Theme Issue: Using the AI-powered cloud for COVID-19 and other infectious disease diagnosis [CFP]

Personal and Ubiquitous Computing


Fadi Al-Turjman
Near East University, Nicosia, Cyprus
Ahmed E. Kamal
Iowa State University, USA
Fabrizio Granelli
University of Trento, Italy.

The COVID-19 pandemic has revealed gaps in our understanding of the spread of contagious diseases, of preventative measures and the development and deployment of vaccines.

The combination of Artificial Intelligence, machine learning, big data, cloud computing, next generation networks and mobile devices may play a role filling some of these gaps.

For example, our mobile devices might be effective in identifying symptoms and diagnosing diseases such as those COVID-19 by using accumulated cloud-based big data on disease prevalence, transmission and diagnosis. This combination effectively forms a system of distributed processing modules that can be used to record data transactions on multiple interconnected smart devices – what we call ‘an internet hospital’.

This special issue seeks research articles that contribute to the current state of the art in cloud-assisted identification, diagnosis and management for COVID-19 and similar diseases.

It aims to draw together research in mobile Internet, big data, artificial intelligence, cloud computing and other technologies that can be combined in novel ways build cost-efficient ‘internet hospitals’ and other types of medical service platforms. The challenges that internet hospitals can meet include intelligent screening, symptom monitoring, online consultation, drug distribution and mental health support.

The issue aims to brings together a broad multidisciplinary community to integrate ideas, theories, models and techniques from different disciplines.


Topics of interest include, but are not limited to:
Cloud-oriented AI for COVID-19 and similar disease diagnosis
Big-Data and Neural Networks for tracking and disease diagnosis
AI-driven internet hospitals and online diagnosis
Image Progressing and ML for diagnosis
Use cases of cloud-assisted disease detection/prevention systems
Patient care and treatment using ML and Cloudlets enabling technologies
Emerging cloud solutions for improved diagnosis
Cloud-oriented ML solutions and services for medical diagnosis
Security and privacy aspects in screening, tracking and diagnosis


Submissions should be original papers and should not be under consideration for publication elsewhere.

Extended versions of papers from relevant conferences and workshops are invited as long as the additional contribution is substantial (at least 30% new content).

Authors should follow the formatting and submission instructions for Personal and Ubiquitous Computing at

For more information visit the
Springer Nature Information for journal Article Authors
pages at

During the first submission step in Editorial Manager select
Original article
as the article type. In further steps, you should confirm that your submission belongs to this special issue by choosing the special issue title from the drop-down menu.

All papers will be peer-reviewed.

Important dates

September 15, 2020.
November 15, 2020.
December 30, 2020.

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