IOT-ENABLED CONSTRUCTION PROJECT MONITORING SYSTEMS A META-ANALYTICAL REVIEW OF EFFICIENCY GAINS IN LARGE-SCALE INFRASTRUCTURE

Abstract

This meta-analytical study investigates the role and impact of Internet of Things (IoT) technologies in enhancing efficiency outcomes within large-scale infrastructure construction projects. With the growing complexity, scale, and performance demands in the global construction sector, IoT-enabled monitoring systems have emerged as a transformative solution for optimizing cost control, schedule adherence, resource utilization, safety, and lifecycle asset management. To provide a comprehensive understanding of this technological advancement, the study systematically reviewed and synthesized findings from 67 empirical studies published between 2010 and 2023. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to ensure methodological rigor and transparency. Key performance indicators (KPIs) analyzed included cost variance, schedule performance index (SPI), resource usage efficiency, rework incidence, and safety outcomes. The findings consistently demonstrated that IoT technologies—such as RFID, wireless sensor networks, GPS tracking, wearables, and predictive analytics—contribute to measurable efficiency gains, including cost savings ranging from 8% to 27%, time reductions of up to 35%, and rework decreases by as much as 28%. Furthermore, IoT systems enhanced labor productivity and safety through real-time monitoring and biometric-based predictive interventions. The review also highlighted critical gaps in the literature, including methodological inconsistencies, a lack of standardized metrics, limited longitudinal data, and geographic imbalances, with underrepresentation of studies from developing countries. These insights underscore the importance of standardized frameworks, inclusive research designs, and strategic integration of IoT with BIM and digital twin technologies. Overall, this study validates IoT as a key enabler of operational efficiency and digital transformation in infrastructure construction, providing a foundation for evidence-based policy, investment decisions, and future research.