ALG-SDE: Developing an Arduino-Based System for Automated Algae Detection and Algaecide Treatment

Harmful algal blooms (HABs) present ecological and public health threats in freshwater systems in the Philippines. Despite attempts of traditional mitigation techniques, they are limited by manual monitoring and treatment delays. Which is why there is a need for automated systems that provide real-time intervention. This study developed and evaluated ALG-SDE, an Arduino-based prototype using pH, temperature, and turbidity sensors to detect and respond to algae conditions via algaecide dispensing. Results showed statistically significant reductions in pH (t = 39.28, p = 0.00065) and turbidity (t = 9.45, p= 0.011), with a strong inverse correlation (r = -0.87) between the two. Chi-square tests confirmed threshold-based activation inconsistencies (p = 0.038), suggesting sensor recalibration is needed. In conclusion, the system effectively alters algae-conducive conditions but requires improved reliability in real-time activation as well as mobility. Further iterations should focus on enhanced sensor accuracy, mobility features, and broader aquatic applicability.