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AmEyeDrunk? The Future of Intoxication Detection

ISEF · 2023 Biomedical Engineering

Motkuri, Advaitha · Richland High School

Overview

The aim of this project is to develop a mobile app that can detect drug/alcohol intoxication levels in individuals using eye-pupil analysis. The app will utilize computer vision algorithms to analyze the size and shape of the pupil in real time and provide a quick and accurate assessment of the individual's sobriety. The app is designed to be user-friendly and will provide an easy-to-use interface for individuals to determine their sobriety level quickly. The project will also consider the privacy and security of user data. This app has the potential to provide a valuable tool for individuals who want to monitor their sobriety, as well as in medical and legal settings where sobriety levels need to be assessed quickly and accurately. This project's results will help advance the field of computational biology and bioinformatics and provide a new tool for studying and understanding the effects of drug and alcohol use on the human body.

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Source: Regeneron International Science and Engineering Fair

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