This research project aims to tackle challenges related to greenhouse climate control by developing a smart and efficient AI-based control framework for greenhouse climate that minimizes costs while maintaining a suitable greenhouse climate for crop growth. In addition, this research will optimize use of resources such as energy and water which are of critical importance, particularly in the era of climate change, further highlighting the importance of efficient greenhouse climate control.
Controlled environmental agriculture (CEA) is a technology-based approach to sustainable food production using facilities like semi-closed greenhouses and exhibits advantages in terms of a potential higher productivity and quality, as well as robustness to external climatic conditions. CEA has been considered as a popular approach to food production at locations with harsh climate condition, in Space Farming and Urban Agriculture, and for the emerging portable plant factories within shipping containers. While the availability of skilled growers capable of managing high-tech greenhouses remains scarce, the increasing adoption of advanced Digital Tools enables the development of automatic and efficient operations in high-tech greenhouses to further improve the productivity and reduce the cost. This project aims to address technological challenges by integrating artificial intelligence (AI), sensing, mobile robots, and Internet of Things (IoT) tools and methods to develop a state-of-the-art digital platform for autonomous greenhouse to address an emerging and important problem that has the potential of paving the way of future farming practices that could be resilient to the climate, location, and space constraints.
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