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A Mobile Application to Assist in Tracking Alcohol Consumption using Machine Learning and Object Detection

Authors

Felix Bai1, Jeremy Taraba2 and Fangzhou Sun3, 1University Prep, USA, 2California State Polytechnic University, USA, 3Match Group LLC, USA

Abstract

Statistics show that excessive alcohol consumption has been a problem and remains a problem in many countries. This paper proposes an application that encompasses a solution which allows users to log and track their alcohol intake over time. It leverages features such as object recognition for drink identification, a history calendar for reflective analysis, and a real time blood alcohol level indicator for health measurements. During experimentation we found that the accuracy of the AI to be exceptional when used on drinks that it has been trained on. Furthermore, the blood alcohol calculator demonstrated a level of accuracy comparable to, if not surpassing, that of online calculators. This heightened accuracy is attributed to its real-time updating capability, ensuring precision in the calculations throughout the user's engagement with the application. The ultimate goal of this initiative is to create a user-friendly, technology-driven solution that empowers individuals to make informed decisions about their alcohol consumption. It promotes responsible drinking behavior and contributes to overall health and well-being.

Keywords

AI, Flutter, Firebase, Alcohol

Full Text  Volume 14, Number 5