Abstract: This study presents an innovative Accident Detection and Alert System employing Deep Learning (DL) and Edge Computing. The system leverages DL algorithms to analyze real-time video feeds from surveillance cameras, detecting patterns indicative of accidents. By deploying computations at the edge, near the data source, latency is minimized, ensuring swift response times. The system's autonomous alert mechanism promptly notifies emergency services, enhancing the efficiency of rescue operations. This integration of DL and edge computing optimizes accident detection, reducing response times critical for mitigating injuries and saving lives on the road.
Keywords: Edge Computing, Deep learning, CCTV, Video processing, CNN
Cite: Dr. Chayapathi A R, Gururaja H S, Cheluvaraj S, Yashwanth N , Puneeth R, "Review on Accident Detection and Alert System using Edge Computing and Deep Learning", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 4, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13426.
|
DOI:
10.17148/IJARCCE.2024.13426
