Strict Implementation of Road safety Rules
An inbuilt vehicle system which helps to stringent laws and a strict implementation of wearing helmet and tight the seat belt during two/ four wheel drive to make India’s roads safe.
Created on 6th September 2020
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Strict Implementation of Road safety Rules
An inbuilt vehicle system which helps to stringent laws and a strict implementation of wearing helmet and tight the seat belt during two/ four wheel drive to make India’s roads safe.
The problem Strict Implementation of Road safety Rules solves
As per the reports of Ministry of Road and Highway around 400,000 people die due to accidents in India and very large number of people get injured and the main reason for these accidents is that people ignore the safety rules wearing of helmet,seat belt and also many of them loose life due to lack of response system.Here we have tried to create a sophisticated inbuilt system which is foolproof in vehicle .
The project has 5 modules
=> Helmet Authentication-
-The helmet detection will be done using the 2 HC-05 Modules.
-One of the Bluetooth modules will act as Master packed into the bike and other as Slave in the helmet.
-When the rider wears the helmet the Bluetooth modules gets paired and thus rider will be able to ignite the bike.
-The helmet model works when the push switches present into the helmet get pressed and is connected.
=>Accident Detection
-The Accident Detection sub module will be powered by MPU 6050.
-As soon as the bike gets into moving state the MPU starts working and it has inbuilt gyroscope and accelerometer.
-The MPU works on 3 Axis force or movement detection,if it detects the sudden force par from its threshold its state gets high and accident is detected.
=>Response System
-As soon as the accident is detected the Response System gets activated.
-The GSM and GPS sub modules instantly connect to the network.
-The GPS sub module freezes co-ordinates and send the messege for heplp instantly.
=>Seat Belt Detection.
-The seat belt detection will be done using the camera.
-The camera here will work on image processing and process the real time frame processing it in the inbuilt classifier.
-The Car wont start until the driver’s seat belt is detected.
=>Alcohol Detection.
-The Alcohol detection will be done by placing the MQ-3 sensor in the helmet unit.
-The sensor senses the breadth of the person as he/she wears the helmet.
-The Bluetooth module wont pair unless the condition of MQ-3 is false.
Challenges we ran into
There were many many problems encountered by us while building this project and finding the right and most efficient approach was the first.As people tend to find out loophole and try to run from following all the safety rules.The main objective of this project of ours was to develop a sophisticated and robust system which is foolproof.
The project has around 7-8 submodules which firstly developed which we developed indicidually due to current situations and also our project is hardware based which made it more difficult for us to integrate it in one complete system. As there were different codes for each modules like HC-05(Bluetooth),MPU6050(Accelerator),SIM900,GPS(for co-ordinates) and MQ-3(Alcohol Detector) in Arduino was completely new to us and the task to compile these codes and generating one infalliable flow of the program was the bigggest hurdle we have faced.We had to make certain changes in the code in a very short time frame, also we had to design hundreds of flow charts and settle for the one which had least complexity as the system was supposed to be very quicky for the tasks like resoponse system and auntentication.
We also faced some issue while fecthing the the Azure API, which had our trained model for Seat Belt detection in the car, in the Raspberry Pi. We also had to make sure the the Raspberry Pi work automatically when the user insert the keys.
The main problem here was to make the system delete the captured image user wearing seatbelt as soon as it is processed and detection is done as it would have violated the privacy of the user if the image of the user were saved in the system. We successfuly solved this issues too by writing a shell script in the Raspberry Pi which deletes all the data when it boots itself.