Intelligent Vehicle Safety and Driver Monitoring System Using IoT and Multi-Sensor Technology

The proposed project, “Development of an IoT-Enabled Smart Vehicle Safety System Using Ultrasonic Sensors for Collision Avoidance and Intelligent Driving Assistance,” provides an integrated approach to improving vehicle safety through embedded systems and IoT technology. The system uses an Arduino UNO controller, an ultrasonic sensor, three IR sensors, and an MQ-3 alcohol sensor to monitor obstacles and potentially unsafe driving conditions. The ultrasonic sensor detects frontal obstacles, while the IR sensors provide additional detection on the left, right, and rear sides. Based on sensor inputs, the controller activates the buzzer, displays warning messages on the LCD, and controls the DC motors through the L298N motor driver to reduce collision risks. Furthermore, the ESP8266/ESP32 module enables wireless communication with a cloud server, allowing remote monitoring of vehicle status and safety events. The lithium-ion battery provides portable power for the prototype. The proposed architecture offers an affordable and modular platform for demonstrating intelligent driving assistance, obstacle detection, and alcohol-related safety interlocking. Its performance can be evaluated through repeated experiments involving detection accuracy, motor response time, sensor reliability, and successful cloud communication. Overall, the system demonstrates the potential of combining multiple sensors, automatic control, and IoT connectivity to enhance prototype-level vehicle safety. Further improvements may include GPS tracking, advanced driver monitoring, and extensive real-world validation before practical automotive deployment.

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