Development of the Internet of Things sensory technology for ensuring proper indoor air quality in hospital facilities: Taxonomy analysis, challenges, motivations, open issues and recommended solution

Baqer, Noor S.; Mohammed, Hussein A.; Albahri, A. S.; Zaidan, A. A.; Al-qaysi, Z.T.; Albahri, O. S.

doi:10.1016/j.measurement.2022.110920

Cited by 30 publications

(9 citation statements)

References 37 publications

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“…The researchers avoided relying on a single database to find literature in the review article, as all relevant references may not be included, so a supplementary search is often necessary [ 32 , 40 ]. According to studies [ 36 , 41 – 43 ], a review should be conducted across multiple databases to capture the majority of publications. The study used the ScienceDirect, PubMed, and IEEE databases for a detailed literature review of articles between 2010 and 2021.…”

Section: Methodsmentioning

confidence: 99%

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology

Albahri

Al-qaysi

Alzubaidi

et al. 2023

International Journal of Telemedicine and Applications

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The significance of deep learning techniques in relation to steady-state visually evoked potential- (SSVEP-) based brain-computer interface (BCI) applications is assessed through a systematic review. Three reliable databases, PubMed, ScienceDirect, and IEEE, were considered to gather relevant scientific and theoretical articles. Initially, 125 papers were found between 2010 and 2021 related to this integrated research field. After the filtering process, only 30 articles were identified and classified into five categories based on their type of deep learning methods. The first category, convolutional neural network (CNN), accounts for 70% ( n = 21 / 30 ). The second category, recurrent neural network (RNN), accounts for 10% ( n = 3 / 30 ). The third and fourth categories, deep neural network (DNN) and long short-term memory (LSTM), account for 6% ( n = 30 ). The fifth category, restricted Boltzmann machine (RBM), accounts for 3% ( n = 1 / 30 ). The literature’s findings in terms of the main aspects identified in existing applications of deep learning pattern recognition techniques in SSVEP-based BCI, such as feature extraction, classification, activation functions, validation methods, and achieved classification accuracies, are examined. A comprehensive mapping analysis was also conducted, which identified six categories. Current challenges of ensuring trustworthy deep learning in SSVEP-based BCI applications were discussed, and recommendations were provided to researchers and developers. The study critically reviews the current unsolved issues of SSVEP-based BCI applications in terms of development challenges based on deep learning techniques and selection challenges based on multicriteria decision-making (MCDM). A trust proposal solution is presented with three methodology phases for evaluating and benchmarking SSVEP-based BCI applications using fuzzy decision-making techniques. Valuable insights and recommendations for researchers and developers in the SSVEP-based BCI and deep learning are provided.

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Section: Methodsmentioning

confidence: 99%

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology

Albahri

Al-qaysi

Alzubaidi

et al. 2023

International Journal of Telemedicine and Applications

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“…The emotions and thoughts of city life can also be expressed through perceptual art. As a place where human beings gather, the city is a place where individuals live and grow (Baqer et al, 2022). Urban Perception Art presents the individual's perception and attitude towards urban life through the artist's emotional experience and thoughts about the urban environment.…”

Section: Concept and Significance Of Urban Perceptual Artmentioning

confidence: 99%

Realization of Urban Perception Art: Painting Expressions of Internet of Things Technologies in Urban Environments

Zhu,

Yao

2024

ICST Transactions on Scalable Information Systems

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INTRODUCTION: With the continuous progress of urbanization, people's perceptions and experiences of the urban environment are increasingly concerned. Traditional forms of artistic expression can no longer fully meet people's needs for urban perception. Therefore, it is especially important to explore new possibilities of urban perception art with the help of modern technology, especially intelligent technology.OBJECTIVES: The main purpose of this study is to explore the feasibility and effectiveness of utilizing advanced technology for urban perception art expression. Through an in-depth understanding of the urban environment and the perceptual needs of urban residents, as well as existing technological means, artistic expressions that can present urban perceptions more intuitively and vividly are developed.METHODS: This study adopts a combination of field research and art practice. Through urban observation and questionnaire surveys, the subjective experience and needs of urban residents for urban perception were collected. Then, using digital painting and video technology, combined with the principles of perception psychology, urban perception works with artistic and technological senses were designed.RESULTS: A series of urban perception artworks were designed in this study, covering all aspects of urban life, including architectural landscapes, transportation scenes, and humanistic customs. These works enable viewers to perceive the urban environment in a more intuitive and immersive way through digital painting and video technology, as well as real-time data and perceptual feedback.CONCLUSION: By exploring new ways of artistic expression of urban perception, this study provides urban residents with a richer and deeper experience of urban perception. The application of digital painting and video technology, as well as the interaction and feedback with urban residents, opens up new possibilities for the development of urban perceptual art.

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“…Smart systems and occupant feedback are essential for improving IAQ and multi-domain IEQ factors. IoT-based sensory technology plays a vital role in monitoring and maintaining IAQ by ensuring the proper deployment of sensors and devices [247]. Smart technologies, such as advanced air distribution, air cleaning, modularization of indoor environmental devices/systems, and sensing systems, help optimize IAQ alongside conventional performance indicators [6].…”

Section: Strategies For Optimizing Human Productivitymentioning

confidence: 99%

Impact of Indoor Air Quality and Multi-domain Factors on Human Productivity and Physiological Responses: A Comprehensive Review

Deng,

Dong,

Guo

et al. 2024

Indoor Air

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Indoor environmental quality (IEQ) significantly impacts human health, well-being, and productivity. However, a comprehensive and in-depth review of the combined effects of IAQ and other multi-domain factors on human productivity is lacking. There has not been any prior review that encapsulates the impact of multi-domain factors on productivity and physiological responses of occupants. To address this gap, this review paper investigates and highlights the impact of IAQ and multi-domain factors (thermal, visual, and acoustic) on human productivity and occupant well-being in the built environment. The review explores various research methods, including evaluation of human productivity and creativity, data collection, and physiological signal analysis. We also examined the interactions between IAQ and multi-domain factors, as well as strategies for optimizing productivity through integrated building design and smart systems. The key findings from this review reveal that IAQ significantly impacts human productivity and occupant well-being, with interactions between IAQ and other IEQ factors further impacting these effects. Despite advances in the field, there are several limitations and gaps in the current research methods and study designs, including small sample sizes, limited and insufficient experimental design and control, reliance on laboratory or simulated environments, lack of follow-up and long-term data, and lack of robust performance metrics. The review proposes future research directions, including specific applications, and follow-up work to address these limitations and further advance the understanding of IAQ and multi-domain factors in the built environment. The implications of this review for policy and practice include the need for holistic and integrated approaches to IAQ and IEQ management, with a focus on creating healthy and productive indoor environments. This review emphasizes the importance of considering the complex interplay between IAQ and multi-domain factors, as well as the potentials of adopting smart control systems and sustainable design strategies to optimize productivity and occupant well-being in the built environment. By addressing these critical issues, we can enhance the overall quality of life for building occupants and contribute to a more sustainable future.

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Development of the Internet of Things sensory technology for ensuring proper indoor air quality in hospital facilities: Taxonomy analysis, challenges, motivations, open issues and recommended solution

Cited by 30 publications

References 37 publications

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology

Realization of Urban Perception Art: Painting Expressions of Internet of Things Technologies in Urban Environments

Impact of Indoor Air Quality and Multi-domain Factors on Human Productivity and Physiological Responses: A Comprehensive Review

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