Smart Farming Experiment: IoT-Enhanced Greenhouse Design for Rice Cultivation with Foliar and Soil Fertilization

This study presents the development and implementation of an IoT-enabled smart green-house system designed not only for rice cultivation but specifically as a controlled exper-imental platform for evaluating fertilizer application methods. Traditional greenhouse rice farming faces persistent challenges such as unpredictable weather, pest infestations, and inefficient resource use. To address these limitations, a smart farming greenhouse system was developed to optimize environmental conditions and enable precise moni-toring and control. The system successfully tracked temperature, humidity, and sunlight intensity via the Thingsboard IoT platform, providing real-time data and analytical capa-bilities. The cultivation process included preparation of Inceptisol soil, slurrying, fertiliza-tion, seeding, transplantation, and continuous monitoring. A key novelty of this system lies in its design as a comparative testing platform: with automated temperature control and humidity regulation, the greenhouse enables parallel experimentation under identical environmental conditions. This allows for rigorous evaluation of nano-silica fertilizer ap-plied via root (soil) and foliar (leaf) methods. The system moves beyond simulation, offer-ing a valid and replicable framework for experimental agronomy. The potential to connect this platform with machine learning models opens new avenues for forecasting plant re-sponses based on historical data. Overall, this study demonstrates how advanced tech-nology can be leveraged to enhance agricultural precision, sustainability, and experi-mental reliability