IOT-Based Automatic Vehicle Accident Detection System
Road accidents remain a pressing global issue, causing significant injuries, loss of life, and economic setbacks. The delayed detection of accidents and communication to emergency responders often worsens these outcomes, highlighting the need for efficient and automated solutions. . An IoT-based Automatic Vehicle Accident Detection and Alert System has been developed to solve the identified problems by integrating superior sensors and real-time communications. The system employs an accelerometer module to continuously monitor vehicle dynamics, identifying sudden deceleration or impact patterns that signify a potential accident. Once an accident is detected, a NEO-6M GPS module accurately determines the exact location, and a GSM module instantly transmits SMS alerts to predefined contacts or emergency services, reducing response times and increasing the chances of saving lives. An Arduino Nano microcontroller acts as the system's core, seamlessly processing data from all sensors and managing the communication protocols. A DC-DC buck converter ensures stable and efficient power delivery, enhancing the system’s reliability, even in adverse conditions. Compact and cost effective, this design can be easily adapted for various vehicle types, ranging from personal cars to commercial fleets. Moreover, the system lays the foundation for future enhancements, such as mobile app integration, cloud-based accident data analysis, real-time updates to stakeholders, and predictive vehicle maintenance. By bridging the gap between accident occurrence and emergency response, this innovation not only promises to save lives but also empowers stakeholders with data-driven insights to improve road safety and vehicle reliability.
Authors
- K. Sushma
- K. Dinesh
- Poosa Vamshi
- E. Akshaya
- L. Sapnil
Publication Details
- Journal
- International Journal Of Recent Trends In Multidisciplinary Research
- Published
- 2025-05-01
- DOI
- https://doi.org/10.59256/ijrtmr.20250502015
- Primary Topic
- IoT and GPS-based Vehicle Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00