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Dong Zhao

Researcher at Michigan State University

Publications -  65
Citations -  1719

Dong Zhao is an academic researcher from Michigan State University. The author has contributed to research in topics: Occupational safety and health & Virtual reality. The author has an hindex of 19, co-authored 62 publications receiving 1059 citations. Previous affiliations of Dong Zhao include Central Queensland University & Virginia Tech.

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Zero latency: Real-time synchronization of BIM data in virtual reality for collaborative decision-making

TL;DR: A BIM VR real-time synchronization system called BVRS is introduced, which is based on an innovative Cloud-based BIM metadata interpretation and communication method and allows users to update BIM model changes in VR headsets automatically and simultaneously.
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Virtual reality simulation for construction safety promotion

TL;DR: The development and utilisation of a training program that is based on virtual reality (VR) simulation is demonstrated that can offer a safe working environment where users can effectively rehearse tasks with electrical hazards and ultimately promote their abilities for electrical hazard cognition and intervention.
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CoVR: Cloud-Based Multiuser Virtual Reality Headset System for Project Communication of Remote Users

TL;DR: This research presents a meta-analyses of communication practices in the construction industry that shows clear trends in how communication among project stakeholders is affected by construction-side constraints.
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Interaction effects of building technology and resident behavior on energy consumption in residential buildings

TL;DR: In this paper, the authors investigated the relationship between building technology and resident behavior and the joint effects on energy consumption in residential buildings and found that only 42% of technological advances directly contribute to home energy efficiency, suggesting the achievable impact on energy savings depends on both technical advances and behavioral plasticity.
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Monitoring workers' attention and vigilance in construction activities through a wireless and wearable electroencephalography system

TL;DR: In this article, a wireless and wearable electroencephalography (EEG) system is proposed to quantitatively and automatically assess construction workers' attention level through processing human brain signals, and the results suggest EEG signal properties such as frequency, power spectrum density and spatial distribution can effectively reflect and quantify the construction workers perceived risk level.