Centre Takes Major Step for Women’s Safety: AI Facial Recognition to Be Installed at 7 Major Indian Railway Stations

In a significant move to enhance women’s safety, the Central Government has announced the installation of AI-based facial recognition systems at seven major railway stations across India. This initiative is part of the government’s Safe City Project, aimed at making public spaces safer for women.

The technology will be installed at the following stations:

Delhi

Mumbai

Chennai

Bengaluru

Hyderabad

Guwahati (Kamrup)

Ahmedabad

Real-Time Detection of Criminals

These AI-powered systems will be linked to the National Database of Sexual Offenders (NDSO), which contains details of over 20 lakh offenders. The system will scan faces in real time and instantly alert the authorities if a known criminal is detected at the premises.

The goal is to proactively identify potential threats, prevent crimes, and ensure rapid response by law enforcement teams stationed at these high-footfall locations.

Under the Safe City Project

The initiative is being rolled out under the Safe City Project, which is part of the Ministry of Home Affairs' larger mission to strengthen urban safety measures for women. This includes not only surveillance technology but also emergency helplines, women’s helpdesks, and the deployment of female officers at sensitive spots.

Government's Strong Message

Speaking on the development, officials emphasized that the government is committed to creating secure environments for women, especially in public transport areas, where cases of harassment and crimes have been a rising concern.

More Cities to Be Covered Soon

If this pilot proves successful, similar systems could soon be introduced in other railway stations, metro networks, and public transit hubs across the country. The government also plans to integrate this AI system with city surveillance networks for broader safety coverage. 

Police officials stationed at these hubs will receive real-time alerts, enabling them to intercept suspects on the spot and prevent incidents from escalating. This tech-policing collaboration aims to reduce dependency on manual surveillance and minimize response time in critical situations.