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

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

3D Map

Graphical Processing Unit

Support Vector Machine. In-core rendering

out-of-core rendering

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

Abubakar, Adamu

Mantoro, Teddy

Moedjiono, Sardjoeni

Ayu, Media Anugerah

Chiroma, Haruna

Waqas, Ahmad

Muhammad Abdulhamid, Shafi’i

Fatihu Hamza, Mukhtar

Gital, Abdulsalam Ya'u

International Journal of Interactive Mobile Technologies (iJIM); Vol. 10 No. 3 (2016); pp. 4-10

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2016-07-26

Copyright (c) 2017 Adamu Abubakar, Teddy Mantoro, Sardjoeni Moedjiono, Media Anugerah Ayu, Haruna Chiroma, Ahmad Waqas, Shafi’i Muhammad Abdulhamid, Mukhtar Fatihu Hamza, Abdulsalam Ya'u Gital

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Peer-reviewed Article