EVOLVING INDUSTRY 4.0: A METHODICAL APPROACH TO OPTIMIZING IOT ONTOLOGIES FOR ENHANCED AUTOMATION

This research advances Industry 4.0 by optimizing IoT ontology models, crucial for enhancing industrial automation's efficiency and adaptability. Employing a mixed-methods approach that integrates a systematic literature review, expert interviews, and case analyses, we identify and address significant gaps in existing IoT ontologies. Our findings reveal that improved interoperability, scalability, and adaptability in IoT ontologies can significantly elevate the robustness and efficiency of Industry 4.0 infrastructures. The study introduces targeted refinement strategies that promise to future-proof IoT ontologies, thereby facilitating more resilient and dynamic industrial automation environments. This work not only sheds light on the current state of IoT ontologies but also sets a forward-looking agenda for their continuous improvement in the evolving landscape of Industry 4.0.