Smart Milk Grading System for Quality Assessment and Adulteration Detection using IoT

Ensuring the consumption of high-quality milk is particularly crucial for infants, especially in environments plagued by pollution. This paper introduces the Smart Milk Grading System (SMGS), an innovative IoT-based approach employing machine learning algorithms to accurately assess milk quality and tackle adulteration issues. The system incorporates an advanced liquid quality analyzer powered by Arduino, which effectively detects milk adulteration by monitoring key parameters such as pH, temperature, humidity, total dissolved solids (TDS), and gas levels. The collected data is then analyzed using six different machine learning classification algorithms. Notably, the Random Forest Classifier demonstrates exceptional accuracy in identifying milk adulteration, making it the most effective among the algorithms tested.