IoT Based Non-Invasive Uric Acid Monitoring System Using Color Sensing And Cloud Analytics

Uric acid is a key biomarker for diagnosing metabolic disorders such as gout and chronic kidney disease. Conventional laboratory methods are expensive, time-consuming, and require trained professionals, limiting accessibility in point-of-care settings. This paper presents a low-cost, portable, IoT-enabled uric acid detection system based on colorimetric analysis using the phosphotungstic acid (Folin\\\'s) method. The system employs a TCS34725 RGB color sensor interfaced with an ESP32 microcontroller via I2C protocol to measure the blue channel intensity of the Tungsten Blue compound formed during the reaction. The principle follows Beer-Lambert law, where absorbance is directly proportional to uric acid concentration. A 3D printed light-isolated chamber ensures consistent optical measurements by eliminating external light interference. The ESP32 processes sensor data using a calibration equation derived from standard solutions and transmits results wirelessly to Arduino IoT Cloud for real-time remote monitoring via web dashboard and mobile application. Validation was performed using bovine urine samples compared against certified laboratory analysis. The proposed system offers a simple, reliable, and affordable solution for point-of-care uric acid monitoring.