Can mixed reality enhance safety communication on construction sites? An industry perspective

Safety Science 133 (2021) 105009

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Can mixed reality enhance safety communication on construction sites? An industry perspective Fei Dai a, *, Abiodun Olorunfemi a, Weibing Peng b, Dongping Cao c, Xiaochun Luo d a

Department of Civil and Environmental Engineering, West Virginia University, P.O. Box 6103, Morgantown, WV 26506, United States College of Civil Engineering and Architecture, Zhejiang University of Technology, Hangzhou 310014, China c Dept. of Construction Management and Real Estate, School of Economics and Management, Tongji Univ., 1239 Siping Rd., Shanghai 200092, China d Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon 999077, Hong Kong b

A R T I C L E I N F O

A B S T R A C T

Keywords: Mixed reality Construction safety Risk communication Technology assessment

Effective communication plays a vital role in hazard identification in construction workplaces. Unfortunately, current practices that rely on modes such as phone calls, walking to people and talk, and video conferencing do not facilitate instant access to information, context-based perception, and visual interaction that are essential for effective communication in modern construction workplaces. This research assessed the feasibility of applying mixed reality in enhancing safety risk communication on construction sites. A holographic application that enables to turn the field of view of mixed reality head mounted display into a collaborative environment where others can see and interact was prototyped. This was followed by an assessment of its feasibility through trials and feedback from potential users in the construction industry. The performance metrics for the assessment included accuracy, efficiency, ease-of-use, and acceptability of mixed reality benchmarked against the existing communication methods (i.e., phone calls, walking to people and talk, video conferencing, and emails). Analyses results showed the potential of mixed reality for visualization, communication, and remote collaboration of safety-related issues on construction sites. The research findings provided better understanding of feasibility, benefits, and limitations of applying the technology in workplaces, which may ameliorate its improvement and adoption in safety management practices in order to reduce the incidences of injuries and fatalities on con­ struction sites.

1. Introduction The U.S. construction industry has long been plagued with a disproportionately high rate of work-related fatalities in comparison to other industries (Center for Construction Research and Training, 2018). In practice of safety risk management in construction workplaces, haz­ ard identification is a key step for accident prevention and worker protection (Luo et al., 2017; Manuele, 2005). Hazard refers to the inherent property or ability of something that causes harm (e.g., floor opening, inappropriate machine guarding, slipping/tripping surface) (Holt, 2001). Identification refers to identifying the potential hazards. The current practice of hazard identification on construction sites still suffers from deficiencies (Albert et al., 2020). Carter and Smith (2006) revealed a maximum hazard identification level of 76.4% based on analysis of three construction projects. Perlman et al. (2014) found that

superintendents with many years of experience still were unable to identify all hazards at jobsites. Consequently, the remaining unidenti­ fied hazards present the most unmanageable risks. Based on (Khanzode et al., 2012; Luo et al., 2017), the challenges for hazard identification management at jobsites include, but are not limited to, limited knowl­ edge of whom performs the safety inspection tasks, obsolete safety plan for task changes, behind-schedule pressure from whom oversees the daily activities, poor communication of hazards to the construction team, and the large-scale, dynamic and complex nature of construction work. Timely and accurate communication has been proven to be instru­ mental to hazard identification and other safety management activities in construction (Abdelhamid and Everett, 2000). Unfortunately, current practices that rely on modes involving phone calls, walking to people and talk, video conferencing, and sending emails are insufficient to

* Corresponding author. E-mail addresses: [email protected] (F. Dai), [email protected] (A. Olorunfemi), [email protected] (W. Peng), [email protected] (D. Cao), [email protected] (X. Luo). https://doi.org/10.1016/j.ssci.2020.105009 Received 6 November 2019; Received in revised form 9 September 2020; Accepted 17 September 2020 Available online 28 September 2020 0925-7535/© 2020 Elsevier Ltd. All rights reserved.

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and sub-contractors with details such as where and when temporary railings need to be installed on site to avert fall hazards (Zhang et al., 2015). The virtualization tools has proven helpful in connecting safety issues to construction planning, providing useful site safety information before construction (Azhar, 2017). Another strategy to improve safety communication is by simulation and visualization. To assist workers overcome the deficiency in con­ verting knowledge gained during remote collaboration into specific site activities and appropriate attitudes, Guo et al. (2012) and Teizer et al. (2013) developed game-based visualization environments that expose workers to hazards similar to what are expected on site. This experien­ tial exposure to simulated hazards in immersive virtual environments serves to stimulate workers’ perceptions and abilities to recall same hazards in real scenarios during risk communication (Guo et al., 2017). In perfect conditions, the dynamic representations of the construction process through computer-based simulation and visualization offer excellent opportunities to assess risks and intuitively communicate areas of potential hazards that may not be readily observed using traditional 2D drawings (Dainty et al., 2007). Recently, to provide automatic hazardous situation recognition and thereby facilitate timely identification and communication of risks and potential accidents among stakeholders, a plethora of studies have been focusing to explore intelligent monitoring that resorts to techniques such as computer vision, machine learning and wearable sensing, coupled with prior safety knowledge and regulations, for site safety performance improvement (Soltanmohammadlou et al., 2019; Zhang et al., 2020). For instance, real-time locating and tracking of site workers and ele­ ments have been developed for use in workplace safety management by exploiting techniques such as computer vision, global positioning sys­ tem (GPS), geographic information system (GIS), and 3G network (Jiang et al., 2015; Seo et al., 2015). Real-time detection of personal protective equipment such as hard hat and safety vest have been studied for site safety by employment of deep learning (Fang et al., 2018; Nath et al., 2020). Additionally, wearable sensors [e.g., electroencephalogram (EEG), electromyography (EMG)] and analysis techniques have been explored to monitor and measure physiological conditions (e.g., stress, heart rate, and muscle activation) of site workers to ensure their safety and health during performance in construction sites (Ahn et al., 2019; Golabchi et al., 2018; Jebelli et al., 2018). The above works have demonstrated great importance of technology in improving communication for hazard identification and potential accident prevention in construction. Technology has been identified as an influential factor of safety maturity among contractors (Karakhan et al., 2018). Nevertheless, constraints such as time, resource, operation, culture, size, and complexity may limit implementation of the abovementioned technologies in practices (Guo et al., 2015). Gaps still exist between cues offered by implementation of these technologies and perception of site workers who might need to take an immediate action upon occurrence of a hazard.

facilitate instant access to information, situational awareness, and visual interaction that are essential for effective communication on modern construction sites (Stanton, 2013). Mixed-reality (MR) is the merging of real and virtual worlds to produce new environments and visualizations where physical and dig­ ital objects co-exist and interact in real time (Ohta and Tamura, 2014). The potential benefits of using MR lie in its ability for interactive annotation, superimposition, and visualization of information that facilitate communication and collaboration. The result will be enhanced understanding and awareness of site safety-related issues for both office and field crews so as to improve workplace safety performance and prevent accidents. Though MR has attracted much attention and been applied in fields such as movies, collaborative design, medical infor­ matics, and interactive entertainment (Forrest et al., 2017; Ohta and Tamura, 2014), its possibility for use in workplace hazard identification and risk communication has yet to be fully explored. 2. State of practice in construction site communication for safety issues Studies (Alsamadani et al., 2013; Christian et al., 2009; Haslam et al., 2005; Sawacha et al., 1999; Shohet et al., 2019) have highlighted the importance of communication in safety performance improvement of construction. In practices, jobsite safety-related issues have been his­ torically communicated on site and in person [e.g., during daily safety inspection, site foremen routinely examine workplace conditions and communicate identified/possible safety issues with relevant personnel to ensure that the workplace conditions conform to applicable Occu­ pational Safety and Health Administration (OSHA) standards (OSHA, 2016)]. Currently, jobsite safety communication heavily relies on modes involving phone calls, walking up to people and talk, video confer­ encing, and emails. Most contractors use these modes to facilitate perception and understanding of field safety risks among different members. However, due to the complex and ever-evolving nature of construction work environments, using these communication modes suffer from limitations. In the communication process, the typical modes do not facilitate instant access to information, situational awareness, context-based perception, and visual interaction that are essential for effective communication on modern construction sites (Stanton, 2013). In specific, phone calls (i.e., audio-only) and video conferencing (i.e., audio–video) communication conditions possess limitations of lacking visual and spatial cues that are deemed important for effective communication (Billinghurst and Kato, 1999). Walking up to someone to talk and report potential hazards is time-consuming and may hence hinder prompt action to risk control. The absence of non-verbal cues in emails induce discontinuities that could lead to misrepresentation of intent and a reduction in perception in addition to possible delay in feedback. As a result, there is a need to improve the way that site hazard and risk communication is performed in construction workplaces. 3. State of research

3.2. Mixed reality as an alternative for construction safety communication

3.1. Communication improvement for construction site safety

With rapid advancement in sensor and computing technologies over the past decades, mixed reality have attracted growing research interests within the Architecture, Engineering and Construction (AEC) commu­ nity (Cai et al., 2019; Elrawi, 2017; Lu et al., 2014; Wang and Dunston, 2013). With an attempt to reduce the time required to understand the design in the field of electrical construction, Chalhoub and Ayer (2018) examined and demonstrated MR capabilities in design communication to onsite personnel. To address the shortage of skilled construction workforce in market, researchers explored the potential of MR in­ terventions in construction education and workforce development (Azhar et al., 2018; Bosch´ e et al., 2016; Wang et al., 2004; Wu et al., 2019). In human–machine interaction during construction field opera­ tions, development with the aid of MR has been made for timely and

Literature has cited poor communication as the primary cause of accidents in construction projects (Abdelhamid and Everett, 2000). The strategy to improve communication for minimizing potential risks in the design phase of construction projects has been primarily focusing on exploitation of virtualization tools such as Building Information Modeling (BIM) (Chi et al., 2012; Zou et al., 2017). These efforts attempt to identify and manage hazards associated with work prior to actual site developments. By using these tools to create interactive models in the design phase, teams gain useful information about project-specific hazardous conditions that may potentially result in accidents during construction (Kiviniemi et al., 2011). For example, the development of BIM-based fall protection model for unprotected edges provides general 2

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accurate decisions in machine operations (Feng et al., 2019; Su et al., 2013). To enable rapid and accurate assessment of structural integrity and safety, efforts have led to MR-based methods that superimpose aprior knowledge into the field situations for deviation detection and measurement (Dai et al., 2011; Zhou et al., 2017). Besides, MR has been exploited as an instrument by which researchers have implemented simulated risky construction workplaces for testing of risk-taking be­ haviors and safety interventions (Hasanzadeh et al., 2020; Li et al., 2018). For remote collaboration in facility management and equipment diagnosis, MR has been applied to develop enhanced methods in improving the efficiency of remote communication between experts and technicians (del Amo et al., 2020; El Ammari and Hammad, 2019). The above literature has manifested the MR potential to simplify complex process for applications in construction planning, architectural design, and provision of high-fidelity platforms for training and educa­ tional purposes, enabling the industry to create new paradigms to integrate construction processes and bridge communication gaps be­ tween project design and implementation. MR merges the real and vir­ tual worlds to produce a new environment where physical and digital objects co-exist and interact in real time (Ohta and Tamura, 2014). This new environment creates unique communication pipeline for users to interact in a more intuitive manner. Imagine that during daily perfor­ mance of a workplace’s inspection, the site engineer who wears a headset can invoke a floating of virtual screen to display information that s/he needs. S/he then pinpoints a hazard, and the headset will visualize and display it on the screen of the manager’s computer in an offsite office. Reciprocally, the manager can draw finger diagrams on his/her screen and have them appear to the headset wearer (i.e., the engineer). This way, access to information is instantaneous and seam­ less, allowing project team walk through the real construction site, while discussing progresses remotely. Apart from the fact that this will significantly minimize the time required for modeling as is the case in BIM/simulation, the spatial capabilities of MR provide avenue to mini­ mize the gap between modeling and user perception. MR holds great potential of creating shared 3D space that enables to generate combined audio, visual, and spatial cues for remote communication and collabo­ ration (Arroyo et al., 2010; Hauber et al., 2006), and therefore improving the way that construction practitioners perform site hazard identification and risk communication.

site safety issues in contrast to the conventional methods, 2) to what extent MR improves such communication as to the above metrics, and 3) to what extent MR is accepted by the industry. 5. Experiment design and implementation Experiments were designed and implemented in which a commer­ cially available MR device was chosen first for development of a collaborative communication environment. Then feedbacks were collected from construction practitioners through trials at neighboring jobsites using the developed environment and a survey questionnaire. Lastly, statistical data analysis was performed to assess the MR perfor­ mance. The following subsections present the design and implementa­ tion in detail. 5.1. Development of MR collaborative communication environment In this study, Microsoft HoloLens® was selected to develop the MR collaborative communication environment. It was chosen because at the time when the authors planned this study, Microsoft just released Hol­ oLens®, which was a novel platform that allows for seeing, hearing, and interacting with holograms within a real environment. Such platform held promise to enable better education, research, collaboration, and practice in areas such as safety communication (Hoffman, 2016). Hol­ oLens® enables to turn a user’s field of view into a collaborative envi­ ronment where remote team members can see and interact. The display of HoloLens® allows for superimposition of computer-generated 3D information over the user’s view of the real world [Fig. 1(a)]. By pre­ senting additional contextual information with quick annotations or drag-and-drop of holographic content over the user’s field of view, the real world is enhanced beyond the user’s normal experience [Fig. 1(b)]. HoloLens® consists of holographic lenses, a depth camera, speakers above the ears, and on-board processing via an Intel 32-bit architecture, an unspecified GPU (graphics processing unit) and HPU (holographic processing unit) that run an application development. Once initial setup is complete, the application is launched using a hand gesture that in­ vokes the holographic equivalent of the Windows start menu (Furlan, 2016). Safety information in the form of a quick manual was prestored in HoloLens®. As such, it can be dragged into the viewer’s space using a pinching gesture while gaze-activated keyboard is used to search rele­ vant information during remote collaboration [Fig. 1(c)].

4. Problem statement, objective, and research questions

5.2. Identification of construction partners for participation

Safety management on construction sites remains challenging. Ef­ forts for improvement have led to adoption of computer-mediated 3D/ 4D visualization and simulation. However, by these means, users are either fully or partially immersed in computer-generated virtual envi­ ronments separate from the real world during collaboration. The rendering also tends to introduce seams, preventing the environments from adequately reflecting construction sites’ changing realities, and thus, make their applications mostly feasible in design and planning phase of construction projects (Park and Kim, 2013). With advancement in technologies, particularly the recent development of lightweight, commercially available Microsoft HoloLens® and DAQRI Smart Glasses®, MR offers a unique opportunity to develop new media to enhance safety communication in construction. Its potential to provide a platform that supports communication between a head-mounted display (HMD) user and others who can join the space by hitching on the view of the HMD user may overcome current limitations and enhance risk communication in real construction scenarios (Chen et al., 2015). Despite its potential, the performance of applying MR for collabo­ rative risk communication in real site scenarios is scientifically un­ known. Therefore, the objective of this study is to assess the feasibility of applying MR to improving safety communication on construction sites from an industry perspective. To accomplish this objective, three research questions are to be answered: 1) whether MR improves the accuracy, efficiency, and ease-of-use on communication of construction

To identify and obtain access to construction sites and recruit sub­ jects for participation, the authors collaborated with their industry partners by introducing the nature of MR and explaining needs and procedures of the assessment activities. As the research is safety rele­ vant, the industry partners had the concern of having their unintended noncompliance data contained in photos or videos, which might get exposed later, if the authors chose to take them when conducting experiment in construction sites. To address the partners’ concern, the authors agreed not to collect any visual data during the performance of the experiment and would provide all collected data (e.g., questionnaire and note) for review and clearance before the research team exited the construction sites. Ten construction sites were identified in Morgan­ town, WV and its neighboring area for undertaking of the experiment. 5.3. Plan of communication scenarios for evaluation To evaluate safety communication in the MR collaborative envi­ ronment, on each construction site, the authors recruited crews such as project engineers, safety managers, superintendents, foremen, and workers, all of whom would be available and willing to participate in the study, to experience the present technology and provide feedback. These participants were instructed to exploit their current workplace to mimic 3

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Fig. 1. Demonstration of collaborative communication environment enabled by HoloLens®.

a scenario on safety risk communication. That was, one at jobsite and one in office and communication was performed with the aid of the MR collaborative environment. The information to be communicated included potential hazards and violations of the current workplace, and spatial annotations and verbalized comments of the hazards, violations, and their suggested preventive and protective measures associated with the video stream. Fig. 2 presents the scheme of the system imple­ mentation architecture. Through the system implementation, the scene that a HoloLens® wearer sees is displayed on the screen of a tablet computer in front of another user in the remote office. Meanwhile, HoloLens® captures the spatial information of the current scene in form of 3D mesh data. This allows for bidirectional MR content communi­ cation including superimposed spatial annotations (e.g., red arrow in Fig. 2) made by the remote office user to be seen by the HoloLens® wearer.

Field of View of HoloLens Wearer 3D Mesh Data of Scene MR Content

Superimposed Spatial Annotations Fig. 2. Scheme of the system implementation architecture.

4

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5.4. Determination of performance metrics

the probability of committing a Type II error and p represents the pro­ portion of the participants in the experiment that the MR technology will impact. Taking 0.1 for β and 0.95 for p, it yielded 45. Considering that some participants might withdraw during the experiment, 55 partici­ pants were therefore recruited in the study. Two participants did not take the survey so totally 53 data points were collected. Among the 53 participants, 49 were males and 4 were females with work experience ranging from 2 to 38 years. These participants were practitioners in the construction industry, including project managers, site managers, safety managers, safety officers, project engineers, superintendents, and la­ borers, who were available on site and were willing to participate in the experiment. A minimum of at least one-year construction experience by the participants was required as necessary to satisfy the condition for participation in the study. There was no exclusion based on gender, ethnicity, race, or socioeconomic status. Each participant provided response based on his/her perceived functionality of and experience with HoloLens®. The research protocol was approved by the West Vir­ ginia University’s Institutional Review Board (IRB).

An important step in assessing the MR feasibility for enhancing construction risk communication was to select a set of relevant perfor­ mance metrics. Based on Thomas et al. (1998), four (4) key performance metrics were selected to include accuracy, efficiency, ease of use, and acceptability of MR that would be benchmarked against the current primary communication methods at jobsites. The current primary communication methods consist of phone calls, walking to people and talk, video conferencing, and emails. Burgoon and White (2009) defined communication accuracy as a measure of how well communicators create verbal and nonverbal messages that are understood by others and how well those messages are recognized, comprehended, recalled, and interpreted. Based on this definition, this study sought to measure ac­ curacy by evaluating whether and the extent to which the participants collectively considered that MR facilitated better understanding, collaboration, and interaction during risk communication. The mea­ surement of efficiency was based on whether and the extent to which the participants felt that MR enabled them to convey and comprehend risk information faster in comparison to the existing methods. To measure ease-of-use, this study evaluated the participants’ opinions on ease-ofoperation and user interface friendliness of HoloLens® during remote risk communication. Since there is no universally agreed construct to test the metric of acceptability (Sekhon et al., 2017), this study focused on the retrospective (i.e., experienced) acceptability from the partici­ pants’ perspective through measurement of their affect (i.e., feelings) and cognition (i.e., perceptions). In specific, the selected measures included the participants’ opinions on level of comfortability of wearing HoloLens®, level of distraction, and willingness-to-use (reuse) of HoloLens®.

5.7. Procedures For experiment on each site, collecting data involved the procedures as illustrated in Fig. 3. Each field experiment began with the research team entering the construction workplace and ended with the partici­ pants providing their feedback to the questionnaire. In the pre-experiment, the hardware and the software were set up by connecting the HoloLens® and a tablet computer over local area network for internet access. Before the demo, the participants were given a short presentation to get familiar with functions and operations of the technology. During this session, answers were provided to any question that the participants had. This process took about 20–25 min depending on the number of questions received. The participants then read and signed-off the IRB approved consent form, indicating their willingness to participate in the study. Next, the participants were paired for trial with the technology. For each paired group, one operated the tablet computer remotely and the other wore the HoloLens® on site. The test employed the current site scene (i.e., where the HoloLens® wearer saw) as the context for communication. During communication, the participants trialed the functions of HoloLens® such as shared field of view, holographic display, and spatial and visual annotation. The trial took place on a spot where both the participants and the research team deemed safe. The one who wore the HoloLens® was advised to remain steady or move with caution of surrounding hazards (e.g. trip hazards, stairs, low ceilings) when s/he was operating this device. Once completed, the two participants swapped roles and locations and repeated the trial procedure. In case of more than two volunteer par­ ticipants, the test continued after the first pair of participants completed. Each participant then completed the questionnaire separately based on his/her trial experience and opinions towards the technology.

5.5. Survey design The design of the questionnaire as an instrument of data collection in this study was based on the performance metrics and guided by communication evaluation guide by Asibey et al. (2008). The reason that this guide was chosen was that it focuses on communication effectiveness and provides a well-defined evaluation strategy tool. As a result, the questionnaire was developed into three categorical items. The first category contained personal/demographic information, occupa­ tional information, and business information. Even though no identifi­ able information was required from the subjects, this section was necessary to determine if there exists any kind of threat to the validity of the responses provided by the participants based on demographics. The second category contained Likert scale items ranging from 1 (strongly agree) to 5 (strongly disagree) for measurements of the defined perfor­ mance metrics. While many other measurement scales exist, the fivepoint Likert scale was adopted because the performance metrics’ di­ mensions are unipolar rather than bipolar (Schwarz, 2014). The third category contained open-ended questions for comments and suggestions. To increase questionnaire reliability, improvement was made with the assistance of an industry collaborator, whose work is associated with jobsite safety supervision. Following his evaluation, the questionnaire was revised with the valuable comments provided by the collaborator. Additional questionnaire was further piloted with two industrial par­ ticipants (one project manager and one field worker) to check its ade­ quacy during the implementation phase and suggestions from these two participants were then incorporated into the final version of the ques­ tionnaire (Creswell, 2013).

5.8. Data processing The response data were entered Excel® for storage, analysis, and archival. The data contained both quantitative and non-quantitative sections and were coded in a format readily for processing by statisti­ cal analysis. In coding the data, this study binned the five (5) categorical responses into three (3) ordinal scales (i.e., strongly disagree/disagree = 0, neutral = 1, and strongly agree/agree = 2) for measuring the col­ lective sentiments of the participants regarding the feasibility of MR. The reason was that typically, the polarity of a sentiment comprises three values, i.e., positive, neutral, or negative (Liu, 2015), and binning the categorical responses facilitated conduct of such measurement. When it came to analyze the strength [strong (or weak) positive (or negative)] of the sentiment, this study remained the five ordinal scales.

5.6. Participants To determine the participant number, n = logβ logp was applied for single-

group experiments (Fleiss et al., 2003), where n is the sample size, β is

5

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Fig. 3. Experiment procedures on site.

5.9. Statistical analysis

6.1.1. Test of accuracy Figs. 5–8 show the frequencies of responses from participants regarding their opinions on accuracy of MR compared to the existing methods. As to labels in these figures, “Con. MSG” denotes the variable of “ease of conveying messages”, “Und. MSG” denotes “ease of under­ standing messages”, “Pin. Haz.” denotes “ease of pinpointing a site hazard being described”, “Shr. FOV” denotes “usability of shared field of view to assist in remote communication”, and “Vis. Annot.” denotes “usability of visual annotation during communication”. Accuracy compared to phone calls: Based on Fig. 5, an average of 80% of responses were in favor of MR, implying that its application would potentially increase the accuracy during risk communication on jobsites compared to phone calls, while the remaining 18% were un­ decided and 2% disagreed. By further observation, users’ ability to pinpoint hazards, to share field of view, and to visually annotate in 3D space during remote communication accounts for 88% of the responses. This revealed a positive relationship between MR capabilities of providing spatial cues and users’ ability to understand each other during communication. Accuracy compared to walking up to people and talk: As indicated in Fig. 6, an average of 66% of responses supported that MR performs more accurately during communication while 25% were undecided and 9% disagreed. Accuracy compared to video conferencing: According to Fig. 7, there was only a marginal difference in opinions between HoloLens® and video conferencing in term of their potential to convey messages between users in remote settings. However, the distribution in bar chart shows that messages communicated with MR has a greater overall average of being clearly understood by others compared to video conferencing. Overall, an average of 75% of responses favored that MR provides higher accurate performance during risk communication in comparison to 23% of responses being neutral and 2% that disagreed. Accuracy compared to emails: In Fig. 8, accuracy was found to be greatly influenced by the spatial capabilities of HoloLens® in remote settings. It was also observed that an average of 67% of responses were in favor of MR while 32% were neutral and 1% disagreed.

The statistical analyses were performed in Minitab® 18. First, the reliability of the questionnaire was assessed. The purpose was to eval­ uate the degree to which the multiple questionnaire items consistently measured the construct of feasibility of applying MR to improve risk communication. This was done by calculating Cronbach’s alpha coeffi­ cient (α), which ranges from 0 to 1 and provides the overall assessment of a measure’s reliability. Typically, an alpha threshold of 0.7 or greater indicates the reliability of the construct (Kline, 2000). In this study, an alpha value of 0.89 was obtained, showing a strong correlation of the questionnaire items and its reliability to measure the construct. The criterion for selection of an appropriate statistical test was based on the type, number, and scale of the testing variables (Parab and Bhalerao, 2010). This study intended to assess whether a significant difference exists in the comparisons of MR with traditional communi­ cation techniques. Such assessment required a test that can handle nonnormal distributed, ordinal-scale data with more than two groups (i.e., disagree, neutral, and agree) (Montgomery, 2005). Kruskal-Wallis H test was considered most suitable for the analysis because of its robustness to skewness and non-normality assumptions. To answer the question of the extent that MR impacts risk communication, the study used the student t test to determine the limits of agreement and provided an estimate of the 95% confidence intervals for the item mean of each construct. This way, it can be 95% confident about where the average opinion stands based on a scale ranging from strongly disagree (0) to strongly agree (4). 6. Results 6.1. Descriptive analysis results Fig. 4 is the boxplot that displays the median distribution of total responses to each category by all participants, indicating that responses with “agree” has a higher median value than responses with “neutral” and “disagree”. Specifically, 58% of the total responses consented that MR has a positive impact on risk communication in comparison with the existing methods while 8% dissented and 34% were neutral. To demonstrate the participants’ opinions to each performance metric, the following subsections presented the detailed descriptive statistical re­ sults. Please be noted that some participants did not provide their re­ sponses to all questions as they did not have any experience or interest in certain communication mode (e.g., video conferencing). As a result, the total number of responses to each question might not be as same as 53.

6.1.2. Test of efficiency Table 1 displays the participants’ consensus on the efficiency of MR benchmarked with the conventional methods. Here, “Comm. Eff.” de­ notes “sense of communication efficiency”. Efficiency compared to phone calls: As shown in Table 1, 59% of responses agreed that MR is more efficient by reducing communication duration during remote collaboration than phone calls while 31% were neutral and 10% disagreed. Efficiency compared to walking up and talk: In Table 1, 59% of responses were in favor that MR reduces discussion time during safety communication in comparison to 25% being neutral and 16% of disagreement. Efficiency compared to video conferencing: In Table 1, 52% of re­ sponses believed that MR leads to better efficiency during risk communication than video conferencing while 39% were neutral and 9% disagreed. Efficiency compared to emails: Based on Table 1, 57% of responses believed that using MR reduces duration of communication compared to 43% that were neutral and 0% that disagreed on the potential of MR to improve the communication efficiency.

Boxplot of Survey Response

25

Frequency

20

15

10

5

0

Disagree

Neutral

Agree

Categorical Responses

6.1.3. Test of ease-of-use Fig. 9 shows the frequencies of responses from the participants

Fig. 4. Total responses to each category by all participants 6

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Fig. 5. Accuracy of HoloLens® vs. phone calls.

Fig. 6. Accuracy of HoloLens® vs. walking up to people and talk.

Fig. 7. Accuracy of HoloLens® vs. video conferencing.

regarding ease-of-use of the MR HoloLens®, where the variables of “Usr. Int.” denotes “friendliness of the user interface of HoloLens®”, and “Oper.” denotes “ease of operation of HoloLens®”. Averagely speaking, 46% of responses agreed that the interface of HoloLens® is easy to operate and user-friendly, whereas 49% were neutral and the remaining 5% disagreed.

6.1.4. Test of acceptability Fig. 10 shows the frequencies of responses from the participants regarding acceptability of the MR HoloLens®, where the variables of “Cmft.” denotes “comfortability of wearing HoloLens®”, “No Dstr.” denotes “no distraction to work wearing HoloLens®”, and “Reuse” de­ notes “willingness to use HoloLens® for work again”. Averagely speaking, 32% of responses were willing to accept MR for risk 7

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Fig. 8. Accuracy of HoloLens® vs. emails.

(i.e., phone calls, walking up to people and talk, video conferencing, and emails).

Table 1 Test results of efficiency. Sentiment

Disagree Neutral Agree

Comm. Eff. (Frequency) HoloLens® vs. Phone Calls

HoloLens® vs. Walking up and Talk

HoloLens® vs. Video Conferencing

HoloLens® vs. Emails

5 16 30

8 12 29

3 12 16

0 13 17

6.2.2. Post hoc analysis The results in the prior section only informed that difference exists among the medians of the three (i.e., disagree, neutral, agree) groups of the responses, but did not address where the difference stands. There­ fore, this study continued to perform a post-hoc test to determine where significant differences occur in the medians of the three response groups using the Kruskal-Wallis pairwise comparison. Table 6 presents the results. Based on Table 6, all pairwise comparisons of HoloLens® against other methods in regard to accuracy led to statistically significant dif­ ferences (p < 0.05), implying that the MR HoloLens® has potential to enhance the accuracy of communication than the other four traditional methods. With respect to efficiency, similar results were obtained in comparisons of HoloLens® with phone calls and walking up to people and talk except that their differences in disagree vs. neutral were insignificant. The results of these comparisons were interpreted as the participants agreed that the use of HoloLens® reduces the time they need to spend in delivering and comprehending messages in comparison to phone calls and walking up and talk, but there is no strong evidence of differences about their opinions in being neutral and disagreement. For the comparisons of HoloLens® with video conferencing and emails, however, there was no significant differences between agree and neutral. This indicated that the respondents do not believe that there is a significant time saving in communication when HoloLens® is used in

communication given the technology in its current state, while 51% of responses were neutral and 17% of responses disagreed that it is the right time to adopt MR for their site risk communication. 6.2. Inferential analysis results 6.2.1. Kruskal Wallis H test of significance To answer the research question as to whether MR improves the performance of jobsite risk communication in a statistically significant manner, this study further applied Kruskal-Wallis H test to assess the differences in the medians of the participants’ responses for each of the constructs and presented the results in Tables 2–5 below. Based on the p-values i.e., p < 0.05 for accuracy, efficiency, ease-ofuse, and acceptability, there are sufficiently statistical grounds to conclude that there is a significant difference in performance of communication when MR is used compared to the traditional methods

Fig. 9. Ease of Use of HoloLens®. 8

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Safety Science 133 (2021) 105009

Fig. 10. Acceptability of HoloLens®.

we could determine the magnitude of responses to each construct (performance measure) at 95% confidence level. In Table 7, the means in all constructs range from 2 to 3, meaning the extent of agreement scaling from neutral to agree. It is noteworthy that the accuracy of MR vs. phone calls yielded the highest mean range of 2.91–3.09, and its upper boundary fell between the agree and strongly agree regions and its lower boundary was close to the scale of agree, signifying a high potential of HoloLens® to improve the accuracy of communication in comparison to phone calls. As to the accuracy of HoloLens® compared with walking up and talk, video conferencing, and emails, it was observed their mean ranges all fell between the neutral and agree regions, but their lower boundaries were closer to the scale of agree. This implied that HoloLens® has superiority in accuracy over the other three methods. In assessing extent of agreement for the efficiency of MR in comparison to phone calls, walking up and talk, video conferencing, and emails, the mean values equally lied between the neutral and agree regions, but this time, with their lower boundaries closer to neutral. The extents of agreement for ease of use and accept­ ability both have the least values for their lower and upper boundaries. This meant that the respondents are more likely to have opinions closer to neutral than agree when comparing the ease of use and acceptability of MR with other methods.

Table 2 Kruskal Wallis H test of significance of accuracy, α = 0.05. Construct

Method

pvalue

Remarks

Accuracy

HoloLens® vs. Phone Calls HoloLens® vs. Video Conferencing HoloLens® vs. Walking up to People and Talk HoloLens® vs. Emails

0.001 0.001 0.001 0.001

< < < <

0.05 0.05 0.05 0.05

Table 3 Kruskal Wallis H test of significance of efficiency, α = 0.05. Construct

Method

Efficiency

HoloLens® HoloLens® HoloLens® HoloLens®

vs. vs. vs. vs.

Phone Calls Video Conferencing Walking up to People and Talk Emails

P-value

Remarks

0.001 0.002 0.001 0.001

< 0.05 < 0.05 < 0.05 < 0.05

Table 4 Kruskal Wallis H test of significance of ease of use, α = 0.05. Construct

Method

p-value

Remarks

Ease of Use

HoloLens®

0.001

< 0.05

7. Discussions This study established a positive and measurable correlation be­ tween communication effectiveness and the MR technology. Both descriptive and inferential statistical analysis results signified the po­ tential of MR in enhancing accuracy and efficiency of the risk commu­ nication in construction workplaces. A large portion of participants reported that HoloLens®, with its shared, real-time visual information, was likely to make communication more accurate and efficient than traditional communication methods including phone calls, walking up to people and talk, video conferencing, and emails. The opinions about whether HoloLens® is easy to use were split in a ratio of about 1 to 1 in agree and neutral. About 1/3 of respondents were prepared to adopt MR for safety communication while 17% of respondents were not. Typically, the acceptance of a new technology is influenced by intuition in con­ struction. The rule of thumb for most practitioners in considering a new technology is to have the grips of it in first few minutes. Such a short time expectation might not be realistic in the case of using HoloLens®. Besides, there were concerns expressed by the participants such as “may limit field of view”, “video gets pixelated when signal is not good”, “headphone to hear better, jobsites is loud”, and “it is hard to wear and walk”, all of which were limitations of HoloLens® for its version that was used in the test. These might explain the less favorable responses to

Table 5 Kruskal Wallis H test of significance of acceptability, α = 0.05. Construct

Method

p-value

Remarks

Acceptability

HoloLens®

0.001

< 0.05

comparison to video conferencing or emails. In addition, the comparison results for the neutral and agree responses regarding ease-of-use and the disagree and agree responses regarding acceptability showed an evi­ dence of insignificance, both of which indicated a phenomenal consensus in agreement does not exist. 6.2.3. Mean of response at 95% confidence interval To answer the research question as to the extent to which MR im­ proves communication based on the measures of performance, Student’s t-test was performed to determine where the majority of agreements falls given the 5-Likert scales of opinions (i.e., strongly disagree = 0, disagree = 1, neutral = 2, agree = 3, and strongly agree = 4). Table 7 lists the results of 95% confidence interval for the extent of agreement of responses. Using this interval, a range of means were obtained, by which 9

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Table 6 Post Hoc analysis, α = 0.05. Construct Accuracy HoloLens® vs. Phone Calls

HoloLens® vs. Walking up and Talk

HoloLens® vs. Video Conferencing

HoloLens® vs. Email

Efficiency HoloLens® vs. Phone Calls

HoloLens® vs. Walking up and Talk

HoloLens® vs. Video Conferencing

HoloLens® vs. Emails

Ease-of-Use

Acceptability

Table 7 Mean of response at 95% CI, α = 0.05. Category

pvalue

Remarks

Comments

Disagree vs. Neutral Disagree vs. Agree Neutral vs Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs Agree

0.017

< 0.05

Significant

0.001

< 0.05

Significant

0.001

< 0.05

Significant

0.021

< 0.05

Significant

0.001

< 0.05

Significant

0.001

< 0.05

Significant

0.034

< 0.05

Significant

0.001

< 0.05

Significant

0.001

< 0.05

Significant

0.001

< 0.05

Significant

0.001

< 0.05

Significant

0.011

< 0.05

Significant

Disagree vs. Neutral Disagree vs. Agree Neutral vs. Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs. Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs. Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs. Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs. Agree Disagree vs. Neutral Disagree vs. Agree Neutral vs. Agree

0.059

> 0.05

0.001

< 0.05

Not significant Significant

0.001

< 0.05

Significant

0.199

> 0.05

0.001

< 0.05

Not significant Significant

0.001

< 0.05

Significant

0.034

< 0.05

Significant

0.001

< 0.05

Significant

0.213

> 0.05

0.003

< 0.05

Not significant Significant

0.001

< 0.05

Significant

0.549

> 0.05

0.001

< 0.05

Not significant Significant

0.001

< 0.05

Significant

1.000

> 0.05

0.001

< 0.05

Not significant Significant

0.051

> 0.05

0.009

< 0.05

Construct Accuracy HoloLens® vs. Phone calls HoloLens® vs. Walking up and Talk HoloLens® vs. Video Conferencing HoloLens® vs Emails Efficiency HoloLens® vs. Phone calls HoloLens® vs. Walking up and Talk HoloLens® vs. Video Conferencing HoloLens® vs. Emails Ease of Use Acceptability

Mean

Standard Deviation

Mean Range @ 95% Confidence Interval

3.00

0.70

2.91–3.09

2.72

0.89

2.61–2.83

2.86

0.65

2.76–2.96

2.86

0.73

2.74–2.97

2.69

0.91

2.43–2.94

2.53

0.96

2.26–2.81

2.45

0.72

2.19–2.72

2.73 2.38 2.21

0.74 0.79 0.78

2.46–3.01 2.22–2.53 2.09–2.34

The present measurements were taken based on survey that might be subject to biases and external threats to validity. Therefore, the exper­ iment was designed as such that only participants with construction background and experience (rather than populations such as students) were allowed for trial and feedback of this technology. This study also ensured that each participant received the same guidance and walkthrough for testing uniformity. The fact that not many participants had used HoloLens® may lead to biases. By quantifying the effect of neutral responses on all variables, this study provided a needed cushion against type I error. Issues relating to narrow field of view, internet connectivity, and safety of the wearer were among the concerns expressed by participants during site trials. Currently, the MR study in construction is ongoing and the motivation for MR technology transfer is still low. The fact that the construction people are conservative and reluctant to embrace new technologies is challenging. Nevertheless, implementation of this study provided the industrial participants with opportunities of trials of this technology. This helped deliver the firsthand experience to the partici­ pants and might increase their confidence towards using the technology in the future. At the time when the authors undertook this study, Microsoft pro­ vided a Development Edition of HoloLens® that costed $3000 in the U.S. market. This price, together with the cost of a tablet, approximately led to $3500 for implementing the technology into an executable system. Such cost, together with possible training and maintenance and opera­ tional budgets, should be a factor that a contractor needs to consider if s/ he has interests in adopting this system. In the experiments, only one system was implemented because Microsoft allowed only two units maximum to be purchased by each user and the authors only purchased one unit. This study did not investigate requirements for the number of units in a small, mid-size and large construction project. However, the economic feasibility of the system seems to be promising because the optimal safety investment ratio in construction projects is about 1% of the project cost (Shohet et al., 2018) and is certainly higher in small projects. The cost of the system may be feasible in large construction projects for particular high-risk tasks but may be economically feasible if the system can be used for application of safety and quality for example. As technologies advance, it can be foreseen that the cost of the hardware needed in adopting the system will become cheaper and more affordable. The findings of this study added additional knowledge to the con­ struction safety science regarding the industry’s respective on the feasibility, benefits, and limitations of applying MR for safe risk communication in construction workplaces. This may facilitate its improvement and adoption in safety management practices, and

Not significant Significant

ease of use and acceptability. The insignificant difference of the neutral vs. agree responses regarding ease of use and acceptability of HoloLens® may imply that some amendments to features and adequate training are needed for use of MR in construction. It is noteworthy that when the authors were preparing for the manuscript, Microsoft released its 2nd version of HoloLens® that improved a lot in aspects such as field of view, gesture control, weight, wearing time and comfortability. It could be foreseen that as technological maturity advances, the industry agree­ ment on ease of use and acceptability will correspondingly increase. 10

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therefore lead to reduction of the injury and fatality incidences on construction sites. Nevertheless, there are still several caveats observed in this study. One is that the cross-sectional strategy was used for data collection. This strategy offers a quick way to gather enough sample considering the time allotted for undertaking of this study. However, the fact that the participation is only limited to participants from the construction in­ dustry brought about extensive delay in consent and site assess ap­ provals, which caused the duration of data collection beyond the targeted summer window (May-August) when outdoor construction activities were at its peak. To complete the set research plan, a com­ plementary indoor data collection procedure was implemented where open field trials were infeasible. By designating participants into sepa­ rate remote areas of existing facilities where routine collaboration is essential to complete tasks, the participants obtained the needed MR experience to provide opinions for the survey. The second caveat is that the learning curve in the experiments might differ from person to person. The fact that the participants only had a few minutes to experience the MR technology and form opinions may lead to either certain biases or unwillingness to express extreme opin­ ions due to the lack of adequate knowledge of the technology. Despite this, analysis of the post hoc test in this study may help reveal this phenomenon to certain extent. The third caveat is that the participants recruited in this study varied in terms background such as years of experience (2–38 years) and roles (e.g., managers, engineers, and laborers). This might have impacts on their perception and responses to the questions. However, this factor was not considered in this study, which left room for future extension. In specific, the full sample might be split into 3–5 groups (e.g., 4 groups according to years of working experience: 2–5, 6–15, 16–25, 26 and above; 3 groups according to project participant roles: managers, engi­ neers, laborers), and then ANOVA (parametric analysis method) or Kruskal-Wallis H test (nonparametric analysis method) could be applied to quantitatively assess whether or not the responses are influenced by the background (i.e., working experience and project participant roles) of the participants. Also, this study was the first evaluation of the feasibility of applying MR for risk communication in construction settings. It requires adequate training for the participants to adequately master the functionality and operations of MR in construction scenarios. Unfortunately, the limited time and resources at the authors’ disposal meant that they could only give short but uniform training across-the-board so as to reduce varia­ tions as much as possible. Residual biases may however still exist due to insufficient training of the participants. Estimation of variations due to such biases and their specific implication on the results is beyond the scope of this study. Another limitation of using questionnaire survey to collect percep­ tual data is that potential response biases might be generated due to subjectivity and social desirability (i.e., common method bias) (Pod­ sakoff and Organ, 1986). As such, Harman’s one-factor test could be further conducted (i.e., assess whether any single dominant factor emerges) to check that the common method bias is unlikely to be a substantial contaminant of the results. This would be future work for this study.

Acknowledgments This research was funded by the Center for Construction Research and Training (CPWR). The authors acknowledge its support. The authors are also grateful to construction companies who volunteered to partic­ ipate in the experiments and provide feedback in this study. Any opin­ ions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the view of the funding agency and participating companies. References Abdelhamid, T.S., Everett, J.G., 2000. Identifying root causes of construction accidents. J. Constr. Eng. Manage. 126, 52–60. https://doi.org/10.1061/(ASCE)0733-9364 (2000)126:1(52). Ahn, C.R., Lee, S., Sun, C., Jebelli, H., Yang, K., Choi, B., 2019. Wearable sensing technology applications in construction safety and health. J. Constr. Eng. Manage. 145, 03119007. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001708. Albert, A., Pandit, B., Patil, Y., 2020. 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