Proceedings of the International Conference on Intelligent Technologies in Security and Privacy for Wireless Communication, ITSPWC 2022, 14-15 May 2022, Karur, Tamilnadu, India

Research Article

AI Based Smart Assistant System for Drowsiness Driver

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  • @INPROCEEDINGS{10.4108/eai.14-5-2022.2318878,
        author={Dinesh  C and Jayasreedhar  N and Lankesh  P and Mugilan  S and Karthikeyan  S},
        title={AI Based Smart Assistant System for Drowsiness Driver },
        proceedings={Proceedings of the International Conference on Intelligent Technologies in Security and Privacy for Wireless Communication, ITSPWC 2022, 14-15 May 2022, Karur, Tamilnadu, India},
        publisher={EAI},
        proceedings_a={ITSPWC},
        year={2022},
        month={8},
        keywords={driverdrowsiness face detection perclos virtual assistant},
        doi={10.4108/eai.14-5-2022.2318878}
    }
    
  • Dinesh C
    Jayasreedhar N
    Lankesh P
    Mugilan S
    Karthikeyan S
    Year: 2022
    AI Based Smart Assistant System for Drowsiness Driver
    ITSPWC
    EAI
    DOI: 10.4108/eai.14-5-2022.2318878
Dinesh C1,*, Jayasreedhar N2, Lankesh P2, Mugilan S2, Karthikeyan S3
  • 1: Assistant Professor, Department of Electrical and Electronics Engineering, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India-641407
  • 2: UG student, Department of Electrical and Electronics Engineering, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India.641 407
  • 3: Managing Partner, ARK Automation Pvt Ltd., Coimbatore - 641029
*Contact email: dineshchml@gmail.com

Abstract

Virtual Assistant is an artificial intelligence-based technology. It was created to assist users with their fundamental chores and offers information in a natural language way. When a user requests that his assistant complete a task, the native language voice stream is translated into digital data that the software can interpret consumers to get the values of specific devices from the system. Many accidents are caused by drivers who are drowsy. It is becoming one of the leading causes of traffic accidents. According to recent statistics, many accidents are caused by drivers who are drowsy. Thousands of lives are lost each year as a result of vehicle accidents caused by drowsy drivers. Drowsiness is responsible for more than 30% of all accidents. To avoid this, a system is needed that detects drowsiness and alerts the driver, saving the driver's life. We describe a strategy for detecting driver tiredness in this research. The motorist is continuously monitored via camera in this scenario. This model employs image processing algorithms that are primarily focused on the driver's face and eyes