Considered a promising avenue for achieving improvements in construction and logistics management, the integration of Building Information Modelling (BIM) and the Internet of Things (IoT) has proposed the ability to revolutionize the Architectural, Engineering, Construction, and Facility Management (AECFM) industry. Many studies have been examining different applications of BIM and IOT integration, specifically within the context of industry 4.0 through recent years. However, the existing literature appears to be fragmented due to the absence of review and categorization, leading to difficulties for practitioners and researchers in identifying trends and gaps. This paper delves into the convergence of BIM and IoT within the field of construction and logistics management by reviewing and categorizing the current cited literature derived from various journals using OpenAlex. On the one hand, the results suggest the utilization of RFID and LoRa for logistics, tracking, and inventory management with BIM and IoT as the most frequent topic. On the other hand, the implementation of BIM and IoT for simulating emergency evacuation scenarios is the least mentioned topic. The main foci within each topic-subcategory are also highlighted and described respectively.

Indoor Environmental Quality (IEQ) plays a vital role in occupant health and productivity. However, current Building Management Systems (BMS) often struggle in sustaining optimal IEQ levels due to limitations in data management and lack of occupant-centric feedback loops. To address these gaps, this research synthesizes the state-of-the-art methods for IEQ monitoring, assessment, and control within Building Automation Systems (BAS), identifying both technological and methodological advancements, as well as highlighting the challenges and potential opportunities for future innovations. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, this multi-stage literature review analyzes 176 publications from 1997 to 2024, with a focus on the decade of rapid technological evolution from 2014 to 2024. The review focuses on high-impact journals indexed in Scopus to ensure quality while acknowledging the potential bias inherent in a single-database search. The synthesis reveals a methodological shift in monitoring from sparse, zone-level sensing towards dense, multi-modal systems that incorporate physiological data via wearables and behavioral recognition through computer vision. Assessment techniques are evolving from static models such as the Predicted Mean Vote (PMV) towards adaptive, personalized frameworks supported by Digital Twins and integrated simulations. Furthermore, control logic is transitioning toward Reinforcement Learning and Model Predictive Control to proactively manage occupancy surges and environmental variables. This evolution of monitoring approaches, assessment techniques, and control strategies is represented within the study’s Three-Tiered Developmental Trajectory, providing a novel Body of Knowledge (BOK) for mapping the transition of building systems from reactive tools to autonomous, occupant-centric agents. This study also introduces a Cross-Modal Interaction Matrix to systematically analyze the systemic trade-offs between IEQ domains. Furthermore, by establishing the “Implementation Frontier,” this work identifies the specific technical and ethical bottlenecks, such as “false vacancy” sensing errors, fragmented data silos, and the ethical complexities of high-resolution data collection that prevent academic innovations from becoming industry standards. To bridge these gaps, we conclude that the next generation of “cognitive buildings” must prioritize three pillars: resolving binary sensing limitations, harmonizing data via vendor-neutral APIs, and adopting privacy-preserving architectures to ensure scalable, interoperable, and occupant-centric optimization.