Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/2763
Title: | Human Tracking and Profiling for Risk Management |
Authors: | Ranjith, K. H. V. S Jayasekara, A. S Ratnasooriya, K. A. L. L Thilini Randika, J. L Rupasinghe, L Liyanapathirana, C |
Keywords: | YOLO (V3) SSD (single shot detector) mobile- net open-CV image processing open pose tenser-flow |
Issue Date: | Jan-2022 |
Publisher: | Global Journals |
Citation: | K.H.V.S, Jayasekara A.S, Ratnasooriya K.A.L.L, J.L Thilini Randika, Dr. Lakmal Rupasinghe, Ms. Chethana Liyanapathirana, R. (2022). Human Tracking and Profiling for Risk Management. Global Journal Of Computer Science And Technology, . Retrieved from https://computerresearch.org/index.php/computer/article/view/2075 |
Series/Report no.: | Global Journal of Computer Science and Technology: DNeural & Artificial Intelligence;Volume 22 Issue 1Version 1.0 |
Abstract: | Infectious viruses are conveyed via respiratory droplets produced by an infected person when they speak, sneeze, or cough. So, to combat virus transmission, the World Health Organization (WHO) has imposed severe regulations such as mandatory face mask use and social segregation in public spaces. The ’Human Tracking and Profiling for Risk Management System (HTPRM)’ is an online application that identifies the risk associated with failing to follow proper health practices. This proposed approach, which is divided into four components, utilizes ’You Only Live Once YOLO (V3)’ to detect facemask danger, which would be determined based on two factors: wearing the face mask properly and the type of mask (Surgical, k95, homemade, and bare). The second phase is to use Open CV and SSDMobilenet to evaluate the value of a one-meter space (Social Distance) between people. The system recognizes the maximum number of individuals that can be in the vicinity of the specific hall that uses YOLO( V3) and image processing as the third procedure. In the last processing, the system identifies each person’s behavior, classifies it as uncommon or not, and calculates the risk associated with each category. Finally, the system computes the overall risk and generates a warning alarm to notify the user that they are in a dangerous scenario. |
URI: | http://rda.sliit.lk/handle/123456789/2763 |
ISSN: | 0975-4172 |
Appears in Collections: | Department of Information Technology-Scopes Research Papers - Dept of Computer Systems Engineering Research Papers - Open Access Research Research Papers - SLIIT Staff Publications |
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