Opportunities and challenges for the building monitoring systems in the age-pandemic of COVID-19: Review and prospects

Saud, S. N.; Kamal, Ahmad Aiman A.

doi:10.1007/s41062-020-00454-0

Cited by 22 publications

(11 citation statements)

References 17 publications

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“…Our scientific work focuses on applications based on wearable devices for fighting the COVID-19 pandemic, including the extremely popular mobile tracing applications, unlike similar review papers that cover other monitoring solutions (drones, robotic applications, etc.) (Nasajpour et al, 2020;Al-Humairi and Kamal, 2021). Furthermore, review papers covering the same topics do not always consider commercial devices, including intelligent masks, which are extensively investigated in this paper (Chamola et al, 2020;Kumar et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Fazio

Giannoccaro

Carrasco

et al. 2021

Front Inform Technol Electron Eng

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Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics.

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Section: Discussionmentioning

confidence: 99%

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Fazio

Giannoccaro

Carrasco

et al. 2021

Front Inform Technol Electron Eng

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“…e study in [53] proposes the construction of intelligent infrastructure. For example, it can be used in buildings, apartments, hotels, large shopping malls, and so on.…”

Section: Public and Social Management Under The Pandemicmentioning

confidence: 99%

“…Therefore, it is very necessary to exploit AIoT to improve the intelligence of infrastructure and maintain social security and stability. The study in [ 53 ] proposes the construction of intelligent infrastructure. For example, it can be used in buildings, apartments, hotels, large shopping malls, and so on.…”

Section: Aiot and Social Lifementioning

confidence: 99%

AIoT Used for COVID-19 Pandemic Prevention and Control

Chen

Wang

et al. 2021

Contrast Media & Molecular Imaging

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The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a vital role in preventing the spread of the pandemic of COVID-19. AI and 5G technologies are advancing by leaps and bounds, further strengthening the intelligence and connectivity of IoT applications, and conventional IoT has been gradually upgraded to be more powerful AI + IoT (AIoT). For example, in terms of remote screening and diagnosis of COVID-19 patients, AI technology based on machine learning and deep learning has recently upgraded medical equipment significantly and has reshaped the workflow with minimal contact with patients, so medical specialists can make clinical decisions more efficiently, providing the best protection not only to patients but also to specialists themselves. This paper reviews the latest progress made in combating COVID-19 with both IoT and AI and also provides comprehensive details on how to combat the pandemic of COVID-19 as well as the technologies that may be applied in the future.

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“…Many kinds of research have been conducted on how to obtain a thermal image of high quality, which is needed in a wide range of applications: face detection and tracking [1], breast abnormality evaluation [2], pipeline leak recognition [3], and advanced driver assistance systems [4][5][6]. Recently, due to the COVID-19 pandemic, the demand for thermalbased technologies, such as contactless body temperature acquisition, has been substantially increased [7][8][9]. As the thermal images are robust to the dark illumination environment and also have the merit of containing the thermal information of an object, they have been playing an important role in addressing the limitations of visual sensors.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Ensemble Learning for Thermal Image Enhancement

Ban

Lee

2021

Applied Sciences

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In this study, we propose a multi-scale ensemble learning method for thermal image enhancement in different image scale conditions based on convolutional neural networks. Incorporating the multiple scales of thermal images has been a tricky task so that methods have been individually trained and evaluated for each scale. However, this leads to the limitation that a network properly operates on a specific scale. To address this issue, a novel parallel architecture leveraging the confidence maps of multiple scales have been introduced to train a network that operates well in varying scale conditions. The experimental results show that our proposed method outperforms the conventional thermal image enhancement methods. The evaluation is presented both quantitatively and qualitatively.

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Opportunities and challenges for the building monitoring systems in the age-pandemic of COVID-19: Review and prospects

Cited by 22 publications

References 17 publications

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

AIoT Used for COVID-19 Pandemic Prevention and Control

Multi-Scale Ensemble Learning for Thermal Image Enhancement

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