Abstract: Digital experimentation proves advantageous for chemical education due to its capabilities in convenient data acquisition, visualization, and intelligent processing. The indirect iodometric determination of copper content requires precise identification of three critical color transitions: the light yellow endpoint after adding starch indicator, the light blue transition after KSCN addition, and the final off-white titration endpoint. Through extensive experimentation, we established a comprehensive database to determine HSV (Hue-Saturation-Value) color thresholds for these key transitions and developed a supporting titration application. The digitally enhanced method demonstrated a relative average deviation of 0.11%, significantly improving measurement precision compared to visual observation while stimulating students’ interdisciplinary research interests.

Key words: Indirect iodometric method, Copper content, HSV color recognition, Experiment digitization