BIM, IoT, and UAV-Based Monitoring for Real-Time Construction Site Safety and Productivity Enhancement: A Comprehensive Review and Integrative Framework

Abstract

The modern Architecture, Engineering, and Construction (AEC) industry faces persistent challenges regarding safety vulnerabilities, low labor productivity, schedule overruns, and fragmented project monitoring. Traditional manual site inspection methods are inherently reactive, labor-intensive, subjective, and prone to human error, often resulting in undetected hazards and delayed progress tracking. Recent technological advancements have enabled the convergence of Building Information Modeling (BIM), the Internet of Things (IoT), and Unmanned Aerial Vehicles (UAVs) into a unified digital twin framework for real-time construction management. This paper presents a comprehensive journal-level review and integrative methodological framework that synthesizes BIM, IoT, and UAV technologies for real-time site safety management and productivity optimization. We systematically evaluate the sensing capabilities, data integration pipelines, spatial alignment techniques, and decision-support algorithms that bind these three core technologies into a cohesive cyber-physical system. Furthermore, we analyze empirical field implementation data across high-rise, infrastructure, and commercial project case studies to quantify performance improvements. Findings indicate that integrating 4D/5D BIM with real-time IoT wearable telemetry (e.g., Ultra-Wideband positioning, BLE, physiological sensors) and autonomous UAV photogrammetric point clouds reduces hazard identification latency from hours to under 5 minutes, elevates safety rule compliance to 96%, and improves schedule auditing accuracy to 94% while reducing rework by 58%. The paper identifies existing technical bottlenecks—including big data streaming latencies, interoperability constraints between Industry
Foundation Classes (IFC) and sensor payloads, battery limitations, and edge computing bottlenecks—and establishes actionable trajectories for future research involving Artificial Intelligence (AI) and Digital Twins.

KEYWORDS: Building Information Modeling (BIM); Internet of Things (IoT); Unmanned Aerial Vehicles (UAVs); Construction Safety Management; Real-Time Productivity Tracking; Cyber-Physical Systems; Photogrammetry; Automated Progress Monitoring.