A study on intelligent women’s security system

Abstract

In today’s world, immoral physical harassment is faced by women. Various types of sexual
cruelty are experienced by women and girls on public transport, parks, colleges, workplaces,
and streets. Many real-time applications are developed using traditional algorithms which
protect women who are in an insecure environment. Recently, the gestures produced by
people at risk could be monitored by Machine learning to identify the level of threat. This
study focuses on the Intelligent System for Women's Safety (ISWS) using machine learning.
It also does a literature review on how the deep neural network (DNN), Convolution Neural
Network (CNN), K-Nearest Neighbour (KNN), and IOT help in women's safety system. A
deep analysis of these algorithms is done and a comparison of accuracy is produced based on
the performance metrics.