Development of autonomous unmanned aerial vehicles based decision-making system for smart fruit growing

Project total budget: 299,999.70 EUR

Project funding source: Ministry of Education and Science, Latvian Science Council

Project number: lzp-2021/1-0134

Project manager/coordinator:

Project goal: to develop an autonomous UAV-based decision-making system for smart fruit farming, which will enable automatic crop yield prediction and the recognition of apple scab symptoms by conducting autonomous orchard inspections using UAVs capable of identifying flowers, fruits, and assessing their quantity, as well as detecting apple scab.

Planned activities and results:

• Develop mathematical models for tree canopy pollination and photography;
• Develop an artificial intelligence solution capable of flower and fruit identification and quantitative assessment using photographs;
• Develop a prototype for testing the invented solutions. The AI tool for crop yield assessment and forecasting will be developed using obtained datasets and the latest deep machine learning solutions.

Expected project results:

• A validated dataset of apple, pear, and sweet cherry fruit and flower images at various developmental stages, supplemented with manual evaluation data;
• An AI module for flower and fruit assessment in the tree;
• A prototype of an autonomous system for smart fruit farming.

Project consortium:

Lead partner:  Rezekne Academy of Technology, Institute of Engineering Sciences;

Collaborating partner: Latvia University of Agriculture, Institute of Horticulture;

Project manager: RTA researcher I. Zarembo;

Project coordinator: G. Lācis

Project researchers and scientific assistants: S. Kodors, L. Litavniece, I. Zarembo, V. Bikovs

Project accountant: Ē. Backāne