Abstract :

Women’s safety has become a critical concern due to the increasing number of harassment and assault incidents in public and private spaces. Traditional safety measures are often reactive and lack realtime monitoring and rapid response capabilities. This project proposes an innovative technology-driven approach that integrates Internet of Things (IoT), Artificial Intelligence (AI), GPS tracking, and mobile communication to enhance women’s safety proactively. The system enables real-time threat detection, emergency alert generation, and location sharing with authorities and trusted contacts. Machine learning techniques are employed to analyze abnormal behavior and distress patterns. The proposed solution ensures faster response time, increased situational awareness, and improved personal security. Experimental results demonstrate improved accuracy in threat detection and reduced response delays. This system aims to provide a reliable, scalable, and intelligent safety mechanism for wo