• LISA M
• MOSHIKA SD
• Mrs.B.ARUNMOZHIKALANCHIYAM

This project aims to revolutionize highway incident management by developing an integrated system leveraging computer vision, optical character recognition (OCR), and database integration. The system detects accidents in real-time, extracts vehicle information from number plates using OCR, and retrieves victim details from a database. It sends immediate alerts to nearby hospitals and police stations, providing crucial information for swift emergency response. Training on a large dataset and utilizing advanced algorithms like YOLO V8 ensures high accuracy in accident detection. By sending detailed alert messages with visual context, the system minimizes resource misallocation and enhances emergency response capabilities, ultimately improving highway safety.

Highway Incident Management, Real-time Incident Detection,OpenCV (Open Source Computer Vision Library) , OCR , SMTP Protocol, Twilio API, Automated Incident Reporting, Efficient Emergency Management, Automated Alert System , Deep Learning , Real-time Video Processing , Data Preprocessing, Model Fine-tuning,Convolutional Neural Networks (CNN) , You Only Look Once (YOLO) algorithm

"OCR-ENABLED HIGHWAY INCIDENT MANAGEMENT AND RAPID EMERGENCY RESPONSE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.p610-p617, April-2024, Available :http://www.jetir.org/papers/JETIR2404G80.pdf

"OCR-ENABLED HIGHWAY INCIDENT MANAGEMENT AND RAPID EMERGENCY RESPONSE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppp610-p617, April-2024, Available at : http://www.jetir.org/papers/JETIR2404G80.pdf