Car Black Box System for Accident Analysis using IoT

AIM:

       The mainstay of the project is to develop a Black Box technology project is to enhance road safety by detecting and analyzing accidents, monitoring driver behavior and engine health, and providing real-time data for timely responses and future analysis

Introduction:

        In the modern era of automotive technology, ensuring the safety of drivers and passengers is paramount. This project presents a “Smart IoT-Based Vehicle Black Box System for Accident Detection and Analysis,” which leverages the capabilities of the ESP32 microcontroller as the brain of the system. The ESP32 interfaces with various sensors to monitor vital parameters and conditions in real-time. An alcohol sensor detects if the driver is under the influence, ensuring safe vehicle operation. The LM35 temperature sensor monitors engine heat, while an ultrasonic sensor checks the distance between vehicles to prevent collisions. A vibration sensor detects accidents, triggering the system to capture GPS location data using a GPS module. This information, along with sensor readings and status, is sent to the cloud for real-time monitoring and analysis. Additionally, an SD card module stores all sensor data and accident causes, serving as a black box for post-accident analysis. By integrating these technologies, the system aims to enhance road safety, provide valuable data for accident analysis, and offer insights into preventing future incidents.

Existing system:

        Existing work in the realm of vehicle black box systems and IoT-based accident detection has seen significant advancements. Various studies and projects have integrated microcontrollers such as Arduino and Raspberry Pi with sensors to monitor parameters like alcohol levels, engine temperature, and vehicle proximity. Systems have employed GSM and GPS modules for location tracking and data transmission to cloud platforms for real-time monitoring. However, many solutions lack comprehensive integration, focusing on isolated functionalities.

Proposed system:

        The proposed “Smart IoT-Based Vehicle Black Box System for Accident Detection and Analysis” aims to enhance road safety through real-time monitoring and post-accident analysis. At the heart of the system is the ESP32 microcontroller, which acts as the central controller and communication hub. The system integrates several sensors: an alcohol sensor to detect driver intoxication, an LM35 temperature sensor to monitor engine heat, an ultrasonic sensor to measure the distance between vehicles, and a vibration sensor to detect collisions. When an accident is detected, the GPS module captures the vehicle’s location, and the ESP32 sends this information along with sensor data to the cloud for immediate access. Additionally, an SD card module stores all sensor data and the cause of the accident, serving as a black box for comprehensive post-accident analysis. This integrated approach not only ensures real-time monitoring and rapid response but also provides valuable data for understanding and preventing future incidents. By combining cloud connectivity with local storage, the system offers a robust solution for enhancing vehicle safety and delivering critical insights in the event of an accident.