A Support Vector Machine Classification of Computational Capabilities of 3D Map on Mobile Device for Navigation Aid



Abubakar, Adamu, Mantoro, Teddy, Moedjiono, Sardjoeni, Ayu, Media Anugerah, Chiroma, Haruna, Waqas, Ahmad ORCID: 0000-0002-3772-194X, Muhammad Abdulhamid, Shafi’i, Fatihu Hamza, Mukhtar and Gital, Abdulsalam Ya'u
(2016) A Support Vector Machine Classification of Computational Capabilities of 3D Map on Mobile Device for Navigation Aid. International Journal of Interactive Mobile Technologies (iJIM), 10 (3). 4 - 4.

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Abstract

<jats:p>3D map for mobile devices provide more realistic view of an environment and serves as better navigation aid. Previous research studies shows differences in 3D maps effect on acquiring of spatial knowledge. This is attributed to the differences in mobile device computational capabilities. Crucial to this, is the time it takes for 3D map dataset to be rendered for a required complete navigation task. Different findings suggest different approach on solving the problem of time require for both in-core (inside mobile) and out-core (remote) rendering of 3D dataset. Unfortunately, studies on analytical techniques required to shows the impact of computational resources required for the use of 3D map on mobile device were neglected by the research communities. This paper uses Support Vector Machine (SVM) to analytically classify mobile device computational capabilities required for 3D map that will be suitable for use as navigation aid. Fifty different Smart phones were categorized on the bases of their Graphical Processing Unit (GPU), display resolution, memory and size. The result of the proposed classification shows high accuracy</jats:p>

Item Type: Article
Depositing User: Symplectic Admin
Date Deposited: 02 Apr 2019 15:47
Last Modified: 03 Mar 2021 10:43
DOI: 10.3991/ijim.v10i3.5056
Open Access URL: https://online-journals.org/index.php/i-jim/articl...
URI: https://livrepository.liverpool.ac.uk/id/eprint/3035645