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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38764
Volume:
8 |
11 |
Nov 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In a time where women’s safety is concerned, there is this recommendation of having a total system of security for women with a deep learning technique, helping increase hazard detection and personal protection that uses powerful algorithms of computer vision along with machine learning models suggested system monitors the identification of a threat in real-time the primary constituents of this system are the facial recognition which identifies the known threats, the object detection that recognizes the suspicious activity, an alarm mechanism alerting authorities or emergency contact in case there is any potential hazard scanned the deep learning framework helps it learn through big data; this is how its accuracy and adaptability come along with several situations and more importantly user- friendly interface of access in order to enjoy safe features of location tracking and prime alerts.
KEYWORDS
Publication Date
11/15/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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