Development of Internet of Things Based Environmental Monitoring Systems for Real Time Data Acquisition and Analysis

Abstract

The lack of real-time analysis and monitoring systems, combined with environmental degradation and pollution, poses serious challenges to environmentally sustainable management. Outdated monitoring systems/technology have high costs and slow, limited data collection and reporting. An IoT-based environmental monitoring system aims to expedite environmental evaluations and informed decision-making through real-time data collection and analysis. The environmental assessment of the proposed system includes temperature, humidity, and air quality sensors, an ESP32 microcontroller, and a cloud-based service for continuous monitoring and data availability. The framework was tested for 7 days, capturing 10,000+ data points. The framework achieved a data-capture accuracy of 95.6% compared to stand-alone reference devices, provided sub-2-second latency for a complete data-capture cycle, and achieved a capture reliability of 98.2%. Compared with current systems, the proposed framework reduced power consumption during the continuous environmental data capture cycle by 30%. The data capture cycle provided an assessment of environmental temperature at 24-36 °C and humidity variability at 45-78%. The framework successfully captured open-loop and time-variant environmental data. To evaluate the environmental capacity for, and the necessary management of, site pollution control to meet the needs of a smart city, the framework is a flexible, high-response, real-time, and economical data-collection system. The proposed framework is also scalable and can be expanded to accommodate predictive analytics for even larger time-variant and dynamic data collection systems. The capture of plenty of data in the proposed and production-ready system supports the framework.