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Special Issue "New Trends in Intelligent Social-Health Systems Empowered by Internet of Every Things"

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

Deadline for manuscript submissions: closed (28 February 2021).

Special Issue Editors

Prof.Dr. Mª Ángeles Verdejo-Espinosa
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Guest Editor
Universidad de Jaen, Jaen, Spain
Interests: Smart Grids; Smart Cities; Accessibility in engineering
Dr. Francisco Javier Cabrerizo-Lorite
grade Website
Guest Editor
Department of Computer Science and Artificial Intelligence University of Granada 18071, Granada, Spain
Interests: group decision making; consensus; fuzzy logic; linguistic modeling
Special Issues and Collections in MDPI journals
Prof.Dr. Yolanda María de la Fuente Robles
Website
Guest Editor
University of Jaén, 23071 Jaén, Spain
Interests: Dependency; Disability; Aging and Accessibility

Special Issue Information

The population pyramid is changing at an increasingly rapid pace, and the new structure involves unavoidable changes in public services and their financing, with particular reference to the world of health and social services. There is a real need to incorporate artificial intelligence into their processes over the next few years with intelligent systems that learn from existing applications in order to process and manipulate data and communicate with other expert systems. In this context, the Internet of Everything and devices with sensors play a key role in providing comfort, greater productivity, and cost reduction for individuals and companies.

This Special Issue is addressed to all intelligent social health systems designed with sensors following the Internet-of-Everything paradigm.

Dr. Macarena Espinilla-Estevéz
Prof. Dr. Mª Ángeles Verdejo-Espinosa
Dr. Francisco Javier Cabrerizo-Lorite
Prof. Dr. Yolanda María de la Fuente Robles
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. 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 2200 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

  • intelligent systems
  • Internet of Everything
  • artificial intelligence
  • soft computing
  • social health systems
  • accessibility
  • dependency
  • disability
  • aging
  • accessibility

Published Papers (1 paper)

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Research

Open AccessArticle
DOLARS, a Distributed On-Line Activity Recognition System by Means of Heterogeneous Sensors in Real-Life Deployments—A Case Study in the Smart Lab of The University of Almería
Sensors 2021, 21(2), 405; https://doi.org/10.3390/s21020405 - 08 Jan 2021
Viewed by 445
Abstract
Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real [...] Read more.
Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real time, including binary, wearable and location sensors. Different descriptors and metrics from the heterogeneous sensor data are integrated in a common feature vector whose extraction is developed by a sliding window approach under real-time conditions. DOLARS provides a distributed architecture where: (i) stages for processing data in AR are deployed in distributed nodes, (ii) temporal cache modules compute metrics which aggregate sensor data for computing feature vectors in an efficient way; (iii) publish-subscribe models are integrated both to spread data from sensors and orchestrate the nodes (communication and replication) for computing AR and (iv) machine learning algorithms are used to classify and recognize the activities. A successful case study of daily activities recognition developed in the Smart Lab of The University of Almería (UAL) is presented in this paper. Results present an encouraging performance in recognition of sequences of activities and show the need for distributed architectures to achieve real time recognition. Full article
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