Artificial Intelligence (AI) is increasingly utilized in agriculture for a variety of uses, from plant disease detection to weeding automation, soil status monitoring, crop prediction, irrigation management, and decreased resource utilization for improving quality and productivity. This Thematic Session welcomes contributions related to a wide range of interdisciplinary research and applications related to the application of intelligence systems in agriculture. AI can, in fact, provide highly positive effects on precision agriculture by optimizing, automating, and forecasting several aspects of farming, thereby revolutionizing the sector and providing helpful information and driving decisions using multiple sources of data and different sensors.
Moreover, in the climate change era, AI can improve sustainability by optimizing resources such as water and soil management, as well as fostering novel methods and approaches.
We welcome innovative contributions, early results, and position papers addressing one or more of the topics listed below. We aim to foster informal discussions and bring together researchers, practitioners, and industry experts to explore the challenges and opportunities of intelligence systems in agriculture.
We look forward to receiving your submissions and seeing you at the thematic session!

Topics

Papers related to theories, methodologies, and applications in science and technology in the field of AI in Agriculture are especially solicited. Topics covering academic research, applications, and lessons learnt are included, but not limited to:


• Computer vision in agriculture
• Signal and image processing in agriculture
• Computational intelligence in agriculture
• Generative AI for Agriculture
• Intelligence systems and decision support in agriculture
• Expert systems & predictive systems
• LLM for AKIS (Agriculture Knowledge Information System)
• AI-based precision agriculture
• Machine learning and pattern recognition
• Federated AI for Agriculture
• IoT, Edge efficient AI & Low-Connectivity ML in agriculture
• Biosecurity & surveillance AI
• Food and livestock management
• Big data
• Water Management
• Remote sensing
• Phenotyping & Genomics
• Uncrewed aerial vehicle vehicles
• Autonomous driving in agriculture
• Geospatial AI in agricultural
• Harvesting automation
• Robotics and robotic perception in agriculture
• Digital twins for agriculture
• Data space for agriculture
• AI for biodiversity and sustainable agroecology
• Ethics and social impact of AI on agriculture
• AI-based crowd-sensing and participatory approaches in agriculture


Thematic Session organizers

• Martinelli Massimo, Institute of Information Science and Technologies, National Research Council of Italy, Pisa, Italy
• Moroni Davide, Institute of Information Science and Technologies, National Research Council of Italy, Pisa, Italy
• Procházka Ales, University of Chemistry and Technology & Czech Technical University CIIRC, Prague, Czech Republic
• Charvat Karel, Czech Center for Science and Society, Prague, Czech Republic


Contact: agriai@fedcsis.org



Program Committee ( updating )

• Bacco Manlio, Joint Research Centre, Varese Italy, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
• Barsocchi Paolo, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
• Christopher Brewster, Data Science Dept., TNO, Soesterberg, Netherlands
• Gajinov Senka, DunavNET, University of Donja Gorica, Novi Sad, Serbia
• Pereira de Figueiredo Felipe Augusto, National Institute of Telecommunications, Santa Rita do Sapucaí, Brazil
• Ienco Dino, Territories, Environment, Remote Sensing and Spatial Information, Montpellier, France
• Kosmopoulos Dimitrios, Computer Engineering and Informatics Department, University of Patras, Greece
• Krco Srdjan, DunavNET, University of Donja Gorica, Novi Sad, Serbia
• Loukatos Dimitrios, Agricultural University of Athens, Greece
• Majdik András, Lászlóm, Institute for Computer Science and Control, Budapest, Hungary
• Mildorf Tomas, University of West Bohemia, Pilsen, Czech Republic
• N.N. Misra, Taif University, Saudi Arabia
• Petrovic Veljko, Faculty of Technical Sciences, University of Novi Sad, Serbia
• Peña Barragán José Manuel, Institute of Agricultural Sciences, CSIC, Madrid, Spain
• Rabbani Kashif , Digital Catapult, London, United Kingdom
• Salvetti Ovidio, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
• Scozzari Andrea, Institute of Information Science and Technologies, National Research Council, Pisa, Italy
• Silvestri Nicola, Department of Agricultural, Food and Agro-environmental Sciences, University of Pisa, Italy
• Szczuka Marcin, Institute of Informatics, The University of Warsaw
• Trocan Maria, Institute of Digital Technology, Paris, France
• Zacepins Aleksejs, Faculty of Information Technologies, University of Life Sciences and Technologies, Jelgava, Latvia