3D geo-clustering for wireless sensor network in smart city

Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used...

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Main Authors: Azri, S., Ujang, U., Abdul Rahman, A.
Format: Conference or Workshop Item
Language:English
Published: 2019
Subjects:
Online Access:http://eprints.utm.my/id/eprint/89199/1/SuhaibahAzri2019_3DGeoClusteringforWirelessSensor.pdf
http://eprints.utm.my/id/eprint/89199/
http://www.dx.doi.org/10.5194/isprs-archives-XLII-4-W12-11-2019
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spelling my.utm.891992021-02-09T02:37:35Z http://eprints.utm.my/id/eprint/89199/ 3D geo-clustering for wireless sensor network in smart city Azri, S. Ujang, U. Abdul Rahman, A. HE Transportation and Communications Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used to acquire information and help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. However, no matter how much smart city may focus on sensor technology, data that are produced from sensors do not organize themselves in a database. Such tasks require a sophisticated database structure to produce informative data output. Besides that, wireless sensor network requires a proper design to improve the energy efficiency. The design will aid to prolong the lifespan of wireless network efficiently. In this study, we proposed a new technique that will be used to organize the information of wireless sensor network in the spatial database. Specific algorithm which is 3D geo-clustering algorithm is used to tackle several issues of location of the sensor in three-dimensional urban area in smart city. The algorithm is designed to minimizing the overlap among group clusters. Overlap plays an important role for energy efficiency. Thus, detection of sensors in two or more group clusters will avoid it from transmitting the same signal to cluster head node. It is prove that this algorithm would only create 5% to 10% overlap among group clusters. Several experiments are performed in this study to evaluate the algorithm. Based on the simulation results indicate that this algorithm can balance nodes energy consumption and prolong the network’s life span. It also has good stability and extensibility. Several tests are performed to validate the efficiency of the technique to measure the database performance. 2019 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/89199/1/SuhaibahAzri2019_3DGeoClusteringforWirelessSensor.pdf Azri, S. and Ujang, U. and Abdul Rahman, A. (2019) 3D geo-clustering for wireless sensor network in smart city. In: 5th International Conference on Geoinformation Science, Geo Advances 2018, 10-11 Oct 2018, Casablanca, Morocco. http://www.dx.doi.org/10.5194/isprs-archives-XLII-4-W12-11-2019
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic HE Transportation and Communications
spellingShingle HE Transportation and Communications
Azri, S.
Ujang, U.
Abdul Rahman, A.
3D geo-clustering for wireless sensor network in smart city
description Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used to acquire information and help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. However, no matter how much smart city may focus on sensor technology, data that are produced from sensors do not organize themselves in a database. Such tasks require a sophisticated database structure to produce informative data output. Besides that, wireless sensor network requires a proper design to improve the energy efficiency. The design will aid to prolong the lifespan of wireless network efficiently. In this study, we proposed a new technique that will be used to organize the information of wireless sensor network in the spatial database. Specific algorithm which is 3D geo-clustering algorithm is used to tackle several issues of location of the sensor in three-dimensional urban area in smart city. The algorithm is designed to minimizing the overlap among group clusters. Overlap plays an important role for energy efficiency. Thus, detection of sensors in two or more group clusters will avoid it from transmitting the same signal to cluster head node. It is prove that this algorithm would only create 5% to 10% overlap among group clusters. Several experiments are performed in this study to evaluate the algorithm. Based on the simulation results indicate that this algorithm can balance nodes energy consumption and prolong the network’s life span. It also has good stability and extensibility. Several tests are performed to validate the efficiency of the technique to measure the database performance.
format Conference or Workshop Item
author Azri, S.
Ujang, U.
Abdul Rahman, A.
author_facet Azri, S.
Ujang, U.
Abdul Rahman, A.
author_sort Azri, S.
title 3D geo-clustering for wireless sensor network in smart city
title_short 3D geo-clustering for wireless sensor network in smart city
title_full 3D geo-clustering for wireless sensor network in smart city
title_fullStr 3D geo-clustering for wireless sensor network in smart city
title_full_unstemmed 3D geo-clustering for wireless sensor network in smart city
title_sort 3d geo-clustering for wireless sensor network in smart city
publishDate 2019
url http://eprints.utm.my/id/eprint/89199/1/SuhaibahAzri2019_3DGeoClusteringforWirelessSensor.pdf
http://eprints.utm.my/id/eprint/89199/
http://www.dx.doi.org/10.5194/isprs-archives-XLII-4-W12-11-2019
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score 13.211869