https://iaeme.com/Home/journal/IJCET 138 editor@iaeme.com International Journal of Computer Engineering and Technology (IJCET) Volume 15, Issue 2, March-April 2024, pp. 138-148, Article ID: IJCET_15_02_017 Available online at https://iaeme.com/Home/issue/IJCET?Volume=15&Issue=2 ISSN Print: 0976-6367 and ISSN Online: 0976–6375 Impact Factor (2024): 18.59 (Based on Google Scholar Citation) © IAEME Publication DROWSINESS AND ACCIDENT DETECTION SYSTEM WITH LOCATION TRACKING Shaun Mascarenhas Student, Department of Computer Engineering, Xavier Institute of Engineering, Mumbai, India Yash Mahajan Student, Department of Computer Engineering, Xavier Institute of Engineering, Mumbai, India Gauri Jadhav Student, Department of Computer Engineering, Xavier Institute of Engineering, Mumbai, India Clarice Dsouza Student, Department of Computer Engineering, Xavier Institute of Engineering, Mumbai, India Prof. Nilambari Narkar Assistant Professor, Department of Computer Engineering, Xavier Institute of Engineering, Mumbai, India ABSTRACT Ensuring the safety of drivers and passengers is of utmost importance in the modern world of traffic, because every year a huge number of human lives, millions, are lost due to vehicle accidents. An often underestimated but critical factor that contributes greatly to these accidents is driver drowsiness. This project aims to address these pressing challenges by developing an integrated system that combines real-time driver drowsiness detection, accident detection and precise location tracking capabilities. Using state-of-the-art technologies such as facial recognition and GPS-based tracking, our system proactively detects signs of driver fatigue in real time [2] and provides timely warnings to drivers to prevent accidents caused by drowsiness. At the same time, the system uses advanced accident detection algorithms that distinguish minor incidents from serious collisions and ensure that appropriate responses are initiated quickly. This comprehensive solution not only improves road safety, but also speeds up emergency response, ultimately saving lives and significantly reducing accidents on our roads.