An IoT-Enabled Smart System for Real-Time Environmental Monitoring and Automated Threshold-Based Irrigation for Water Stress Testing in Precision Agriculture

Abstract

Internet of Things is a major technology for improving agricultural practices and devel-oping intelligent research environments dedicated to biologists. Real-time monitoring of environmental parameters promotes efficient crop management and data-driven deci-sion-making. Nonetheless, the majority of existing IoT systems are limited to data visu-alization or alert generation, they rarely exploit the full potential of measurements for automation. In this context, this study proposes an intelligent system enabling not only real-time monitoring of environmental parameters but also automated irrigation man-agement through water stress scenarios defined by biologists in a controlled environment. Our system integrates an IoT measurement unit and a microservices-based web applica-tion for advanced management and analysis. The evaluation results after the deployment of a single unit in an agricultural field indicate that our IoT system provides measure-ments with effective stability, reflected by a low variance of 0.0721 for soil moisture, 0.0552 for soil temperature, 0.0081 for air temperature and 0.0023 for air humidity, and executes 50000 water stress scenarios in 872 ms without any error. These results highlight the system’s capability for data-driven automation, decision support and environmental sustainability in precision agriculture.