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Intelligent climate optimization with and for horticulturists (Klimop-AI)

In the KlimOp project, techniques from artificial intelligence (AI) are used to give Flemish horticulturists a better insight into their greenhouse climate and thus improve climate control. For this, data from the climate computer is analyzed and combined with plant insights obtained via plant sensors. This project focuses on heated crops, including tomato, lettuce, pepper and strawberry, but the results will also be applied to other crops.
 This is a four-year LA trajectory that starts on September 1, 2021. This project is being carried out by two partners. The Energy Knowledge Center of Thomas More University of Applied Sciences is responsible for the climate-technical part and the Laboratory for Plant Ecology of the Faculty of Bioscience Engineering, Ghent University will work out the interaction between climate and plant and the communication with the plant via plant sensors. The project is followed up by an extensive guidance group, consisting of 11 growers, 8 suppliers and cultivation advisors and 7 research centers.
Improving the climate control in the conservatory
AI will provide new insights into greenhouse climate control. This will help the individual grower to detect climatic irregularities and answer decision questions to adjust the control technology of the greenhouse. This leads to better planting conditions, energy savings and emission reductions.
The project will start with company-specific analyzes together with 24 individual horticulturists. In addition to improving climate control, these analyzes will demonstrate the possibilities of AI techniques, whether or not supplemented with additional plant measurements. If necessary, additional experiments will also be set up in the new climate chambers at Thomas More.
 The generic advice obtained from these individual analyzes will also be made accessible to the broad group of horticulturists. Horticulturalists who do not actively use their climate data themselves will also be able to use the project results in this way.
Date:1 Sep 2021 →  Today
Keywords:greenhouse horticulture, climat control, AI, machine learning, plant sensors
Disciplines:Energy in buildings and built environments
Project type:Collaboration project