Smart System Approach for Prediction of Microbial Quality of Milk Using Machine Learning

Developing a real-time system to assess milk quality using Resazurin dye and machine learning. The system combines an Arduino Uno, color sensor, and LCD display to detect color changes in milk samples. These changes indicate microbial activity and quality. By integrating Python and machine learning algorithms, the system processes and analyzes data, providing accurate and immediate milk quality assessments. This automated solution enhances efficiency and reliability, reducing the need for manual inspections and improving overall dairy quality control.The system's ability to deliver accurate, real-time information underscores its potential for impactful use in scientific and industrial settings, highlighting its significance in the field of chemical analysis.