INTELLIGENT ACCIDENT AVOIDING SYSTEM IN AUTOMOBILE USING RASPBERRY PI
Janhvi Dhande1, Yash Funde2, Akshay Chavan3
1Electronics and Telecommunication, Sinhgad college of Engineering
2Electronics and Telecommunication, Sinhgad college of Engineering
3Electronics and Telecommunication, Sinhgad college of Engineering
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Abstract - This system aims to make driving vehicles safer and protect against drowsiness. Alcohol detection prevents accidents and collisions between vehicles while driving and reduces road accidents. This product will come to prepare a combination of face detection and face contours, as well as an additional feature of the driver’s alcohol consumption, and in accordance, the vehicle acceleration is maintained. This product is made up of deep learning algorithms that are used in conjunction with a microcontroller and interface with a microprocessor. The face will be detected using computer vision and contours will be formed around it. A set of devices is used to check the person for drowsiness and then for alcohol. The set of devices examines the person’s alcohol parameters. To show and notify alertness, the device in this paper employs a display interface. It sends a message to the person in charge to pick up the alcoholic. When the ignition lock is reset and the quality of alcohol consumed is checked, the ignition lock is removed. It will determine where the alcohol consumption device will exit. The device will detect alcohol consumption and stop the vehicle accordingly. The Open CV library is being used to aid in the detection of face drowsiness. To detect collisions, the product includes a distance tracker on each side of the vehicle that detects the distance between the vehicle with the model and the vehicles around it.
Key Words: Internet of Things, Haar-cascade, Open CV, Euclidian distance, Deep Learning.
