A Knowledge-Driven Approach for Dynamic Reconfiguration of Control Design in Internet of Things and Cyber–Physical Systems

Dynamic control software reconfiguration for the Internet of Things (IoT) and cyber-physical systems (CPSs) is crucial for adaptable and efficient automation. This article presents a knowledge-driven architecture enabling dynamic device reconfiguration using the Web ontology language (OWL) and terse triple language (TTL) formats. Key components include a capability ontology, session-type information for sequencing and concurrent operations, and an integrated development environment (IDE) for automated control design. The capability ontology standardizes machine capabilities, facilitating device integration based on their capabilities, while session-type information ensures correct sequencing and synchronization of machine functions. The IDE platform supports dynamic reconfiguration by automating device selection, control strategy formulation, and system adjustments across diverse use cases. The architecture has been validated in real-world scenarios, including smart meeting rooms, warehouse automation, and energy management, showing a reduction in manual configuration time (up to 50%), development time (86% in some cases), and error rates (30%). Benchmarking results indicate faster code generation (40% improvement) and efficient component integration across different CPS environments. Challenges like computational complexity, scalability, and integration with existing systems highlight limitations. Future research will explore further optimizations and broader applicability to ensure low-latency, high-accuracy, and seamless integration in complex CPS. This work advances dynamic control software reconfiguration by providing a flexible solution that enhances CPS reliability and efficiency through a knowledge-driven approach.