Abstract:
Over the past twenty years, Kenya's food security has been threatened by the sub-division of land into tiny areas and the
clearance of forests to make way for settlement. These actions have an impact on soil moisture, rainfall patterns, and regional
temperature changes. Clear response plans and adaption techniques have been required to address the threats that have arisen.
Greenhouse farming, where warmer temperatures are attained and the impact of unfavourable weather conditions on plants is
mitigated by the enclosure, is one strategy being used to combat the production of food and climate change. Nevertheless, crop
production and quality are negatively impacted by traditional techniques of regulating temperature and humidity through
arbitrary opening and closing of the greenhouse walls. In light of this, the goal of this research was to enhance greenhouse
farming as it exists today by implementing a dynamic, adjustable system that would create ideal climate conditions for plant
growth. This mostly entailed controlling the greenhouse's humidity, temperature, and vapour pressure deficit to the ideal ranges
needed by various plants. The humidity and air temperature within the greenhouse were the controlled microclimate
conditions. These were accomplished by simulating the convectional heat transfer and mass transfer that occur inside the
greenhouse to control the temperature and humidity, and by developing mathematical model utilizing differential equations.
Proportional Integral Derivative (PID) was utilized to automatically modify SIMULINK, a block-based modelling and
simulation tool. Regardless of the different external conditions, the numerical values for internal temperature and humidity
were calculated and graphically depicted. The model made it possible to modify the outcomes according to the needs of the
plant. To increase crop productivity in greenhouse farming, it was suggested that a physical prototype model be constructed
and integrated into the greenhouse construction
