Research Trends of Human–Computer Interaction Studies in Construction Hazard Recognition: A Bibliometric Review

Human–computer interaction, an interdisciplinary discipline, has become a frontier research topic in recent years. In the fourth industrial revolution, human–computer interaction has been increasingly applied to construction safety management, which has significantly promoted the progress of hazard recognition in the construction industry. However, limited scholars have yet systematically reviewed the development of human–computer interaction in construction hazard recognition. In this study, we analyzed 274 related papers published in ACM Digital Library, Web of Science, Google Scholar, and Scopus between 2000 and 2021 using bibliometric methods, systematically identified the research progress, key topics, and future research directions in this field, and proposed a research framework for human–computer interaction in construction hazard recognition (CHR-HCI). The results showed that, in the past 20 years, the application of human–computer interaction not only made significant contributions to the development of hazard recognition, but also generated a series of new research subjects, such as multimodal physiological data analysis in hazard recognition experiments, development of intuitive devices and sensors, and the human–computer interaction safety management platform based on big data. Future research modules include computer vision, computer simulation, virtual reality, and ergonomics. In this study, we drew a theoretical map reflecting the existing research results and the relationship between them, and provided suggestions for the future development of human–computer interaction in the field of hazard recognition from a practical perspective.

Temporal Visual Patterns of Construction Hazard Recognition Strategies

Visual cognitive strategies in construction hazard recognition (CHR) signifies prominent value for the development of CHR computer vision techniques and safety training. Nonetheless, most studies are based on either sparse fixations or cross-sectional (accumulative) statistics, which lack consideration of temporality and yielding limited visual pattern information. This research aims to investigate the temporal visual search patterns for CHR and the cognitive strategies they imply. An experimental study was designed to simulate CHR and document participants’ visual behavior. Temporal qualitative comparative analysis (TQCA) was applied to analyze the CHR visual sequences. The results were triangulated based on post-event interviews and show that: (1) In the potential electrical contact hazards, the intersection of the energy-releasing source and wire that reflected their interaction is the cognitively driven visual area that participants tend to prioritize; (2) in the PPE-related hazards, two different visual strategies, i.e., “scene-related” and “norm-guided”, can usually be generalized according to the participants’ visual cognitive logic, corresponding to the bottom-up (experience oriented) and top-down (safety knowledge oriented) cognitive models. This paper extended recognition-by-components (RBC) model and gestalt model as well as providing feasible practical guide for safety trainings and theoretical foundations of computer vision techniques for CHR.