You are currently viewing a new version of our website. To view the old version click .
Sustainability
  • Review
  • Open Access

10 September 2021

COVID-19 Pandemic Waves: 4IR Technology Utilisation in Multi-Sector Economy

,
and
1
Research, Innovation and Engagement, Central University of Technology, Bloemfontein 9301, South Africa
2
Centre for Sustainable Smart Cities 4.0, Faculty of Engineering, Built Environment and Information Technology, Central University of Technology, Bloemfontein 9301, South Africa
*
Author to whom correspondence should be addressed.
This article belongs to the Section Health, Well-Being and Sustainability

Abstract

In this paper, we reviewed the Fourth Industrial Revolution (4IR) technologies applied to waves of the coronavirus disease (COVID-19). COVID-19 is an existential threat that has resulted in an unprecedented loss of lives, disruption of flight schedules, shutdown of businesses and much more. Though several researchers have highlighted the enormous benefits of 4IR technologies in containing the COVID-19 pandemic, the recent waves of the pandemic call for a thorough review of these technological interventions. The cyber-physical space has had its share of the COVID-19 pandemic effect, and through this review, we highlight the salient issues to help policy formulation towards managing the impact of subsequent COVID-19 waves within such environments. Hence, the purpose of this paper is to review the application of 4IR technologies during the COVID-19 pandemic waves and to highlight their shortcomings. Recent research articles were sourced from an online repository and thoroughly reviewed to highlight 4IR technology applications, innovations, shortcomings and multi-sector challenges. The outcome of this review indicates that the second wave of the pandemic resulted in a lower proportion of patients requiring invasive mechanical ventilation and a lower rate of thrombotic events. In addition, it was revealed that the delay between ICU admissions and tracheal intubation was longer in the second wave in the health care sector. Again, the review suggests that 4IR technologies have been utilized across all the sectors including education, businesses, society, manufacturing, healthcare, agriculture and mining. Businesses have revised their service delivery models to include 4IR technologies and avoid physical contacts. In society, digital certificates, among other digital platforms, have been utilized to assist with the movements of persons who have been vaccinated. Manufacturing concerns have also utilized robots in manufacturing to reduce human-to-human physical contact. The mining sector has automated their work processes, utilising smart boots to prevent infection, smart health bands and smart disinfection tunnels or walkthrough sanitization gates in the mining work environment. However, the identified challenges of implementing 4IR technologies include low-skilled workers, data privacy issues, data analysis poverty, data management issues and many more. The boom in 4IR technologies calls for intense legislation on sweeping data privacy for regulated tech companies. These findings hold salient implications for policy formulation towards tackling future pandemic outbreaks.

1. Introduction

The Coronavirus disease 2019 (COVID-19) pandemic, as a public health issue, has disrupted every aspect of our lives. Businesses, education and social structures have been disrupted leading to economic challenges. Recently, the COVID-19 pandemic has been associated with different forms of “pandemic waves”, which are identified by their characteristics [1]. Iftimie, López-Azcona [2] indicated that COVID-19 will not disappear in the short or medium term because of these changing characteristics; hence, the vaccination process might linger until a sufficiently high percentage of the population has been vaccinated. Furthermore, in order to prevent and slow down virus transmission rate, one has to be well informed about the COVID-19 virus, the disease it causes and how it spreads [3]. The COVID-19 virus spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, so it is important to practice respiratory etiquette such as “coughing into a flexed elbow” [3]. Being informed about these etiquettes are primary in slowing down the transmission rate. Preventive measures to avoid its spread include social or physical distancing, hand-washing or using alcohol-based hand sanitizer and mask-wearing [4]. In addition, the idea of “lockdown light” and “hard lockdown” (or strict lockdown) are some of the measures taken by governments to minimise human movement and reduce the spread of COVID-19 [5]. However, the sustenance of strict lockdowns for longer periods has dire consequences due to economic, social and psychological reasons. Fortunately, the hard lockdown brought the infection under control with reduced cases whereas the “lockdown light” proved unsuccessful [5]. Unfortunately, people became exhausted with adhering to preventive measures, thereby ushering in the different COVID-19 pandemic waves. In addition, the virus’s behaviour has changed, leading to a faster rate of transmission. Currently, the third wave of the pandemic being witnessed overstretched the existing health facilities in terms of human capacity and a lack of space in hospitals as COVID-19 patients are staying longer in health facilities. As such, the stretched hospital staff prioritised people with greater survival chances [6].
COVID-19 facilitated paradigm shifts in work structures and revealed larger dependencies on the human work force and intelligence. The continued waves of COVID-19 infections made countries constantly optimise their policy responses and technology interventions [7]. The COVID-19 pandemic has significantly accelerated the global use of technologies associated with 4IR. For instance, in sub-Saharan Africa, many now see the 4IR as a strategy for engendering the region’s COVID-19 recovery [8]. Recently, it was announced that the African continent was set to receive a total of USD 50 billion in support from the World Bank to invest in digital technologies through the introduction of new digital platforms, digital infrastructure installation, digital skills development and provision of enabling a regulatory environment for COVID-19 recovery [8]. Although the 4IR agenda has been the part of the strategy of most organizations and governments, the COVID-19 pandemic accelerated the pace of its adoption via cyber-physical infrastructures in education, health service, social interactions and environmental monitoring. Thus, the COVID-19 pandemic has revealed how we are dependent socially, economically and politically and “exploded the myth of 4IR” in the short term [6].
Technological initiatives have been deployed in the cyber-physical space in an attempt to reduce the spread of the COVID-19 and monitor public areas and patients, develop new effective vaccines and guarantee the continuity of social activities [9]. Since the outbreak of COVID-19 in March 2020, researchers from different fields have provided a wide range of solutions to contain the pandemic. The enormous amount of research makes it difficult to have a general view of the different applications of such technologies towards the management of COVID-19 and an understanding of how research has either evolved or is evolving [10]. Furthermore, the resurgence of COVID-19 infections has accelerated the need for just-in-time government policy responses. Thus, it is imperative to review the technology-related responses by different sectors such as education, business, social environment, manufacturing, health, mining and agriculture within their cyber-physical space in tackling the COVID-19 pandemic waves and highlight the shortfalls, if any. Therefore, the main purpose of this review is to present the technological interventions to containing the COVID-19 pandemic waves. An exploratory study was conducted on recent and related literature, using online repositories, detailing the application of mainstream emerging technologies associated with the 4IR and big data during COVID-19 pandemic waves. The lessons learned contribute to policy formulation and the development of sector-specific strategic planning for 4IR technology use. The remaining sections of this paper are structured as follows: Section 2 discusses the related work, Section 3 presents the shortcomings of 4IR, while future research direction is presented in Section 4. The paper is concluded in Section 5.

3. Shortcomings of 4IR Interventions to COVID-19 Pandemic Waves

In this section, the shortcomings of the Fourth Industrial Revolution (4IR) intervention in different sectors are presented in Table 1. The shortcomings emanated from the review of literature on 4IR technologies used in education, business, society, manufacturing, health, mining and agriculture to resolve challenges identified in these economic sectors. The 4IR technologies are grouped into physical, digital and biological space.
Table 1. Sectoral shortcomings of 4IR intervention during COVID-19 pandemic waves.
Table 1 presents the shortcoming of the 4IR application to sectors of an economy. These sector categories were impacted by the COVID-19 pandemic waves and a cursory review helped clarify the areas to focus on. The shortcomings of 4IR technologies to fight the waves of the COVID-19 pandemic is that countries vary in terms of capacity on the cyber-physical space and human skills for utilizing these technologies. The threat to digitization is cybersecurity; upskilling workers and young people through the educational systems to new technologies and digitization [69]; broader social, financial investment and international cooperation on policies; and understanding of the social and ethical impacts of emerging technologies, particularly on the young [36]. The cause of different pandemic waves can be attributed to different human behaviour, viral variants and minimal government actions [4]. The imported COVID-19 cases are attributed to the movement of people who are not aware that they carry the coronavirus. The impact of 4IR technologies that were used can be summarised as follows: In education, the second and third waves of the COVID-19 pandemic witnessed an acceleration of the use of digital technologies, digital repository and self-learning; In business, business service delivery models shifted from traditional face-to-face models to massive expansion in mobile technology, and e-commerce boomed during the pandemic; In society, the digital documentation of COVID-19 certificates was used to aid movement; In manufacturing, the use of robots for most manufacturing tasks to reduce human contacts; In health, the use of robots for disinfection of public areas and drones to deliver medical supplies; In Agriculture, the use drones to spray crops; In mining, the use of smart health bands, disinfection tunnels or walkthrough sanitization gates and mobile health alerts are among the 4IR technologies implemented. Increased digitization because of the pandemic has introduced another challenge in terms of managing the disruptive technologies associated with the 4IR [36]. Although digitization resulted in the availability of large volumes of data, there is data analysis poverty created due to lack of technical knowhow to analyse the variety of data and create value from the data. Opportunities that exist in healthcare include promoting education and training for non-face-to-face healthcare services and policy regarding telemedicine care deregulation [33].

4. Future Research Direction

The physical, digital and biological components of 4IR technology are creating a robotic socioeconomic ecosystem in the long term because of the redefinition of business models and much more. Future research directions should generally focus on improving privacy and data protection, the sustainability and management of digital technologies and the standardization of contactless services. Concerning the pace of digitization, protecting the use of personal information should be the topmost priority, thus calling for sweeping data privacy legislation to regulate tech companies that champion the use of these 4IR technologies within different sectors of an economy. Such regulation is necessary because of the fact that some of the digital systems developed in the midst of the pandemic were either not internationally standardised or accredited [9]. Generally, it is important to leverage 4IR technologies to help create a digital village concept, the rapid use of blockchain technology to improve the supply chain of goods and products and the rapid deployment of drone technology in agriculture and manufacturing. In addition, there are some gains in terms of mobile technology platforms for mobile payment, e-learning platforms and the boom in e-commerce. When these gains are not well managed and sustained, it could be eroded. Thus, if countries can bridge infrastructure and education gaps, it can continue leveraging 4IR, both as an enabler for the COVID-19 recovery and as the foundation for a successful and inclusive future [8].
The sustenance of the digital world needs governments and institutions to work together to promote policies that continue to foster digital innovation and learning [36]. Thus, government should support the practical training of professionals in job-related re-skilling and up-skilling programs, the practical education and training of children and young people in new technologies who can be ready for the labour market and programs to encourage lifelong learning for the elderly to adequately adapt to the new technologies that were introduced during the COVID-19 pandemic [69].
Given that the pace 4IR with which technologies have accelerated during the COVID-19 pandemic, digital maturity models should be defined to help manage any gains recorded during this era. Such digital maturity models should include novice, followers, innovators and champions [68]. This is because the COVID-19 pandemic took the world by surprise, where persons who both are and are not technologically savvy had to use digital tools for most activities. In addition, technology innovators and businesses helped create these technologies for addressing physical distancing and many more platforms that encourage remote interactions.
Investment in digital technologies would increase throughput, increase efficiency, lower costs of digital transactions and improve the health and safety of workers. Digitization has impacted economic growth through inclusive finance, enabling the unbanked to migrate to formal digital payments and savings technology platforms [70]. Businesses have to rethink their business models to impact society and other sectors. The digitisation agendas of these sectors should be backed by their organizational culture to keep up with the times. Thus, without the right leadership and clear vision for the digital future, the gains would be difficult to sustain and manage.
The lessons learned during the COVID-19 pandemic waves and 4IR technology interventions can be applied to the future outbreaks. For instance, the outbreak of the Marburg virus in February 2021 in Guinea, West Africa. Though the Marburg virus has not been declared as a pandemic, the lessons learned from the use of 4IR technologies can be applied to avoid much infection spread worldwide.
In furtherance to the foregoing, this review has shown the increasing reliance by organisations, situated across a multiplicity of sectors, on these 4IR technologies in tackling operational challenges posed by the pandemic. It is implied that the continued deployment of these technologies will remain central to the strategic objective of such organisations whilst forming an integral part of any containment policies formulated and implemented at national and sub-national levels of government. However, the deployment of these technologies in situations such as is currently being experienced are not without shortcomings, as highlighted in Table 1. Therefore, it is expected that the findings from this review regarding these shortcomings will be considered by the leadership of such organisations and governments in the development of policies or strategies towards engendering more beneficial deployment of these technologies towards minimizing the impact of subsequent pandemic waves.

5. Conclusions

In this paper, we reviewed the use of 4IR technology to tackle the COVID-19 pandemic waves. Among the 4IR technologies include artificial intelligence, big data, blockchain, cloud computing, IoT, 3D printing and robotics. We found that the COVID-19 pandemic has greatly accelerated research on the integration of digital technologies in healthcare, businesses, society, manufacturing and agriculture. These technologies have been applied to tackle the issues of contact tracing, social distancing, hotspot detection of the outbreak, supply chain and value addition, contactless services and many more. However, the issues of governments in creating the enabling network infrastructure that encourages farming digitization worldwide remain a challenge.
In respect of multi-sectors, the education sector has kept pace with digitization where students learn using online platforms thus encouraging social distancing and self-learning. The business sector experienced a boom in the use of digital platform for mobile money payment, increased migration of the unbanked to formal digital payment platforms, a boom in e-commerce and the redesign of the traditional face-to-face business service delivery. Social interaction and movement have been facilitated with the introduction of digital travel certificates, health status checkers, contact tracing platforms and the use of robots for disinfection tasks in the public space. The manufacturing sector has seen the use of blockchain technology to improve supply chain and the use of robots to perform some human related tasks. Agriculture has seen the use of drone technology for the surveillance and spraying of crops, the digitization of smallholder farms and the creation of digital villages. The mining sector saw the use of smart devices, including smart boot to prevent infectious viruses and smart health bands. The health sector witnessed the use of 4IR technologies including the use of robots for disinfection tasks and the use of telemedicine, thermal sensors, biosensors and much more.
Countries stand the chance to benefit immensely from the digitization to reform and empower the poor with access to information, more job opportunities, business-to-business growth in agro-processing and an increase in the usage of technology-based banking services. The IoT, AI and blockchain technologies can enhance data gathering and analysis for a targeted poverty reduction campaign. Moreover, 4IR technologies could help build a sustainable healthcare system and encourage the use of mobile technology to improve data collection, medical supply delivery and other healthcare service delivery. It could upskill the healthcare workers to offer improved services to patients. It is imperative to prioritise labour issues, 4IR integration into the global value chains, sweeping personal data privacy laws for tech industries and developing the physical and digital infrastructure of key sectors of a country. Open issues regarding digital platforms include personal data protection on a digital platform, data analysis poverty, how to sustain the gains made through government support programs, investment in drone technology in farming and the delivery of medical supplies.

Author Contributions

Conceptualization, writing—original draft preparation, I.E.A.; writing—review and editing, B.O.A.; conceptualization, writing—review and editing, A.B.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not Applicable.

Data Availability Statement

The study did not report any data.

Conflicts of Interest

The authors declare that they have no conflict of interest.

References

  1. Dutta, P.K. What Is a COVID-19 Wave? How Do We Identify It? Available online: https://www.indiatoday.in/coronavirus-outbreak/story/what-is-a-covid19-wave-how-do-we-identify-it-1800810-2021-05-10 (accessed on 10 May 2021).
  2. Iftimie, S.; López-Azcona, A.D.; Vallverdú, I.; Hernández-Flix, S.; de Febrer, G.; Parra, S.; Hernández-Aguilera, A.; Riu, F.; Joven, F.; Andreychuk, N.; et al. First and second waves of coronavirus disease-19: A comparative study in hospitalized patients in Reus, Spain. PLoS ONE 2021, 16, e0248029. [Google Scholar] [CrossRef] [PubMed]
  3. World Health Organization. There Is a Current Outbreak of Coronavirus (COVID-19) Disease. 2021. Available online: https://www.who.int/health-topics/coronavirus#tab=tab_1 (accessed on 4 August 2021).
  4. Health Desk. What Are First, Second and Third Waves of Infections? 2021. Available online: https://health-desk.org/articles/what-are-first-second-and-third-waves-of-infections (accessed on 7 June 2021).
  5. Graichen, H. What is the difference between the first and the second/third wave of Covid-19?—German perspective. J. Orthop. 2021, 24. [Google Scholar] [CrossRef] [PubMed]
  6. Results for Development. Implications of the Fourth Industrial Revolution for the Development Agenda in the Indo-Pacific Region; Results for Development: Washington, DC, USA, 2020; p. 32. [Google Scholar]
  7. Khan, M.F.; Kaiser, K.; Morisset, J. Confronting COVID-19 Second Waves: How “Big Data for Good” Can Inform Policy in Vietnam. 2020. Available online: https://blogs.worldbank.org/eastasiapacific/confronting-covid-19-second-waves-how-big-data-good-can-inform-policy-vietnam (accessed on 9 July 2020).
  8. Oxford Business Group. The Fourth Industrial Revolution in Sub-Saharan Africa: Key to the Coronavirus Recovery? 2021. Available online: https://oxfordbusinessgroup.com/news/fourth-industrial-revolution-sub-saharan-africa-key-coronavirus-recovery (accessed on 6 May 2021).
  9. Ibrahim, M. The Fourth Industrial Revolution Combatting COVID-19: The Role of Smart and Sustainable Cities; United Nations Department of Economic and Social Affairs: New York, NY, USA, 2020; p. 6. [Google Scholar]
  10. Rodríguez, I.; Rodríguez, J.V.; Shirvanizadeh, N.; Ortiz, A.; Pardo-Quiles, D.J. Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining. Int. J. Environ. Res. Public Health 2021, 18, 8578. [Google Scholar] [CrossRef] [PubMed]
  11. He, S.; Yang, J.; He, M.; Yan, D.; Tang, S.; Rong, L. The risk of future waves of COVID-19: Modeling and data analysis. Math. Biosci. Eng. 2021, 18, 5409–5426. [Google Scholar] [CrossRef]
  12. Coccia, M. The impact of first and second wave of the COVID-19 pandemic in society: Comparative analysis to support control measures to cope with negative effects of future infectious diseases. Environ. Res. 2021, 197, 111099. [Google Scholar] [CrossRef]
  13. Contou, D.; Fraissé, M.; Pajot, O.; Tirolien, J.A.; Mentec, H.; Plantefève, G. Comparison between first and second wave among critically ill COVID-19 patients admitted to a French ICU: No prognostic improvement during the second wave? Crit. Care 2021, 25, 1–4. [Google Scholar] [CrossRef]
  14. Bontempi, E.; Vergalli, S.; Squazzoni, F. Understanding COVID-19 diffusion requires an interdisciplinary, multi-dimensional approach. Environ. Res. 2020, 188, 109814. [Google Scholar] [CrossRef]
  15. Neto, R.d.C.S.; Maia, J.S.; de Silva Neiva, S.; Scalia, M.D.; de Andrade, J.B.S.O. The fourth industrial revolution and the coronavirus: A new era catalyzed by a virus. Res. Glob. 2020, 2, 7. [Google Scholar]
  16. Sima, V.; Gheorghe, I.G.; Subić, J.; Nancu, D. Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability 2020, 12, 4035. [Google Scholar] [CrossRef]
  17. Alsunaidi, S.J.; Almuhaideb, A.M.; Ibrahim, N.M.; Shaikh, F.S.; Alqudaihi, K.S.; Alhaidari, F.A.; Khan, I.U.; Aslam, N.; Alshahrani, M.S. Applications of Big Data Analytics to Control COVID-19 Pandemic. Sensors 2021, 21, 1–24. [Google Scholar] [CrossRef]
  18. OECD. Cloud Computing: The Concept, Impacts and the Role of Government Policy. In OECD Digital Economy Papers; OECD Publishing: Paris, France, 2014; pp. 1–35. [Google Scholar]
  19. HealthNewToday. Coronavirus May Spread Faster than WHO Estimate. 2020. Available online: https://www.medicalnewstoday.com/articles/coronavirus-may-spread-faster-than-who-estimate (accessed on 4 August 2021).
  20. Foote, K.D. A Brief History of Cloud Computing. 2017. Available online: https://www.dataversity.net/brief-history-cloud-computing/ (accessed on 4 August 2021).
  21. Mahler, T.; Weber, M. Mobile Device Interaction in Ubiquitous Computing. In Advances in Human Computer Interaction; IntechOpen: London, UK, 2008. [Google Scholar]
  22. ORock Technologies. A Practical Guide to Mission-Critical Cloud Computing; ORock Technologies: Reston, VA, USA, 2021; pp. 1–13. [Google Scholar]
  23. Torre-Bastida, A.I.; Díaz-de-Arcaya, J.; Osaba, E.; Muhammad, K.; Camacho, D.; Del Ser, J. Bio-inspired computation for big data fusion, storage, processing, learning and visualization: State of the art and future directions. Neural Comput. Appl. 2021, 1–31. [Google Scholar] [CrossRef]
  24. Javaid, M.; Haleem, A.; Vaishya, R.; Bahl, S.; Suman, R.; Vaish, A. Industry 4.0 technologies and their applications in fighting COVID-19 pandemic. Diabetes Metab. Syndr. Clin. Res. Rev. 2020, 14, 419–422. [Google Scholar] [CrossRef]
  25. Zhang, P.; White, J.; Schmidt, D.C.; Lenz, G. Applying Software Patterns to Address Interoperability in Blockchain-basedHealthcare Apps. In Proceedings of the 24th Pattern Languages of Programming Conference, Vancouver, BC, Canada, 22–25 October 2017. [Google Scholar]
  26. IBM Global Business Services Public Sector Team. Blockchain: The Chain of Trust and Its Potential to Transform Healthcare–Our Point of View. In Proceedings of the ONC/NIST Use of Blockchain for Healthcare and Research Workshop, Gaithersburg, MD, USA, 8 August 2016.
  27. Wang, Q.; Su, M.; Zhang, M.; Li, R. Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare. Int. J. Environ. Res. Public Health 2021, 18, 6053. [Google Scholar] [CrossRef]
  28. Agbehadji, I.E.; Awuzie, B.O.; Ngowi, A.B.; Millham, R.C. Review of Big Data Analytics, Artificial Intelligence and Nature-inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing. Int. J. Environ. Res. Public Health 2020, 17, 1–13. [Google Scholar] [CrossRef]
  29. Langthaler, M.; Bazafkan, H. Digitalization, Education and Skills Development in the Global South: An Assessment of the Debate with a Focus on SubSaharan Africa; ÖFSE Briefing Paper, No. 28; Austrian Foundation for Development Research (ÖFSE): Vienna, Austria, 2020. [Google Scholar]
  30. Khomo, F.L.; Abayomi, A.; Adetiba, E.; Agbehadji, I.E.; Mutanga, B.M.; Jugoo, V. Digital Innovations for Post-CoViD-19 Pandemic Recovery. In Proceedings of the 2021 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, Durban, South Africa, 5–6 August 2021; p. 7. [Google Scholar]
  31. Miller, P. COVID-19 Fast-Tracking the Fourth Industrial Revolution. 2021. Available online: https://www.cipla.co.za/press-releases/covid-19-fast-tracking-the-fourth-industrial-revolution (accessed on 6 May 2021).
  32. Villegas-Ch, W.; Palacios-Pacheco, X.; Luján-Mora, S. Application of a Smart City Model to a Traditional University Campus with a Big Data Architecture: A Sustainable Smart Campus. Sustainability 2019, 11, 1–28. [Google Scholar] [CrossRef] [Green Version]
  33. Lee, S.M.; Lee, D. Opportunities and challenges for contactless healthcare services in the post-COVID-19 Era. Technol. Forecast. Soc. Chang. 2021, 167, 120712. [Google Scholar] [CrossRef]
  34. Chu, D.K.; Akl, E.A.; Duda, S.; Solo, K.; Yaacoub, S.; Schünemann, H.J.; El-Haraheh, A.; Bognanni, A.; Lotfi, T.; Loeb, M.; et al. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A systematic review and meta-analysis. Lancet 2020, 395, 1973–1987. [Google Scholar] [CrossRef]
  35. Rubega, G.F. How COVID-19 Accelerated Manufacturing into the 4IR. 2021. Available online: https://www.wolfandco.com/resources/insights/how-covid-19-accelerated-manufacturing-into-the-4ir/ (accessed on 4 August 2021).
  36. Al-Ulyan, Y. Rebuilding after COVID: The Challenge Is Digital. 2021. Available online: https://www.weforum.org/agenda/2021/06/rebuilding-the-world-after-covid-the-challenge-is-digital/ (accessed on 10 June 2021).
  37. Zeng, Z.; Chen, P.; Lew, A. From high-touch to high-tech: COVID-19 drives robotics adoption. Tour. Geogr. 2020, 22, 1–11. [Google Scholar] [CrossRef]
  38. Lee, S.M.; Lee, D. Untact’: A new customer service strategy in the digital age. Serv. Bus. 2020, 14, 1–22. [Google Scholar] [CrossRef]
  39. World Health Organization. Digital Documentation of COVID-19 Certificates: Vaccination Status. In Technical Specifications and Implementation Guidance; World Health Organization: Geneva, Switzerland, 2021; p. 99. [Google Scholar]
  40. European Parliament. EU Covid-19 Certificate: A tool to Help Restore the Free Movement of People Across the European Union; European Parliament: Brussels, Belgium, 2021; p. 12. [Google Scholar]
  41. European Commission. EU Digital COVID Certificate; European Commission: Brussels, Belgium, 2021; p. 3. [Google Scholar]
  42. Schengenvisainfo News. All Details on EU COVID-19 Vaccine Passport Revealed: Here’s What You Need to Know. 2021. Available online: https://www.schengenvisainfo.com/news/all-details-on-eu-covid-19-passport-revealed-heres-what-you-need-to-know/ (accessed on 2 July 2021).
  43. Elflein, J. COVID-19 Vaccine Doses Administered Worldwide as of August 2021, by Country. Available online: https://www.statista.com/statistics/1194934/number-of-covid-vaccine-doses-administered-by-county-worldwide/ (accessed on 30 August 2021).
  44. World Health Organization. Assessment of the COVID-19 Supply Chain System: Full Report. 2021. Available online: https://www.who.int/publications/m/item/assessment-of-the-covid-19-supply-chain-system-report (accessed on 30 April 2021).
  45. Ahuja, A.S.; Reddy, V.P.; Marques, O. Artificial Intelligence and COVID-19: A Multidisciplinary Approach. Integr. Med. Res. 2020, 9. [Google Scholar] [CrossRef]
  46. Sattari, N. Women driving women: Drivers of women-only taxis in the Islamic Republic of Iran. Women’s Stud. Int. Forum 2020, 78, 102324. [Google Scholar] [CrossRef]
  47. Devrim, I.; Bayram, N. Infection control practices in children during COVID-19 pandemic: Differences from adults. Am. J. Infect. Control. 2020, 48, 933–939. [Google Scholar] [CrossRef] [PubMed]
  48. Signé, L.; Khagram, S.; Goldstein, J. Using the Fourth Industrial Revolution to fight COVID-19 Around the World. 2020. Available online: https://www.brookings.edu/techstream/using-the-fourth-industrial-revolution-to-fight-covid-19-around-the-world/ (accessed on 28 April 2020).
  49. George, K. Manufacturing Reimagined: From Improved Productivity to Profitable Growth. 2021. Available online: https://www.weforum.org/agenda/2021/01/manufacturing-reimagined-from-improved-productivity-to-profitable-growth/ (accessed on 18 January 2021).
  50. Barata, J.; Da Cunha, P.R.; Stal, J. Mobile supply chain management in the Industry 4.0 era. J. Enterp. Inf. Manag. 2018, 31, 173–192. [Google Scholar] [CrossRef]
  51. MCA Connect. The Future of Manufacturing: Digital Acceleration, in New Trends and Innovations for the Industry; MCA Connect: Denver, CO, USA, 2021; pp. 1–14. [Google Scholar]
  52. Battle-Fisher, M. Transhuman, posthuman and complex humanness in the 21st century. Ethics Med. Public Health 2020, 13, 100400. [Google Scholar] [CrossRef]
  53. Liu, Y.; Zhang, W.; Pan, S.; Li, Y.; Chen, Y. Analyzing the robotic behavior in a smart city with deep enforcement and imitation learning using IoRT. Comput. Commun. 2020, 2020, 346–356. [Google Scholar] [CrossRef]
  54. Lamptey, E.; Serwaa, D. The use of Zipline drones technology for COVID-19 samples transportation in Ghana. HighTech Innov. J. 2020, 1, 67–71. [Google Scholar] [CrossRef]
  55. Zhu, B.; Zheng, X.; Liu, H.; Li, J.; Wang, P. Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. Chaos Solitons Fractals 2020, 140, 110123. [Google Scholar] [CrossRef]
  56. Allam, Z.; Dey, G.; Jones, D.S. Artificial intelligence (AI) provided early detection of the coronavirus (COVID-19) in China and will influence future Urban health policy internationally. AI 2020, 1, 156–165. [Google Scholar] [CrossRef] [Green Version]
  57. Shakhovska, N.; Fedushko, S.; Melnykova, N.; Shvorob, I.; Syerov, Y. Big Data analysis in development of personalized medical system. Procedia Comput. Sci. 2019, 160, 229–234. [Google Scholar] [CrossRef]
  58. People’s Daily Online. In This Way, Close Contacts Are Detected. Available online: http://paper.people.com.cn/rmrb/html/2020-02/14/nw.D110000renmrb_20200214_1-12.htm (accessed on 4 August 2021).
  59. Ahmed, N.; Michelin, R.A.; Xue, W.; Ruj, S.; Malaney, R.; Kanhere, S.S.; Seneviratne, A.; Hu, W.; Janicke, H.; Jha, S. A Survey of COVID-19 Contact Tracing Apps. IEEE Access 2020, 8, 134577–134601. [Google Scholar] [CrossRef]
  60. Vidakis, N.; Petousis, M.; Velidakis, E.; Tzounis, L. The Response of the Hellenic 3D-Printing Community over the COVID-19 Pandemics: The Success Story of the Hellenic Mediterranean University. Am. J. Biomed. Sci. Res. 2020, 9, 199–203. [Google Scholar]
  61. Pappas, G.; Vidakis, N.; Petousis, M. Technology Driven Mitigation of COVID-19 Infection Risk in Retinal Surgery, by means of 3D Visualization Systems. J. Ophthalmol. Res. 2020, 3, 65–70. [Google Scholar] [CrossRef]
  62. Nageshwaran, G.; Harris, R.C.; Guerche-Seblain, C.E. Review of the role of big data and digital technologies in controlling COVID-19 in Asia: Public health interest vs. privacy. Digit. Health 2021, 7, 1–12. [Google Scholar]
  63. Atif, I.; Cawood, F.T.; Mahboob, M.A. The Role of Digital Technologies that Could Be Applied for Prescreening in the Mining Industry During the COVID-19 Pandemic. Trans. Indian Natl. Acad. Eng. 2020, 5, 663–674. [Google Scholar] [CrossRef]
  64. Marin, A. Telemedicine Takes Center Stage in the Era of COVID-19. Science 2020, 370, 731–733. [Google Scholar] [CrossRef]
  65. Wenyan, W.M. AI Strawberries and Blockchain Chicken: How Digital Agriculture Could Rescue Global Food Security. 2021. Available online: https://www.weforum.org/agenda/2021/01/china-digital-agriculture-global-food-security/ (accessed on 26 January 2021).
  66. Fox, L.; Signé, L. The Fourth Industrial Revolution (4IR) and the Future of Work: Could this Bring Good Jobs to Africa? Evidence Synthesis Paper Series; INCLUDE Knowledge Platform: Leiden, The Netherlands, 2021; Volume 6, p. 51. [Google Scholar]
  67. Mining Review Africa. Ten Insights Into 4IR—the State of Digital Transformation. 2021. Available online: https://www.miningreview.com/gold/ten-insights-into-4ir-digital-transformation-in-the-mining-industry/ (accessed on 18 May 2021).
  68. Temkin, S. Ten Insights Into 4IR—The State of Digital Transformation in the South African Mining Industry; PwC and Minerals Council of South AFrica Report. 2021. Available online: https://www.pwc.co.za/en/press-room/10-insights-into-4ir.html (accessed on 4 August 2021).
  69. Zervoudi, E.K. Fourth Industrial Revolution: Opportunities, Challenges, and Proposed Policies. In Industrial Robotics—New Paradigm; IntechOpen: London, UK, 2020; p. 26. [Google Scholar]
  70. Ndung’u, N.; Signé, L. The Fourth Industrial Revolution and Digitization Will Transform Africa into a Global Powerhouse. 2020. Available online: https://www.brookings.edu/research/the-fourth-industrial-revolution-and-digitization-will-transform-africa-into-a-global-powerhouse/ (accessed on 4 August 2021).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.