Next Article in Journal
Field Effect Sensors for Nucleic Acid Detection: Recent Advances and Future Perspectives
Previous Article in Journal
Novel Real-Time Diagnosis of the Freezing Process Using an Ultrasonic Transducer
Previous Article in Special Issue
Adaptive Control of the Packet Transmission Period with Solar Energy Harvesting Prediction in Wireless Sensor Networks
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(5), 10350-10379; doi:10.3390/s150510350

WSN- and IOT-Based Smart Homes and Their Extension to Smart Buildings

SEAT, Massey University, Palmerston North 4442, New Zealand
*
Author to whom correspondence should be addressed.
Academic Editors: Luciano Lavagno and Mihai T. Lazarescu
Received: 9 February 2015 / Revised: 13 April 2015 / Accepted: 24 April 2015 / Published: 4 May 2015
(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)

Abstract

Our research approach is to design and develop reliable, efficient, flexible, economical, real-time and realistic wellness sensor networks for smart home systems. The heterogeneous sensor and actuator nodes based on wireless networking technologies are deployed into the home environment. These nodes generate real-time data related to the object usage and movement inside the home, to forecast the wellness of an individual. Here, wellness stands for how efficiently someone stays fit in the home environment and performs his or her daily routine in order to live a long and healthy life. We initiate the research with the development of the smart home approach and implement it in different home conditions (different houses) to monitor the activity of an inhabitant for wellness detection. Additionally, our research extends the smart home system to smart buildings and models the design issues related to the smart building environment; these design issues are linked with system performance and reliability. This research paper also discusses and illustrates the possible mitigation to handle the ISM band interference and attenuation losses without compromising optimum system performance. View Full-Text
Keywords: IOTs; wellness function; behavioral detection; attenuation loss; interference; SNR (signal to noise ratio) IOTs; wellness function; behavioral detection; attenuation loss; interference; SNR (signal to noise ratio)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ghayvat, H.; Mukhopadhyay, S.; Gui, X.; Suryadevara, N. WSN- and IOT-Based Smart Homes and Their Extension to Smart Buildings. Sensors 2015, 15, 10350-10379.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top