A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid

3D maps for mobile devices provide more realistic views of environments and serve as better navigation aids. Previous research studies show differences on how 3D maps effect the acquisition of spatial knowledge. This is attributable to the differences in mobile device computational capabilities....

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Main Authors:	Abubakar, Adamu, Mantoro, Teddy, Moedjiono, Sardjoeni, Anugerah Ayu, Media, Chiroma, Haruna, Waqas, Ahmad, Abdulhamid, Shafi’i Muhammad, Hamza, Mukhtar Fatihu, Ya’u Gital, Abdulsalam
Format:	Article
Language:	English English
Published:	International Association of Online Engineering 2016
Subjects:	QA76 Computer software
Online Access:	http://irep.iium.edu.my/51422/ http://irep.iium.edu.my/51422/ http://irep.iium.edu.my/51422/ http://irep.iium.edu.my/51422/1/Attached_SVM.pdf http://irep.iium.edu.my/51422/4/51422_A%20support%20vector%20machine%20classification.pdf

id	iium-51422
recordtype	eprints
spelling	iium-514222017-01-17T08:06:28Z http://irep.iium.edu.my/51422/ A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid Abubakar, Adamu Mantoro, Teddy Moedjiono, Sardjoeni Anugerah Ayu, Media Chiroma, Haruna Waqas, Ahmad Abdulhamid, Shafi’i Muhammad Hamza, Mukhtar Fatihu Ya’u Gital, Abdulsalam QA76 Computer software 3D maps for mobile devices provide more realistic views of environments and serve as better navigation aids. Previous research studies show differences on how 3D maps effect the acquisition of spatial knowledge. This is attributable to the differences in mobile device computational capabilities. Crucial to this is the time it takes for a 3D map dataset to be rendered for a complete navigation task. Different findings suggest different approaches on how to solve the problem of time required for both in-core (inside mobile) and out-core (remote) rendering of 3D datasets. Unfortunately, there have not been sufficient studies regarding the analytical techniques required to show the impact of computational resources required to use 3D maps on mobile devices. This paper uses a Support Vector Machine (SVM) to analytically classify mobile device computational capabilities required for 3D maps that are suitable for use as navigation aids. Fifty different Smart phones were categorized on the basis of their Graphical Processing Unit (GPU), display resolution, memory and size. The result of the proposed classification shows high accuracy. International Association of Online Engineering 2016-07-27 Article PeerReviewed application/pdf en http://irep.iium.edu.my/51422/1/Attached_SVM.pdf application/pdf en http://irep.iium.edu.my/51422/4/51422_A%20support%20vector%20machine%20classification.pdf Abubakar, Adamu and Mantoro, Teddy and Moedjiono, Sardjoeni and Anugerah Ayu, Media and Chiroma, Haruna and Waqas, Ahmad and Abdulhamid, Shafi’i Muhammad and Hamza, Mukhtar Fatihu and Ya’u Gital, Abdulsalam (2016) A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid. International Journal of Interactive Mobile Technologies, 10 (3). pp. 4-10. ISSN 1865-7923 http://online-journals.org/index.php/i-jim/article/view/5056 10.3991/ijim.v10i3.5056
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Abubakar, Adamu Mantoro, Teddy Moedjiono, Sardjoeni Anugerah Ayu, Media Chiroma, Haruna Waqas, Ahmad Abdulhamid, Shafi’i Muhammad Hamza, Mukhtar Fatihu Ya’u Gital, Abdulsalam A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid
description	3D maps for mobile devices provide more realistic views of environments and serve as better navigation aids. Previous research studies show differences on how 3D maps effect the acquisition of spatial knowledge. This is attributable to the differences in mobile device computational capabilities. Crucial to this is the time it takes for a 3D map dataset to be rendered for a complete navigation task. Different findings suggest different approaches on how to solve the problem of time required for both in-core (inside mobile) and out-core (remote) rendering of 3D datasets. Unfortunately, there have not been sufficient studies regarding the analytical techniques required to show the impact of computational resources required to use 3D maps on mobile devices. This paper uses a Support Vector Machine (SVM) to analytically classify mobile device computational capabilities required for 3D maps that are suitable for use as navigation aids. Fifty different Smart phones were categorized on the basis of their Graphical Processing Unit (GPU), display resolution, memory and size. The result of the proposed classification shows high accuracy.
format	Article
author	Abubakar, Adamu Mantoro, Teddy Moedjiono, Sardjoeni Anugerah Ayu, Media Chiroma, Haruna Waqas, Ahmad Abdulhamid, Shafi’i Muhammad Hamza, Mukhtar Fatihu Ya’u Gital, Abdulsalam
author_facet	Abubakar, Adamu Mantoro, Teddy Moedjiono, Sardjoeni Anugerah Ayu, Media Chiroma, Haruna Waqas, Ahmad Abdulhamid, Shafi’i Muhammad Hamza, Mukhtar Fatihu Ya’u Gital, Abdulsalam
author_sort	Abubakar, Adamu
title	A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid
title_short	A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid
title_full	A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid
title_fullStr	A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid
title_full_unstemmed	A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid
title_sort	support vector machine classification of computational capabilities of 3d map on mobile device for navigation aid
publisher	International Association of Online Engineering
publishDate	2016
url	http://irep.iium.edu.my/51422/ http://irep.iium.edu.my/51422/ http://irep.iium.edu.my/51422/ http://irep.iium.edu.my/51422/1/Attached_SVM.pdf http://irep.iium.edu.my/51422/4/51422_A%20support%20vector%20machine%20classification.pdf
first_indexed	2023-09-18T21:12:48Z
last_indexed	2023-09-18T21:12:48Z
_version_	1777411364867801088

A support vector machine classification of computational capabilities of 3D map on mobile device for navigation aid

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