vContact: Private WiFi-Based IoT Contact Tracing With Virus Lifespan

Li, G.; Hu, Siyan; Zhong, Shuhan; Tsui, W. L.; Chan, S.-H. Gary

doi:10.1109/jiot.2021.3100276

Cited by 24 publications

(22 citation statements)

References 18 publications

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“…The

weights choice is a more qualitative problem, and it may require the social-psychology perspective in choosing it adequately. While the

distances are today easily measured via positioning or proximity-detection sensors, as can be seen in recent examples in [ 85 , 86 , 87 , 88 ], the measurements of

are less trivial and may require various underlying models and inter-dependencies of various parameters related to loneliness. Some of those parameters are discussed further in Section 4.4 and Table 2 , and a survey of possible sensors to measure

and

parameters is further given in Section 5 .…”

Section: Loneliness Measures and Metricsmentioning

confidence: 99%

Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions

Site

Lohan

Jolanki

et al. 2022

Sensors

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As an inevitable process, the number of older adults is increasing in many countries worldwide. Two of the main problems that society is being confronted with more and more, in this respect, are the inter-related aspects of feelings of loneliness and social isolation among older adults. In particular, the ongoing COVID-19 crisis and its associated restrictions have exacerbated the loneliness and social-isolation problems. This paper is first and foremost a comprehensive survey of loneliness monitoring and management solutions, from the multidisciplinary perspective of technology, gerontology, socio-psychology, and urban built environment. In addition, our paper also investigates machine learning-based technological solutions with wearable-sensor data, suitable to measure, monitor, manage, and/or diminish the levels of loneliness and social isolation, when one also considers the constraints and characteristics coming from social science, gerontology, and architecture/urban built environments points of view. Compared to the existing state of the art, our work is unique from the cross-disciplinary point of view, because our authors’ team combines the expertise from four distinct domains, i.e., gerontology, social psychology, architecture, and wireless technology in addressing the two inter-related problems of loneliness and social isolation in older adults. This work combines a cross-disciplinary survey of the literature in the four aforementioned domains with a proposed wearable-based technological solution, introduced first as a generic framework and, then, exemplified through a simple proof of concept with dummy data. As the main findings, we provide a comprehensive view on challenges and solutions in utilizing various technologies, particularly those carried by users, also known as wearables, to measure, manage, and/or diminish the social isolation and the perceived loneliness among older adults. In addition, we also summarize the identified solutions which can be used for measuring and monitoring various loneliness- and social isolation-related metrics, and we present and validate, through a simple proof-of-concept mechanism, an approach based on machine learning for predicting and estimating loneliness levels. Open research issues in this field are also discussed.

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“…The

weights choice is a more qualitative problem, and it may require the social-psychology perspective in choosing it adequately. While the

distances are today easily measured via positioning or proximity-detection sensors, as can be seen in recent examples in [ 85 , 86 , 87 , 88 ], the measurements of

and

parameters is further given in Section 5 .…”

Section: Loneliness Measures and Metricsmentioning

confidence: 99%

Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions

Site

Lohan

Jolanki

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Upon diagnosis of a user, the ENACT server performs a matching of the tags which reveals people who had close contacts. A similar study was carried out by [ 88 ] where the authors proposed VContact, a Wi-Fi-based contact tracing protocol. In this protocol, Wi-Fi provides the communication platform for some internet of things (IoT) devices such as smartphones, smart wristwatches e.t.c which perform the sensing of close devices.…”

Section: Technology-based Contact Tracing Methods Against Covid-19mentioning

confidence: 89%

Non-Pharmaceutical Interventions against COVID-19 Pandemic: Review of Contact Tracing and Social Distancing Technologies, Protocols, Apps, Security and Open Research Directions

Alo¹,

Nkwo²,

Nweke

et al. 2021

Sensors

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The COVID-19 Pandemic has punched a devastating blow on the majority of the world’s population. Millions of people have been infected while hundreds of thousands have died of the disease throwing many families into mourning and other psychological torments. It has also crippled the economy of many countries of the world leading to job losses, high inflation, and dwindling Gross Domestic Product (GDP). The duo of social distancing and contact tracing are the major technological-based non-pharmaceutical public health intervention strategies adopted for combating the dreaded disease. These technologies have been deployed by different countries around the world to achieve effective and efficient means of maintaining appropriate distance and tracking the transmission pattern of the diseases or identifying those at high risk of infecting others. This paper aims to synthesize the research efforts on contact tracing and social distancing to minimize the spread of COVID-19. The paper critically and comprehensively reviews contact tracing technologies, protocols, and mobile applications (apps) that were recently developed and deployed against the coronavirus disease. Furthermore, the paper discusses social distancing technologies, appropriate methods to maintain distances, regulations, isolation/quarantine, and interaction strategies. In addition, the paper highlights different security/privacy vulnerabilities identified in contact tracing and social distancing technologies and solutions against these vulnerabilities. We also x-rayed the strengths and weaknesses of the various technologies concerning their application in contact tracing and social distancing. Finally, the paper proposed insightful recommendations and open research directions in contact tracing and social distancing that could assist researchers, developers, and governments in implementing new technological methods to combat the menace of COVID-19.

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“…Furthermore, a graph search algorithm takes the user's trajectory and produces a location and proximity report of the exposed users. Other research groups have used Wi-Fi based smartphone applications [21] to capture beacon frames from nearby APs and upload the data to the cloud. This allows the authorities to track the visited places and the positions of the confirmed cases.…”

Section: Contact Tracingmentioning

confidence: 99%

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

Yuen¹,

Bie²,

Cairns³

et al. 2022

Preprint

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A custom Wi-Fi and Bluetooth indoor contact tracing system is created to find detailed paths of infected individuals without any user intervention. The system tracks smartphones, but it does not require smartphone applications, connecting to the routers, or any other extraneous devices on the users. A custom Turtlebot3 is used for site surveying, where it simulates mobile device movement and packet transmission. Transmit power, receive power, and round trip time are collected by a custom ESP32C3 router. MAC randomization is defeated to identify unique smartphones. Subsequently, the wireless parameters above are converted to signal path loss and time of flight. Bidirectional long short term memory takes the wireless parameters and predicts the detailed paths of the users within 1 m. Public health authorities can use the contact tracing website to find the detailed paths of the suspected cases using the smartphone models and initial positions of confirm cases. The system can also track indirect contact transmissions originating from surfaces and droplets due to having absolute positions of users.

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vContact: Private WiFi-Based IoT Contact Tracing With Virus Lifespan

Cited by 24 publications

References 18 publications

Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions

Managing Perceived Loneliness and Social-Isolation Levels for Older Adults: A Survey with Focus on Wearables-Based Solutions

Non-Pharmaceutical Interventions against COVID-19 Pandemic: Review of Contact Tracing and Social Distancing Technologies, Protocols, Apps, Security and Open Research Directions

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

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