Generative Artificial Intelligence and Virtual Reality: Emerging Future of the Building Component Inspection Training

The assessment of building components, which is typically performed through visual inspections, is critical to the maintenance planning and other decisions made during the operation and use stage of the building life cycle. This paper introduces a framework leveraging generative artificial intelligence (Gen AI) and virtual reality (VR) to improve facility inspectors' training, which eventually can help with the informed decisions that stakeholders should make. Buildings are complex facilities that demand precise and unbiased condition evaluations. Traditional training approaches rely heavily on limited texture images and descriptions collected in prior studies, which restrict the range of conditions inspectors can study and limit their ability to recognize varied deterioration accurately. This gap in training materials prevents the effective transfer of critical knowledge to trainees, hampering their preparation for real-world scenarios. Our solution integrates the immersive environment of VR with the capabilities of Gen AI. This approach simulates deterioration processes for different building components, such as boilers and pipes, in various conditions, providing an interactive VR training environment. Trainees can thus engage in hands-on practice in condition identification and assessment. Advancing training in Gen AI transforms textual descriptions of component states into realistic visual textures, offering trainees a rich diversity of examples to study. This methodology aims to reduce the subjective nature of inspections and improve learning outcomes. This study proposes a framework for implementing Gen AI to produce realistic textures and develop immersive VR simulations, thereby enhancing the training environment for facility inspectors. The proposed AI-based VR framework is applied to enhance inspector training for a hypothetical scenario to demonstrate its implementation. This innovative framework has the potential to improve professional training and serve as a training application in other sectors requiring exacting and impartial assessments.