SPECIAL SESSION #09

Carlos Kamienski

Federal University of ABC (UFABC - Brazil)

• carlos.kamienski@ufabc.edu.br

Dener Silva

FEI University Center & Federal University of ABC (UFABC - Brazil)

• dener.siva@ufabc.edu.br

Lei Xue

Sun Yat-Sen University (China)

• xuelei3@mail.sysu.edu.cn

Marco Di Felice

University of Bologna - Italy

• marco.difelice3@unibo.it

Ronaldo Prati

Federal University of ABC (UFABC - Brazil)

• ronaldo.prati@ufabc.edu.br

The growing use of sensing technologies, Internet of Things (IoT) infrastructure, and Artificial Intelligence (AI) is driving a shift toward autonomous agriculture systems. In this context, AI agents are emerging as a key enabler for managing complex agricultural environments. These agents are intelligent software entities capable of perception, reasoning, learning, and autonomous decision-making. They help navigate uncertainty, variability, and resource constraints.

AI agents can coordinate heterogeneous sensing platforms. They orchestrate distributed devices across the computing continuum (device-edge–fog–cloud) and support adaptive decision processes for irrigation management, crop and soil monitoring, pest detection, and sustainability optimization. Integrating intelligent agents with metrology and measurement systems is essential. This integration ensures reliability, accuracy, trustworthiness, and reproducibility, which are fundamental requirements for real-world deployment in agriculture applications.

We invite researchers and practitioners to submit their original work to this special session on advances in autonomous agriculture enabled by AI agents, with a focus on intelligent sensing, measurement methodologies, distributed architectures, autonomous control, and experimental validation. Contributions addressing theoretical foundations, system architectures, field deployments, and interdisciplinary approaches are particularly encouraged, as we aim to foster impactful discussions and drive innovation in the field.

Topics include, but are not limited to:

• AI agents for agriculture systems;
• Multi-agent systems for distributed sensing and decision-making;
• Autonomous monitoring and control using intelligent agents;
• IoT architectures and computing continuum for agriculture;
• Intelligent measurement and metrology for autonomous agriculture systems;
• Agent-based irrigation and resource management;
• Digital twins and simulation environments with agent intelligence;
• Trustworthy, explainable, and reliable AI agents;
• Edge intelligence and embedded agents for IoT systems;
• Robotics and UAV coordination using intelligent agents;
• Generative AI and foundation models for agricultural agents;
• Interoperability, standards, and system integration;
• Experimental validation and real-world deployments;
• Performance evaluation and benchmarking of agent-based agriculture systems;
• Evaluation methodologies and benchmarks for measurement-driven autonomous agriculture.

Carlos Kamienski is a Full Professor of Computer Science at the Federal University of ABC (UFABC, Brazil). He was the Brazilian coordinator of SWAMP from 2017 to 2021, an EU-Brazil collaborative research project that developed IoT-based methods and approaches for smart water management in precision irrigation. From May 2023 to April 2024, he was a visiting scholar at the University of Bologna's IoT-Prism Lab. From January 2025 on, he is the Brazilian coordinator of the SMART (Sustainable Management of Agriculture with the Intelligent Computing Continuum), a collaborative project between Brazil and China that develops trustworthy platforms across using IoT and artificial intelligence in smart irrigation and fertilization to reduce water and fertilizer usage, thus contributing to sustainability goals and addressing the challenges of climate change. Prof. Kamienski served as Technical Program Co-Chair for MetriAgriFor 2020 and 2021, and as co-organizer of Special Session #6 (Smart Agriculture Metrology: Leveraging the Internet of Things and Artificial Intelligence) in MetroAgriFor 2025. His current research interests include the Internet of Things, artificial intelligence, and smart agriculture.

Dener Edson Ottolini Guedes da Silva holds a Ph.D. in Information Engineering from the Federal University of ABC (UFABC), Brazil. He is currently a postdoctoral researcher at the Centro Universitário FEI and a researcher on projects related to the Internet of Things (IoT), distributed computing, and intelligent infrastructure. He also serves as a technical specialist at UFABC, where he coordinates high-performance computing infrastructure and cloud environments. His research focuses on IoT architectures, computing continuum (cloud–fog–edge), smart cities, and artificial intelligence applied to distributed IoT systems. He has participated in several research projects, including SMART (Sustainable Management of Agriculture with the Intelligent Computing Continuum), COSMIC-SWAMP, and INCT initiatives on intelligent IoT networks. His research interests include Internet of Things, distributed systems, artificial intelligence, and smart agriculture platforms.

Lei Xue is a Professor in the School of Cyber Science and Technology at Sun Yat-sen University (SYSU). He received his Ph.D. in Computer Science from The Hong Kong Polytechnic University (PolyU). Before joining SYSU, he served as a Research Assistant Professor and Postdoctoral Research Fellow at PolyU. His research focuses on designing and implementing efficient, practical, smart connected systems. He has served on the program committees of various conferences, including NSS, CSS, SocialSec, SANER, CoNEXT, and CCS. He has reviewed for journals such as IEEE Transactions on Intelligent Transportation Systems (TITS), IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Mobile Computing (TMC), and IEEE Transactions on Multimedia (TMM). Prof. Xue served as co-organizer of Special Session #6 (Smart Agriculture Metrology: Leveraging the Internet of Things and Artificial Intelligence) in MetroAgriFor 2025.

Marco Di Felice received his Laurea and Ph.D. degrees in computer science from the University of Bologna in 2004 and 2008, respectively. He has held visiting research positions at the Georgia Institute of Technology and Northeastern University. Currently, he is a Full Professor of computer science at the University of Bologna and serves as the Co-Director of the IoT PRISM Laboratory. With over 150 papers published, his research focuses on wireless and mobile systems, including self-organizing networks, unmanned aerial systems, IoT, WoT, and context-aware computing. He has been recognized with three Best Paper Awards and is an Associate Editor for the IEEE Internet of Things Journal.

Ronaldo Cristiano Prati holds a Ph.D. in Computer Science and Computational Mathematics from the University of São Paulo (USP), Brazil, with a research period at the University of Bristol, United Kingdom. He is currently an Associate Professor at the Federal University of ABC (UFABC), Brazil, where he previously served as coordinator of the Graduate Program in Computer Science, leading the creation of both the Master’s and Ph.D. programs. He is also a CNPq Productivity Research Fellow. His research spans artificial intelligence, machine learning, and data mining, including the development of novel methods for imbalanced datasets, multi-label classification, and data streams, with applications across domains such as smart agriculture, computational science, and engineering. He has participated in several national and international research projects, including SWAMP (Smart Water Management Platform) and COSMIC-SWAMP, focusing on IoT-based smart irrigation and data-driven agricultural systems. His research interests include machine learning, artificial intelligence, data mining, and intelligent IoT-enabled applications. Prof. Prati served as co-organizer of Special Session #6 (Smart Agriculture Metrology: Leveraging the Internet of Things and Artificial Intelligence) in MetroAgriFor 2025.