An intelligent framework using disruptive technologies for COVID-19 analysis

Faculty Computer Science Year: 2021
Type of Publication: ZU Hosted Pages:
Authors:
Journal: TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE Elsevier Volume:
Keywords : , intelligent framework using disruptive technologies , COVID-19    
Abstract:
This paper describes a framework using disruptive technologies for COVID-19 analysis. Disruptive technologies include high-tech and emerging technologies such as AI, industry 4.0, IoT, Internet of Medical Things (IoMT), big data, virtual reality (VR), Drone technology, and Autonomous Robots, 5 G, and blockchain to offer digital transformation, research and development and service delivery. Disruptive technologies are essential for Industry 4.0 development, which can be applied to many disciplines. In this paper, we present a framework that uses disruptive technologies for COVID-19 analysis. The proposed framework restricts the spread of COVID-19 outbreaks, ensures the safety of the healthcare teams and maintains patients' physical and psychological healthcare conditions. The framework is designed to deal with the severe shortage of PPE for the medical team, reduce the massive pressure on hospitals, and track recovered patients to treat COVID-19 patients with plasma. The study provides oversight for governments on how to adopt technologies to reduce the impact of unprecedented outbreaks for COVID-19. Our work illustrates an empirical case study on the analysis of real COVID-19 patients and shows the importance of the proposed intelligent framework to limit the current outbreaks for COVID-19. The aim is to help the healthcare team make rapid decisions to treat COVID-19 patients in hospitals, home quarantine, or identifying and treating patients with typical cold or flu.
   
     
 
       

Author Related Publications

  • Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019 More
  • Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014 More
  • Mohammed Abdel Basset Metwally Attia, "A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems", Springer London, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection", Pergamon, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations", Pergamon, 2021 More

Department Related Publications

  • Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019 More
  • Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014 More
  • Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015 More
  • Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013 More
  • Saber Mohamed, "Differential Evolution with Dynamic Parameters Selection for Optimization Problems", IEEE, 2014 More
Tweet