In this modern, fast moving and insecure world, it is a basic necessity to be aware of one’s safety. Moreover, the number of accidents occurrence of accidents is increasing day by day. Many statistics say that most of the accidents are caused due to consumption of alcohol or due to the drowsiness of the driver. A system using modern technology is developed to over come such accidents by monitoring the activities of driver. Pi camera is used to monitor the drowsiness of driver using machine learning. Alcohol sensor is used for the detection of alcohol consumption by the driver. Ultrasonic sensor is used to detect the obstacle, if any vehicle comes near to his vehicle. Heartbeat sensor is used to monitor the heartrate of the driver. GPS module is used to track the live location of the vehicle in the form of latitude and longitude values. GSM module is used for sending alert SMS and location link to the predefine mobile number, if the heartbeat value crosses the set limit or if the driver consumes alcohol or if the ultrasonic sensor detects obstacle close the vehicle. In this BLDC motor works as a vehicle which is controlled by the Arduino through VSI (Voltage source inverter). In this vehicle accelerator control automatically based on the heartrate of the driver and stop the vehicle automatically if the driver was alcoholic or if the ultrasonic sensor detects obstacle very close the vehicle. The main controlling device of the project is raspberry pi4 processor. Pi camera attached to the Raspberry Pi processor, it will monitor the person face whether the driver in drowsy or not using machine learning algorithm. The status of the project will display on LCD screen. To achieve this task raspberry pi loaded program written in python language.

   

The main objectives of the project are:

1. Automatic Drowsiness detection using machine learning.
2. Automatic alcohol detection and ignition control system.
3. Automatic obstacle detection and ignition control system.
4. Automatic driver heartrate detection and SMS alert.
5. GPS based vehicle location tracking system.
6. GSM based SMS alerting system.
7. Pi camera-based driver drowsiness detection.
8. To achieve this using Raspberry Pi4 Processor.

The major building blocks of the project are:

• Power supply.
• Raspberry pi4.
• SD card.
• Pi Camera.
• Arduino UNO.
• Alcohol sensor.
• Ultrasonic sensor.
• Heartbeat sensor.
• GPS Receiver.
• GSM.
• VSI.
• BLDC motor.

Software’s used:

1. Arduino IDE for dumping the code into the Arduino UNO.
2. Raspbian OS.
3. Python language.
4. Machine learning Algorithm.
5. Express SCH for Circuit design.

     

   

Block diagram:    

 

     

 

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