Alcohol Detection System in Vehicles

Nikita SonavaneStudent, Department of Computer Science Engineering, Siddhant College of Engineering, IndiaProf. Pratiksha KaleProfessor, Department of Computer Science Engineering, Siddhant College of Engineering, IndiaAishwarya SonkambleStudent, Department of Computer Science Engineering, Siddhant College of Engineering, IndiaNikita SuryavanshiStudent, Department of Computer Science Engineering, Siddhant College of Engineering, IndiaGaurav MayaneStudent, Department of Computer Science Engineering, Siddhant College of Engineering, India

Vol 7 No (2023): Volume 7, Special Issue of ICRTET- 2023 | Pages: 193-196

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 16-07-2023

doi Logo IRJIET.ICRTET40

Abstract

This system is designed to detect the alcohol level in the body of the person who is driving car and avoid accidents occurring due to drunk and driving. The system uses raspberry pi with alcohol sensor, dc motor. System uses alcohol sensor with, raspberry pi with dc motor to demonstrate as vehicle engine. System constantly monitors the sensitivity of alcohol sensor for drunk driver detection. If driver is drunk, the processor instantly stops the system ignition by stopping the motor. If alcohol sensor is not giving high alcohol intensity signals, system lets engine run. The raspberry pi processor constantly processes the alcohol sensor data to check drunk driving and operates a lock on the vehicle engine accordingly. We proposed to reduce the number of accidents caused by driver fatigue and thus improve road safety. This system treats the automatic detection of driver drowsiness based on visual information and artificial intelligence. We locate, track and analyze both the driver face and eyes to measure PERCLOS (percentage of eye closure) with Softmax for neural transfer function. it will be also uses alcohol pulse detection to check out the person is normal or abnormal. Driver’s fatigue is one of the major causes of traffic accidents, particularly for drivers of large vehicles (such as buses and heavy trucks) due to prolonged driving periods and boredom in occupied conditions.

Keywords

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Citation of this Article

Aaysha Inamdar, Mohit Pandey, Sonali Ghorpade, Prajakta Dawari, Prof. Rashmi kulkarni, Prof. Kalyani kadam, “Medical Chatbot in Artificial Intelligence and Machine Learning to help Human” in proceeding of International Conference of Recent Trends in Engineering & Technology ICRTET - 2023, Organized by SCOE, Sudumbare, Pune, India, Published in IRJIET, Volume 7, Special issue of ICRTET-2023, pp 193-196, June 2023.

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