Aug 2026· 2026 6th International Conference on Emerging Smart Technologies and Applications (eSmarTA)· pp. 1-9· 0 citations· 57 references
Abstract
This paper develops a BIM-integrated, explainable, and deployment-aware decision-support framework for real-time personal protective equipment (PPE) monitoring in Yemen’s construction sector. Its contribution is an integration-based decision-support artifact rather than a new PPE detection algorithm. The study addresses a persistent practical gap: many vision-based PPE systems can detect violations, yet they rarely convert image-level detections into auditable, location-aware, and managerially defensible interventions. Using a design science research approach, the paper re-specifies the original detection-centered concept as a socio-technical artifact composed of six tightly coupled layers: multimodal site capture, RF-DETR-based PPE perception, explanation generation, BIM spatial anchoring, AHP-TOPSIS-driven prioritization, and governance-oriented analytics. The assessment remains analytical, and field validation is left for future work. The framework formalizes an event schema that links each alert to confidence, explanation evidence, anchor confidence, zone semantics, response ownership, and closure status. It also introduces a resource-aware deployment path suited to fragile and connectivity-constrained projects by combining smartphone inspections, CCTV streams, offline buffering, staged BIM anchoring, and selective explanation triggering. The main contribution is therefore not merely improved PPE recognition; rather, it is the conversion of real-time vision outputs into trustworthy safety intelligence that supports prioritization, hotspot discovery, accountability, and progressive digital-twin readiness.
The BIM–VR workflow advances design-phase H&S by enabling immersive hazard review, metadata integration, and collaborative issue resolution, offering a replicable solution aligned with digital construction practices.
Digital Twins (DT) are increasingly positioned as key enablers of sustainable urban development, yet many implementations remain fragmented, technology-driven, and weakly connected to clearly defined decision-making needs. The present study develops a structured information governance framework for DTs, drawing on the principles of ISO 19650. The framework establishes a traceable hierarchy linking organizational objectives, DT use cases, information requirements, the Level of Information Need, information exchange processes and machine-readable Information Delivery Specifications. Its purpose is to ensure that information is clearly defined, exchanged, validated, and maintained in a consistent and verifiable manner before it is used for monitoring, simulation, predictive analytics, or decision support. The proposal is illustrated through an urban air-quality Digital Shadow demonstrator integrating BIM, GIS, weather services, and a real-time visualization environment. Candidate information-quality indicators are also introduced and demonstrated through synthetic calculations intended to explain their application. Neither the demonstrator nor the calculated KPI values constitute validation of the framework or evidence of improved operational performance. Instead, they establish a structured basis for future testing in operational Urban Digital Twin (UDT) implementations. The contribution lies in integrating established BIM concepts into a single DT-oriented traceability chain rather than introducing them as new standards or methods.
Andrei Crișan, S. Herban, Massimiliano Pepe et al.· Urban Science· 0 citations
Healthcare facilities represent some of the most operationally complex and critical built environments, in which building performance directly influences patient safety, clinical outcomes, staff wellbeing and management efficiency. The progressive digitisation of the construction and Facility Management (FM) sectors, driven by Building Information Modelling (BIM), Digital Twin (DT), the Internet of Things (IoT) and Artificial Intelligence (AI), offers transformative potential for the management of hospital infrastructure, predictive maintenance and indoor environmental monitoring. Despite a growing body of scientific literature, existing systematic reviews focus predominantly on clinical or patient-facing Digital Twin applications, leaving the built environment perspective—encompassing architectural systems, technical infrastructure and post-construction lifecycle management—largely unexplored. This Systematic Scoping Review follows the PRISMA-ScR protocol. A structured database search on Scopus yielded 194 records; after title/abstract screening and full-text review, the final corpus, defined here as the final set of included studies, comprises 166 studies (2013–2026; 2026 partial through 21 April) coded through a multidimensional thematic matrix. Results reveal a marked acceleration in publications from 2023 onwards, with BIM (56.6%) and Digital Twin (46.4%) as the dominant technologies and Facility Management as the prevailing domain (69.3%). The principal finding concerns implementation maturity: 52.4% of studies remain at a conceptual level, 38.6% are Prototype/Proof-of-Concept and 9.0% are Pilot/Testbed; no study documents a fully operational hospital deployment. Identified gaps include limited system interoperability, the absence of explicit normative references and insufficient integration of environmental sustainability. Beyond technical and sustainability dimensions, the review highlights a critical gap in the explicit linkage between built environment management and direct health outcomes for occupants: real-time digital monitoring of indoor environmental quality (IEQ) parameters remains the least operationally implemented domain (9.6% of studies), despite its documented effects on patient recovery, infection control and healthcare staff performance.
Virginia Adele Tiburcio· Green Health· 0 citations
This study aims to develop and validate a building information modeling (BIM)-based automation framework that integrates the Estidama Pearl Rating System (PRS) directly into Autodesk Revit. The research focuses on the Materials category, addressing the industry’s reliance on manual documentation and static assessment methods. It seeks to enable real-time sustainability evaluation and enhance accuracy, efficiency and decision-making during the design phase of residential projects in the United Arab Emirates.
A partially automated Revit-based framework was developed using parameterized data structures representing Estidama’s Materials subcredits. These parameters are dynamically linked with Dynamo automation scripts for rule-based calculations and credit scoring, while One Click Life Cycle Assessment (LCA) integration provides embodied carbon and environmental impact data consistent with Estidama’s requirements. The system was validated through a three-story residential villa in Dubai, testing feasibility, accuracy and responsiveness under actual design conditions.
The framework partially automated measurable subcategories of Estidama’s Materials section, reducing manual effort by approximately 90% and improving calculation accuracy to within a 1% error margin. Dynamic linkage between model parameters and sustainability metrics allowed real-time recalculation of scores following design modifications. The results confirm that BIM can function as an intelligent sustainability engine, transforming Estidama assessment into a proactive design-stage process.
The framework currently depends on accurate manual entry of supplier and material data. Future enhancements could integrate automated data sourcing and expand applicability to other rating systems, including Leadership in Energy and Environmental Design and Building Research Establishment Environmental Assessment Method.
By automating Estidama assessments, the framework minimizes consultant workload, reduces reporting time and ensures consistent compliance, supporting faster project approvals and improved sustainability outcomes.
The study promotes climate-responsive construction aligned with the UAE’s Net Zero 2050 strategy by encouraging wider adoption of digital sustainability assessment practices in the Gulf region.
This research is the first to automate Estidama PRS scoring within Autodesk Revit using Dynamo and LCA integration. Unlike existing LEED or BREEAM automation frameworks, it provides a region-specific, parameterized and scalable solution tailored to the UAE’s sustainability standards. The study contributes a replicable foundation for future digitalization of local certification systems and advances BIM’s role in data-driven environmental compliance.
P. Youssef, Malek Masmoudi, Ali Cheaitou et al.· Facilities· 0 citations
Construction sites continue to face persistent PPE non-compliance despite regulatory requirements and routine inspections. Manual monitoring and post-incident CCTV reviews remain reactive and difficult to sustain across multiple work zones, highlighting the need for affordable real-time monitoring tools for small and medium-sized firms. This study developed and evaluated P.P.Eye‑TRACK, a YOLOv8-based PPE detection and dashboard analytics system for proactive construction safety monitoring. Using a design and development research approach, the system was trained to detect hard hats, safety vests, and safety shoes from CCTV images, deployed for four weeks at an ABC Company project, and evaluated through validation metrics, field observations, real-time performance testing, usability assessment, cost-benefit analysis, and pilot-final survey comparisons. Results showed strong validation performance, with mAP@0.5:0.95 reaching 85.98%. Field deployment accuracy was moderate at 65.94%, with hard hats detected most reliably and safety shoes most affected by object size, distance, lighting, obstruction, and perspective. Green Zone observations were more accurate than Red Zone, confirming the importance of camera placement. The system met real-time performance thresholds, achieved an excellent SUS score of 90.31, and produced a cost-benefit ratio of 1.55 with a 1.82-year payback period. Findings indicated that P.P.Eye‑TRACK is feasible for proactive PPE compliance monitoring, but implementation should include user training, human verification of alerts, expanded safety-shoe datasets, and continuous refinement under varied conditions. This study contributes to SDG 8 by promoting safer workplaces and supports SDG 9 through affordable AI-driven construction safety management.
Abner Albito, James Jose Suntay, Jomary Perez et al.· International Journal of Sus...· 0 citations
Integratingartificial intelligence (AI), the Internet of Things (IoT), and Building Information Modeling (BIM) holds considerable promise for modernizing construction management, yet a unified real-time framework connecting these technologies for heavy civil earthmoving remains lacking. This paper presents BIM-iDT, a BIM-Integrated Digital Twin framework that couples multi-source IoT sensing with an IFC-based BIM model to enable intelligent fleet coordination and automated progress control. The research follows a design-science methodology comprising framework formulation, modular development, field deployment, and multi-project validation. The framework comprises a heterogeneous sensor fusion layer aligning GPS, IMU, fuel-consumption, and LiDAR data within the BIM coordinate system; a spatio-temporal graph attention network (ST-GAT) that recognizes equipment states and predicts short-horizon productivity by modeling fleet-level spatial dependencies; a temporal point cloud differencing module that quantifies cut/fill volumes against BIM design surfaces; and a constrained multi-objective evolutionary optimizer (CMOEO) that generates Pareto-optimal dispatch plans balancing fuel, cycle time, utilization, and schedule adherence. Validation on a highway project with instrumented machines shows that ST-GAT achieves a macro-averaged F1 of 0.943, volume MAPE stays below 3%, and CMOEO reduces fuel consumption by 12.6% and cycle time by 9.3% while maintaining schedule adherence above 96%, yielding an estimated 168-ton CO2 emission reduction. End-to-end latency averages 600 ms, satisfying real-time requirements. Cross-project transfer experiments on a secondary dam construction site further confirm framework generalizability, establishing BIM-iDT as a scalable paradigm for AI-and-IoT-enabled smart construction in infrastructure engineering.
