ACCIRESCUE: Life Saver in Every Accident

Abstract

Road traffic accidents represent a critical global public health challenge, claiming millions of lives annually. A significant factor contributing to fatalities is the delay between the occurrence of an accident and emergency medical response. This paper presents AcciRescue, an intelligent real-time accident detection and alert system designed to minimise response time and improve survival rates. The system integrates NEO-6M GPS and SIM800L GPS modules with an accelerometer and gyroscope sensor connected to an Arduino Nano microcontroller to continuously monitor vehicle movement and detect collision events. Upon detecting sudden velocity changes indicative of an accident, AcciRescue automatically transmits the precise incident location to emergency contacts and nearby hospitals. The proposed system offers a cost-effective, scalable solution that can be seamlessly integrated into vehicles or smartphones, addressing the critical need for rapid emergency response in traffic accidents.

Introduction

Road accidents cause numerous deaths and injuries worldwide, often worsened by delays in reporting or communicating accident locations. The Accident Detection and Alert System addresses this by using sensors (accelerometers, gyroscopes, and cameras) to detect collisions or abnormal vehicle movements in real time. A microcontroller processes sensor data, and upon detecting an accident, the system automatically retrieves GPS coordinates and sends alerts via GSM to hospitals, ambulances, police, and emergency contacts, enabling rapid response and potentially saving lives.

The system architecture consists of four layers: Sensing, Processing, Communication, and Response. Validation logic and a short delay window reduce false alarms, while GPS tracking ensures accurate location reporting. The system is cost-effective, automatic, and extendable to AI-based enhancements. Key modules include Accident Detection, Processing, Location Tracking, Communication, and Emergency Response, supported by a tech stack of frontend (HTML, CSS, JavaScript), backend (Node.js, Python, Java), and databases (MySQL, MongoDB, Firebase). The design enables fast, reliable, and automated emergency notification, improving road safety and timely medical assistance.

Conclusion

The proposed system, AcciRescue: Accident Detection and Alert System, successfully demonstrates an efficient and reliable solution for reducing emergency response time in road accidents. By integrating sensors such as accelerometer and gyroscope with a microcontroller, the The proposed system, AcciRescue: Accident Detection and Alert System, successfully demonstrates an efficient and reliable solution for reducing emergency response time in road accidents. By integrating sensors such as accelerometer and gyroscope with a microcontroller, the system is capable of accurately detecting sudden impacts, collisions, and abnormal vehicle movements in real time. The implementation of GPS and GSM modules ensures that the exact location of the accident is immediately transmitted to emergency services, hospitals, and registered contacts. This eliminates the dependency on manual reporting, which is often delayed or impossible in critical situations where victims are unconscious or unable to communicate. The system’s multi-sensor approach combined with decision-making logic improves detection accuracy while minimizing false alarms. Additionally, the inclusion of automated alert mechanisms ensures rapid communication, which plays a crucial role in saving lives during the “golden hour” of medical emergencies. Overall, the proposed model is cost-effective, easy to implement, and highly scalable. It can be integrated into various types of vehicles and extended with advanced technologies such as machine learning, cloud connectivity, and smart city infrastructure. The system contributes significantly to improving road safety and provides a practical solution for real-time accident monitoring and emergency response.

References

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Copyright

Copyright © 2026 Prof. Vibha Gomase, Sambhavi Petkar, Muskan Harde, Prutha Rajgure, Tanishka Gajbhiye, Tejas Parate. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.