India is motorizing at a fast pace, and this has tremendously escalated traffic accidents, deaths, and injuries and has become a serious public health concern. Most accidents take place at particular spots referred to as "black spots." This paper introduces an Android application that is designed to alert users in real time when they are getting near such accident spots. The system draws on user-reported data on accidents, which are stored in a Firebase database. The system monitors the location of the user using location-based services and cross-references them with database records to determine probable black spots. For greater accuracy, we apply the ECLAT algorithm to cluster accident data and determine frequently occurring locations. The project is equipped with an easy-to-use interface that facilitates rapid reporting of accidents with less user intervention and makes use of alerting functions of sound and vibration to warn users of hazardous areas. By virtue of the ability of users to input information in real time and immediate alerts, this project seeks to minimize road accidents and enhance traffic safety.Based on historical accident records and user reports to be updated continuously, the app is beneficial to both individual consumers and urban planners. The essay discusses the app's architecture, technical requirements, limitations, and potential increases Keywords: Black Spot Detection, ECLAT Algorithm, Android App, Real-time Alerts, Road Safety, Accident Detection, Accident Prevention, Emergency Response, Crime Mapping, Traffic Management, Geo-location, Machine Learning, Pattern Recognition GPS, IoT Integration, Crime Hotspots, Safety Alert System, Safety Monitoring, Public Safety.