Agri-food systems enabled by interconnected digital technologies that are more transparent to consumers, farmers and other stakeholders along the agri-food value chain.
The ability to single out healthy fruits/plants from those with problems and to selectively start the harvesting or apply a remedy without wasting resources or contaminating the environment is critical for precision farming. This project develops a unifying framework to combine different sensor modalities that include standard (e.g., RGB-D cameras) with novel sensors (e.g., gas sensors), methods for creating accurate maps to facilitate operations on a narrow scale with a smaller environment footprint, artificial intelligence algorithms for data processing and decision support, and applications to make relevant information easily visible to the farmer.
The application of fertilizers, pesticides and herbicides where and when needed will result in optimal amounts of inputs, applied, without losses. This will reduce the input cost in general. If the reduced input cost is accompanied by increased yields, then profitability is guaranteed. The proposed system will demonstrate the integration of robotics- and sensor technology into the digital agricultural workflow. This will allow farmers to share and use the data within the digital systems they have already in use and thus lead to a larger applicability of robotics technology in agriculture.
STAR will enable a fully automated ICT-based platform for fruit freshness assessment/health monitoring in vineyards. The data collected with both ‘innovative’ proximal and remote sensing technologies on fruit monitoring for disease will be recorded. A unique sensing system, dubbed GMOS, will be integrated onboard an autonomous farmer robot that detects concentration of gasses around the fruit providing important information about the health status.
Main project activities
- An autonomous farmer robot that monitors the health status of a vineyard row without any human supervision.
- Unique sensing system, dubbed GMOS, that selectively detects parts-per-billion concentration of gases to monitor the freshness level and reduce food waste throughout the supply chain.
- Gas emission analysis to enable closer monitoring of plant health, as well as, for yield mapping and forecasting.
- Multisensory data processed to extract relevant agronomic information from the crop.
- Decision support system for the generation of application maps for plant protection products.
- AI module for the decision support system.
Expected social impact
The STAR project will contribute to reach the United Nations Sustainable Development Goals SDG 3: Good Health and Well Being, SDG 8: Decent Work and Economic Growth, SDG 13: Climate Action.
The implemented system will demonstrate the integration of robotics- and sensor technology into the digital agricultural workflow. This will allow farmers to share and use the data within the digital systems they have already in use and thus lead to a larger applicability of robotics technology in agriculture.
The precise application of pesticides and herbicides during the cropping season is expected to reduce the amount of agrochemicals applied into the soil and ground and surface water resources, which will have a positive impact on the environment, with reference to the EU framework directive for “A thematic strategy on the sustainable use of pesticides” (COM(2006)372, COM(2006)778). The adoption of the unique sensing that selectively detects concentration of gasses around the fruit to monitor the freshness level will reduce food waste throughout the supply chain. It will promote transparency of information from the producers to the consumers.
Residues of pesticides and herbicides are considered to have a significant impact on food and feed safety. Securing clean of pesticides and herbicides will reduce the risk to human health, and lead to improving food safety. Furthermore, the technology developed in STAR will make robotics accessible to traditional farming environments, making farming more attractive for the young and tech-affine generation, and thus counteracting the emerging shortage of young, skilled workers.
- Precision agriculture
- Field robotics
- Crop monitoring
- Sensor fusion
- Robotic smell
Prof. Reina - Politecnico di Bari, POLIBA, Italy
- ISRAEL: Todos Technologies Ltd, Todos
- GERMANY: Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, FRA
Expected project start date and end date
The STAR project starts on May 2023 and runs until 2026.