Pervasive agriculture: Measuring and predicting plant growth using statistics and 2D/3D imaging

The growing of Earth population and the need of food provisioning to remote areas make pervasive agriculture the research problem of high priority. In this work, we present a 2D/3D scanning system with the intelligent data processing mechanism which can be easily deployed in a greenhouse. The proposed solution enables finding of correlations between the leaf area and biomass and thereby helps predict the plant metrics including the growth rate and leaf area. This knowledge is of particular significance for actuating the plant growth parameters depending on the context and feedback. Our experimental results conducted on two sorts of tomatoes and salad demonstrate high potential of this approach.