Enterprise Interoperability XI : Enterprise Interoperability Through Data, Artificial Intelligence and Robotics

This book gathers the proceedings of the I-ESA’24 Conference, which was held in Elounda (Crete), Greece, between 10 and 12 April 2024. It presents contributions ranging from academic research and case studies to industrial and administrative experiences with interoperability. These contributions show how industries can be helped to develop high-quality products and services with enhanced efficiency and potential for customization and reduced production cost. The focus of this edition of the conference is the contribution that can be made to interoperability by good data management, judicious use of artificial intelligence and the employment of robots.

Many of the papers in this 12th volume of the Proceedings of the I-ESA Conferences include examples and illustrations to help deepen readers’ understanding and generate new ideas. Offering a detailed guide to the state of the art in systems interoperability, the book is of great value to all engineers and computer scientists who wish to promote innovation in manufacturing and other process industries and to software engineers and electronic and manufacturing engineers working in academic settings.

Dr. Stefanos Vrochidis received the Diploma degree in electrical engineering from Aristotle University of Thessaloniki, the M.Sc. degree in radio frequency communication systems from the University of Southampton, and the Ph.D. degree on Interactive video retrieval based on implicit user feedback from Queen Mary, University of London. Currently, he is a senior researcher (Grade C’) at the Information Technologies Institute of the Centre for Research and Technology Hellas (CERTH-ITI). Dr. Vrochidis is the head of the Multimodal Data Fusion and Analytics Group of the Multimedia Knowledge and Social Media Analytics Lab. His research interests include multimodal data fusion, multimedia understanding, artificial intelligence, web and social media mining, multimodal analytics, digital twins, as well as industrial, security, health and environmental applications.

Yves Ducq is a specialist in the domain of Enterprise Modelling, Business Process Management, Enterprise Interoperability (EI), System Performance Evaluation and Implementation of Indutry 4.0 solutions. He is the main author of the GRAI Model and the GRAI Integrated Methodology (GIM) since the 1980s and has managed more than twenty important European and International projects during the last 30 years in his competence domains. He has published more than 300 articles and four books.

Dr. Ilias Gialampoukidis received the Bachelor degree in Mathematics and the M.Sc. in Statistics and Modelling from the Aristotle University of Thessaloniki, where he also received a Ph.D. degree in Mathematics, with a special interest in applied mathematics, time series analysis, stochastic modelling, and network analytics. Dr. Gialampoukidis is a senior postdoctoral researcher at the Centre for Research and Technology Hellas at the Information Technologies Institute, with extensive experience in EC-funded research projects through work package leaderships and critical roles in several projects. His research interests involve multimodal information retrieval, Industry 4.0, big data analytics, multimodal fusion, supervised (deep) and unsupervised learning, and social media mining and network analytics. He has co-authored more than 50 publications in international journals and conferences

Karl A. Hribernik studied Computer Science at the University of Bremen. He worked as a software developer at Produtec Ingenieurgesellschaft mbH on both research and commercial e-logistics and e-commerce projects from 1997 to 2002. He joined BIBA – Bremer Institut für Produktion und Logistik GmbH as a research scientist in 2002. He has been the head of the department of Intelligent ICT for Co-operative Production at BIBA since 2013 and manages BIBA’s iotfablab. His research interests are focused on product-centric information and closed-loop product lifecycle management, and include the investigation of the Internet of Things and Industrie 4.0 in the product lifecycle; semantic models, interoperability and search; item-level digital product representations and digital twins; data analysis, AI and machine learning as well as knowledge-based engineering.