Women Safety - Safest Route Using Machine Learning

Abstract

Victimization of sensible phones has increased in today's world, and thus sensible phones can be used quickly for private security. A number of new apps have been developed to provide girls with a security system via their phones. According to World Health Organization NCRB Social Government Organization reports, one-third of all girls worldwide are subjected to dishounarable physical harassment in public places such as railways, buses, and on roads. We've analyzed various existing systems on women's security in this paper. We've seen a decline in the demand for advanced girls security systems to ensure their safety in public places as well as when travelling alone on public transportation such as college buses, company vehicles, and so on. This paper proposed a completely new model for women’s security publicly places.