Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Master of Engineering Science

Program

Electrical and Computer Engineering

Supervisor

Grolinger, Katarina

2nd Supervisor

Sadhu, Ayan

Co-Supervisor

Abstract

As civil infrastructures around the world faces escalating threats from climate change, urbanization, and increased vehicular loads, there is an urgent need for advanced methods to monitor and maintain structural integrity. Traditional inspection techniques, which largely depend on visual assessments and the deployment of heavy machinery, often fall short in terms of efficiency and safety. These methods face several limitations, including restricted accessibility, high costs, time-consuming processes, and inconsistent accuracy due to human error and subjective judgment. To address these limitations, this thesis presents a remote collaborative inspection framework that integrates Augmented Reality (AR) with high-speed 5G networks to offer a more flexible and effective solution for structural monitoring. The proposed framework introduces an approach that combines AR technology with enhanced 3D Building Information Modeling (BIM) capabilities and holographic damage markers. The AR interface supports real-time visualization of structural conditions, while off-site inspectors can contribute to the evaluation process via a web-based platform, facilitated by the robust bandwidth and low latency of 5G networks. A key feature of the framework is its ability to project interactive holographic markers that provide clear, visual indications of damage locations on the 3D model as observed in the real-world context. This real-time data exchange and collaborative environment enable inspectors to make more informed decisions and respond to structural issues with greater agility. This system not only enables on-site inspectors to visualize and interact with detailed 3D models superimposed onto physical structures but also allows for the dynamic manipulation of these models to enhance damage detection and assessment. The effectiveness of this approach is demonstrated through a series of experiments involving a laboratory beam model and a full-scale bridge, illustrating the framework’s potential to revolutionize structural inspection practices by merging advanced AR technologies with cutting-edge 5G communication infrastructure.

Summary for Lay Audience

In today’s world, the safety and longevity of civil structures are increasingly threatened by different factors like climate change and urban expansion that cause it to age rapidly. These issues can often go unnoticed until an accident happens, which can be both dangerous and costly. To prevent such failures and ensure the safety of our structures, engineers and inspectors need better ways to inspect and monitor their condition with more accuracy in a more cost-effective and autonomous manner that can be deployed rapidly. This research focuses on creating a new and improved method for inspecting and monitoring civil infrastructure. Instead of relying on traditional methods that can be slow and expensive, the proposed approach uses advanced technology to make inspections safer, faster, and more effective.

At the heart of this method is a combination of Augmented Reality (AR) and high-speed 5G internet technology. Augmented Reality allows inspectors to see and interact with detailed 3D models of structures, overlaid onto the real-world view of the actual buildings or bridges they are examining. This means they can visualize the structure’s condition virtually right in front of them, which helps them diagnose problems more clearly. Additionally, the system uses 5G technology to enable real-time communication between inspectors on-site and experts who might be working from a distance. This advanced connectivity allows remote experts to view the data, provide advice, and help make decisions instantly while the on-site team is inspecting the structure. The system is evaluated using both a small lab model and a full-scale bridge, demonstrating its effectiveness and potential for improving infrastructure monitoring and maintenance.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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