RescueNow: Real-time SOS and Predictive Womens Safety System

Abstract: This research paper presents the real-world implementation of "RescueNow", an AI-integrated women’s safety mobile application aimed at enhancing emergency responsiveness through smart technology. The system combines real-time SOS alerting, GPS-based location tracking, silent audio-video recording, and multi-channel emergency communication using services like Twilio. Designed with a user-centric approach, the app provides multiple trigger mechanisms including voice command, shake detection, and one-tap alerts, ensuring accessibility in high-stress situations. It also features community safety ratings and direct communication with law enforcement authorities. A notable aspect of this project is its machine learning module, which analyses patterns to predict potential crime-prone zones, allowing for proactive measures. Extensive testing in simulated and real-world scenarios validated the system’s effectiveness, reliability, and scalability. This paper documents the design, implementation, and evaluation of RescueNow, demonstrating how technology can be a powerful ally in building a safer environment for women.