Low-Cost Arduino-Based Multi-Parameter Detection of Milk Adulteration

Milk is one of the most nutritionally vital and widely consumed food products globally, making it a frequent target of adulteration. Common adulterants , water (to increase volume), starch (to restore viscosity after dilution), and detergent (to create artificial foam) pose serious public health risks including nutritional deficiency and acute gastrointestinal disease. This paper reviews existing methods for milk adulteration detection and proposes a low-cost Arduino Uno-based multi-parameter monitoring system that simultaneously measures pH, Total Dissolved Solids (TDS), and Electrical Conductivity (EC) to classify milk quality in real time. The proposed system uses a combined decision logic framework calibrated against physiologically and chemically established reference thresholds. Results are displayed on a 16×2 LCD I2C module and streamed to a Serial Monitor dashboard. The learning model, making it ideal for interdisciplinary B.Tech education integrating electronics, analytical chemistry, and biomedical instrumentation. Controlled experiments with four sample types water, water+starch, pure milk, and milk+detergent achieved 100% classification accuracy. The novelty lies in the combination of sensing modalities, rule-based combined detection logic, that bridges food safety, sensor physics, and electronics engineering.