Real-Time Drinking Detection: Building Hydrovisor

Hydrovisor is a web app developed by Riaz Virani that uses computer vision to monitor drinking behavior and remind users to hydrate, capitalizing on the capabilities of models like Roboflow for object detection and Google's FaceMesh for facial tracking. The app overcomes the complexity of detecting drinking actions by employing specialized tools for each task, such as identifying cups and tracking facial landmarks, rather than relying on a single all-encompassing model. Through iterative refinement and real-world data contributions, Virani achieved a robust detection system that runs entirely in the browser using Roboflow's Inference.js, ensuring cost-free operation without requiring cloud infrastructure. The app's design prioritizes user-friendliness and efficiency, operating at 5 FPS to balance performance with resource conservation, and it effectively distinguishes between potential drinking actions by tracking the largest visible cup. Hydrovisor exemplifies how combining existing technologies can solve practical challenges, offering a simple and accessible solution to promote hydration without compromising user privacy or incurring additional costs.