Authors - Yash Tekade, Mayur Shinde, Bhumika Lipane, Nikita Patil, Suhasini Bhat Abstract - The paper presents the idea and methodology of development of a real-time threat detection system designed to enhance women's safety across various environments using AI technology and CCTV surveillance. The system consists of features like real-time person detection, gender classification, and SOS gesture recognition, all connected to an alert system for law enforcement authorities. It effectively identifies potential threats, including a lone woman at night or a woman surrounded by men, enabling proactive actions before incidents escalate. Additionally, the system maps hotspot areas where previous incidents have been recorded, allowing authorities to allocate resources efficiently. It also alerts security personnel about low-light conditions in an area, ensuring surveillance even in challenging environments. By combining these capabilities, the system aims to create a safer atmosphere for women, promoting proactive measures that can significantly reduce crime rates and contribute to enhance overall safety strategies.
