Browsing by Author "Guo BHW"
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- ItemAugmented reality applications in construction productivity: A systematic literature review(Elsevier Ltd, 2024-10) Xu Z; Feng Z; Babaeian Jelodar M; Guo BHWAugmented reality (AR) has been extensively researched for its applications in the construction industry. However, there is limited focus on its effects on productivity. This paper aims to bridge the gap by using a systematic literature review to investigate AR applications in the planning, design, and construction phases, focusing on their mechanisms for enhancing productivity. The paper classifies AR applications by their target construction tasks, features, and factors contributing to improved productivity. Additionally, it proposes a framework for prototyping AR applications and evaluating their effects on productivity. Key findings reveal several contributions: the need for further investigation of AR for positioning and hazard notification tasks; the utilisation of different augmentation methods, display tools, and tracking methods based on specific construction tasks; AR's positive impact on productivity in design review, discrepancy check, assembly, and hazard notification, while future research on evaluating productivity in progress management, planning simulation, and positioning.
- ItemInvestigating situation awareness transition in construction hazard recognition: A multimodal study of cognitive and neural mechanisms(Elsevier Ltd, 2025-11-01) Zhang Z; Guo BHW; Feng Z; Goh YMConstruction sites are dynamic and hazardous environments where workers often struggle to maintain high levels of situation awareness (SA), essential for effective hazard recognition. While technologies exist to aid hazard perception, limited research has explored how external environmental stimuli and internal safety goals jointly influence the SA transition across perception (SA1), comprehension (SA2), and projection (SA3). This study investigates the effects of augmented stimuli and safety goals setting on SA levels, SA transition and hazard recognition. A multimodal experimental approach was employed, integrating virtual reality (VR), eye tracking, modified Situation Awareness Global Assessment Technique (SAGAT) and event-related potentials (ERPs). A novel Temporal Hybrid Situation Awareness Measurement (THSAM) method was introduced to quantify SA by linking eye-tracking data with SAGAT responses. SAGAT data showed that both augmented stimuli and safety goals improved SA across all levels. SAGAT and THSAM indicated that the combination of the two interventions led to the largest improvements across SA1, SA2, and SA3. SA transition analysis revealed that augmented stimuli effectively facilitated the shift from unawareness (SA0) to SA1. THSAM and SA transition analysis confirmed safety goals primarily enhanced SA2. ERPs analyses further indicate distinct brain activity patterns (P2 and N400) associated with each SA level. This study contributes to construction safety research by providing quantitative evidence on the cognitive and neural mechanisms underlying SA transition. It also introduces THSAM as a methodological advancement for capturing real-time SA dynamics and offers practical implications for designing integrated safety interventions that align with workers’ goals and environmental demands.
- ItemInvestigating the interplay of bottom-up and top-down attention in hazard recognition: Insights from immersive virtual reality, eye-tracking and electroencephalography(Elsevier Ltd, 2025-07) Zhang Z; Guo BHW; Feng Z; Goh YMThe construction industry's high-risk environment demands effective hazard recognition strategies. Attention, a critical cognitive process, plays a crucial role in this task. Previous research focused on individual attention process, such as sustained attention, selective and divided attention. However, no research has been conducted to investigate the effects of the interplay between endogenous and exogenous factors on hazard recognition in construction settings. This paper aims to investigate the effects of the interplay between top-down (T-D) and bottom-up (B-U) attention networks on hazard recognition, using immersive virtual reality (IVR), eye tracking (ET), and electroencephalography (EEG). Two safety interventions—augmented stimuli and toolbox meetings—were tested in a dynamic IVR construction site. The results showed that both augmented stimuli and the safety toolbox meeting significantly affected B-U, T-D, and hazard recognition. This paper provided evidence that the interplay between B-U and T-D can significantly improve workers’ hazard recognition performance. The results improved our understanding of the mechanisms that control selective attention and the source of guidance over attention orientation. By demonstrating that T-D and B-U processes can work together rather than in isolation, this research contributes a key theoretical insight: attentional orientation in hazardous construction environments is neither fully determined by external stimuli nor entirely controlled by internal cognitive sets. In addition, this paper highlights and calls for an integrated approach to improving worker's hazard recognition performance, by combining digital-technology-enabled stimuli with safety-goal-oriented training and managerial practices.