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Advanced Intelligent Systems and Data Engineering to Defeat COVID-19 Outbreak
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Advanced Intelligent Systems and Data Engineering to Defeat COVID-19 Outbreak

A special issue of Applied System Innovation (ISSN 2571-5577). This special issue belongs to the section "Medical Informatics and Healthcare Engineering".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 13859

Special Issue Editors

Prof. Dr. Teen-Hang Meen

E-Mail Website
Guest Editor
Department of Electronic Engineering, National Formosa University, Yunlin City 632, Taiwan
Interests: IoT devices; photovoltaic devices; STEM education
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Charles Tijus

E-Mail Website
Guest Editor
Director of the Cognitions Humaine et Artificielle Laboratory, University Paris 8, 93526 Saint-Denis, France
Interests: internet of objects; data mining; brain–computer interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The World Health Organization has announced that COVID-19 is a pandemic which has now become an international public health emergency. The COVID-19 pandemic is dramatically impacting the population and healthcare systems across the world.

In data science, this represents a typical problem of deep learning over incomplete or limited data in the early stage of an epidemic. Over the last decades, numerous machine-learning—including deep-learning—algorithms have been developed for dealing with various health-related problems. Given the proliferation of such approaches, it is important to have a thorough understanding of their value, usability and applicability in the fight against COVID-19 to minimize the loss of human lives, societal costs and economic losses caused by this infectious disease.

This Special Issue provides a platform for authors from various disciplines to disseminate crucial information, aiming to gather a selection of papers presenting original and innovative contributions in the field of data engineering and intelligent systems approaches for detecting, assessing and predicting the outbreak of the COVID-19 virus. Potential topics include, but are not limited to:

  • Innovations in intelligent systems for detecting COVID-19;
  • Mathematical control theories and systems to predict the epidemic of COVID-19;
  • Computer-aided methods to predict the epidemic of COVID-19;
  • Intelligent robots and their control on the detection and defeat of COVID-19;
  • Application of Internet of Things on the detection of COVID-19;
  • Big data and cloud computing on the prediction of the COVID-19 epidemic.

Prof. Dr. Teen-­Hang Meen
Prof. Dr. Charles Tijus
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. Applied System Innovation 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 1400 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 (3 papers)

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Research

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18 pages, 482 KiB  
Article
An Empirical Algorithm for COVID-19 Nowcasting and Short-Term Forecast in Spain: A Kinematic Approach
by Enrique Orihuel, Juan Sapena and Josep Navarro-Ortiz
Appl. Syst. Innov. 2021, 4(1), 2; https://0-doi-org.brum.beds.ac.uk/10.3390/asi4010002 - 02 Jan 2021
Cited by 5 | Viewed by 3197
Abstract
In the context of the COVID-19 pandemic, the use of forecasting techniques can play an advisory role in policymakers’ early implementation of non-pharmaceutical interventions (NPIs) in order to reduce SARS-CoV-2 transmission. In this article, we present a simple approach to even day and [...] Read more.
In the context of the COVID-19 pandemic, the use of forecasting techniques can play an advisory role in policymakers’ early implementation of non-pharmaceutical interventions (NPIs) in order to reduce SARS-CoV-2 transmission. In this article, we present a simple approach to even day and 14 day forecasts of the number of COVID-19 cases. The 14 day forecast can be taken as a proxy nowcast of infections that occur on the calculation day in question, if we assume the hypothesis that about two weeks elapse from the day a person is infected until the health authorities register it as a confirmed case. Our approach relies on polynomial regression between the dependent variable y (cumulative number of cases) and the independent variable x (time) and is modeled as a third-degree polynomial in x. The analogy between the pandemic spread and the kinematics of linear motion with variable acceleration is useful in assessing the rate and acceleration of spread. Our frame is applied to official data of the cumulative number of cases in Spain from 15 June until 17 October 2020. The epidemic curve of the cumulative number of cases adequately fits the cubic function for periods of up to two months with coefficients of determination R-squared greater than 0.97. The results obtained when testing the algorithm developed with the pandemic figures in Spain lead to short-term forecasts with relative errors of less than ±1.1% in the seven day predictions and less than ±4.0% in the 14 day predictions. Full article
(This article belongs to the Special Issue Advanced Intelligent Systems and Data Engineering to Defeat COVID-19 Outbreak)
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21 pages, 8959 KiB  
Article
Comparison of the Evolution of the COVID-19 Disease between Romania and Italy
by Ciprian Chiruţă, Emilian Bulgariu, Jurij Avsec, Brigita Ferčec and Matej Mencinger
Appl. Syst. Innov. 2020, 3(4), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/asi3040044 - 14 Oct 2020
Cited by 2 | Viewed by 3315
Abstract
After the outbreak of COVID-19 in Italy, thousands of Romanian citizens who worked in Northern Italy, Spain or Germany returned to Romania. Based on the time-dependent susceptible–infected–recovered—SIR model, this paper compares the evolution of the COVID-19 disease between Romania and Italy, assuming that [...] Read more.
After the outbreak of COVID-19 in Italy, thousands of Romanian citizens who worked in Northern Italy, Spain or Germany returned to Romania. Based on the time-dependent susceptible–infected–recovered—SIR model, this paper compares the evolution of the COVID-19 disease between Romania and Italy, assuming that the parameter value of R0 in the time-dependent SIR model decreases to R1 < R0 after publicly announced restrictions by the government, and increases to a value of R2 < R1 when the restrictions are lifted. Among other things, we answer the questions about the date and extent of the second peak in Italy and Romania with respect to different values of R2 and the duration of the restrictions. Full article
(This article belongs to the Special Issue Advanced Intelligent Systems and Data Engineering to Defeat COVID-19 Outbreak)
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Other

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7 pages, 1486 KiB  
Concept Paper
Proposed Design of Walk-Through Gate (WTG): Mitigating the Effect of COVID-19
by Saddam Hussain, Muhammad Jehanzeb Masud Cheema, Saad Motahhir, Muhammad Mazhar Iqbal, Arfan Arshad, Muhammad Sohail Waqas, Muhammad Usman Khalid and Saba Malik
Appl. Syst. Innov. 2020, 3(3), 41; https://0-doi-org.brum.beds.ac.uk/10.3390/asi3030041 - 21 Sep 2020
Cited by 8 | Viewed by 6292
Abstract
The world is facing a new challenge to overcome the pandemic disease of Coronavirus (COVID-19). An outbreak of COVID-19 to more than 213 countries and territories caused damage to the economy of every country. The proper vaccine to combat this pandemic disease is [...] Read more.
The world is facing a new challenge to overcome the pandemic disease of Coronavirus (COVID-19). An outbreak of COVID-19 to more than 213 countries and territories caused damage to the economy of every country. The proper vaccine to combat this pandemic disease is not invented yet. Due to the lockdown situation, there is a shortage of daily used products globally. To overcome the issue of food shortage and economic survival, the world has to ease the lockdown rules and become operational with the precautionary measures. COVID-19 has a fast transmission rate, therefore, while living with COVID-19, breaking the fast transmission chain of COVID-19 is the only vital solution. Furthermore, there is a dire need to disinfect every individual and his luggage at the entrance of every shopping mall, hospital, public and private institutions, bus stops, metro stations, and railway stations. Hence, the proposed walk-through gate (WTG) with different sensors, i.e., infrared thermal camera, UV disinfectant sensor, disinfectant spraying system, touch-less hand sanitizer, and box having a face mask with a dustbin to discard the previous mask can provide an effective and efficient relief. The world cannot stop working and cannot survive for more than 3–6 months in a lockdown, hence the proposed idea is to install the disinfectant automated spraying WTG with a security walk-through gate at every possible entrance to conform living with the COVID-19 disease such as many other diseases. Breaking the transmission chain is the only solution to win the battle against COVID-19 until an effective vaccine invention. Full article
(This article belongs to the Special Issue Advanced Intelligent Systems and Data Engineering to Defeat COVID-19 Outbreak)
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