Application of Internet of Things for Early Detection of COVID-19 using Wearables

Uddin, Taki; Uddin, Md. Borhan; Islam, A.K.M. Muzahidul; Islam, Salekul; Shatabda, Swakkhar

doi:10.1109/icsecs52883.2021.00080

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…IoT devices have the ability to transmit data by connecting wirelessly to a network (Ding et al, 2020;Al-Emran and Ehrenfeld, 2021;Elbasi et al, 2021). Thus, wearable devices, such as head bands, chest bands, and wrist bands (Awotunde et al, 2021;Uddin et al, 2021;Goergen et al, 2022) have been used to collect real-time vital information from people to their smartphones for COVID-19 monitoring and detection. The focus of these technologies is on the health and wellbeing of occupants within a certain area.…”

Section: Detection and Monitoringmentioning

confidence: 99%

“…Detection and monitoring (Arun et al, 2020;Choyon et al, 2020;Dhadge and Tilekar, 2020;Ding et al, 2020;Hossain et al, 2020;Josephine et al, 2020;Karthi and Jayakumar, 2020;Seshadri et al, 2020;Swayamsiddha and Mohanty, 2020;Al-Emran and Ehrenfeld, 2021;Anjali et al, 2021;Ashwin et al, 2021;Awotunde et al, 2021Awotunde et al, , 2022Chakkor et al, 2021a,b;Elbasi et al, 2021;Lo and Sim, 2021;Lubecke et al, 2021;Mukati et al, 2021;Mumtaz et al, 2021;Ni et al, 2021b;Peladarinos et al, 2021;Rehman et al, 2021;Tan et al, 2021;Uddin et al, 2021;Zhang et al, 2021;Dadon et al, 2022;Goergen et al, 2022) Contact tracing Indoor contact tracing (Jeong et al, 2019;Dmitrienko et al, 2020;Kumar et al, 2022;Li et al, 2020b;Otoom et al, 2020;Schmidtke, 2020;Thangamani et al, 2020;Abueg et al, 2021;Lo and Sim, 2021;Mcheick et al, 2021;Wojtusiak et al, 2021) Outdoor contact tracing (Elbir et al, 2020;Maghdid and Ghafoor, 2020;Ting et al, 2020;…”

Section: Section Category Referencesmentioning

confidence: 99%

See 1 more Smart Citation

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Shen

Ghatti

Levkov

et al. 2022

Front. Artif. Intell.

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Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.

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Section: Detection and Monitoringmentioning

confidence: 99%

Section: Section Category Referencesmentioning

confidence: 99%

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Shen

Ghatti

Levkov

et al. 2022

Front. Artif. Intell.

View full text Add to dashboard Cite

show abstract

“…As a key component of HealthIIoT, a wireless medical sensor network (WMSN) has been implemented to assist in containing the spread of COVID-19. Since early diagnosis and isolation are effective and imperative strategies for epidemic prevention and control, WMSN can effectively identity those who exhibit symptoms and are most likely to be infected with the virus, and help the diagnosis system to automatically collect COVID-19 data [7,8]. HealthIIoT is thus profoundly changing the healthcare industry.…”

Section: Introductionmentioning

confidence: 99%

Public auditing for real-time medical sensor data in cloud-assisted HealthIIoT system

Wang

Tian

et al. 2022

Front. Optoelectron.

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With the advancement of industrial internet of things (IIoT), wireless medical sensor networks (WMSNs) have been widely introduced in modern healthcare systems to collect real-time medical data from patients, which is known as HealthIIoT. Considering the limited computing and storage capabilities of lightweight HealthIIoT devices, it is necessary to upload these data to remote cloud servers for storage and maintenance. However, there are still some serious security issues within outsourcing medical sensor data to the cloud. One of the most significant challenges is how to ensure the integrity of these data, which is a prerequisite for providing precise medical diagnosis and treatment. To meet this challenge, we propose a novel and efficient public auditing scheme, which is suitable for cloud-assisted HealthIIoT system. Specifically, to address the contradiction between the high real-time requirement of medical sensor data and the limited computing power of HealthIIoT devices, a new online/offline tag generation algorithm is designed to improve preprocessing efficiency; to protect medical data privacy, a secure hash function is employed to blind the data proof. We formally prove the security of the presented scheme, and evaluate the performance through detailed experimental comparisons with the state-of-the-art ones. The results show that the presented scheme can greatly improve the efficiency of tag generation, while achieving better auditing performance than previous schemes. Graphical abstract

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Application of Internet of Things for Early Detection of COVID-19 using Wearables

Cited by 2 publications

References 18 publications

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Public auditing for real-time medical sensor data in cloud-assisted HealthIIoT system

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