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AI-Enabled IoT for Smart Healthcare Systems: Current Applications and Future Trends

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (10 March 2022) | Viewed by 10431

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Special Issue Editors

Prof. Dr. Subhas Mukhopadhyay

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Guest Editor

School of Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: smart sensors; sensing technology; WSN; IoT; ICT; smart grid; energy harvesting
Special Issues, Collections and Topics in MDPI journals

Dr. Shantanu Pal

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Guest Editor

School of Information Technology, Deakin University, Melbourne, Australia
Interests: Internet of Things (IoT); access control; distributed systems; blockchain; machine learning; artificial intelligence; sensor networks
Special Issues, Collections and Topics in MDPI journals

Dr. Nagender Kumar Suryadevara

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Guest Editor

Associate Professor, School of Computer and Information Sciences, University of Hyderabad, Hyderabad, Telangana 500046, India
Interests: internet of things; time series data mining, smart cities and applications; internet of things in intelligent health monitoring; wireless sensor networks, artificial intelligence in smart business applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial Intelligence (AI) and Internet of Things (IoT) are two emerging topics in current research in computer communication and networking. They have many interdisciplinary areas of application, including smart cities, smart transportation, and smart healthcare. The combination of AI with IoT is becoming common practice. There has been a tremendous rise in the use of AI and IoT together in healthcare to make it autonomous, intelligent and readily accessible to users at the highest operational functionalities. The combination of AI and IoT can ensure efficient data collection, enable proper analysis of the collected data and provide greater control in automation and management. However, better resource utilization, minimal human intervention and advocation for intelligent applications using AI-enabled IoT in the context of smart healthcare systems are still needed.

The rapid development of IoT further highlights the need for small, affordable sensors that allow accurate and reliable data recording, processing, storing and communication. AI brings many advantages when combined with IoT, particularly in the field of smart healthcare systems for which ubiquitous computing and traditional computational methods are inadequate. New challenges and opportunities represent a fertile ground for research and innovation in the development and deployment of AI with IoT in the broad context of smart healthcare systems. This requires novel methodological, theoretical and mathematical modelling and the implementation of protocols and computational methods that reflect recent advancements.

This Special Issue seeks novel contributions in the form of high-quality, unpublished and in-depth fundamental research that aims to address the existing technical problems and challenges in the domain of AI and IoT-enabled technologies, which an emphasis on smart heathcare systems. The goal of this Special Issue is to explore the existing architectures, models and techniques and to integreate new technologies, focusing on performance evaluation and comparison with existing solutions in field of AI and IoT for smart heathcare systems. This Special Issue encourages both theoretical and experimental studies of typical AI and IoT-related approaches foused on smart heathcare systems. Furthermore, high-quality review and survey papers are welcome. Acedemic researchers, developers and industry practitioners are invited to contribute papers to this Special Issue. Topics of Interest include (but are not limited to) one or more of the following topics:

Novel infrastructures, architectures and protocols for AI and IoT-enabled healthcare systems.
Techniques for AI and IoT-enabled mobile and cloud-based applications for healthcare management.
Remote healthcare and patient activity monitoring based on AI and IoT technologies.
Design and evaluation of AI and IoT technologies for healthcare automation.
Blockchain models and applications for AI and IoT systems in healthcare.
Hybrid approaches and emerging real-world applications of AI-enabled IoT in healthcare.
Energy-efficient AI and IoT applications and data analytics techniques in healthcare.
Energy-efficient hybrid AI and IoT-enabled systems for healthcare.
Tools, techniques and infrastructure that support development and deployment of AI and IoT-enabled systems for healthcare.
State-of-practice, industrial experiments, case studies and other technologies in the field of AI and IoT-enabled healthcare systems.
Security, privacy, and trust issues for large-scale IoT systems, including Industry 4.0, Industrial IoT, etc.

Prof. Dr. Subhas Mukhopadhyay
Dr. Shantanu Pal
Dr. Nagender Kumar Suryadevara
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 submissions that pass pre-check are 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. Applied Sciences 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 2400 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

sensors for healthcare
internet of things
wireless sensors
smart sensors
wearable sensors
smart healthcare
artificial intelligence
patient care and monitoring
patient activity recognition
blockchain for healthcare
secure communications
security and privacy
WSN for smart activity
IoT enabled smart healthcare

Published Papers (2 papers)

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Research

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16 pages, 1969 KiB

Open AccessArticle

Blockchain-Based Healthcare Information Preservation Using Extended Chaotic Maps for HIPAA Privacy/Security Regulations

by Tian-Fu Lee, I-Pin Chang and Ting-Shun Kung

Appl. Sci. 2021, 11(22), 10576; https://doi.org/10.3390/app112210576 - 10 Nov 2021

Cited by 17 | Viewed by 3184

Abstract

A healthcare information system allows patients and other users to remotely login to medical services to access health data through the Internet. To protect the privacy of patients and security over the public network, secure communication is required. Therefore, the security of data in transmission has been attracting increasing attention. In recent years, blockchain technology has also attracted more attention. Relevant research has been published at a high rate. Most methods of satisfying relevant security-related regulations use modular and exponential calculation. This study proposes a medical care information preservation mechanism that considers the entire process of data storage in devices from wearable devices to mobile devices to medical center servers. The entire process is protected and complies with HIPAA privacy and security regulations. The proposed scheme uses extended chaotic map technology to develop ID-based key negotiation for wearable devices, and thereby reduces the amount of computing that must be carried out by wearable devices and achieve lightness quantify. It also uses the non-tamperability of the blockchain to ensure that the data have not been tampered with, improving data security. The proposed mechanism can resist a variety of attacks and is computationally lighter than the elliptic curve point multiplication that has been used elsewhere, while retaining its security characteristics. Full article

(This article belongs to the Special Issue AI-Enabled IoT for Smart Healthcare Systems: Current Applications and Future Trends)

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Review

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33 pages, 838 KiB

Open AccessReview

Analysis of Security Issues and Countermeasures for the Industrial Internet of Things

by Shantanu Pal and Zahra Jadidi

Appl. Sci. 2021, 11(20), 9393; https://doi.org/10.3390/app11209393 - 10 Oct 2021

Cited by 33 | Viewed by 5817

Abstract

Industrial Internet of Things (IIoT) can be seen as an extension of the Internet of Things (IoT) services and applications to industry with the inclusion of Industry 4.0 that provides automation, reliability, and control in production and manufacturing. IIoT has tremendous potential to accelerate industry automation in many areas, including transportation, manufacturing, automobile, marketing, to name a few places. When the benefits of IIoT are visible, the development of large-scale IIoT systems faces various security challenges resulting in many large-scale cyber-attacks, including fraudulent transactions or damage to critical infrastructure. Moreover, a large number of connected devices over the Internet and resource limitations of the devices (e.g., battery, memory, and processing capability) further pose challenges to the system. The IIoT inherits the insecurities of the traditional communication and networking technologies; however, the IIoT requires further effort to customize the available security solutions with more focus on critical industrial control systems. Several proposals discuss the issue of security, privacy, and trust in IIoT systems, but comprehensive literature considering the several aspects (e.g., users, devices, applications, cascading services, or the emergence of resources) of an IIoT system is missing in the present state of the art IIoT research. In other words, the need for considering a vision for securing an IIoT system with broader security analysis and its potential countermeasures is missing in recent times. To address this issue, in this paper, we provide a comparative analysis of the available security issues present in an IIoT system. We identify a list of security issues comprising logical, technological, and architectural points of view and consider the different IIoT security requirements. We also discuss the available IIoT architectures to examine these security concerns in a systematic way. We show how the functioning of different layers of an IIoT architecture is affected by various security issues and report a list of potential countermeasures against them. This study also presents a list of future research directions towards the development of a large-scale, secure, and trustworthy IIoT system. The study helps understand the various security issues by indicating various threats and attacks present in an IIoT system. Full article

(This article belongs to the Special Issue AI-Enabled IoT for Smart Healthcare Systems: Current Applications and Future Trends)

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