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The Role of Novel Technologies in Combating COVID-19

By Himanshi Babbar, Roopali Dogra, Shalli Rani, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

The recent coronavirus commenced in Wuhan at the end of 2019. Historical records provide details on three deadly disease outbreaks observed in 1918, 1957, and 1968. On 30 January 2020, the World Health Organization (WHO) declared a cause of concern regarding potential transmission of the coronavirus (COVID-19) [5]. A pandemic occurs when a disease is quickly transmitted across different countries and continents, and typically has extraordinary social and economic impacts. Furthermore, current globalization is fueled by growing urbanization, growing populations, and enhanced worldwide travel, which has turned many cities throughout the world into COVID transmission hubs.

Advanced technologies such as Internet of Things (IoT)-based healthcare [1], big data, Software Defined Networking (SDN), Wireless Sensor Networks (WSN), and Artificial Intelligence (AI) have made cities more robust to track, report, prevent, and hinder virus transmission. The WHO-China Joint Mission report praised China’s techno-driven strategy as “one of most comprehensive, nimble, and vigorous disease containment campaigns in existence,” and it’s been successful, for the most part, in combating the pandemic. The human-centered strategies taken by countries in Europe and within the United States, on the other hand, have had less of an impact on the pandemic’s transmission. During this time, people had an advantage in the fight against COVID-19—technology. Many efforts in predicting, analyzing, tracking, etc. were capable by use of technology in addition to the inventive deployment of healthcare IoT in smart cities throughout China, Europe, and the United States. Constant monitoring and quick decision-making are now possible thanks to these technologies. This article illustrates how various healthcare IoT technologies have progressed in the battle against and management of the COVID-19 pandemic.

A. Role of SDN on Combating COVID-19

Software-Defined Networking (SDN) [2] is a core network strategy that enables network infrastructures to improve the monitoring and efficiency of the network, similar to how some leverage cloud computing instead of conventional network management. The COVID-19 pandemic had a favorable impact on the SDN industry [9]. The increasing convergence of big data is the primary driver of industry growth. Since the virus was transmitted globally, researchers, clinicians, and data analysts from around the world were encouraged to collaborate and develop solutions. At this point in time, investigators are employing big data, Machine Learning and Deep Learning, and other modern technologies. Big data [8] is crucial in this scenario as it aids in the analysis of datasets and the identification of trends. This information can them be used to aid in COVID-19 identification.

The value of big data is becoming more evident since organizations such as the WHO and Microsoft are generating analytical dashboards that depend on these technologies [3]. These dashboards pull data from different nations and provide the confirmed number of cases and deaths that have occurred. Datasets for big data models are also generated using these dashboards. These models can predict potential hotspots and outbreaks and notify healthcare officials ahead of time. Even during a pandemic, the development of big data technologies has had a positive effect on the software-defined networking business.

Furthermore, some nations had government-imposed curfews that forced individuals to stay home to prevent the virus from spreading. Internet access has increased significantly, which further encouraged and allowed people to stay home. IT infrastructure monoliths have relocated networking infrastructures that allows staff to work from home. The widespread usage of virtual private networks (VPNs) and video conferencing for working remotely has resulted in increased data traffic on the Web. All IT infrastructure suppliers have been forced to embrace SDN technology as a result of the pandemic.

B. Role of WSN/IoT in Combating COVID-19

Aircraft cancellations; travel restrictions and curfews; hotel closures; interior events constrained, and maximum occupancy significantly limited; over fifty countries declared to be in a state of emergency; tremendous supply chain bottlenecks and conflicts; stock market index variations; decreased business confidence and stability; rising panic amongst the population; and ambiguity about the future have all been outcomes resulting from the COVID-19 pandemic [6]. In the event a global pandemic emerges, it is crucial to prevent and prohibit the disease from further spreading. Worldwide effects of COVID-19 have already been felt, and Wireless Sensor Networks (WSNs) have considerably impacted 2020 during this time.

Healthcare, education, as well as the economy, are all impacted by wireless communication and locating technologies. Hospitals receive wired broadband solutions, which are offered by several different companies. Besides broadband service, Wireless Wide Area Network (WAN) technologies used in hospitals and businesses are sufficient for facilitating essential internet access and privacy. However, the situation is becoming increasingly difficult due to the COVID-19 outbreak. WANs are efficient in terms of providing broadband service, internet access, and security. WAN solutions were built by utilizing current resources to ensure that hospitals in crisis received uninterrupted service. Google [4] was the first to offer zero-trust security to the general public. This solution was implemented by the COVID-19 pandemic work-from-home program. All users connect to the enterprise networks directly from their homes and remote locations. As a result, the frequency and severity of cyber-attacks has increased exponentially. Zero-trust security ensures security for all use cases, like VPN solutions offered by almost every major company.

C. A Few Roles AI played in Combating COVID-19

The entire scientific research community entered overdrive attempting to understand the essence of the COVID-19 virus. People wanted to understand how it spreads and discover potential vaccines once majority of the world went into lockdown in 2020. The notion that progress has been made with the help of technology is a little-known fact. For instance, since the outbreak, Artificial Intelligence (AI) has been discretely and diligently helping to overcome the constraints of human understanding in this vast undertaking. When the first incident of coronavirus was discovered in China on 31 December 2019 [7], a Canadian AI-business, BlueDot, designed an AI algorithm that notified the world of the virus. This tool was created to anticipate the transmission of contagious diseases, as well as to identify and monitor them. It functions by integrating AI with epidemiologists’ expertise as to how to recognize indications of a new disease, and where to look for them. BlueDot analyzes approximately 100,000 records every day in a variety of languages and delivers out regular notifications to clients in health care, government, industry, and public health. The warnings give a quick rundown of unusual disease outbreaks, and threats they may bring, found by an AI algorithm.

In response to VPN solutions, Akamai has developed a new solution for cloud infrastructure security. Since all work from home plans have prompted employees to access applications from their own devices, existing options must move to a zero-trust platform. Intruders will and have taken full advantage of this, and attacks were attempted against the networks using the server’s identical devices. COVID-19 pandemic, Oracle, IBM, and other major organizations turned to AI enabled solutions. Nvidia is also putting money into artificial intelligence to develop solutions for life science applications. Whenever feasible, these solutions were designed to provide agility and efficiency to maintain a safe, reliable network. These systems are cloud-based which allowed for a prompter response to the coronavirus.

References 

  1. Ndiaye, M., Oyewobi, S.S., Abu-Mahfouz, A.M., Hancke, G.P., Kurien, A.M. and Djouani, K., 2020. IoT in the wake of COVID-19: A survey on contributions, challenges and evolution. IEEE Access, 8, pp.186821-186839.
  2. Bokolo, A.J. and Nweke, L.O., 2020. Applying software-defined networking to support telemedicine health consultation during and post-Covid 19 era.
  3. Chowdhury, M.E., Rahman, T., Khandakar, A., Mazhar, R., Kadir, M.A., Mahbub, Z.B., Islam, K.R., Khan, M.S., Iqbal, A., Al Emadi, N. and Reaz, M.B.I., 2020. Can AI help in screening viral and COVID-19 pneumonia?. IEEE Access, 8, pp.132665-132676.
  4. Cohen, J.P., Dao, L., Roth, K., Morrison, P., Bengio, Y., Abbasi, A.F., Shen, B., Mahsa, H.K., Ghassemi, M., Li, H. and Duong, T., 2020. Predicting covid-19 pneumonia severity on chest x-ray with deep learning. Cureus, 12(7).
  5. Abuelkhail, A., Baroudi, U., Raad, M. and Sheltami, T., 2021. Internet of things for healthcare monitoring applications based on RFID clustering scheme. Wireless Networks, 27(1), pp.747-763.
  6. Nasajpour, M., Pouriyeh, S., Parizi, R.M., Dorodchi, M., Valero, M. and Arabnia, H.R., 2020. Internet of Things for current COVID-19 and future pandemics: An exploratory study. Journal of healthcare informatics research, pp.1-40.
  7. Saeed, N., Bader, A., Al-Naffouri, T.Y. and Alouini, M.S., 2020. When wireless communication faces COVID-19: Combating the pandemic and saving the economy. arXiv preprint arXiv:2005.06637.
  8. Alsunaidi, S.J., Almuhaideb, A.M., Ibrahim, N.M., Shaikh, F.S., Alqudaihi, K.S., Alhaidari, F.A., Khan, I.U., Aslam, N. and Alshahrani, M.S., 2021. Applications of Big Data Analytics to Control COVID-19 Pandemic. Sensors, 21(7), p.2282.
  9. BABAYİĞİT, B. and Hascokadar, E., 2021. A software-defined network approach for the best hospital localization against Coronavirus (COVID-19).

Dr. Himanshi Babbar is Assistant Professor- Research in CSE, working in Chitkara University, Rajpura, Punjab, India. She has 2 years of teaching experience, CGC, Landran, Mohali, Punjab. She received an MCA (Master’s in Computer Applications) degree from Chitkara University, Punjab Campus in 2015 and completed her Ph.D. in Computer Applications from Chitkara University, Punjab Campus in 2021. She is a PostDoctoral Fellow from Dubai, UAE. Her area of research is Software Defined Networking, Load Balancing and Internet of Things. She has published/accepted/presented many papers in national conferences, published papers in Scopus and SCI indexed journals and filed/published/granted various patents.

Dr. Ms. Roopali Dogra is pursuing her PhD in Electronics and Communication Engineering Department in Chitkara University, Rajpura Punjab. She has completed her Masters of Electrical from Maharishi Markandeshwar University, Ambala in Year 2015. She has completed her btech from Rayat College, Railmajra. Her research interest includes energy-efficient Wireless Sensor Networks and IoT based architectures. She has published many papers in national and international journals.

Dr. Shalli Rani is an Associate Professor in CSE with Chitkara University (Rajpura (Punjab)), India. She has 14+ years of teaching experience. She received an MCA degree from Maharishi Dayanand University, Rohtak in 2004 and the M.Tech. degree in Computer Science from Janardan Rai Nagar Vidyapeeth University, Udaipur in 2007 and a Ph.D. degree in Computer Applications from Punjab Technical University, Jalandhar in 2017. Her main area of interest and research is Wireless Sensor Networks, Underwater Sensor networks and Internet of Things.

She has published/accepted/presented more than 25 papers in international journals /conferences. She has worked on Big Data, Underwater Acoustic Sensors and IoT to show the importance of WSN in IoT applications. She received a young scientist award in Feb. 2014 from Punjab Science Congress, in the same field.

Editor: 

Dr. Mohammad Asif Khan is a Postdoc Research Fellow with the Electrical Engineering department at Qatar University, Doha, Qatar. He received the Ph.D. degree in Electrical Engineering from Qatar University (2019), M.Sc. in Telecommunication Engineering from University of Engineering and Technology Taxila, Pakistan (2013), and B.Sc. degree in Telecommunication Engineering from University of Engineering and Technology Peshawar, Pakistan (2009). He was a researcher assistant at Qatar University (Aug 2014-May 2015) and at Qatar Mobility Innovation Center, Doha, Qatar (Jan 2016-Dec 2016).

He is a senior member of IEEE and a member of IET. He is an editorial board member of Frontiers in Communications and Networks, and IEEE Future Direction Newsletter. He has served as a reviewer of various international Journals including IEEE Transactions on Emerging Topics in Computing, IEEE Communications Surveys and Tutorials, IEEE Access, IET Communications, IET Intelligent Transportation System, and KSII Transactions on Internet and Information Systems. He has served as a TPC member of several international conferences including IEEE ICC’2021, IEEE CNCC’2021, IEEE SusTech’2021, and IEEE WF-IoT’2018. His current research interests include wireless communication, mobile edge computing, federated learning, and UAV communication. For more information, visit his homepage www.asifk.me.