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Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence
Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence
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Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence
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Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence
Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence

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Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence
Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence
Journal Article

Barriers, Enablers, and Adoption Patterns of IoT and Wearable Devices in the Saudi Construction Industry: Survey Evidence

2026
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Overview
The construction industry relies on the Internet of Things (IoT) and wearable technologies to enhance workplace safety. This research investigates the use of IoT and wearable technology among Saudi Arabian construction sector employees, analyzing their implementation difficulties and the factors contributing to successful implementation. A structured questionnaire was distributed to 567 construction professionals across different roles and projects. Frequency analysis was used to study adoption patterns, chi-square tests to study demographic factors, and principal component analysis for exploratory factor analysis to discover hidden adoption factors. The findings show that smart safety vests and helmets receive the highest level of recognition. On the other hand, advanced monitoring systems, including fatigue and environmental sensors, are not used enough. Group differences in device adoption were investigated in terms of years of experience, academic qualification, job role, and project budget. The findings from factor analysis show that three main factors determine adoption rates, which include (1) safety and operational effectiveness, (2) worker acceptance and support structures, and (3) technical and adoption barriers. A data-driven system is created to help policymakers and industry leaders accelerate construction safety digitalization efforts.