Numerical Modeling and Thermal Analysis of an Energy‐Efficient Smart Greenhouse

The majority of today's farming challenges cannot be addressed by traditional farming methods, which is why it is critical to develop an affordable, energy‐efficient system that can increase agricultural productivity, operate in a monitored environment, and handle a variety of challenges related to climate, pests, and other issues. Using greenhouses is one possible way to achieve most of these. Previous studies on greenhouse have not carried out a smart climate conditions monitoring and prediction approach with a mathematical modeling technique for optimized and best system designs and operations. This study aims to address this by using sensors to control the climate in a way that is adaptable to various crops and numerical modeling of an optimized greenhouse system. To achieve this, humidity and optical sensors were integrated into the system to regulate the ambient conditions effectively. Results show a direct correlation between solar radiation and temperature. The imposed peak solar radiation and ambient temperature values of 1100 W/m 2 and 37.3°C were used for the input variables. For over a 72‐h period, the temperature absorbed inside the glass (59°C) was observed to be higher than that of the room (38°C) with their respective peak accumulated energy values of 119 and 92 kJ for glazing and smart room, respectively. The peak thermal efficiencies recorded during mid‐day for the glazing and the smart rooms were 68% and 47%, respectively.