Currently, there is a significant increase in incidents of drunk driving and road accidents, primarily caused by drivers who lack control over their vehicles. Approximately 31% of traffic crash fatalities in the United States are attributed to drivers who were under the influence of alcohol. The number of fatalities resulting from these avoidable collisions in 2021 amounted to 13,384 individuals. Over a span of 10 years, the average number of fatalities amounted to 10,850 individuals. Implementing an engine locking system that incorporates alcohol detection can effectively mitigate the occurrence of accidents caused by intoxicated driving. An engine locking system that incorporates alcohol detection technology can prove highly beneficial for law enforcement agencies. It offers an automated safety solution for automobiles and other vehicles. While it is not possible for a person to expedite their sobriety, there are several methods that can enhance their alertness and give the appearance of being more sober. One such solution is the implementation of alcohol detection and engine locking system. When a driver attempts to operate the vehicle while heavily intoxicated, the MQ3/BAC sensor detects the presence of alcohol. If the alcohol concentration exceeds a certain threshold, a signal is transmitted to the Arduino UNO. Based on this signal, the engine will be deactivated. This measure has the potential to decrease the occurrence of accidents caused by driving under the influence of alcohol, hence minimizing the risk of fatalities and property damage resulting from drunk driving. In this article a comprehensive study is carried out on various alcohol detection and engine locking systems using Arduino. The various components used in each of the systems are analyzed.


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    Titel :

    A Comprehensive Study on Alcohol Detection and Engine Locking System using Arduino


    Beteiligte:
    U, Prabu (Autor:in) / Karre, Meenakshi (Autor:in) / Kolli, Maheswari (Autor:in) / N, Malarvizhi (Autor:in)


    Erscheinungsdatum :

    03.05.2024


    Format / Umfang :

    837845 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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