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Special Issue "Sensor Technology for Smart Homes"

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

Deadline for manuscript submissions: 20 December 2019

Special Issue Editors

Guest Editor
Dr. Juan Ye

School of Computer Science, University of St Andrews, UK
Website | E-Mail
Interests: Privacy; Activity Recognition; Wearable computing
Guest Editor
Dr. Michael O'Grady

School of Computer Science, University College Dublin, Ireland
Website | E-Mail
Interests: ambient intelligence, pervasive computing, ubiquitous sensing
Guest Editor
Dr. Oresti Banos

Computational Behaviour Modelling Research Centre for Information and Communications Technology, University of Granada (UGR), 18071 Granada, Spain
Website | E-Mail
Interests: wearable, ubiquitous, and mobile computing, artificial intelligence, data mining, digital health

Special Issue Information

Dear Colleagues,

With the relentless advance in sensing technologies, we are witnessing an increasing number of sophisticated smart home deployments covering a wide spectrum of applications including  health monitoring and home automation. However, the inherent complexity of real-world deployment is significantly challenging current smart home systems; such complexity includes the inherently imperfect nature of sensing technologies, the dynamic nature of human behaviour, and the unpredictability of situations or events occurring in the home. Various problems accrue as a result of such complexity; these include  decreased accuracies in recognising human activities over time and subsequent degradation of the performance of smart home systems with negative implications for user experience.

The objective of this Special Issue is to present the state-of-the-art in sensing technologies for the smart home; document realistic experiences of long-term, real-world smart home deployments; explore novel intelligent algorithms to discover and adapt smart home systems to changes in human daily routines and other contexts; and present new research challenges and opportunities in the smart home domain.

Original, high-quality contributions from both academia and industry are sought. Manuscripts submitted for review should not have been published elsewhere or be under review by other journals or peer-reviewed conferences.

Topics of interest include, but are not limited to, the following:

  • Novel sensing technologies for smart homes;
  • Standardisation initiatives applicable to smart homes;
  • Internet of Things approaches for smart homes;
  • Privacy, security, and data management within smart homes;
  • User experiences of smart home technologies;
  • Human activity recognition, both predictive and in near real time;
  • Interaction design and novel user interfaces for smart homes;
  • Approaches to modelling computational and social intelligence within smart homes;
  • Novel applications and services for the smart home;
  • Smart homes and their inter-relationship with smart cities.
The editors are particularly interested in receiving submissions that consider the following issues:
  • The lifelong learning of occupant behaviour in smart home systems;
  • Human-centred learning in smart home systems;
  • Methodologies for benchmarking smart home platforms and services;
  • Ethical and privacy-preservation approaches to smart homes.

Dr. Juan Ye
Dr. Michael O'Grady
Dr. Oresti Banos
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 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

  • Sensing technologies
  • Intelligence systems
  • Context reasoning
  • Intelligent user interfaces
  • Smart environments

Published Papers (3 papers)

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Research

Open AccessArticle A Multi-Agent Gamification System for Managing Smart Homes
Sensors 2019, 19(5), 1249; https://doi.org/10.3390/s19051249
Received: 13 February 2019 / Revised: 6 March 2019 / Accepted: 7 March 2019 / Published: 12 March 2019
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Abstract
Rapid development and conducted experiments in the field of the introduction the fifth generation of the mobile network standard allow for the flourishing of the Internet of Things. This is one of the most important reasons to design and test systems that can [...] Read more.
Rapid development and conducted experiments in the field of the introduction the fifth generation of the mobile network standard allow for the flourishing of the Internet of Things. This is one of the most important reasons to design and test systems that can be implemented to increase the quality of our lives. In this paper, we propose a system model for managing tasks in smart homes using multi-agent solutions. The proposed solution organizes work and distributes tasks to individual family members. An additional advantage is the introduction of gamification, not only between household members, but also between families. The solution was tested to simulate the entire solution as well as the individual components that make up the system. The proposal is described with regard to the possibility of implementing smart homes in future projects. Full article
(This article belongs to the Special Issue Sensor Technology for Smart Homes)
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Open AccessArticle The Effects of Housing Environments on the Performance of Activity-Recognition Systems Using Wi-Fi Channel State Information: An Exploratory Study
Sensors 2019, 19(5), 983; https://doi.org/10.3390/s19050983
Received: 18 January 2019 / Revised: 20 February 2019 / Accepted: 21 February 2019 / Published: 26 February 2019
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Abstract
Recently, device-free human activity–monitoring systems using commercial Wi-Fi devices have demonstrated a great potential to support smart home environments. These systems exploit Channel State Information (CSI), which represents how human activities–based environmental changes affect the Wi-Fi signals propagating through physical space. However, given [...] Read more.
Recently, device-free human activity–monitoring systems using commercial Wi-Fi devices have demonstrated a great potential to support smart home environments. These systems exploit Channel State Information (CSI), which represents how human activities–based environmental changes affect the Wi-Fi signals propagating through physical space. However, given that Wi-Fi signals either penetrate through an obstacle or are reflected by the obstacle, there is a high chance that the housing environment would have a great impact on the performance of a CSI-based activity-recognition system. In this context, this paper examines whether and to what extent housing environment affects the performance of the CSI-based activity recognition systems. Activities in daily living (ADL)–recognition systems were implemented in two typical housing environments representative of the United States and South Korea: a wood-frame apartment (Unit A) and a reinforced concrete-frame apartment (Unit B), respectively. The experimental results show that housing environments, combined with various environmental factors (i.e., structural building materials, surrounding Wi-Fi interference, housing layout, and population density), generate a significant difference in the accuracy of the applied CSI-based ADL-recognition systems. This outcome provides insights into how such ADL systems should be configured for various home environments. Full article
(This article belongs to the Special Issue Sensor Technology for Smart Homes)
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Open AccessArticle A Human–Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things
Sensors 2019, 19(4), 859; https://doi.org/10.3390/s19040859
Received: 2 January 2019 / Revised: 11 February 2019 / Accepted: 12 February 2019 / Published: 19 February 2019
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Abstract
People with severe disabilities may have difficulties when interacting with their home devices due to the limitations inherent to their disability. Simple home activities may even be impossible for this group of people. Although much work has been devoted to proposing new assistive [...] Read more.
People with severe disabilities may have difficulties when interacting with their home devices due to the limitations inherent to their disability. Simple home activities may even be impossible for this group of people. Although much work has been devoted to proposing new assistive technologies to improve the lives of people with disabilities, some studies have found that the abandonment of such technologies is quite high. This work presents a new assistive system based on eye tracking for controlling and monitoring a smart home, based on the Internet of Things, which was developed following concepts of user-centered design and usability. With this system, a person with severe disabilities was able to control everyday equipment in her residence, such as lamps, television, fan, and radio. In addition, her caregiver was able to monitor remotely, by Internet, her use of the system in real time. Additionally, the user interface developed here has some functionalities that allowed improving the usability of the system as a whole. The experiments were divided into two steps. In the first step, the assistive system was assembled in an actual home where tests were conducted with 29 participants without disabilities. In the second step, the system was tested with online monitoring for seven days by a person with severe disability (end-user), in her own home, not only to increase convenience and comfort, but also so that the system could be tested where it would in fact be used. At the end of both steps, all the participants answered the System Usability Scale (SUS) questionnaire, which showed that both the group of participants without disabilities and the person with severe disabilities evaluated the assistive system with mean scores of 89.9 and 92.5, respectively. Full article
(This article belongs to the Special Issue Sensor Technology for Smart Homes)
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