Ai-driven Accident Analysis And Real-time Emergency Alert System

• Author(s):

  Dhanesh E | Viswanathan S | Bala S

• Keywords:

  Accident Detection , Artificial Intelligence , Deep Learning , Real-Time Alert System , YOLOv8.

• Abstract:

  Road Accidents Are A Major Cause Of Death And Serious Injuries Worldwide, Substantially Due To Delayed Discovery And Exigency Response. This Design Presents An AI- Grounded Real- Time Road Accident Detection, Beget Analysis, And Future Accident Prevention System Using CCTV Surveillance And Deep Literacy Ways. The System Continuously Monitors Road Business And Automatically Detects Accidents In Real Time Using The YOLOv8 Model. Once An Accident Is Detected, The System Estimates Its Inflexibility And Incontinently Sends Cautions With Position Details To The Nearest Hospitals To Insure Quick Medical Backing. In Addition, The System Analyzes Possible Causes Of Accidents Similar Asover-speeding, Collisions, And Business Violations While Storing All Incident Data For Farther Analysis. The Collected Data Is Used To Identify Accident-prone Areas And Induce Intelligent Forestallment Suggestions To Ameliorate Road Safety. Eventually, This System Reduces Exigency Response Time, Supports Authorities, And Helps In Minimizing Road Accident Losses Through AI- Driven Robotization And Analysis.

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Other Details

• Paper id:

  IJSARTV12I4105179

• Published in:

  Volume: 12 Issue: 4 April 2026

• Publication Date:

  2026-04-27

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