Assessing Oxygen Dynamics in Eutrophic Waters: A Review of IoT Sensor Applications

Eutrophication, caused by excessive nutrient accumulation, leads to oxygen depletion and water quality degradation in aquatic ecosystems. Core indicators such as dissolved oxygen (DO), biological oxygen demand (BOD), and chemical oxygen demand (COD) are critical to assessing eutrophic conditions. Advances in Internet of Things (IoT) and artificial intelligence (AI) have enabled real-time water quality monitoring, but practical implementations remain limited, especially in low-resource settings. This systematic review analyzed 28 peer-reviewed studies (2015–2025) selected via PRISMA guidelines from Scopus, Google Scholar, and Web of Science. Sensor performance, AI integration, and deployment challenges were assessed. In parallel, a novel low-cost IoT-based circuit using ESP32 and open-source platforms (Blynk, Arduino IDE) was constructed and field-tested to demonstrate feasibility of real-time multi-parameter monitoring in the absence of DO-specific sensors. Optical DO sensors showed the highest accuracy (90–96%), with BOD and COD sensors achieving moderate performance (78% and 75–82%, respectively). Predictive forecasting for DO using AI achieved an R² = 0.85. Practical testing of the prototype showed reliable readings for pH, temperature, turbidity, and TDS, with effective real-time data visualization via mobile and cloud dashboards. Despite budgetary constraints, the circuit demonstrated adaptability and scalability for future DO integration. IoT-based monitoring systems are effective for managing eutrophication, with significant accuracy gains through AI-enhanced analytics. The prototype system developed in this study represents a novel, scalable solution for water quality monitoring in resource-constrained contexts. Its low-cost architecture, real-time capabilities, and cloud connectivity offer a practical pathway for broader adoption of smart environmental sensing technologies. Future work should incorporate nano-coated DO sensors, hybrid cloud-local architectures, and extended deployment trials to enhance reliability and impact.