Real-Time IoT-based Vehicle Accident Detection and Emergency Response System using Multi-Sensor Fusion

This paper presents a real-time vehicle accident detection system using IoT and multi-sensor fusion to improve emergency response. The proposed solution integrates an MPU6050 accelerometer for impact detection, ultrasonic sensors for collision proximity assessment, GPS for location tracking, and GSM for emergency alerts, all controlled by an Arduino UNO. Through dual-sensor validation, the system achieves 95% detection accuracy while maintaining a false alarm rate below 5%. Experimental results demonstrate a response time under 10 seconds for transmitting accident coordinates via SMS. The system's low-cost design (~$50) and modular architecture make it particularly suitable for regions with limited emergency infrastructure. This work advances intelligent transportation safety by providing a reliable, scalable solution for rapid accident detection and response.