Development of an Arduino-Based Photometer for Reactive Red 120 Dye Detection COVID-19 (Asean Journal of Engineering Education, 2024)
During the COVID-19 pandemic, traditional laboratory access was limited, prompting innovative approaches to education and research. An undergraduate chemistry student undertook the development of an Arduino-based photometer as a remote learning final year project. This project aimed to measure RR-120 dye concentrations in water using affordable and accessible technology, providing practical experience in photometry, electronics, and programming despite the constraints of the pandemic. The removal of Reactive Red 120 from water bodies is a significant environmental concern. The photometer, constructed using an Arduino UNO microcontroller, a green LED (500-570 nm), resistors, a plastic cuvette, and a BH1750FVI digital light intensity sensor module, is designed to be a cost-effective and user-friendly device for classroom and laboratory use. The device's operation is controlled via Arduino IDE 1.8.19 software, providing hands-on experience with programming and electronics. Calibration with seven RR-120 solutions (0.2 to 1.4 mg/L) produced an R² value of 0.9823, with a detection limit of 0.47 mg/L. The photometer achieved 98.66% accuracy demonstrating its reliability. Performance comparison with a commercial benchtop UV-Visible spectrophotometer (R² = 0.9956) further demonstrates the photometer’s reliability. This Arduino-based photometer not only offers a practical application for teaching principles of photometry and spectroscopy but also illustrates the integration of affordable technology in scientific education, enhancing student engagement and learning in STEM fields during challenging times. Most importantly, this device also provided hands-on experience in photometry, enhancing remote learning during restricted lab access. The device’s scalability suggests potential applications in broader environmental monitoring and educational settings, beyond the initial scope of dye detection.
Keywords: Arduino; Photometer; COVID-19 Remote Learning; Home-built; dye; Reactive Red 120