REthinking the food system together; DESIGNing a hightech and data-driven food system of the future (REDESIGN)
Dr. Anand Gavai
Assistant Professor, IEBIS Department, University of Twente.
To accelerate food system transformations, local and contextualized solutions are needed. Current physical and digital technologies are mostly developed in silos and with leading market players. Therefore, they are not connected to local consumer food and health demands, data sovereignty and local context. This program develops a complete solution which is scalable across urban environments, i.e. we develop the high-tech and data-driven agri-food system of the future.
This is a collaboration project within 4TU as other universities are also involved. From UT 5 members are involved.
- Anand Gavai
- Renata Guizzardi-Silva Souza
- Gayane Sedrakyan
- Donika Xhani
- Jos van Hillegersberg
“Dr. ir. Anand K. Gavai is a researcher who focuses on agriculture and food systems. He specializes in utilizing data to gain valuable insights and is particularly skilled in privacy-preserving data platforms. In this field, he designs and implements data infrastructures and develops customized machine learning algorithms. These algorithms effectively integrate data from diverse sources by employing semantic web technologies. Driven by a deep commitment to sustainable change, Dr. Gavai aims to optimize farming practices and enhance resource management. His extensive background in both computer science and agricultural sciences allows him to construct robust frameworks for efficient data collection and analysis. By harnessing the power of AI, these kind of algorithms derive actionable insights from a wide array of data, including weather patterns, soil composition, crop yields, and market trends. With his expertise in semantic web technologies, Dr. Gavai promotes collaboration and facilitates knowledge sharing within the agricultural community. He is dedicated to making a positive impact on agriculture and food systems. His current research revolves around development of solutions that enable efficient, resilient, open, and sustainable global food supply chain.”
Validating (agent-based) simulation models using process mining techniques
Rob Bemthuis
Researcher, EEMCS Faculty, University of Twente.
In simulation, the primary goal for a system designer is to develop a model that not only performs a specific task but also accurately represents real-world systems or processes. However, creating a valid simulation model—a key factor for enhancing understanding and decision-making in the real world—proves to be challenging and time-consuming. The emerging data-driven discipline of process mining can assist in the validation process by extracting process models and insights from event/data logs generated during simulation. These techniques, particularly when paired with effective visualization, show promise in extracting valuable insights. We explore an approach that uses process mining techniques to evaluate the face validity of agent-based simulation models. The approach is demonstrated through illustrative scenarios.
Rob Bemthuis, a researcher in the Pervasive Systems department at the EEMCS faculty, obtained both his bachelor’s and master’s degrees in IEM at the UT. His doctoral research was focused on designing a resilient logistics supply chain. The research aimed to understand how intelligent distributed business entities, such as smart pallets or containers, could improve the detection, guidance, and prediction of disruptive emergent behaviors. He proposed various methods for assessing, extracting, and learning from emergent phenomena using business rules. Rob was a visiting researcher at the University of Southern Denmark and the Karlsruhe Institute of Technology. Currently, he is a postdoctoral researcher, coordinating and conducting research within a sustainable construction logistics project.