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http://dx.doi.org/10.22156/CS4SMB.2020.10.06.140

Development of Checking System for Emergency using Behavior-based Object Detection  

Kim, MinJe (Dept. of Smart Information and Communication Engineering, Sangmyung University)
Koh, KyuHan (Dept. of Computer Science, California State University Stanislaus)
Jo, JaeChoon (Division of Computer Engineering, Hanshin University)
Publication Information
Journal of Convergence for Information Technology / v.10, no.6, 2020 , pp. 140-146 More about this Journal
Abstract
Since the current crime prevention systems have a standard mechanism that victims request for help by themselves or ask for help from a third party nearby, it is difficult to obtain appropriate help in situations where a prompt response is not possible. In this study, we proposed and developed an automatic rescue request model and system using Deep Learning and OpenCV. This study is based on the prerequisite that immediate and precise threat detection is essential to ensure the user's safety. We validated and verified that the system identified by more than 99% of the object's accuracy to ensure the user's safety, and it took only three seconds to complete all necessary algorithms. We plan to collect various types of threats and a large amount of data to reinforce the system's capabilities so that the system can recognize and deal with all dangerous situations, including various threats and unpredictable cases.
Keywords
Deep Learning; SSD Model; UDP Socket; Object Detection; OpenCV;
Citations & Related Records
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