To ensure the feasibility and the success of the project in and in the proximity of smart cities, the project implies 4 main scientific objectives (SO):
- SO1 consists in developing a computer-vision ultra-precise plant classification capabilities, integrated into the ground robotic module. Corresponding KPI include ultra-precise data characterizing individual plants in a greenhouse throughout an extended growth phase, achieving a minimum 10% precision enhancement compared to the literature baseline.
- SO2 refers to the development and incorporation of a ground robotic module with a mobile soil analysis toolkit for in-situ on-board measurements of soil suitability, nutrients, moisture, and minerals, considering individual plant locations. KPI is a location-specific soil characterization data, conveying a rich set of information on soil conditions.
- SO3 implies the develop a ground robotic module with a plant-level multispectral image analysis feature, allowing precise spatial-temporal characterization of individual plants and fruits. Testing and previous developments in SO1 and SO2 are used in this step. Performance indicators refer to characterization at plant and fruit level to provide specifics in terms of leaf-area-ratio, leaf-fruit-ratio, covering area, and canopy density.
- SO4 considers the built-up of a robotic platform with seamless integration of computer vision and multispectral sensing capabilities, capable of transmitting data to the central command and control center for aggregation by the digital platform. The autonomous robotic platform is designed for deployment in greenhouses.
- SO5 refers to development of the digital platform with robot interaction, data management, and analysis built on open standards (establishing middleware for seamless interoperability and integration of all data sources). Resources developed in SO1- SO4 will be optimized and outdoor tested.