Applications of AI and IoT in COVID-19 Vaccine and Its Impact on Social Life

Almars, Abdulqader M.; Gad, Ibrahim; Atlam, El-Sayed

doi:10.1007/978-3-030-91103-4_7

Cited by 16 publications

(8 citation statements)

References 47 publications

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“…It will aid in forecasting demand and improve vaccine delivery just in time (Asundi et al, 2021). Manufacturers must work with stakeholders to exchange data such as possible accurate delays, expected delivery dates and the number of vials shipped to model the SC (Almars et al, 2022). Most vaccines require at least two doses, which simplifies transportation and supply.…”

Section: Introductionmentioning

confidence: 99%

Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach

Mukherjee

Baral

Chittipaka

et al. 2022

JHLSCM

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PurposeImmunization is one of the most cost-effective ways to save lives while promoting good health and happiness. The coronavirus disease 2019 (COVID-19) pandemic has served as a stark reminder of vaccines' ability to prevent transmission, save lives, and have a healthier, safer and more prosperous future. This research investigates the sustainable development (SD) of the COVID-19 vaccine supply chain (VSC).Design/methodology/approachThis study investigates the relationship between internal process, organizational growth, and its three pillars of SD environmental sustainability, economic sustainability and social sustainability. Survey-based research is carried out in the hospitals providing COVID-19 vaccines. Nine hypotheses are proposed for the study, and all the hypotheses got accepted. The survey was sent to 428 respondents and received 291 responses from health professionals with a response rate of 68%. For the study, the healthcare professionals working in both private and public hospitals across India were selected.FindingsThe structural equation modelling (SEM) approach is used to test the hypothesis. All nine hypotheses are supported. This study examines a link between internal processes and organizational learning and the three sustainability pillars (environmental sustainability, economic sustainability and social sustainability).Practical implicationsThis study will help the management and the policymakers to think and adopt SD in the COVID-19 VSC. This paper also implies that robust immunization systems will be required in the future to ensure that people worldwide are protected from COVID-19 and other diseases.Originality/valueThis paper shows the relationship between organizational learning and internal process with environmental sustainability, economic sustainability and social sustainability for the COVID-19. Studies on VSC of COVID-19 are not evident in any previous literature.

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Section: Introductionmentioning

confidence: 99%

Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach

Mukherjee

Baral

Chittipaka

et al. 2022

JHLSCM

View full text Add to dashboard Cite

show abstract

“…Some form of AI is now used in almost all areas of technology, and it will continue to spread throughout society (Grace et al, 2018;Almars et al, 2022). Current application areas include voice assistants, automatic speech recognition, translation, and generation that can exceed the human performance (Corea, 2019), automated driving and flying (Klos et al, 2020;Kulida and Lebedev, 2020), and medical technologies (areas where AI could touch our personal lives) (Klos et al, 2020;Jovanovic et al, 2022), as well as production control (Brauner et al, 2022), robotics and human-robot interaction (Onnasch and Roesler, 2020;Robb et al, 2020), human resource management, and prescriptive machine maintenance (areas where AI could touch our professional lives).…”

Section: Overview On Aimentioning

confidence: 99%

What does the public think about artificial intelligence?—A criticality map to understand bias in the public perception of AI

Brauner

Hick

Philipsen

et al. 2023

Front. Comput. Sci.

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IntroductionArtificial Intelligence (AI) has become ubiquitous in medicine, business, manufacturing and transportation, and is entering our personal lives. Public perceptions of AI are often shaped either by admiration for its benefits and possibilities, or by uncertainties, potential threats and fears about this opaque and perceived as mysterious technology. Understanding the public perception of AI, as well as its requirements and attributions, is essential for responsible research and innovation and enables aligning the development and governance of future AI systems with individual and societal needs.MethodsTo contribute to this understanding, we asked 122 participants in Germany how they perceived 38 statements about artificial intelligence in different contexts (personal, economic, industrial, social, cultural, health). We assessed their personal evaluation and the perceived likelihood of these aspects becoming reality.ResultsWe visualized the responses in a criticality map that allows the identification of issues that require particular attention from research and policy-making. The results show that the perceived evaluation and the perceived expectations differ considerably between the domains. The aspect perceived as most critical is the fear of cybersecurity threats, which is seen as highly likely and least liked.DiscussionThe diversity of users influenced the evaluation: People with lower trust rated the impact of AI as more positive but less likely. Compared to people with higher trust, they consider certain features and consequences of AI to be more desirable, but they think the impact of AI will be smaller. We conclude that AI is still a “black box” for many. Neither the opportunities nor the risks can yet be adequately assessed, which can lead to biased and irrational control beliefs in the public perception of AI. The article concludes with guidelines for promoting AI literacy to facilitate informed decision-making.

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“…IoT plays a crucial role in this disease as an IoT-based system is able to manage and balance the impact of SARS-CoV-2 in smart cities by cluster identification which identifies people who are not wearing face masks (Herath et al 2021). Other examples include monitoring vaccine temperature using IoT (Almars et al 2022).…”

Section: Applications Of Iot Imagesmentioning

confidence: 99%

Deep learning: survey of environmental and camera impacts on internet of things images

et al. 2023

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Internet of Things (IoT) images are captivating growing attention because of their wide range of applications which requires visual analysis to drive automation. However, IoT images are predominantly captured from outdoor environments and thus are inherently impacted by the camera and environmental parameters which can adversely affect corresponding applications. Deep Learning (DL) has been widely adopted in the field of image processing and computer vision and can reduce the impact of these parameters on IoT images. Albeit, there are many DL-based techniques available in the current literature for analyzing and reducing the environmental and camera impacts on IoT images. However, to the best of our knowledge, no survey paper presents state-of-the-art DL-based approaches for this purpose. Motivated by this, for the first time, we present a Systematic Literature Review (SLR) of existing DL techniques available for analyzing and reducing environmental and camera lens impacts on IoT images. As part of this SLR, firstly, we reiterate and highlight the significance of IoT images in their respective applications. Secondly, we describe the DL techniques employed for assessing the environmental and camera lens distortion impacts on IoT images. Thirdly, we illustrate how DL can be effective in reducing the impact of environmental and camera lens distortion in IoT images. Finally, along with the critical reflection on the advantages and limitations of the techniques, we also present ways to address the research challenges of existing techniques and identify some further researches to advance the relevant research areas.

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Applications of AI and IoT in COVID-19 Vaccine and Its Impact on Social Life

Cited by 16 publications

References 47 publications

Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach

Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach

What does the public think about artificial intelligence?—A criticality map to understand bias in the public perception of AI

Deep learning: survey of environmental and camera impacts on internet of things images

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