Making location-aware computing working accurately in smart spaces

In smart environment, making a location-aware personal computing working accurately is a way of getting close to the pervasive computing vision. The best candidate to determine a user location in indoor environment is by using IEEE 802.11 (Wi-Fi) signals, since it is more and more widely available a...

Full description

Bibliographic Details
Main Authors:	Mantoro, Teddy, Ayu, Media Anugerah, Weyn, Maarten
Other Authors:	Cruz-Cunha, Maria Manuela
Format:	Book Chapter
Language:	English
Published:	IGI Global 2011
Subjects:	T Technology (General) T58.5 Information technology
Online Access:	http://irep.iium.edu.my/3410/ http://irep.iium.edu.my/3410/ http://irep.iium.edu.my/3410/ http://irep.iium.edu.my/3410/1/LocationAwareIGI.pdf

id	iium-3410
recordtype	eprints
spelling	iium-34102011-09-22T00:49:50Z http://irep.iium.edu.my/3410/ Making location-aware computing working accurately in smart spaces Mantoro, Teddy Ayu, Media Anugerah Weyn, Maarten T Technology (General) T58.5 Information technology In smart environment, making a location-aware personal computing working accurately is a way of getting close to the pervasive computing vision. The best candidate to determine a user location in indoor environment is by using IEEE 802.11 (Wi-Fi) signals, since it is more and more widely available and installed on most mobile devices used by users. Unfortunately, the signal strength, signals quality and noise of Wi-Fi, in worst scenario, it fluctuates up to 33% because of the reflection, refraction, temperature, humidity, the dynamic environment, etc. We present our current development on a light-weight algorithm, which is easy, simple but robust in producing the determination of user location using WiFi signals. The algorithm is based on “multiple observers” on ηk-Nearest Neighbour. We extend our approach in the estimation indoor-user location by using combination of different technologies, i.e. WiFi, GPS, GSM and Accelerometer. The algorithm is based on opportunistic localization algorithm and fuse different sensor data in order to be able to use the data which is available at the user position and processable in a mobile device. IGI Global Cruz-Cunha, Maria Manuela Moreira, Fernando 2011 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/3410/1/LocationAwareIGI.pdf Mantoro, Teddy and Ayu, Media Anugerah and Weyn, Maarten (2011) Making location-aware computing working accurately in smart spaces. In: Handbook of Research on Mobility and Computing. IGI Global, Hershey, pp. 539-557. ISBN 978-1-60960-042-6 http://dx.doi.org/10.4018/978-1-60960-042-6.ch035 10.4018/978-1-60960-042-6.ch035
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General) T58.5 Information technology
spellingShingle	T Technology (General) T58.5 Information technology Mantoro, Teddy Ayu, Media Anugerah Weyn, Maarten Making location-aware computing working accurately in smart spaces
description	In smart environment, making a location-aware personal computing working accurately is a way of getting close to the pervasive computing vision. The best candidate to determine a user location in indoor environment is by using IEEE 802.11 (Wi-Fi) signals, since it is more and more widely available and installed on most mobile devices used by users. Unfortunately, the signal strength, signals quality and noise of Wi-Fi, in worst scenario, it fluctuates up to 33% because of the reflection, refraction, temperature, humidity, the dynamic environment, etc. We present our current development on a light-weight algorithm, which is easy, simple but robust in producing the determination of user location using WiFi signals. The algorithm is based on “multiple observers” on ηk-Nearest Neighbour. We extend our approach in the estimation indoor-user location by using combination of different technologies, i.e. WiFi, GPS, GSM and Accelerometer. The algorithm is based on opportunistic localization algorithm and fuse different sensor data in order to be able to use the data which is available at the user position and processable in a mobile device.
author2	Cruz-Cunha, Maria Manuela
author_facet	Cruz-Cunha, Maria Manuela Mantoro, Teddy Ayu, Media Anugerah Weyn, Maarten
format	Book Chapter
author	Mantoro, Teddy Ayu, Media Anugerah Weyn, Maarten
author_sort	Mantoro, Teddy
title	Making location-aware computing working accurately in smart spaces
title_short	Making location-aware computing working accurately in smart spaces
title_full	Making location-aware computing working accurately in smart spaces
title_fullStr	Making location-aware computing working accurately in smart spaces
title_full_unstemmed	Making location-aware computing working accurately in smart spaces
title_sort	making location-aware computing working accurately in smart spaces
publisher	IGI Global
publishDate	2011
url	http://irep.iium.edu.my/3410/ http://irep.iium.edu.my/3410/ http://irep.iium.edu.my/3410/ http://irep.iium.edu.my/3410/1/LocationAwareIGI.pdf
first_indexed	2023-09-18T20:11:14Z
last_indexed	2023-09-18T20:11:14Z
_version_	1777407491497263104

Making location-aware computing working accurately in smart spaces

Similar Items