Special Session #6

Agriculture practices have been increasingly becoming smarter in the last years with the introduction of different levels of nano, bio, electronics, and information technological advances. When it comes to the use of information systems in agriculture, new advances are needed in the design, implementation, deployment, management, and testing of software tools. Particularly, the concept of smart agriculture is entirely dependent on data coming from the field, collected by different measurement techniques. The growth in the use of computerized systems for data collection, classification, and processing, and consequently the generation of valued information, creates conditions to raise agriculture to new levels of sustainable production. Continuously taking smart agriculture to the next level of automation requires new contributions to the generation of knowledge beyond the current state of the art and the practice. Particularly, software tools are increasingly required to support the Internet of Things (IoT) and artificial intelligence (AI) concepts, together with the novel developments in software engineering and information systems. This special session aims at bringing together scientists and practitioners imbued with the development of concepts and technologies for a new breed of software tools to support the future of smart agriculture measurement.

This special session invites scholars and practitioners to submit research papers that report their recent advances in software tools for smart agriculture measurement, including but not limited to, the following topics:

• Visualization techniques and Human-Computer Interfaces for smart agriculture measurement;
• Simulation techniques and simulators for smart agriculture measurement;
• IoT Platforms and systems for smart agriculture measurement;
• Digital twin design and implementation for smart agriculture measurement;
• Artificial intelligence based-systems for smart agriculture measurement, including recent machine and deep learning techniques;
• Software systems for the integration of fixed, mobile, and flying sensors for smart agriculture measurement;
• Systems of systems for smart agriculture measurement.

Carlos Kamienski is a Full Professor of Computer Science at the Federal University of ABC (UFABC, Brazil). Currently, he leads the NUVEM Strategic Research Unit comprising 20 faculty members and their students working in five broad research lines, namely smart societies, virtual sensations, connected mobility, extreme computing, and integrated universes. He is the Brazilian coordinator of SWAMP (swamp-project.org), an EU-Brazil collaborative research project that develops IoT-based methods and approaches for smart water management in precision irrigation. His current research interests include the Internet of Things, smart agriculture, smart cities, fog computing, network softwarization, and Future Internet.

Ronaldo Prati is an Associate professor in Computer Science at the Federal University of ABC. He has a doctorate degree in Computer Science and Mathematical Computing from Universidade de São Paulo (2006). Has experience in Computer Science, acting on the following subjects: knowledge discovery, machine learning, data mining, and data science, with applications in different areas such as engineering, text mining, and smart agriculture.

João Henrique Kleinschmidt is an Associate Professor in Information Engineering at the Federal University of ABC (UFABC), Brazil. He has a doctorate degree in Electrical Engineering from the State University of Campinas. He participates in several projects in the area of the Internet of Things, including SWAMP, an EU-Brazil collaborative research project that develops IoT-based methods for smart water management. His current research interests include the Internet of Things, wireless networks, information security, smart cities, and smart agriculture.

Marcos Cezar Visoli is a researcher in Computer Science at the Brazilian Agricultural Research Corporation (Embrapa). He has been working in the field of design, development, and testing or software tools for agriculture for almost 30 years, and has vast experience with projects involving research and development of computational solutions applied to agriculture, including the themes of software engineering, computer architectures, interoperability, and integration of data and systems, and open technologies. He is currently involved in projects with IoT applied to topics such as smart irrigation and crop-livestock-forestry systems integration, simulation systems, dairy farm management systems, and agricultural data management.