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DOI Prefix: 10.47001/IRJIET
Vol 10 No 3 (2026): Volume 10, Issue 3, March 2026 | Pages: 130-135
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 21-03-2026
Road accidents remain one of the major causes of fatalities and property loss, primarily due to delayed response, lack of evidence, and unmonitored driver behavior. This project presents an IoT-enabled Car Black Box System designed to enhance vehicle safety, monitor driving conditions, and assist post-accident investigation. The system integrates Raspberry Pi 3B+ with various sensors such as ADXL335 accelerometer, HC-SR04 ultrasonic sensor, MQ-3 alcohol sensor, and limit switch to continuously collect real-time data related to vehicle motion, distance, and driver condition. In case of an accident or abnormal event, the system automatically triggers alerts through a buzzer and restricts vehicle movement via the L298N motor driver. A secondary Arduino Nano unit handles GPS tracking, GSM communication, and on-board display for immediate status updates. The recorded data is transmitted to cloud servers through an ESP-01 IoT module, while MCP2515 supports CAN-based vehicle data logging. The system functions as a cost-effective black box, providing crucial evidence during accidents, enabling emergency response, and supporting analysis for improved road safety.
Car Black Box, Raspberry Pi 3B+, Arduino Nano, Accident Detection, GPS Tracking, GSM Alert, IoT Monitoring, Driver Safety, CAN Bus, ADXL335, Alcohol Detection
Tejasvi Nigade, & Dr. Kanchan Vaidya. (2026). IoT-Based Black Box System Using CAN Protocol for Automobiles. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(3), 130-135. Article DOI https://doi.org/10.47001/IRJIET/2026.103017
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