Development of an IoT-based multi-level system for real-time water quality monitoring in industrial wastewater

Abstract

Abstract Industrialization and urbanization contribute significantly to environmental pollution, particularly in water bodies. The consequences of this pollution are dire, impacting both the environment and public health. A serious hazard to life on Earth, contaminated water can cause food poisoning, diarrhea, respiratory diseases, and skin ailments, among other health problems. In countries like Bangladesh, where industrial activities, particularly in the garment sector, are prevalent, waste dumping into rivers and canals has reached alarming levels. This has resulted in a drastic decline in water quality, endangering aquatic life and ecosystems. To solve this important issue, we built an innovative real-time water quality monitoring system using the Internet of Things (IoT). Our system operates at three levels, collecting data from different layers of wastewater. Key parameters, including temperature, turbidity, total dissolved solids (TDS), and pH, are continuously monitored to assess water quality. The analysis revealed that wastewater temperature varied between 25 and 37 °C across different sites, with higher temperatures observed in industrial zones, indicating potential thermal pollution. Total dissolved solids (TDS) levels exhibited substantial variations, ranging from 170 to 360 ppm, surpassing standard thresholds and posing a threat to aquatic ecosystems. Turbidity readings ranged from 1.30 to 12.89 NTU, with higher turbidity observed in areas receiving industrial discharge, highlighting the impact of suspended solids on water clarity. pH values exceeded 7.0 across all sites, ranging from 9.5 to 10.32, indicating alkaline wastewater, particularly in regions with dyeing and textile industries. By integrating these specific metrics into our monitoring system, we provide valuable insights into industrial wastewater quality and its environmental implications. These findings underscore the urgent need for real-time monitoring and targeted interventions to address water pollution. Implementing sustainable water management strategies in industrial contexts is critical to protecting public health and preserving ecosystems for future generations.

Keywords

• IoT
• Arduino UNO
• pH sensor
• TDS
• Turbidity
• LM-35 water temperature sensor