An Intelligent Women Safety and Predictive Alert System

Abstract

This project presents a women safety system that combines web technologies, machine learning, and location-based services to improve personal security. The application allows users to register, log in, and access multiple safety features through a simple and interactive interface. A neural network model is trained on historical crime data to predict crime rates in different regions, helping users better understand potential risks. In addition to prediction, the system provides real-time navigation to nearby police stations using mapbased visualization. During emergency situations, users can quickly send alerts via email to their registered contacts using a panic button feature. A heatmap is also incorporated to visually highlight crime-prone areas, making it easier for users to identify unsafe regions. By integrating predictive analytics, geolocation services, and emergency communication tools into a single platform, the system offers a practical and efficient solution for improving women’s safety. The proposed approach not only supports quick response during emergencies but also promotes awareness and preventive decision-making.