Evaluation of Smart Greenhouse Monitoring System using Raspberry-Pi Microcontroller for the Production of Tomato Crop

Abstract

To provide fresh and highly nutritive food, automated greenhouses and smart farming systems had proved to be helpful for growing world population. The smart greenhouse house monitoring system not only helpful in exploiting the production but also helpful to bridge up the quality of the produce. The current study was designed to explore the potential use of a smart greenhouse monitoring system using Raspberry-Pi microcontroller. The aim of the study was to create a smart automation system to control the microclimate of greenhouse. Two varieties of tomato (Roma and cherry tomato) were used both in smart greenhouse system as well as in conventional greenhouse system to compare the agronomic and quality parameters. Temperature and humidity were set according to the production technology of tomato using automation system. Proper fertilization and irrigation requirements were considered equal in all aspects in smart greenhouse and conventional greenhouse. The smart greenhouse monitoring system worked better in maintaining the microclimate inside the greenhouse with a difference of about 5-6 ℃ temperature and 20-30% humidity higher than the conventional greenhouse. The results predicted a progressive increase in agronomic parameter with a difference of 10-15% in plant height, number of leaves, number of fruits and weight of fruit as compared with growth parameters in conventional greenhouse. Similarly the quality parameters were effective with maximum size of fruit in Roma variety that was 75 mm as compared to fruit size 65 mm in conventional farming. The over average yield of tomato per plant (5.5 kg/plant) was also recorded in smart greenhouse that was significantly increased as compared with conventional greenhouse. The results predicted that the yield of tomato was positively affected using smart greenhouse monitoring system and consequently, the smart technologies could be used for the potential crop production and monitoring of cultivation activities.