Information and Communications Technologies (ICT) to Deal with COVID-19

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 20858

Special Issue Editors

Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
Interests: opportunistic networks; network performance evaluation; VANETs; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
Interests: high performance computing; artificial intelligence; social sensing; internet of things

Special Issue Information

Dear Colleagues,

The COVID-19 pandemic outbreak has become a severe threat to our society and our way of living. As of now, more than two million people have died, and the collateral effects of this pandemic are affecting each and every part of our society and economy. The surveillance and control of emerging infectious diseases, such as COVID-19, are vital for public health. The utilization of new information and communications technologies (ICTs), such as Internet-based surveillance, infectious diseases modelling, remote sensing, telecommunications, and mobile phones, can predict, prevent, and control these infectious diseases.  This Special Issue encourages submissions from academia, industry, and governments to share the application of ICTs to combat COVID-19, during the various stages of this pandemic, namely: early diagnosis, contact tracing, evolution, prevention of spread, isolation measures, etc. 

Topics of interest include, but are not limited to, the following:

  • Contact tracing Apps including the related privacy issues
  • Internet of Things (IoT) and wearable systems for the control and monitoring of patients
  • Data science and network analytics applied to COVID-19
  • Social sensing for analyzing and managing COVID-19
  • Machine learning techniques for the prediction of COVID-19 evolution
  • Analytical and simulation models for evaluating and studying COVID-19
  • AI-based methods for COVID-19 diagnostic systems
  • Novel ICT methods for predicting the long-term risk of COVID-19
  • Novel predictive modeling for viruses in the era of post-COVID-19
  • Novel ICT recommendation systems for the treatment of COVID-19 patients

Prof. Dr. Enrique Hernández-Orallo
Dr. José M. Cecilia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

19 pages, 2030 KiB  
Article
A near Real-Time Monitoring System Using Public WI-FI Data to Evaluate COVID-19 Social Distance Measures
by Bartomeu Alorda-Ladaria, Maurici Ruiz-Pérez and Vicente Ramos
Electronics 2022, 11(18), 2897; https://doi.org/10.3390/electronics11182897 - 13 Sep 2022
Cited by 3 | Viewed by 1127
Abstract
This study assessed the applicability of geolocation data provided by public Wi-Fi infrastructures as information sources that can contribute to urban planning and management. We focused particularly on modeling and monitoring real-time mobility and congestion using geolocation capabilities of Wi-Fi public networks in [...] Read more.
This study assessed the applicability of geolocation data provided by public Wi-Fi infrastructures as information sources that can contribute to urban planning and management. We focused particularly on modeling and monitoring real-time mobility and congestion using geolocation capabilities of Wi-Fi public networks in Smart cities. The proposed methodology combines a detailed geographic analysis of the space with high-frequency indicators generated from network data. This study emphasizes the importance of Wi-Fi infrastructures as noninvasive monitoring systems, and describes how network data can be applied to generate useful indicators for urban planning and management. The methodology was empirically implemented in the city of Palma (Balearic Islands, Spain), where the social distance level was measured to identify conflicting areas. We demonstrate how the proposed solution can estimate pedestrians’ density efficiently and precisely through high-frequency monitoring (5 min or less) and the construction of comprehensive indicators. In this context, we suggest several public policies that can be implemented by using this methodological approach to monitor dynamic patterns of pedestrian mobility, especially during health crises or during high tourist seasons. Full article
Show Figures

Figure 1

26 pages, 28805 KiB  
Article
Sound Feedback for Social Distance: The Case for Public Interventions during a Pandemic
by William Primett, Hugo Plácido Da Silva and Hugo Gamboa
Electronics 2022, 11(14), 2151; https://doi.org/10.3390/electronics11142151 - 09 Jul 2022
Viewed by 1884
Abstract
Within the field of movement sensing and sound interaction research, multi-user systems have gradually gained interest as a means to facilitate an expressive non-verbal dialogue. When tied with studies grounded in psychology and choreographic theory, we consider the qualities of interaction that foster [...] Read more.
Within the field of movement sensing and sound interaction research, multi-user systems have gradually gained interest as a means to facilitate an expressive non-verbal dialogue. When tied with studies grounded in psychology and choreographic theory, we consider the qualities of interaction that foster an elevated sense of social connectedness, non-contingent to occupying one’s personal space. Upon reflection of the newly adopted social distancing concept, we orchestrate a technological intervention, starting with interpersonal distance and sound at the core of interaction. Materialised as a set of sensory face-masks, a novel wearable system was developed and tested in the context of a live public performance from which we obtain the user’s individual perspectives and correlate this with patterns identified in the recorded data. We identify and discuss traits of the user’s behaviour that were accredited to the system’s influence and construct four fundamental design considerations for physically distanced sound interaction. The study concludes with essential technical reflections, accompanied by an adaptation for a pervasive sensory intervention that is finally deployed in an open public space. Full article
Show Figures

Graphical abstract

17 pages, 1540 KiB  
Article
COVIDSensing: Social Sensing Strategy for the Management of the COVID-19 Crisis
by Alicia Sepúlveda, Carlos Periñán-Pascual, Andrés Muñoz, Raquel Martínez-España, Enrique Hernández-Orallo and José M. Cecilia
Electronics 2021, 10(24), 3157; https://doi.org/10.3390/electronics10243157 - 18 Dec 2021
Cited by 7 | Viewed by 2315
Abstract
The management of the COVID-19 pandemic has been shown to be critical for reducing its dramatic effects. Social sensing can analyse user-contributed data posted daily in social-media services, where participants are seen as Social Sensors. Individually, social sensors may provide noisy information. However, [...] Read more.
The management of the COVID-19 pandemic has been shown to be critical for reducing its dramatic effects. Social sensing can analyse user-contributed data posted daily in social-media services, where participants are seen as Social Sensors. Individually, social sensors may provide noisy information. However, collectively, such opinion holders constitute a large critical mass dispersed everywhere and with an immediate capacity for information transfer. The main goal of this article is to present a novel methodological tool based on social sensing, called COVIDSensing. In particular, this application serves to provide actionable information in real time for the management of the socio-economic and health crisis caused by COVID-19. This tool dynamically identifies socio-economic problems of general interest through the analysis of people’s opinions on social networks. Moreover, it tracks and predicts the evolution of the COVID-19 pandemic based on epidemiological figures together with the social perceptions towards the disease. This article presents the case study of Spain to illustrate the tool. Full article
Show Figures

Figure 1

15 pages, 3893 KiB  
Article
Social Distance Monitoring Approach Using Wearable Smart Tags
by Tareq Alhmiedat and Majed Aborokbah
Electronics 2021, 10(19), 2435; https://doi.org/10.3390/electronics10192435 - 08 Oct 2021
Cited by 19 | Viewed by 11208
Abstract
Coronavirus has affected millions of people worldwide, with the rate of infected people still increasing. The virus is transmitted between people through direct, indirect, or close contact with infected people. To help prevent the social transmission of COVID-19, this paper presents a new [...] Read more.
Coronavirus has affected millions of people worldwide, with the rate of infected people still increasing. The virus is transmitted between people through direct, indirect, or close contact with infected people. To help prevent the social transmission of COVID-19, this paper presents a new smart social distance system that allows individuals to keep social distances between others in indoor and outdoor environments, avoiding exposure to COVID-19 and slowing its spread locally and across the country. The proposed smart monitoring system consists of a new smart wearable prototype of a compact and low-cost electronic device, based on human detection and proximity distance functions, to estimate the social distance between people and issue a notification when the social distance is less than a predefined threshold value. The developed social system has been validated through several experiments, and achieved a high acceptance rate (96.1%) and low localization error (<6 m). Full article
Show Figures

Figure 1

11 pages, 516 KiB  
Article
Digital Contact Tracing: Large-Scale Geolocation Data as an Alternative to Bluetooth-Based Apps Failure
by José González-Cabañas, Ángel Cuevas, Rubén Cuevas and Martin Maier
Electronics 2021, 10(9), 1093; https://doi.org/10.3390/electronics10091093 - 05 May 2021
Cited by 11 | Viewed by 2894
Abstract
The currently deployed contact-tracing mobile apps have failed as an efficient solution in the context of the COVID-19 pandemic. None of them have managed to attract the number of active users required to achieve efficient operation. This urges the research community to re-open [...] Read more.
The currently deployed contact-tracing mobile apps have failed as an efficient solution in the context of the COVID-19 pandemic. None of them have managed to attract the number of active users required to achieve efficient operation. This urges the research community to re-open the debate and explore new avenues to lead to efficient contact-tracing solutions. In this paper, we contribute to this debate with an alternative contact-tracing solution that leverages the already available geolocation information owned by BigTech companies that have large penetration rates in most of the countries adopting contact-tracing mobile apps. Our solution provides sufficient privacy guarantees to protect the identity of infected users as well as to preclude Health Authorities from obtaining the contact graph from individuals. Full article
Show Figures

Figure 1

Back to TopTop