Automated smart handbag with enhanced women's safety using cutting edge technology

Abstract

Women’s safety has been an area of concern, especially in public places where timely assistance cannot be provided. To mitigate this problem, this paper proposes an intelligent handbag-based women’s safety system that utilizes the concept of biometric identification, location tracking, and edge computing-based AI threat verification. The proposed system, unlike other traditional women’s safety devices that rely on GPS-GSM for emergency alerts and are more likely to send false alarms, utilizes fingerprint identification for secure and authorized use, along with YOLO v3 vision model on an ESP32-CAM for threat verification. Upon failure in the authentication process or threat detection, the system sends an SOS message with the current location via GSM with the help of GPS coordinates. The system achieves an emergency response time of 33 seconds, primarily limited by GPS acquisition delay. The results confirm the effectiveness and applicability of the proposed system in providing an intelligent emergency response system for women’s safety.