Evaluates compliance checking in construction, suggesting improved safety in product reuse.
The Architecture, Engineering, and Construction (AEC) sector suffers persistent challenges in formalising and automating regulatory compliance, especially for the safe reuse of construction products at their end of life (EoL). Current approaches lack compliance automation aligned with regulation semantics and do not integrate human expertise in the verification of automated decisions. This increases chances of incorrect reasoning over complex regulatory texts. This paper presents the Human-in-the-Loop Semantic Middleware (HiLSeM). Its scientific contribution to Engineering Informatics is a computational formalism for lifecycle-aware regulatory knowledge and verification. It includes a pseudo-automated step (LLM-assisted) to formalise regulatory knowledge into machine-readable structures. It also facilitates a traceable, machine-to-machine automated compliance reasoning over isolated data sources while integrating human oversight to override automated compliance decisions. The HiLSeM framework builds upon the AEC3PO ontology and related ontology-driven compliance checking streams, extending them with a formal human-verification layer and lifecycle-aware compliance history. Regulatory clauses are analysed using structured RASE (Requirement, Applicability, Selection, Exception) semantics and mapped to interconnected OWL ontologies, to deliver executable compliance requirements. The framework was evaluated using multiple real-world use cases to assess its relevance in compliance assessments. In a qualitative study involving four clauses of varying structure, clause-level extraction achieved precision from 0.50 to 1.00, recall from 0.70 to 1.00, and F1 from 0.67 to 0.93. Gold-standard annotations showed almost-perfect agreement (κ = 0.956). This work contributes a novel computational formalism by bridging semantic legal knowledge representation, automated reasoning and human in the loop verification for engineering regulation.
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Adu-Duodu et al. (2026) studied this question.
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