Real time monitoring of microclimatic parameters of polyhouse using IOT embeeded sensor system

Abstract

In the light of increasing global challenges such as climate change, rapid urbanization, and the growing demand for food due to population rise, there is an urgent need to implement sustainable and efficient agricultural practices. One promising solution is the application of smart farming technologies that utilize realtime data for decision-making. This project, conducted at KCAEFT, Tavanur between January and May 2025, focuses on the development and deployment of a real-time microclimate monitoring system inside a polyhouse using IoT-embedded sensor technologies. The system is built around a microcontroller-based architecture with ESP32 modules, enabling wireless communication and real-time data visualization. Multiple environmental parameters critical for crop production—such as air temperature, relative humidity, soil temperature, light intensity, and wind speed—were continuously monitored using a network of strategically placed sensors. Data collected was transmitted to an integrated cloud platform, allowing for remote access and timely insights without manual supervision. To ensure accuracy and reliability, sensor calibration was carried out through comparative analysis with standard instruments and digital weather applications such as Wind Compass Pro and Zoom Earth. Though some sensors (e.g., anemometer, soil temperature, and BH1750 light sensor) initially showed minor deviations of recorded data from their true values, the calibration process yielded highly satisfactory results, as reflected by high R² values, validating their performance. A well-planned wiring layout ensured minimal energy usage and cost-efficiency, with total wire requirements of 842 meters per module. Visualization tools and analytics helped track trends in microclimatic variations, enabling precise climate monitoring. This project demonstrates a scalable, low-cost, and energy-efficient solution for real-time microclimatic monitoring of polyhouse environments. It provides a robust foundation for future automation, paving the way for smart farming systems that optimize resource usage, reduce labour dependency, and enhance productivity through precision agriculture practices