Overview / Usage

The problem regarding vehicle accidents in developing countries is the time required for aid to reach the person or persons involved in the incident due to the lack of a system that can inform the required authorities quickly. Often is the situation where the traffic congestion due to the aforesaid incident can give rise to an adverse circumstance which in turn delays the medical relief. So we tried to come up with a solution where our system will automate the necessary steps to be taken such as informing the nearest police station and hospital so that emergency aid can be sent to the accident site as early as possible and the traffic management can re-route the vehicles heading towards the accident site. The system will also upload the important data of the vehicle such as GPS location, vehicle type, vehicle number, color, speed, engine rpm at the time of the crash.
The data will be made available to the public for their convenience as they will be able to view and possibly avoid that route.
The data can also be used for further diagnosis by the law enforcement agencies and can be extrapolated to form various crash statistics.

Methodology / Approach

1. Initially, the ELM327 device will fetch the data from the OBD2 port of the car using CAN protocol.
2. The data will be stored on the internal storage of the onboard Computer, here the Intel UP2 board.
3. There will be a sensor which detects the inflation of the air-bag, this will initiate the system.
4. The computer will fetch the GPS location using the Neo6M GPS Module.
5. At the exact time, the computer will push a notification with data (GPS Location, vehicle type, vehicle number, color) to the local authorities using MQTT.
6. It will also upload the data along with engine rpm and speed at the time of the accident to database in the cloud.
7. The informations will be available to be accessed through a web app and the locations of the accident will be pointed in maps using google maps API.
8. The data will be processed and visualized to extrapolate crucial information.
9. A statistical representation of the data can also be produced for further analysis.

Technologies Used

1. Intel UP2 Board
2. OBD 2
3. MariaDB
4. IoT
5. Python
6. Neo6M GPS Module
7. WiFi AP or GSM Module

Collaborators