IoT-based system to consolidate indoor environmental control systems with real-time data from microclimate sensors in a scale model greenhouse

Samer, Mohamed; Amer, Mariam A.; Helmya, Haytham S

doi:10.21608/agro.2025.339656.1572

IoT-based system to consolidate indoor environmental control systems with real-time data from microclimate sensors in a scale model greenhouse

Document Type : Original Article

Authors

¹ Department of Agricultural Engineering, Faculty of Agriculture, Cairo University.

² Agricultural engineering research institute

³ Department of Agricultural Engineering, Faculty of Agriculture, Cairo University

10.21608/agro.2025.339656.1572

Abstract

The present research utilized a wireless smart prototype greenhouse monitoring and control system that is cost-effective, flexible, and easily maintained and assembled. This research project's main goal was to develop, assemble, and test a microcontroller-based prototype that would use sensors and the Blynk IoT application to monitor and regulate greenhouse parameters. The prototype included several devices of hardware such as a digital humidity and temperature sensor, a light-dependent resistor sensor, and a soil moisture sensor. In addition, a NodeMCU microcontroller, an LCD module, and a 5 volt 1 channel relay module. When the environmental factors fall below the threshold value, the Soil Moisture Sensor, Humidity and Temperature Sensor, and Light Dependent Resistor work together to control the pump triggering, fan activation, and lighting respectively. Additionally, two NodeMCU development boards' WiFi capabilities enable IoT to be used to process and store data, forward it to the end user's web application for environmental parameter monitoring in the greenhouse, and store the data in a database. The sensor's digitalized readings are continuously monitored by the microcontroller, which compares them to the optimized values to determine whether any control actions are required. The Internet-based smart greenhouse system offers a workable way to boost efficient resource management, lessen manual intervention, and improve agricultural productivity.

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