RescueNow: Real-time SOS and Predictive Women’s Safety System

RescueNow: Real-time SOS and Predictive Women's Safety System

Sandip Shankar Pawar1, Riya Roy2, Kalyani Vikas Sawant3, Rishu Bhagat Singh4,

Dr. Mahesh Navale5

 1, 2, 3, 4, 5 Department of Computer Engineering & Zeal College of Engineering and Research, Pune, India

Abstract - This paper presents a comprehensive women’s safety application designed to address the growing concerns of personal safety through technological intervention. The system integrates multiple advanced features such as real-time SOS alerts, geofencing to detect high-risk areas, AI-driven crime predictions, and multiple SOS activation methods, including voice commands, shake detection, and button press. Additionally, the app employs silent recording functionality to gather evidence in distress situations and incorporates secure communication channels for contacting law enforcement. The application also supports community-driven safety ratings and crime reporting. Tested with real-world scenarios, the system demonstrates high accuracy in predictive analytics and provides a seamless, scalable solution for enhancing women’s safety. This project contributes to the field of personal safety technologies by introducing a multi-faceted, AI-enabled framework for real-time risk mitigation.

Key Words: Women’s safety, SOS alerts, AI crime prediction, geofencing, real-time GPS tracking, predictive analytics, Firebase Cloud Messaging, Twilio, silent recording, crime reporting.