Special Issue "Smart Homes: Current Status and Future Possibilities"

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708).

Deadline for manuscript submissions: 31 January 2018

Special Issue Editors

Guest Editor
Prof. Dr. Subhas Chandra Mukhopadhyay

School of Engineering, Macquarie University, NSW 2109, Sydney, Australia
Website | E-Mail
Phone: +61-2-9850-6510
Fax: +61-2-9850-9128
Interests: Smart Sensors; Sensors Modeling; Sensor Networks; Giant Magneto Resistive Sensor; Wireless Sensor Networks; Internet of Things; Healthcare
Guest Editor
Prof. Dr. Nagender Kumar Suryadevara

Computer Science and Engineering, Geethanjali College of Engineering and Technology, Hyderabad 501301, Andhra Pradesh, India
Website | E-Mail
Phone: +91-850-0118-379
Interests: wireless sensor networks; internet of things; time series data mining

Special Issue Information

Dear Colleagues,

Smart Homes are the building blocks of Smart Cities under the theme of Internet of Things. In the most recent decade, advances in remote detecting innovation frameworks have led to an expansive number of different sorts of “Smart Homes”. The Smart Home is an integration system made of about three important entities: Firstly, the physical components (smart sensors and electronic gadgets); Secondly, the communication system (significant wireless advances used to actualize the frameworks using Z-Wave, Insteon, Wavenis, Bluetooth, WiFi, and ZigBee); Thirdly, the information processing through artificial intelligence programs (machine learning and data mining). Numerous proportional names are utilized for the savvy home framework, e.g., home observation, home computerization, assisted living framework, wise home etc.

The current advances in home computerization contribute towards achieving risk-free sheltered living as well as comfortable real life settings for the residential home environment. The Ubiquitous Monitoring systems might be more readily adopted by the residents if the monitoring systems were designed and developed as a custom-made tool. Ambient Assisted Living (AAL) is one of the brilliant home applications, which contains interoperable ideas, items, and administrations, which coordinate new data and correspondence advances and home situations with the aim of increasing the personal satisfaction of individuals in all phases of life.

This Special Issue aims to publish original, significant and visionary papers describing scientific methods and technologies that improve efficiency, productivity, quality and reliability in all areas of wireless home automation and Ambient Assisted Living. This Special Issue will provide a broad platform for publishing the many rapid advances that have been achieved to date in the area of wireless home automation and Ambient Assisted Living. In this Special Issue, we would like to focus on understanding what should be done to improve humans’ sensing awareness. Submissions of scientific results from experts in academia and industry worldwide are strongly encouraged.

Contributions may include, but are not limited to:

  • Intelligent sensors and actuators for homes, buildings and infrastructures
  • Real-time control and optimization
  • Distributed, networked and collaborative systems
  • Big data and real-time data processing
  • Wireless Communication protocols and implementation
  • Modelling and analysis of physical components and the environment
  • Modelling, analysis and integration of human activities
  • Energy efficiency in homes, buildings and infrastructures
  • Practical deployment and case studies
  • Anomaly detection in the smart home environment
  • Innovative wireless sensing and computing systems or prototypes
  • Innovative use of smartphones or mobile tablets for smart homes
  • Cloud-based data processing for human-awareness in home automation
  • Internet of Things (IOT) and cloud computing for the smart environment
  • Real-time and semantic web services

Prof. Dr. Subhas Chandra Mukhopadhyay
Prof. 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 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. Journal of Sensor and Actuator Networks is an international peer-reviewed open access quarterly 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 350 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

  • Smart Home
  • Wireless Sensor Networks
  • Ambient Assisted Living Environment
  • Home Monitoring System
  • Home Appliances

Published Papers (3 papers)

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Research

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Open AccessFeature PaperArticle Analyzing the Relationship between Human Behavior and Indoor Air Quality
J. Sens. Actuator Netw. 2017, 6(3), 13; doi:10.3390/jsan6030013
Received: 7 July 2017 / Revised: 29 July 2017 / Accepted: 31 July 2017 / Published: 2 August 2017
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Abstract
In the coming decades, as we experience global population growth and global aging issues, there will be corresponding concerns about the quality of the air we experience inside and outside buildings. Because we can anticipate that there will be behavioral changes that accompany
[...] Read more.
In the coming decades, as we experience global population growth and global aging issues, there will be corresponding concerns about the quality of the air we experience inside and outside buildings. Because we can anticipate that there will be behavioral changes that accompany population growth and aging, we examine the relationship between home occupant behavior and indoor air quality. To do this, we collect both sensor-based behavior data and chemical indoor air quality measurements in smart home environments. We introduce a novel machine learning-based approach to quantify the correlation between smart home features and chemical measurements of air quality, and evaluate the approach using two smart homes. The findings may help us understand the types of behavior that measurably impact indoor air quality. This information could help us plan for the future by developing an automated building system that would be used as part of a smart city. Full article
(This article belongs to the Special Issue Smart Homes: Current Status and Future Possibilities)
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Open AccessArticle Improvement of Ultrasound-Based Localization System Using Sine Wave Detector and CAN Network
J. Sens. Actuator Netw. 2017, 6(3), 12; doi:10.3390/jsan6030012
Received: 5 June 2017 / Revised: 9 July 2017 / Accepted: 18 July 2017 / Published: 31 July 2017
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Abstract
This paper presents an improved indoor localization system based on radio frequency (RF) and ultrasonic signals, which we named the SNSH system. This system is composed of a transmitter mounted in a mobile target and a series of receiver nodes that are managed
[...] Read more.
This paper presents an improved indoor localization system based on radio frequency (RF) and ultrasonic signals, which we named the SNSH system. This system is composed of a transmitter mounted in a mobile target and a series of receiver nodes that are managed by a coordinator. By measuring the Time Delay of Arrival (TDoA) of RF and ultrasonic signals from the transmitter, the distance from the target to each receiver node is calculated and sent to the coordinator through the CAN network, then all the information is gathered in a PC to estimate the 3D position of the target. A sine wave detector and dynamic threshold filter are applied to provide excellent accuracy in measuring the range from the TDoA results before multilateration algorithms are realized to optimize the accuracy of coordinate determination. Specifically, Linear Least Square (LLS) and Nonlinear Least Square (NLS) techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculation time are carefully considered to ensure optimal system performance and prepare for field application. Experiments show that the sine wave detector algorithm has greatly improved the accuracy of range measurement, with a mean error of 2.2 mm and maximum error of 6.7 mm for distances below 5 m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with the mean error in position remaining under 15 mm. Furthermore, there are 90% confidence error values of 23 mm for LLS and 20 mm for NLS. The update in the overall system has been verified in real system operations, with a maximum rate of 25 ms, which is a better result than many other existing studies. Full article
(This article belongs to the Special Issue Smart Homes: Current Status and Future Possibilities)
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Review

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Open AccessReview A Review of Smart House Analysis Methods for Assisting Older People Living Alone
J. Sens. Actuator Netw. 2017, 6(3), 11; doi:10.3390/jsan6030011
Received: 18 May 2017 / Revised: 4 July 2017 / Accepted: 14 July 2017 / Published: 21 July 2017
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Abstract
Smart Houses are a prominent field of research referring to environments adapted to assist people in their everyday life. Older people and people with disabilities would benefit the most from the use of Smart Houses because they provide the opportunity for them to
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Smart Houses are a prominent field of research referring to environments adapted to assist people in their everyday life. Older people and people with disabilities would benefit the most from the use of Smart Houses because they provide the opportunity for them to stay in their home for as long as possible. In this review, the developments achieved in the field of Smart Houses for the last 16 years are described. The concept of Smart Houses, the most used analysis methods, and current challenges in Smart Houses are presented. A brief introduction of the analysis methods is given, and their implementation is also reported. Full article
(This article belongs to the Special Issue Smart Homes: Current Status and Future Possibilities)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Intelligent Modeling and Analysis of Smart Home Environment for Fire Prevention and Safety
Authors: Anand Paul 1, Faisal Saeed 1, Abdul Rehman 1, Hong Won Hwa 2, Hyuncheol Seo 2
Affiliation: 1 The school of Computer Science and Engineering, Kyungpook National University
2 School of Architectural, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu, South Korea
Abstract: Fire generally occurs in house due to human carelessness and change in air conditions. They cause threats to the residential community and may result in human death and property damage. Consequently, house fires must be detected early to prevent greater damages. Immediate notification of the fire is the most critical issue in domestic fire detection systems. WSN can provide real-time fire detection with high accuracy. In this paper we proposed three methods to detect fire on early stage with the help of neighboring sensor if the particular sensor fails to detect the fire. First we proposed multi-sensors network, those multiple-sensors in one house or building work as a cluster and Second method is multi sensors network connected in a mesh ,if any sensor is inactive then the nearest sensor will help to generate alarm. The last one method that is our ultimate objective is to use uni-functional single sensor that is having some sensing problem, to immediate action we used probabilistic method to detect fire region and generate alarm. Our probability based statistical analysis proved to be very effective early detection of fire as well as warning through cloud based IoT.
Keywords: Fire detection; Multi-sensors; uni-functional

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