Web based IoT System for Monitoring and Visualizing Qualitative and Quantitative Data of River

Abstract

Rapid urbanization, industrial effluents, agricultural runoff, and climate variability have increasingly degraded river water quality and disrupted natural flow patterns. Traditional monitoring methods—based on manual sampling and lab analysis—lack real-time capability and scalability. This study presents a real-time river monitoring system built on an Internet of Things (IoT) architecture using a Raspberry Pi microcontroller. The system connects to environmental sensors (pH, turbidity, temperature, dissolved oxygen, and flow rate) for on-site data acquisition and processing. Sensor data is transmitted to the ThingSpeak cloud platform, enabling remote access and real-time visualization via interactive dashboards. Optional GIS and satellite integration enhance geospatial insights. The system offers a reliable, cost-effective, and scalable solution for continuous monitoring, early pollution detection, and informed water resource management—providing a practical alternative to conventional methods for sustained environmental oversight.