Wearable sensing devices (WSDs) are increasingly helping workers stay safe and healthy in several industries. However, workers, especially in the construction industry, have shown some aversion towards the use of WSDs due to their ability to capture specific information that may be considered personal and private. However, this revered information may provide some critical insight needed by management to plan and optimize worksite safety and support technology adoption in decision making. Therefore, there is a need to develop personalized WSD systems that are mutually beneficial to workers and management to ensure successful WSD integration. The present study aims to contribute to knowledge and practice by filling this critical gap using insight from 330 construction workers with experience using WSDs. The results from this study indicate that all 11 WSD functions identified through this study play a vital role in improving worker safety and health and that approximately two out of three workers are open to sharing the physiological and environmental information captured using these WSDs with their management. However, functions for detecting workers’ proximity to workplace hazards, specifically energized electrical materials, toxic gas, and fire/smoke, were the most critical functions that had mutual value to workers and management. Finally, the present study proposed and evaluated a phased personalized WSD system that should encourage successful WSD integration.

Technology use in the construction industry fosters improvements in schedule, safety, cost, productivity, and quality. In this domain, the construction technologies adoption highly depends on stakeholders, who may exhibit some resistance to operational use. This underscores the importance of determining technology integration success using effective methods such as predictive and explanatory modelling. Although existing literature has provided some critical insight into the use of these models and theories, there is no domain-based synthesis on the utility of these models and theories as tools to facilitate the integration of emerging construction technologies. Therefore, this paper provides a systematic review and content analysis showcasing different methods and theories for investigating technology acceptance and generates insights expected to guide future technology acceptance studies. Using a three-phase systematic review process, 35 relevant articles were identified and analysed. This review identified perceived ease of use, perceived usefulness, social norm, attitude, perceived behavioural control, and facilitating conditions as key constructs impacting workers’ intention to accept a construction technology. TAM, TPB, and UTAUT were identified as popular choices for developing hybrid models, while UTAUT provided a relatively higher predictive power. Finally, seven areas for further exploration were discussed. This study contributes to construction knowledge by providing a better understanding of technology acceptance research and generating fundamental insights needed to develop robust and effective predictive and explanatory models for advancing technology acceptance research which would support successful technology integration.

The construction work environment remains one of the most hazardous worldwide. As a result of dangerous working environments, construction workers often face safety and health risks throughout the construction process. However, an emphasis on construction safety has increased mainly in the aspect of safety performance, and efforts are required to not only monitor but also seek to improve safety performance. This research develops a safety activity analysis framework and tool to facilitate the collection and analysis of the safety activity data for continuous evaluation of safety performance. A case study is also carried out on an active construction project to implement and validate the framework and tool. The findings of the case study show that the safety index of the construction site increased from 37.0 to 62.8% and was in consonance with the actual site records of the project’s total recordable incident rate, which decreased from 7.11 to 1.42. This study contributes to the body of knowledge b...

The high frequency of work-related injuries and fatalities experienced on construction sites makes the construction process a very hazardous endeavor. The collection and analysis of safety data is an important element in measurement and improvement strategy development. Wearable sensing devices (WSDs) and the internet of things (IoT) have been identified as emerging technologies with strong potential for a transformative change in many aspects of construction workers safety monitoring including tracking and transmitting workers safety information in real-time. This paper provides an evaluation of the potential applications of WSDs and IoT for the continuous collection, analysis, and monitoring of construction workers’ safety metrics to mitigate safety hazards and health risks on construction sites. Wearable sensors and systems that can be used for physiological monitoring, environmental sensing, proximity detection, and location tracking of a wide range of construction hazards and vital signals which can provide early warning signs of safety issues to construction workers are reviewed. A schematic model for integrating wearable sensors for interoperability and multi-parameter monitoring to capture and track several safety metrics is also presented. The challenges facing the widespread adoption of WSDs and IoT in construction are also identified and evaluated. Based on the outcomes of the review completed, recommendations are made on how WSDs and IoT can be effectively implemented to enhance safety performance on construction sites.