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Driving situations include a lot of safety considerations. One of the major factors in road accidents is drunk driving by drivers of vehicles. Due to advancements, notably in the area of biometrics, it is now possible to determine a person's state of drunkenness on alcohol. Therefore, creating an intelligent system to address this issue is important. These systems generally employ artificial vision or sensor networks. For the purpose of evaluating the collected data, we additionally utilize feature selection and supervised classification methods. Every technique and algorithm has been created to use the least amount of analytical resources feasible because the whole acquisition and analysis process will be completed within an embedded device.This paper provides an overview of current developments in the field of neural network-based driver intoxication detection.Different methods for detecting drunkenness have been examined, and potential areas for improvement have been identified.

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