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tac_detection

Transdermal Alcoholic Concentration Detection Based On Smartphone Accelerometer's Data

You give it your accelerations, it tells you if you're drunk

What is it?

Drinking alcohol can become dangerous when you drive any vehicle.
However, it is difficult to check whether a person who wants to rent an electric scooter or bike is drunk or not.
Furthermore, a possible test to be conducted every time you try to access these vehicles would heavily limit their usability.
So, it would be useful, minimally invasive from the point of view of privacy and usability,
to check the smartphone accelerometer data, easily obtainable by the app that the user uses to rent the vehicle.
When alcohol acts on a person's body the way it moves changes, therefore there could be a relationship
between the accelerometer data, which describes the movements,
and the TAC (Transdermal Alcoholic Concentration), that describes whether you are drunk or not.

Having found a dataset with the data just mentioned, we apply some machine learning algorithms
to build a model that relates them and can predict if the user is drunk or not (then give him/her access to the vehicle or not).
Dataset: https://archive.ics.uci.edu/ml/datasets/Bar+Crawl%3A+Detecting+Heavy+Drinking

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This repo contains the project files of the TAC detection ML work.

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  • Python 100.0%