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Drink Sense
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Drink Sense
This mobile application helps users track and manage their alcohol consumption while providing real-time predictions of future blood alcohol content (BAC) based on their intake. Users can log each drink, review their past consumption, receive personalized insights, and set notifications to monitor their habits. The app encourages more informed decisions about drinking by offering a clear picture of the user’s alcohol intake and its potential effects.
Initially, the system’s BAC prediction model was based on the widely-used Widmark formula, which estimates BAC by considering the user’s height, weight, and sex. However, the app has since evolved to adopt a more sophisticated pharmacokinetic model—the Gelabert model—offering greater accuracy in predicting the diffusion of ethanol into the bloodstream. This enhanced model accounts for a wider range of physiological factors, making the BAC predictions more reliable for users.
Built with a modern, scalable tech stack, the app is available on Android, ensuring smooth performance and accessibility. Additionally, a web version provides administrative functionality, supporting features like user management and data analysis. The app is a powerful tool for those seeking to understand and control their alcohol consumption in a meaningful, data-driven way.
TypeScript
Kotlin
React
Material UI
Firebase
GraphQL
BullJS
NestJS
NodeJS
PostgreSQL
Redis
NX
Android
