Modelling the Inspection of Storey Buildings Under Construction Using a Knowledge-Based System Approach

Rapid urbanization in Kenya has intensified the construction of multi-storey buildings, exposing deficiencies in traditional inspection methods that are manual, subjective, and prone to knowledge loss, inefficiency, and regulatory gaps. This study aimed to address these challenges by developing and evaluating a knowledge-based system (KBS) to enhance inspection processes, institutionalize expert knowledge, and support regulatory compliance. Guided by the Design Science Research (DSR) methodology, the study pursued three objectives: analyzing current inspection practices and stakeholder requirements; designing and implementing a user-centered KBS; and evaluating its effectiveness and usability. Empirical data were gathered through a multiple embedded case study in Nakuru City involving 47 stakeholders, whose insights informed the modular design of a rule-based KBS, modeled using CommonKADS and UML, and implemented in CLIPS. The prototype provided transparent, auditable decision support, interactive guidance, and structured documentation aligned with regulatory workflows. Evaluation confirmed the system’s potential to improve inspection consistency, enhance organizational learning, and support governance reforms aligned with sustainability goals. The study contributes to theory, practice, and policy by demonstrating the transformative role of intelligent systems in construction inspection and outlining pathways for future research.