NariRaksha: Gender-Responsive AI for Women’s Safety

Women’s safety in public spaces remains a persistent concern in many urban environments. Harassment, unsafe transit routes, poorly lit streets, and delayed emergency responses can make everyday mobility difficult for women. While cities increasingly deploy surveillance infrastructure and smart-city technologies, these systems often lack a gender-responsive approach to safety. NariRaksha addresses this gap by integrating artificial intelligence with urban command and control centers to monitor safety risks, provide real-time alerts, and support preventive planning for safer public environments.

The system is designed to work alongside existing smart city infrastructure, including CCTV networks, emergency helplines, GPS-enabled public transport systems, and integrated command centers. AI-powered computer vision models analyze live video feeds to detect potentially unsafe situations such as harassment, suspicious behavior, crowd distress, or individuals in vulnerable circumstances. When such patterns are detected, the system can generate alerts that are routed to city authorities or emergency response teams through the command center. This enables quicker intervention and helps authorities respond to incidents before they escalate.

NariRaksha also supports real-time safety alerts and assistance for women. Through mobile applications or integrated public safety platforms, users can receive notifications about high-risk areas, report suspicious activities, or trigger emergency alerts that share their location with nearby response teams or trusted contacts. By combining AI-based monitoring with citizen reporting, the system creates a more responsive safety ecosystem that bridges the gap between individuals and public authorities.

In addition to real-time monitoring, the platform enables predictive and preventive urban safety planning. AI models can analyze historical crime records, crowd movement patterns, lighting conditions, and transport data to identify areas that consistently present safety risks. These insights help city planners and administrators implement targeted interventions such as improved street lighting, increased police patrols, safer public transport routes, or redesigned urban spaces that discourage harassment and crime.

Another important component of NariRaksha is its emphasis on gender-responsive data analysis. Traditional safety systems often rely on generalized crime statistics that may overlook the specific experiences of women in public spaces. By incorporating gender-disaggregated data and safety reports from women, the platform can highlight patterns of harassment or unsafe environments that might otherwise remain unnoticed.

Ultimately, NariRaksha demonstrates how AI can be used not only to respond to incidents but also to prevent safety risks and create more inclusive urban environments. By combining real-time monitoring, citizen reporting, and data-driven urban planning, the system empowers cities to proactively design safer public spaces where women can move freely and confidently.

For additional context and detailed documentation of this use case, please refer to pages 68-70 in the attached Casebook.