles using the AI DNN-based Template Matching technology, MLP algorithm and CNN-based YOLO SPP DNN model for CCTV images. In addition, it is designed to automatically disseminate image information and situation information to adjacent ward offices when vehicles and people escape from the competent ward office. The escape route prediction and tracking system using artificial intelligence can expand the smart city integrated platform nationwide.
Keywords
Intelligent image analysis; Escape route prediction; Automatic situation propagation; Smart city Integrate platform;
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Times Cited By KSCI : 1  (Citation Analysis)
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