Promoting employee health in smart office: A survey

Zhang, Xiangying; Zheng, Pai; Peng, Tao; He, Qiqi; Lee, C.K.M.; Tang, Renzhong

doi:10.1016/j.aei.2021.101518

Cited by 31 publications

(10 citation statements)

References 84 publications

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“…Extraocular symptoms were consistent with our research. (15) In our study, 33% of students reported experiencing a burning sensation, which is comparable to a previous study where 32% of medical students reported experiencing a burning sensation. (16) According to another study c, only 28.9% of the participants reported experiencing a burning sensation, which is a relatively low prevalence.…”

Section: Discussionsupporting

confidence: 88%

Risk Factors of Computer Vision Syndrome and its Prevention

Imran¹,

Khan²,

Zaib³

et al. 2023

PJMHS

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Background: The 21st century is thought to need these gadgets. They are employed in households, as well as in recreational settings and educational organizations, in addition to workplaces and businesses. The term "video display terminal" is used to refer to a computer screen (VDT). It includes computers, tablets, e-readers, smartphones, and other electronic gadgets. According to estimates, 45 million employees use computers directly by gazing at VDTs nonstop for long periods. Aim: The goal of this study was to count how many CMT (college of Medical Technology) students have computer vision syndrome and to identify the risk factors that go along with it. Methods: This cross-sectional research was conducted on 198 CMT students at Pakistan institute of Medical Sciences, Islamabad, Pakistan, from 1st April 2022, to 30th September, 2022. The research covered all students between the ages of 17 and 25 who had used a computer in the month before the programs start date. Those students who were using eye medications, those with underlying systemic conditions like diabetes or hypertension, those with pre-existing eye problems, and those who did not provide informed written permission were excluded from the study. To demonstrate relationships between categorical data, the chi-square test was performed. The SPSS version 23 was used to analyze the data. Results: Age of 20.16 ± 3.81 years on average. Out of 198 respondents, 133 (67.2%) said they had at least one of the following symptoms of computer vision syndrome: headache, eye tiredness, burning, eye irritation, neck discomfort, and shoulder pain. Computer users' eye complaints included eye irritability (48%), burning (33%), and eye weariness (15%). Extraocular symptoms range from headaches (38%) to neck and shoulder discomfort (21.8%). Computer use time (240 minutes/four hours) was substantially correlated with eye tiredness and headache. Practical Implication: The benefit of this study is to identify the risk variables linked with computer vision syndrome and its incidence among undergraduate medical students. It will aid in raising public awareness of the health risks associated with computers and other digital electronic devices, as well as assisting public health experts and other stakeholders in taking action to address this public health problem Conclusions: The ailment known as "Computer Vision Syndrome" affects a lot of young students who use computer regularly Keywords: Computer Vision Syndrome, Risk, Prevention, households, irritability, pain, eye tiredness, .

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Section: Discussionsupporting

confidence: 88%

Risk Factors of Computer Vision Syndrome and its Prevention

Imran¹,

Khan²,

Zaib³

et al. 2023

PJMHS

View full text Add to dashboard Cite

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“…A company can leverage these technologies to improve the comfort and well-being of the workers, which may result in higher performance and productivity [4]. With this aim, smart offices must efficiently and proactively manage the infrastructure deployed in the workplace and the enterprise systems [27]. The scientific literature shows different approaches addressing smart offices and identifies the main challenges to tackle in the design, implementation, and optimization of these systems [28][29][30][31].…”

Section: Smart Officesmentioning

confidence: 99%

Semantic Modeling of a VLC-Enabled Task Automation Platform for Smart Offices

Muñoz

Iglesias

Scheianu³

et al. 2022

Electronics

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The evolution of ambient intelligence has introduced a range of new opportunities to improve people’s well-being. One of these opportunities is the use of these technologies to enhance workplaces and improve employees’ comfort and productivity. However, these technologies often entail two major challenges: the requirement for fast and reliable data transmission between the vast number of devices connected simultaneously, and the interoperability between these devices. Conventional communication technologies present some drawbacks in these kinds of systems, such as lower data rates and electromagnetic interference, which have prompted research into new wireless communication technologies. One of these technologies is visible light communication (VLC), which uses existing light in an environment to transmit data. Its characteristics make it an up-and-coming technology for IoT services but also aggravate the interoperability challenge. To facilitate the continuous communication of the enormous amount of heterogeneous data generated, highly agile data models are required. The semantic approach tackles this problem by switching from ad hoc application-centric representation models and formats to a formal definition of concepts and relationships. This paper aims to advance the state of the art by proposing a semantic vocabulary for an intelligent automation platform with VLC enabled, which benefits from the advantages of VLC while ensuring the scalability and interoperability of all system components. Thus, the main contributions of this work are threefold: (i) the design and definition of a semantic model for an automation platform; (ii) the development of a prototype automation platform based on a VLC-based communication system; and (iii) the integration and validation of the proposed semantic model in the VLC-based automation platform.

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“…Data-driven modelling approaches are widely used in many disciplines [6][7][8][9][10]. Therefore, data-driven approaches have been effectively applied in predictive maintenance [11,12], especially fault diagnosis [13,14].…”

Section: Data-driven Modelling Approaches With Limited Datamentioning

confidence: 99%

Privacy‐preserving gradient boosting tree: Vertical federated learning for collaborative bearing fault diagnosis

Xia

Zheng

et al. 2022

IET Collab Intel Manufact

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Data-driven fault diagnosis approaches have been widely adopted due to their persuasive performance. However, data are always insufficient to develop effective fault diagnosis models in real manufacturing scenarios. Despite numerous approaches that have been offered to mitigate the negative effects of insufficient data, the most challenging issue lies in how to break down the data silos to enlarge data volume while preserving data privacy. To address this issue, a vertical federated learning (FL) model, privacy-preserving boosting tree, has been developed for collaborative fault diagnosis of industrial practitioners while maintaining anonymity. Only the model information will be shared under the homomorphic encryption protocol, safeguarding data privacy while retaining high accuracy. Besides, an Autoencoder model is provided to encourage practitioners to contribute and then improve model performance. Two bearing fault case studies are conducted to demonstrate the superiority of the proposed approach by comparing it with typical scenarios. This present study's findings offer industrial practitioners insights into investigating the vertical FL in fault diagnosis.

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Promoting employee health in smart office: A survey

Cited by 31 publications

References 84 publications

Risk Factors of Computer Vision Syndrome and its Prevention

Risk Factors of Computer Vision Syndrome and its Prevention

Semantic Modeling of a VLC-Enabled Task Automation Platform for Smart Offices

Privacy‐preserving gradient boosting tree: Vertical federated learning for collaborative bearing fault diagnosis

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