Abstract: Chemical oxygen demand (COD) serves as a crucial parameter for assessing organic pollution in water and represents a routine analytical requirement. Building upon the standard method HJ/T399-2007 (“Water Quality-Determination of Chemical Oxygen Demand-Rapid Digestion Spectrophotometric Method”), this study innovatively developed a smartphone-based real-time visual detection system for COD analysis. The system utilizes smartphone color recognition to extract RGB values from digested water samples and establishes a ternary multiple regression model based on these values. A dedicated WeChat mini-program was developed to enable online visualization and analysis of COD, facilitating rapid on-site measurement of multiple water samples. This approach demonstrates advantages including operational simplicity, cost-effectiveness, and rapid analysis. Educational practice has shown that this technology not only finds application in environmental monitoring but also effectively enhances analytical chemistry pedagogy. It promotes outdoor teaching activities for undergraduates, stimulates students’ interest in chemistry, fosters scientific thinking and innovation awareness, and cultivates rigorous scientific attitudes.

Key words: Chemical oxygen demand (COD), RGB value, Smartphone, WeChat mini-program development