Women Safety is one of the challenging areas in daily life’s, and it has led to different security problems. Due to security issues, women hesitate to work beyond hours to reach the safety targets. Our proposed system announces the real-time concept of live surveillance tracking system when the Women available in various unprotected places, and its to tracking many through IoT and Deep Learning. It observes and capture images from live streaming and tracks the exact situations or movements where unacceptable situations on dangerous, abnormalities take places. Risk Desk System will track automatically notified with alerts and when there is changes in unacceptable behaviour happens. Current research work mainly focus on the posture estimation to resolve the identified problems through deep learning, and computer vision. It will be capable of identifying persons, recognize their gender, and estimate their situation exactly on live or SOS. It will help in recognizing harmful situations, where a women is left alone or occupied with a group of men, which also does not limit to only night time but daytime too. Additionally, it observes the people rigorously and continuously, providing more data related to the group of people acting in that situation. The system proposed mainly focuses on SOS gestures, alert automatically to concerned dedicated teams on surrounding police station’s , NGOs, existing family relatives with noticeable alerts on timely and live tracking.
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*Corresponding Author: Dr D Aruna Kumari, arunakumari@vjit.ac.in
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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