University of Padova, Italy
Institute of BioEconomy
National Research Council, Italy
Poznań University of Life Sciences, Poland
Over the last few years, the advent of digital agriculture exponentially increased the amount of data per hectare produced by agricultural activities due to the availability of several sensors. According to this, the demand for efficient, fast, and smart data processing is rising. Artificial Intelligence (AI) and advanced statistical methods make it possible to collect and analyse a large amount of agricultural data (in some cases classified as Big Data), which might help improve the sustainable intensification of crop and food production. In 2020, the European Commission released a white paper on AI, addressing the development and the application of these methods in all research fields. AI and advanced statistical methods can be used for the analysis of both proximal and remote images (e.g. drones and satellites), data provided by sensors networks and IoT tools.
This session highlights the potential application of AI and related techniques (ML, DL, CNN, supervised and unsupervised learning) to develop agriculture and food application such as crop models, DSS, biotic and abiotic stress early detection and yield features estimation.
Topics include, but are not limited to:
- Image analysis;
- Classification, object detection and semantic segmentation;
- Statistical analysis of IoT data;
- Wireless sensor networks;
- Data analysis for agriculture and food monitoring;
- Integration of data for models and decision support system.