A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues

Nguyen, Cong T.; Saputra, Yuris Mulya; Huynh, Nguyễn Văn; Nguyen, Nhan T.; Khoa, Tran Viet; Tuan, Bui Minh; Nguyen, Diep N.; Hoang, Dinh Thai; Vu, Thang X.; Dutkiewicz, Eryk; Chatzinotas, Symeon; Ottersten, Björn

doi:10.1109/access.2020.3018124

Cited by 84 publications

(65 citation statements)

References 156 publications

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“…We selected cameras at busy locations where the risk of social distancing directives is arguably highest, which may have inflated the violation rate. To enable the collection and processing of data about physical proximity between people on a larger scale, promising technologies are ultra-wideband, Bluetooth, pedestrian tracking sensors, and machine learning [ 8 , 9 , 61 , 62 ].…”

Section: Discussionmentioning

confidence: 99%

Social distancing compliance: A video observational analysis

et al. 2021

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Purpose Virus epidemics may be mitigated if people comply with directives to stay at home and keep their distance from strangers in public. As such, there is a public health interest in social distancing compliance. The available evidence on distancing practices in public space is limited, however, by the lack of observational data. Here, we apply video observation as a method to examine to what extent members of the public comply with social distancing directives. Data Closed Circuit Television (CCTV) footage of interactions in public was collected in inner-city Amsterdam, the Netherlands. From the footage, we observed instances of people violating the 1.5-meter distance directives in the weeks before, during, and after these directives were introduced to mitigate the COVID-19 pandemic. Results We find that people complied with the 1.5-meter distance directives when these directives were first introduced, but that the level of compliance started to decline soon after. We also find that violation of the 1.5-meter distance directives is strongly associated with the number of people observed on the street and with non-compliance to stay-at-home directives, operationalized with large-scale aggregated location data from cell phones. All three measures correlate to a varying extent with temporal patterns in the transmission of the COVID-19 virus, temperature, COVID-19 related Google search queries, and media attention to the topic. Conclusion Compliance with 1.5 meter distance directives is short-lived and coincides with the number of people on the street and with compliance to stay-at-home directives. Potential implications of these findings are that keep- distance directives may work best in combination with stay-at-home directives and place-specific crowd-control strategies, and that the number of people on the street and community-wide mobility as captured with cell phone data offer easily measurable proxies for the extent to which people keep sufficient physical distance from others at specific times and locations.

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Section: Discussionmentioning

confidence: 99%

Social distancing compliance: A video observational analysis

et al. 2021

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“…Many cities have already transformed into “smart” digital/virtual hubs in which the most of services are provided online with limitations of citizen contacts (PricewaterhouseCoopers 2016 ; McClellan et al 2017 ; Smart City Index 2020 ; Smart Cities World City Profiles 2020 ). Smart city approaches have been elaborated to face health care challenges (Islam et al 2015 ; Baker et al 2017 ; Marjani et al 2017 ; Cook et al 2018 ; Allen et al 2019 ; Akyildiz et al 2020 ) and to resist pandemic outbreak expansion with accents on data (Costa and Peixoto 2020 ; Webb and Toh 2020 ), social distancing (Cecilia et al 2020 ; Nguyen et al 2020a , b ), Internet of Things (IoT) and Artificial Intelligence (AI) (Chamola et al 2020 ; Tropea and De Rango 2020 ), smart health care devices (Jaiswal et al 2020 ), and waste management (Onoda 2020 ). Data governance and digital services ensure city life safe without an economy lockout and unemployment.…”

Section: Introduction: the Era Of Smart Citiesmentioning

confidence: 99%

Sociological modeling of smart city with the implementation of UN sustainable development goals

Kolesnichenko

Mazelis

Sotnik³

et al. 2021

Sustain Sci

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The COVID-19 pandemic before mass vaccination can be restrained only by the limitation of contacts between people, which makes the digital economy a key condition for survival. More than half of the world’s population lives in urban areas, and many cities have already transformed into “smart” digital/virtual hubs. Digital services ensure city life safe without an economy lockout and unemployment. Urban society strives to be safe, sustainable, well-being, and healthy. We set the task to construct a hybrid sociological and technological concept of a smart city with matched solutions, complementary to each other. Our modeling with the elaborated digital architectures and with the bionic solution for ensuring sufficient data governance showed that a smart city in comparison with the traditional city is tightly interconnected inside like a social “organism”. Society has entered a decisive decade during which the world will change by moving closer towards SDGs targets 2030 as well as by the transformation of cities and their digital infrastructures. It is important to recognize the large vector of sociological transformation as smart cities are just a transition phase to human-centered personal space or smart home. The “atomization” of the world urban population raises the gap problem in achieving SDGs because of different approaches to constructing digital architectures for smart cities or smart homes in countries. The strategy of creating smart cities should bring each citizen closer to SDGs at the individual level, laying in the personal space the principles of sustainable development and wellness of personality.

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“…Despite the large number of recent vision-based solutions for COVID-19, 68 the risk level assessment for a particular environment is neither defined nor addressed properly. Comparing different environments (using a combination of vision techniques for social distancing, face mask identification and other visible metrics) and quantifying the risk of transmission in those particular environments would be helpful in making decision such as implementing social distancing measures and easing/strengthening problem.…”

Section: Discussion and Potentials Of Ai For Future Avenuesmentioning

confidence: 99%

Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review

Jayatilaka

Hassan²,

Marikkar

et al. 2020

Preprint

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The COVID-19 pandemic, within a short time span, has had a significant impact on every aspect of life in almost every country on the planet. As it evolved from a local epidemic isolated to certain regions of China, to the deadliest pandemic since the influenza outbreak of 1918, scientists all over the world have only amplified their efforts to combat it. In that battle, Artificial Intelligence, or AI, with its wide ranging capabilities and versatility, has played a vital role and thus has had a sizable impact. In this review, we present a comprehensive analysis of the use of AI techniques for spatio-temporal modeling and forecasting and impact modeling on diverse populations as it relates to COVID-19. Furthermore, we catalogue the articles in these areas based on spatio-temporal modeling, intrinsic parameters, extrinsic parameters, dynamic parameters and multivariate inputs (to ascertain the penetration of AI usage in each sub area). The manner in which AI is used and the associated techniques utilized vary for each body of work. Majority of articles use deep learning models, compartment models, stochastic methods and numerous statistical methods. We conclude by listing potential paths of research for which AI based techniques can be used for greater impact in tackling the pandemic.

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A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues

Cited by 84 publications

References 156 publications

Social distancing compliance: A video observational analysis

Social distancing compliance: A video observational analysis

Sociological modeling of smart city with the implementation of UN sustainable development goals

Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review

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