nodata

The current growing need to have sustainable food production requires the application of smart technologies in agriculture. Smart greenhouses are a feasible solution as they facilitate accurate manipulation of environmental cues to optimize crop productivity and resource use. In this paper, we describe the design and evaluation of a smart green-house system with sensors and actuators that control and monitor the vital variables, such as temperature, humidity, soil moisture, and NPK level. The main purpose of this work is to develop a data-driven approach for real-time environmental monitoring and predictive control based on machine learning models. A dataset of 37,922 samples was gathered through the implemented smart greenhouse