Special Issue "IoT, Edge Computing and AI: Enabling Emerging Intelligent Applications"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 30 September 2021.

Special Issue Editors

Dr. Abayomi Otebolaku
Website
Guest Editor
Department of Computing, College of Business, Technology and Engineering, Sheffield Hallam University, City Campus, Howard Street, Sheffield, S1 1WB, UK
Interests: mobile data management; ambient intelligence; context awareness; activity recognition; service personalization; IoT trust management; machine learning
Special Issues and Collections in MDPI journals
Prof. Gyu Myoung Lee
Website
Guest Editor
Reader, School of Computer Science and Mathematics, Liverpool John Moores University, L3 3AF, Liverpool, UK, Adjunct Professor, Daejeon, South Korea
Interests: internet of things; digital twin; trust in AI and data; 5G/6G networks
Special Issues and Collections in MDPI journals
Prof. Edward Meinert
Website
Guest Editor
University of Plymouth
Interests: eHealth; digital health; data science; artificial intelligence
Dr. Asiya Khan
Website
Guest Editor
University of Plymouth
Interests: video quality prediction and control; digital health; artificial intelligence
Dr. Gloria Iyawa

Guest Editor
Sheffield Hallam University
Interests: Digital Health, mhealth and ehealth

Special Issue Information

Dear Colleagues,

One of the critical factors for digital healthcare transformation is the proliferation of Internet of Things (IoT) devices to support healthcare and wellbeing. These devices allow connected and remote management of citizens’ healthy living and wellbeing, particularly as occasioned by the current coronavirus pandemic. IoT devices, i.e., wearable devices, from fitness trackers to portable blood pressure and insulin monitors, etc., generate an incredible amount of data, which could be analyzed to make time-critical and delay-sensitive decisions. However, current solutions rely on data processing and management in the cloud, which does not support time-critical decision making. Therefore, emerging and disruptive technologies such as edge computing, artificial intelligence (AI) and machine learning (ML) have the potential to address the challenges of citizens’ health and wellbeing using IoT and edge devices. With these technologies, data can be processed at the network edge, closer to the citizens, thereby allowing critical data to be collected and processed in real time, arming healthcare givers with the essential knowledge to save lives.

In this Special Issue, the aim is to publish high-quality articles including reviews that address various challenges in the use of these technologies (AI, IoT, edge computing) to support the healthcare and wellbeing of citizens.

The topics of interest include but not limited to:

  • Complex physical activity monitoring using IoT devices and AI;
  • AI techniques for health and wellbeing monitoring and prediction using IoT devices;
  • Security and privacy preservation of citizen sensitive data;
  • mHealth sensing and apps in healthcare;
  • Edge intelligence for healthcare management;
  • Real time and context-aware wellbeing/activity monitoring using IoT devices;
  • Edge computing for healthcare and citizens’ wellbeing management;
  • Ambient intelligence for homecare management using AI and edge computing;
  • Embedded AI for healthcare and wellbeing management;
  • AI powered Edge devices for physical activity monitoring, such as sport activity monitoring;
  • Mobile and ambient assisted living in smart home environment;
  • Senior citizens activity monitoring;
  • Medical image analysis;
  • Supporting citizens with disabilities using edge devices and AI, e.g., dangerous situation recognition, best route recommendation for blind pedestrians;
  • Security, privacy and trust in IoT for citizen’s healthcare and wellbeing;
  • Other emerging applications of AI, Edge computing and IoT.

Dr. Abayomi Otebolaku
Prof. Gyu Myoung Lee
Prof. Edward Meinert
Dr. Asiya Khan
Dr. Gloria Iyawa
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Complex physical activity monitoring using IoT devices and AI
  • AI techniques for health and wellbeing monitoring and prediction using IoT devices
  • Security and privacy preservation of citizen sensitive data
  • mHealth sensing and apps in healthcare
  • Edge intelligence for healthcare management
  • Real time and context-aware wellbeing/activity monitoring using IoT devices
  • Edge computing for healthcare and citizens’ wellbeing management
  • Ambient intelligence for homecare management using AI and edge computing
  • Embedded AI for healthcare and wellbeing management
  • AI powered Edge devices for physical activity monitoring, such as sport activity monitoring
  • Mobile and ambient assisted living in smart home environment
  • Senior citizens activity monitoring
  • Medical image analysis
  • Supporting citizens with disabilities using edge devices and AI, e.g., dangerous situation recognition, best route recommendation for blind pedestrians
  • Security, privacy and trust in IoT for citizen’s healthcare and wellbeing
  • Other emerging applications of AI, Edge computing and IoT

Published Papers

This special issue is now open for submission.
Back to TopTop