ARCHIVES

Adequate hydration is crucial for health and performance, yet many fail to maintain it due to reliance on manual tracking or generic reminders. This project presents a Smart Predictive Hydration Monitoring System that integrates IoT and predictive analytics to provide an automated, personalized solution. Using a load cell sensor and ESP32 microcontroller, the system measures water consumption via weight changes and transmits data via BLE to a mobile app, which calculates personalized goals. All data is stored securely in Firebase for real-time sync and trend analysis. A predictive module evaluates consumption patterns to forecast deficits and trigger adaptive alerts, reducing notification fatigue. This Phase I report covers the system’s analysis, design, and validation via the WOKWI simulation platform, demonstrating its feasibility and potential for health, fitness, elderly care, and workplace applications