phat 21(26): e1

Research Article

Intelligent Internet of Things and Advanced Machine Learning Techniques for COVID-19

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  • @ARTICLE{10.4108/eai.28-1-2021.168505,
        author={Chinmay Chakraborty and Arij Naser Abougreen},
        title={Intelligent Internet of Things and Advanced Machine Learning Techniques for COVID-19},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        keywords={Machine learning, Coronavirus, Artificial Intelligence, Internet of Things},
  • Chinmay Chakraborty
    Arij Naser Abougreen
    Year: 2021
    Intelligent Internet of Things and Advanced Machine Learning Techniques for COVID-19
    DOI: 10.4108/eai.28-1-2021.168505
Chinmay Chakraborty1,*, Arij Naser Abougreen2
  • 1: Electronics & Communication Engineering, Birla Institute of Technology, Mesra, Jharkhand, India
  • 2: Electrical and Electronics Engineering Department, Faculty of Engineering, University of Tripoli, Tripoli, Libya
*Contact email:


INTRODUCTION: Coronavirus disease (COVID-19) has recently emerged around the world. The beginning of the disease was in the Chinese city of Wuhan and then it has been spread and became a global epidemic. An early diagnosis of COVID-19 disease is absolutely necessary to control the epidemic.

OBJECTIVES: The aim of this paper is to present a review of the contribution of machine learning (ML) and IoT to confront the epidemic.

METHODS: Diagnosis using real-time reverse transcriptase-polymerase chain reaction (RT-PCR) is a definite diagnosis, but this method takes time, while a diagnosis using a computed tomography (CT) scan is a faster approach to diagnosis. However, a large number of patients need a CT scan, which puts a lot of pressure on the radiologist so visual fatigue may lead to diagnostic errors so there is an urgent need for additional solutions. Artificial intelligence (AI) is an efficient tool to combat COVID-19 disease. Computer scientists have been developing many systems to handle this epidemic.

RESULTS: It was found that ML is an efficient and powerful AI technology that can be used for trustworthy COVID-19 detecting and diagnosis from X-ray and CT images and it can be a potential method for diagnosis in the radiology department. In addition, ML can be used in segmentation, prediction purposes for COVID-19. Furthermore, ML can effectively support drug discovery procedure and can reduce clinical failures.

CONCLUSION: IoT has a significant role in monitoring an individual's health and COVID-19 diagnosis. This paper also highlights the challenges of employing ML and intelligent IoT for fighting COVID-19.