Cognitive ergonomics-based Augmented Reality application for construction performance

Wu, Shaoze; Hou, Lei; Chen, Haosen; Zhang, Guomin; Yang, Ziqiang; Tushar, Quddus

doi:10.1016/j.autcon.2023.104802

Cited by 13 publications

(4 citation statements)

References 46 publications

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“…These advancements in wearable sensor technology have paved the way for applications in healthcare monitoring, disease diagnostics, and HMI [30][31][32][33]. Overall, wearable sensors have the potential to play a transformative role in healthcare and ergonomics, offering continuous, non-invasive monitoring of physiological signals of individuals [31,34]. Importantly, it should be noted that CW monitoring through behavioral and gesture analysis has been proposed so far.…”

Section: Physiological Signals Acquired Through Wearable Sensors For Hmimentioning

confidence: 99%

An Overview of Approaches and Methods for the Cognitive Workload Estimation in Human–Machine Interaction Scenarios through Wearables Sensors

Iarlori,

Perpetuini,

Tritto

et al. 2024

BioMedInformatics

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Background: Human-Machine Interaction (HMI) has been an important field of research in recent years, since machines will continue to be embedded in many human actvities in several contexts, such as industry and healthcare. Monitoring in an ecological mannerthe cognitive workload (CW) of users, who interact with machines, is crucial to assess their level of engagement in activities and the required effort, with the goal of preventing stressful circumstances. This study provides a comprehensive analysis of the assessment of CW using wearable sensors in HMI. Methods: this narrative review explores several techniques and procedures for collecting physiological data through wearable sensors with the possibility to integrate these multiple physiological signals, providing a multimodal monitoring of the individuals’CW. Finally, it focuses on the impact of artificial intelligence methods in the physiological signals data analysis to provide models of the CW to be exploited in HMI. Results: the review provided a comprehensive evaluation of the wearables, physiological signals, and methods of data analysis for CW evaluation in HMI. Conclusion: the literature highlighted the feasibility of employing wearable sensors to collect physiological signals for an ecological CW monitoring in HMI scenarios. However, challenges remain in standardizing these measures across different populations and contexts.

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Section: Physiological Signals Acquired Through Wearable Sensors For Hmimentioning

confidence: 99%

An Overview of Approaches and Methods for the Cognitive Workload Estimation in Human–Machine Interaction Scenarios through Wearables Sensors

Iarlori,

Perpetuini,

Tritto

et al. 2024

BioMedInformatics

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“…After evaluating the situation, workers will select and execute one of the options to avoid the risk of work accidents in the construction area. [48].…”

Section: Augmented Realitymentioning

confidence: 99%

Literature review: A study of cognitive aspects in minimizing human error in construction

Zahra Mutmainah,

Pramudya,

Akbar Rufa’i

2024

SHS Web Conf.

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Human error is a mistake due to human negligence, both consciously and unconsciously, which can cause a system to experience disruption and not run as planned. These errors can occur at the managerial, conceptual, or technical level. One of the activities with a high potential for finding human error is construction activities. Construction activities are a series of activities that include the construction, operation, maintenance, demolition, and construction of a building. Infrastructure development is one of the government’s policy focuses in 2023, with development from four main areas: water resources, roads and bridges, settlements, and housing. These infrastructure projects must have a good quality because they are closely related to user safety and security. Based on data from the Social Security Organizing Agency (BPJS) Employment and statements from the Ministry of PUPR, the industrial sector is an enormous contributor to work accidents with an average percentage of 32% each year. The human factor is one of the forerunners of human error apart from equipment and working environment conditions. Viewed from the perspective of Cognitive System Engineering, human error is caused by the failure of human cognitive processes where the process is related to Human Information Processing (HIP). This paper will describe and briefly discuss the problem of human error and its relation to Human Information Processing (HIP). This paper will examine various literature and summarize efforts that can be applied to improve the information processing process in the hope of minimizing the occurrence of human error in the scope of construction work.

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“…A digital twin is an isolated specialised theme that integrates advanced technology in sustainable building construction. Connecting links to this theme, building information modelling, and building information management were implemented in several studies to formulate energy-efficient carbonneutral buildings [117,118] (Figure 9h). The design of residential buildings as zero-energy, carbon emissions-free buildings, and the optimisation of energy, models, and environmental impacts were prominent research themes in this phase [119][120][121][122][123].…”

Section: Third Phase (2017-2023)mentioning

confidence: 99%

A Review of Evaluative Measures of Carbon-Neutral Buildings: The Bibliometric and Science Mapping Analysis towards Sustainability

Tushar,

Zhang,

Navaratnam

et al. 2023

Sustainability

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This study aims to comprehensively depict a thematic evaluation within the context of carbon-neutral buildings over this century at variable time phases (2000–2008, 2009–2016, and 2017–2023). The overarching objectives of this study are delineated into three (3) contexts. Firstly, a bibliometric network encompassing influential research documents, authors, prominent journals, organisations, and countries is erected in pertinent fields. Secondly, significant terms are extracted from the scientific literature to exhibit co-occurrence patterns. Finally, an analysis of the evaluative clusters across variable phases was conducted to ascertain their intricate interrelations. The software tool VOSviewer Version 1.6.19 successfully achieves the initial objectives by visualising networks based on co-authorship, citations, co-citations, and bibliographic coupling. The ultimate goal of this research is fully realised through the application of the Science Mapping Analysis Tool (SciMAT), Version 3, which facilitated the evaluation of diverse clusters, phases, and thematic domains. The findings from the initial stages of research conducted on carbon-neutral buildings primarily revolve around energy-savings measures, environmental impacts, and the pursuit of energy-efficient design. As the research progressed into subsequent phases, the scope of inquiry broadened into specific themes, such as (1) optimisation, (2) retrofitting, (3) transitioning, and exploring (4) phase change materials (PCMs). Moreover, the areas of study continued to expand by developing diverse scenarios, algorithms, and digital twin technologies. The graphical representations of the strategic diagrams, evaluation areas, and cluster networks are a valuable resource for practitioners and policymakers, offering valuable insight and understanding of the multifaceted landscape of thematic evaluation in carbon-neutral buildings, thus facilitating further investigations and informed decision making.

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Cognitive ergonomics-based Augmented Reality application for construction performance

Cited by 13 publications

References 46 publications

An Overview of Approaches and Methods for the Cognitive Workload Estimation in Human–Machine Interaction Scenarios through Wearables Sensors

An Overview of Approaches and Methods for the Cognitive Workload Estimation in Human–Machine Interaction Scenarios through Wearables Sensors

Literature review: A study of cognitive aspects in minimizing human error in construction

A Review of Evaluative Measures of Carbon-Neutral Buildings: The Bibliometric and Science Mapping Analysis towards Sustainability

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