Engineering Informatics and Intelligent Systems: Scope, Vision, and a Research Agenda for an AI-Enabled Engineering Future
Keywords:
Trustworthy AI, Knowledge-based Systems, Semantic Interoperability, Digital Twins, Human–AI CollaborationAbstract
Engineering is entering a period in which data abundance, pervasive sensing, high-performance computing, and rapidly advancing artificial intelligence are reshaping how physical systems are conceived, analysed, operated, and governed. Yet the practical integration of AI into engineering remains uneven. Many current deployments are still model-centric rather than decision-centric: they optimise benchmark performance but remain weakly connected to domain knowledge, physical law, regulation, lifecycle information, and the accountability structures required in safety-critical practice. This inaugural editorial introduces Engineering Informatics and Intelligent Systems (EIIS) as a forum for research at the intersection of engineering data architectures, knowledge representation, intelligent computation, and socio-technical decision support. It argues that the field now requires a coherent research agenda organised around four pillars: data-enriched engineering systems and semantic interoperability; knowledge-informed intelligence that embeds physical and regulatory constraints; trustworthy and explainable decision support; and human--AI collaboration in engineering workflows. The editorial further identifies hybrid AI, semantic digital twins, and federated intelligent infrastructures as emerging frontiers that will define the next phase of the discipline. The aim is to clarify what kinds of intelligence are genuinely usable, governable, and valuable in real engineering contexts.
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