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Radiation is a crucial factor in the field of agrivoltaics in greenhouses. Depending on the type of photovoltaics integrated into greenhouses, the effect on radiation varies through the phenomenon of shading. Shading in greenhouses can be either beneficial or detrimental, making its analysis imperative. In this study, the improvements and modifications made in an algorithm capable of calculating the shading from photovoltaic units installed in greenhouses are presented. A key modification to the algorithm is the calculation of shading from semi-transparent photovoltaic modules, in contrast to its original form, in which photovoltaic modules were considered opaque. The algorithm was validated using radiation data from pyranometers within a greenhouse. The coefficients used were Pearson's r correlation coefficient and the Coefficient of Variation. The correlation coefficients for times without shading effect approached the values for the case without photovoltaics installed on the roof. Simultaneously, based on the coefficients of variation, the uniformity of radiation within the shade was validated, thereby confirming its existence. Finally, the effect of semi-transparent photovoltaic units on Global Horizontal Irradiance and Photosynthetically Active Radiation was studied, with the reduction for the former approaching 52 % and about 60 % for the latter. These changes in radiation can be either beneficial or not, depending on the type of crop and the needs of the greenhouse, such as cooling.

This research aims to address the critical challenges caused by global population increase, climate change, and urbanization on food production by means of a Fuzzy Logic controller in a small-scale greenhouse and improving agricultural efficiency and sustainability.The growing global population has stressed the significance of implementing efficient food production techniques. Furthermore, the impact of climate change and extreme weather events complicates the production process. The goal of this study is to combine an innovative small greenhouse design with a fuzzy logic-based control system in order to develop an IoT-enabled self-regulating environment for autonomous plant growing.Continuous advances in technology have been focusing on automating greenhouses to provide self-regulating microclimates and optimal developmental conditions. Current trends focus on automating greenhouses to provide self-regulating microclimates. Looking ahead, the strategy entails combining automated approaches with precisely planned structures via IoT.This study's key findings include the successful integration of a fuzzy logic control system with greenhouse infrastructure, allowing for real-time monitoring and adjustment of environmental parameters, as well as the development of a pilot IoT ecosystem demonstrating the feasibility of self-regulating microclimates for improved plant growth.