In this project, we plan to develop an M2M-based automated greenhouse monitoring system for boosting the productivity of growing orchids. Orchid greenhouse is chosen to be the monitoring target due to following reasons.
Smart services –
(1) Pest monitoring and control – Bemisia tabaci (Gennadius), as known as Silverleaf Whitefly, is one of the major insects that could cause severe damage to the plants inside greenhouses. We plan to integrate cameras to observe the population size of Silverleaf Whitefly inside and outside the greenhouse. Modeling the population dynamics of Silverleaf Whitefly is of interest of the greenhouse owners. To understand better about the dynamics of pest population, we will deploy a camera and a monitoring station outside of the greenhouse. The camera is to observe the number of pest in outdoor environment, and the monitoring station is to record ambient conditions (temperature, humidity, light intensity, rainfall, etc.) These data will be used to uncover the dynamics of pest population outside of the greenhouse. Cameras will be used inside the greenhouse to monitor the distribution changes of pest, and also to analyze the correlation between pest populations inside and outside of the greenhouse. The model of the pest dynamics can serve as a reference for greenhouse owners to know when they have to pay extra care about their plants inside the greenhouse.
(2) Plant growth condition inspection & yield prediction – We also plan to install cameras at certain positions to observe the growth condition of the plant. Morphology and eco- physiological analysis method will be developed to screen the growth condition of every single plant on the plant tray. With this information, we can also help the greenhouse owner to predict seasonal yield of their product. Also, we will also use regular visible light cameras to analyze the morphological traits of the orchid leaves. By integrating this technology with the growth condition records, we can also find out the best indoor condition to cultivate the best quality 40 of plants. We can use this information to predict the seasonal yields of the greenhouse.