Artificial Intelligence Assisted Infrastructure Assessment Using Mixed Reality Systems

TL;DR

This paper presents a mixed reality framework integrated with AI to enhance infrastructure inspection by providing real-time defect analysis, reducing inspection time and costs, and supporting inspectors with objective data and professional judgment.

Contribution

It introduces a novel mixed reality system combined with attention-guided semi-supervised deep learning for interactive, human-centered infrastructure assessment.

Findings

Real-time defect measurement and condition assessment

Reduced inspection time and costs

Enhanced data objectivity and inspector support

Abstract

Conventional methods for visual assessment of civil infrastructures have certain limitations, such as subjectivity of the collected data, long inspection time, and high cost of labor. Although some new technologies i.e. robotic techniques that are currently in practice can collect objective, quantified data, the inspectors own expertise is still critical in many instances since these technologies are not designed to work interactively with human inspector. This study aims to create a smart, human centered method that offers significant contributions to infrastructure inspection, maintenance, management practice, and safety for the bridge owners. By developing a smart Mixed Reality framework, which can be integrated into a wearable holographic headset device, a bridge inspector, for example, can automatically analyze a certain defect such as a crack that he or she sees on an element, display its dimension information in real-time along with the condition state. Such systems can potentially decrease the time and cost of infrastructure inspections by accelerating essential tasks of the inspector such as defect measurement, condition assessment and data processing to management systems. The human centered artificial intelligence will help the inspector collect more quantified and objective data while incorporating inspectors professional judgement. This study explains in detail the described system and related methodologies of implementing attention guided semi supervised deep learning into mixed reality technology, which interacts with the human inspector during assessment. Thereby, the inspector and the AI will collaborate or communicate for improved visual inspection.