IoT-Enabled Environmental Monitoring for Water and Air Quality: System Design, Field Deployment, and Data Analytics

Abstract

Continuous monitoring of water and air quality is essential for the timely detection of environmental degradation and for protecting public health. This paper presents the design, field deployment and data-analytics framework of an Internet of Things (IoT) environmental monitoring network that simultaneously measures key water-quality parameters (temperature, pH, dissolved oxygen, turbidity and electrical conductivity) and airborne particulate matter (PM2.5 and PM10) across three water and three air monitoring sites. Six low-power wireless sensing nodes were deployed for a combined study period of 90 to 120 days, transmitting data to a cloud platform through a LoRaWAN and 4G uplink. The results show that the network achieved a mean packet-delivery rate above 94 percent, with good temporal coverage of the targeted parameters. Water-quality measurements remained within typical freshwater ranges for most of the deployment, although episodic turbidity spikes were observed after rainfall. Air-quality measurements revealed that daily mean PM2.5 and PM10 concentrations frequently exceeded the 2021 World Health Organization air quality guideline values. A field inter-comparison between the low-cost particulate-matter sensors and a reference monitor produced a coefficient of determination of 0.87 for hourly PM2.5, confirming adequate performance after a relative-humidity correction. The findings demonstrate that low-cost IoT systems can deliver operationally useful environmental intelligence and support evidence-based management decisions, provided that careful calibration, data-quality control and network maintenance are sustained.