AI-BASED VEHICLE ACCIDENT DETECTION AND GPS EMERGENCY NOTIFICATION SYSTEMID: 3809 Abstract :Road Traffic Accidents Remain One Of The Leading Causes Of Fatalities And Severe Injuries Worldwide, Particularly Due To Delayed Emergency Response And The Inability To Quickly Communicate The Accident Location To Rescue Teams. Conventional Accident Reporting Systems Rely Primarily On Manual Phone Calls Or Eyewitness Reports, Which May Result In Significant Delays In Medical Assistance, Especially In Remote Areas. Recent Advancements In Artificial Intelligence (AI), Internet Of Things (IoT), Global Positioning System (GPS), Global System For Mobile Communication (GSM), Embedded Systems, Wireless Communication, And Real-time Monitoring Have Enabled The Development Of Intelligent Accident Detection Systems Capable Of Automatically Identifying Vehicle Crashes And Immediately Notifying Emergency Services. This Project Presents CrashGuard: Intelligent Vehicle Accident Detection And GPS Emergency Notification System, An Intelligent Safety Framework Designed To Detect Vehicle Accidents Automatically And Transmit The Precise Accident Location To Emergency Responders. The Proposed System Integrates An ESP32 Microcontroller, Accelerometer Sensor, Gyroscope Sensor, GPS Module, GSM/Wi-Fi Communication Module, Buzzer, Cloud Monitoring Platform, And Emergency Notification Unit Into A Unified Accident Monitoring Architecture. During Vehicle Operation, The Accelerometer And Gyroscope Continuously Monitor Sudden Impact Forces, Abnormal Acceleration, And Vehicle Orientation. When The Measured Values Exceed Predefined Safety Thresholds, The System Identifies A Potential Accident, Acquires The Vehicles GPS Coordinates, And Immediately Transmits An Emergency Notification Containing The Vehicle Location, Date, Time, And Accident Information To Predefined Emergency Contacts And Rescue Services. Simultaneously, The Event Is Recorded For Future Analysis And Displayed On A Cloud Monitoring Platform. Experimental Evaluation Demonstrates High Accident Detection Accuracy, Low False Alarm Rate, Rapid Notification Response, Reliable GPS Positioning, Stable Communication Performance, And High Overall System Reliability. The Proposed CrashGuard Framework Significantly Reduces Emergency Response Time, Improves Passenger Safety, Minimizes Accident-related Fatalities, And Provides A Costeffective Intelligent Vehicle Safety Solution For Nextgeneration Transportation Systems. Keywords: Intelligent Vehicle Safety, Accident Detection, GPS, GSM, ESP32, IoT, Accelerometer, Gyroscope, Emergency Notification, Vehicle Monitoring System. |
Published:07-8-2026 Issue:Vol. 26 No. 8 (2026) Page Nos:749 - 757 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to Cite1CHERUKU ABHINAY,2Mrs.FATHIMA ZAHEERA,3T.SHIVA CHARI,4SAYYED SUMAYYA,5NETHIBOTTU PRABHAKAR, AI-BASED VEHICLE ACCIDENT DETECTION AND GPS EMERGENCY NOTIFICATION SYSTEM , 2026, International Journal of Engineering Sciences and Advanced Technology, 26(8), Page 749 - 757, ISSN No: 2250-3676. |