Vision-Based Women Safety System: Detecting High- Risk Situations Using Deep Learning

Women’s safety is a major concern, especially in crowded public places. This project introduces asmart surveillance system that uses Artificial Intelligence (AI) to help detect potentially unsafe situations forwomen in real time. The system uses a camera feed and combines object detection (to find people in the frame)with a gender classification model (to identify if a person is male or female). It then checks if a female issurrounded by four or more males. If such a situation is found, the system draws a red box around the femaleand triggers an alert to notify authorities or take action. This tool can be used in public places like colleges, busstations, parks, or offices to monitor surroundings and act early to prevent possible threats. By usingtechnologies like computer vision and deep learning, the system helps improve safety and provide fasterresponses in risky situations. By combining computer vision, deep learning, and real-time analysis, this projectoffers a proactive tool for improving public safety. The solution can be deployed in universities, transport hubs,workplaces, and other sensitive areas, enhancing monitoring capabilities and supporting preventive actionagainst potential harassment or assault scenarios