Smart Systems for Healthcare

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Techno-Social Smart Systems".

Deadline for manuscript submissions: closed (10 April 2019) | Viewed by 6621

Special Issue Editors


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Guest Editor
Department of Computer Science, University of Verona, Strada le Grazie, 15, 37134 Verona, Italy
Interests: computer science; bioinformatics; computational biology; parallel computing; graph theory; data integration
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Guest Editor
Associate Professor, School of Software, Dalian University of Technology, Dalian 116024, China
Interests: data analytics; scholarly big data; urban big data; open data; digital libraries; knowledge computing; vehicular social networks; ad hoc social networks; socially-aware networking; intelligent systems; human behaviours; social informatics; human dynamics; social network science; social computing and networking

Special Issue Information

Dear Colleagues,

Health automation systems are emerging as a new and interdisciplinary research field, in two different ways: medical smart assistance and the use of biomedical and/or bioinformatics approaches. We are witnessing a rapid development of advanced applications (by using information, communications, automation, and networking technologies) to realize smart and autonomous control systems in several systems regarding healthcare. Smart systems are critical in driving innovations in the field of medical technology, as they provide the basis for information-based health maintenance, and guarantee an efficient management of medical data and information processes (i.e., big data management in smart systems and smart networks).

Moreover, the integration of micro-sensors and micro-actuators will provide a technological healthcare for better treating and taking care of patients in the hospital and at home. The linking of micro-systems to telemetric and telediagnostic infrastructure significantly increases the effectiveness of treatments and simultaneously contributes to reducing public healthcare costs. Further applications regard professional sport and amatorial fitness areas, where such systems are applied for performance monitoring and body development. However, investigation of the communication techniques, computational models, and smart self-decisioning approaches are needed in terms of responsive time for automation systems. They will have a key role in the wireless or remote management of control applications, especially in the case of dynamic and shared environments with human beings. A variety of recent advanced technologies and approaches play important roles by exploiting innovative technologies and solutions that are applied to a variety of medical scenarios. They range from low-invasive solutions (e.g., the Fitbit) to implantable devices. Such technologies allow a wide spectrum of measurable evidence, from physiological events to micro-biological signals.

This special section solicits high-quality unpublished work on recent advances in smart systems in healthcare. The main topics of interest include but are not limited to the following:

  • Responsive architectures and technologies for medical automation systems
  • Sustainable design and solutions for responsive automation systems for healthcare
  • Efficient communications and management in medical automation application
  • Big data and data management for medical automation scenarios
  • Telemedicine and patients mobility management
  • Authentication security and privacy in health

Dr. Vincenzo Bonnici
Prof. Mario Collotta
Prof. Xiangjie Kong
Guest Editors

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Keywords

  • smart systems
  • healthcare
  • responsive architectures
  • medical automation
  • sustainable healthcare

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Published Papers (1 paper)

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Research

23 pages, 5134 KiB  
Article
An Investigation into Healthcare-Data Patterns
by Aaron Boddy, William Hurst, Michael Mackay, Abdennour El Rhalibi, Thar Baker and Casimiro A. Curbelo Montañez
Future Internet 2019, 11(2), 30; https://doi.org/10.3390/fi11020030 - 30 Jan 2019
Cited by 4 | Viewed by 5843
Abstract
Visualising complex data facilitates a more comprehensive stage for conveying knowledge. Within the medical data domain, there is an increasing requirement for valuable and accurate information. Patients need to be confident that their data is being stored safely and securely. As such, it [...] Read more.
Visualising complex data facilitates a more comprehensive stage for conveying knowledge. Within the medical data domain, there is an increasing requirement for valuable and accurate information. Patients need to be confident that their data is being stored safely and securely. As such, it is now becoming necessary to visualise data patterns and trends in real-time to identify erratic and anomalous network access behaviours. In this paper, an investigation into modelling data flow within healthcare infrastructures is presented; where a dataset from a Liverpool-based (UK) hospital is employed for the case study. Specifically, a visualisation of transmission control protocol (TCP) socket connections is put forward, as an investigation into the data complexity and user interaction events within healthcare networks. In addition, a filtering algorithm is proposed for noise reduction in the TCP dataset. Positive results from using this algorithm are apparent on visual inspection, where noise is reduced by up to 89.84%. Full article
(This article belongs to the Special Issue Smart Systems for Healthcare)
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