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Sensor Networks and IoT for E-health Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 7968

Special Issue Editors


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Guest Editor
Department of Computer Science and Engineering, Maharaja Agrasen institute of Technology (GGSIPU), Delhi 110086, India
Interests: software engineering; software usability; human computer interaction; algorithm computing; soft computing; neural networks; testing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, sensor networks (SN) and Internet of Things (IoT) became emerging technologies with tremendous popularity among industry and academia. Due to their multidisciplinary approach, sensor networks and IoT have been phenomenal in revolutionizing many aspects of traditional healthcare and ambient assisted living paradigms. At the same time, traditional healthcare systems can no longer satisfy the needs of a continuously growing and developing society.

Sensor networks are composed of resource-constrained devices to gather data from the environment. These devices allow the continuous and real-time collection of an individual's health information and their related behavior. IoT is considered a bridging platform that connects the physical world and cyberspace so that healthcare services and applications with high efficiency and productivity can be obtained. However, in-depth research efforts on IoT systems, networks, and architectures for efficient large-scale deployments are still required to fill the gaps between the satisfying quality of service requirements and cost-effective implementations and operations.

IoT and sensor networks have emerged as very effective services in the healthcare industry as the integration of IoT devices with medical applications improves their performance and quality, thus providing high value to patients. IoT and sensor networks have been applied for various e-Health applications and thus improve the diagnostic tools, such as body monitoring, and epigenetic and neuropsychological tests.

All submitted papers to this Special Issue should focus on new contributions to the state-of-the-art in various aspects of sensor networks and IoT, supported with e-Health applications, from both academia and industry.

Prof. Dr. Joel J. P. C. Rodrigues
Dr. Deepak Gupta
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. Sensors 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 2600 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

  • IoT sensors and architectures for e-Health
  • Intelligent sensing technologies for e-Health
  • Cloud and Edge computing for IoT on e-Health
  • Data science and data analytics in e-Health
  • Ambient assisted living IoT for active and healthy aging
  • Interoperability and standards for IoT on e-Health
  • Blockchain service for e-Health
  • IoT and cyber-physical systems for eHealth
  • E-Health devices and instruments
  • E-Health services and applications
  • Telemedicine and telerehabilitation
  • Safety, security, privacy, and ethics in IoT on e-Health
  • Exploiting 5G for IoT and SN on e-Health

Published Papers (2 papers)

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Research

20 pages, 20841 KiB  
Article
Secure Patient Data Transfer Using Information Embedding and Hyperchaos
by Hanan Aljuaid and Shabir A. Parah
Sensors 2021, 21(1), 282; https://doi.org/10.3390/s21010282 - 04 Jan 2021
Cited by 13 | Viewed by 2051
Abstract
Health 4.0 is an extension of the Industry standard 4.0 which is aimed at the virtualization of health-care services. It employs core technologies and services for integrated management of electronic health records (EHRs), captured through various sensors. The EHR is processed and transmitted [...] Read more.
Health 4.0 is an extension of the Industry standard 4.0 which is aimed at the virtualization of health-care services. It employs core technologies and services for integrated management of electronic health records (EHRs), captured through various sensors. The EHR is processed and transmitted to distant experts for better diagnosis and improved healthcare delivery. However, for the successful implementation of Heath 4.0 many challenges do exist. One of the critical issues that needs attention is the security of EHRs in smart health systems. In this work, we have developed a new interpolation scheme capable of providing better quality cover media and supporting reversible EHR embedding. The scheme provides a double layer of security to the EHR by firstly using hyperchaos to encrypt the EHR. The encrypted EHR is reversibly embedded in the cover images produced by the proposed interpolation scheme. The proposed interpolation module has been found to provide better quality interpolated images. The proposed system provides an average peak signal to noise ratio (PSNR) of 52.38 dB for a high payload of 0.75 bits per pixel. In addition to embedding EHR, a fragile watermark (WM) is also encrypted using the hyperchaos embedded into the cover image for tamper detection and authentication of the received EHR. Experimental investigations reveal that our scheme provides improved performance for high contrast medical images (MI) when compared to various techniques for evaluation parameters like imperceptibility, reversibility, payload, and computational complexity. Given the attributes of the scheme, it can be used for enhancing the security of EHR in health 4.0. Full article
(This article belongs to the Special Issue Sensor Networks and IoT for E-health Applications)
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23 pages, 2814 KiB  
Article
An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare
by Deep Kumar Bangotra, Yashwant Singh, Arvind Selwal, Nagesh Kumar, Pradeep Kumar Singh and Wei-Chiang Hong
Sensors 2020, 20(14), 3887; https://doi.org/10.3390/s20143887 - 13 Jul 2020
Cited by 48 | Viewed by 4770
Abstract
The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets [...] Read more.
The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services. Full article
(This article belongs to the Special Issue Sensor Networks and IoT for E-health Applications)
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