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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM50373
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Road accidents remain one of the leading causes of premature death globally, claiming thousands of lives every day and often leaving survivors with lifelong disabilities. A considerable part of these deaths is linked to the lag in delivering prompt medical help, especially in rural or isolated regions where witnesses might not be available to notify others of the occurrence. In such circumstances, an automatic accident detection system can be crucial for saving lives by shortening the time it takes to respond in an emergency. This paper puts forward a Vehicle Accident Detection System that utilizes an Arduino microcontroller and is based on an economical embedded platform. The system integrates the MPU6050, which combines a gyroscope and accelerometer for real-time motion and orientation tracking; a GPS module for accurate location monitoring; and a SIM900A GSM module to send instant SMS alerts. To identify occurrences like unexpected collisions, rollovers, or unusual changes in orientation, the system continuously monitors the vehicleâs acceleration and tilting behaviour. When a potential accident is confirmed, the system automatically dispatches a text message with precise GPS coordinates to emergency contacts that have been preconfigured. The system guarantees quicker communication with emergency responders and enhances accident victimsâ survival chances by removing the necessity for manual accident reporting. Moreover, the suggested system establishes a solid basis for future developments, including Internet of Things (IoT) integration, real-time data recording, cloud-based emergency services, and machine learning-driven accident prediction and categorization. The prototype that was developed shows great reliability in accident detection and could greatly improve road safety and emergency response systems in various situations.
KEYWORDS
Publication Date
6/15/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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