Research Repository

A Type-2 Fuzzy Logic Based System for Augmented Reality Visualisation of Georeferenced Data

Pena Rios, AC and Hagras, Hani and Owusu, Gilbert and Gardner, Michael (2018) A Type-2 Fuzzy Logic Based System for Augmented Reality Visualisation of Georeferenced Data. In: 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2018-07-08 - 2018-07-13, Rio de Janeiro.

[img]
Preview
Text
penarios.pdf - Accepted Version

Download (4MB) | Preview

Abstract

Planning of infrastructure's provision and maintenance tasks is commonly done in a planning office using paper maps and desktop applications. However, any infrastructure plan has to be verified on location before being submitted to the responsible authorities. This task is usually accomplished by taking paper maps to the field and annotating them on site, or in the best case, using two-dimensional (2D) maps on mobile devices. Augmented reality (AR) can provide enhanced experiences of real-world situations by overlaying key information and three-dimensional (3D) visualizations when needed, thus supporting decision-making processes. AR could support land surveyors and mobile planners with a graphical overlay of the planned changes, highlighting relevant information and assets in their field of view. This paper presents an AR application, which uses interval type-2 fuzzy logic mechanisms to visualise immersive 3D georeferenced data; supporting planning and designing of infrastructure by directly modifying data to incorporate required changes, without the need of any post-processing. Immersive visual feedback is provided via a head mounted display (HMD), enhancing user's 3D spatial perception of georeferenced data.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 05 Dec 2018 15:28
Last Modified: 05 Dec 2018 16:15
URI: http://repository.essex.ac.uk/id/eprint/23472

Actions (login required)

View Item View Item