Figure 12 Current visualization system running in the Tinmith emulator showing first person (left) and birds eye (right) views
Tinmith input menu operations are passed to the library, where it tracks its own menu state. Upon loading, the library dynamically loads sensor instances from a dataset, allowing the user to navigate the dataset via the use of system’s inputs. The use of hardware inputs, via the use of Phidgets2, has been implemented, providing a dedicated set of inputs for controlling data navigation.
Semi-opaque structures have been implemented, allowing for ‘x-ray vision’ to see the position of other walls and sensors through walls (Figure 12).
Currently, the system supports the visualization of two structures, displaying sensors on two corners of each building (Figure 12). Idly, these sensors are the Box representation, however when the user focuses on them, they rotate/shrink to display a Gauge representation to provide more detailed and exact values. Users can select ‘groups’ of walls from the structures that share a common property, in this case the direction (north, south, etc.) they are facing.
A formal evaluation of the first iteration of development is pending ethics approval.
Schedule
This section outlines the proposed research schedule.
Period
|
Task
|
Completed Status
|
Comments
|
Jan-Feb
|
Initial project analysis
|
100%
|
|
Feb
|
Literature Review
|
100%
|
|
Feb-Mar
|
Task identification and breakdown
|
100%
|
|
Mar
|
Propose representations for data visualization
|
100%
|
Iteration 1
|
Mar-Apr
|
Create representation in OpenGL
|
100%
|
|
Apr
|
Establish Tinmith plug-in template
|
100%
|
|
Apr
|
Integrate representations into Tinmith
|
100%
|
|
Apr-May
|
Establish input handling and rendering of objects at correct GPS positions
|
100%
|
|
May
|
Ability to render and navigate structure in AR
|
100%
|
|
May
|
Integrate Phidgets inputs into system
|
75%
|
|
May
|
Ethics approval
|
50%
|
|
May
|
Prepare research Proposal
|
100%
|
|
May-Jun
|
|
0%
|
|
Jun
|
User testing
|
0%
|
|
Jun-Jul
|
Review of user testing
|
0%
|
Iteration 2
|
Jul
|
Implement changes based on feedback
|
0%
|
|
Jul-Aug
|
User testing
|
0%
|
|
Aug
|
Review of user testing
|
0%
|
|
Aug-Sep
|
Begin writing thesis
|
0%
|
|
Sep
|
Review Completed Thesis
|
0%
|
|
Oct
|
Thesis submission
|
0%
|
|
Table 1 Proposed schedule
Proposed Thesis Table of Contents
Following the conclusion of the research, the written thesis will be provided, detailing the work undertaken. This is the proposed table of contents for the final work.
Abstract
Chapter 1. Introduction
1.1 Motivation
1.2 The Problem
1.3 Research question
1.4 Contribution
1.5 Dissertation structure
Chapter 2. Literature review
2.1 Augmented Reality
2.1.1 Definition of AR
2.1.2 Classification of AR
2.1.3 Tinmith and Mobile AR
2.1.4 Applications of AR
2.2 Visualization
2.2.1 Data Visualization
2.2.2 Structure Visualization
2.3 Summary
Chapter 3. Research methodology
3.1 Initial analysis
3.2 Research methodology
3.3 Expected outcome
3.4 Summary
Chapter 4. Visualization techniques
4.1 Motivation
4.1.1 Goals
4.1.2 Considerations
4.2 Design and Implementation
4.2.1 Initial aim and requirements
4.2.2 Design reasoning
4.2.3 Limitations
4.2.4 Model refinement technique
4.3 Evaluation and discussion
4.3.1 Benefits
4.3.2 User Evaluations
4.3.2 Discussion
4.4 Summary
Chapter 5. Sensor Visualization System
5.1 Motivation
5.2 Design and implementation
5.2.1 Aim and constraints
5.2.2 Sensors and input devices analysis for Tinmith
5.2.3 System construction
5.3 Evaluation
5.3.1 Benefits
5.3.2 Limitations
5.3.3 Evaluation
5.4 Summary
Chapter 6. Conclusion
6.1 Corrosion visualization techniques
6.2 Considerations regarding visualization techniques
6.3 Future work
6.4 Concluding remarks
Chapter 7. References
|
Table 2 Proposed thesis Table of Contents
Summary
This research project is motivated to develop techniques to assist in the visualization of outdoor environmental corrosion in mobile augmented reality. The integration of sensor networks with situated visualization in mobile augmented reality will result in benefits for on-site inspections of large structures. The use of in-situ visualization of environmental data provides an intuitive method of understanding information that was previously difficult to interpret and hard to extract meaningful inferences.
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