SafeDrive: A Framework for Real-Time Risk Mitigation in Smart Vehicles

Abstract- with the increasing integration of intelligent systems in automobiles, ensuring safety in real-time has become both a challenge and a necessity. This paper introduces SafeDrive, a comprehensive framework designed to mitigate risks in smart vehicles by leveraging real-time data analysis, sensor fusion, and machine learning. The framework focuses on detecting and responding to potential hazards dynamically, thus reducing the probability of accidents and enhancing overall road safety. By incorporating proactive risk assessment, multi-sensor input fusion, and adaptive decision-making capabilities, SafeDrive provides a scalable and intelligent solution to modern vehicular safety needs. Keywords: Smart vehicles, real-time risk mitigation, SafeDrive, sensor fusion, machine learning, automotive safety, V2X communication