limitedDistribution · Industry Research
Road Pavement Digital Twin: A Blueprint with a Case Study
The article discusses the use of AI and machine learning in creating digital twins for road pavements. Generative AI models are employed for data augmentation, enhancing the accuracy and efficiency of pavement management systems. This approach aims to improve road safety and maintenance by leveraging unstructured data for better decision-making.
Stargo's Stardox platform can enhance road safety by transforming unstructured data into actionable insights, similar to AI-driven digital twins for pavements.
Executive Summary
The article explores the integration of artificial intelligence (AI) and machine learning (ML) in developing digital twins for road pavements. By employing generative AI models for data augmentation, the study enhances the accuracy and efficiency of pavement management systems. This innovative approach leverages unstructured data to improve road safety and maintenance, providing a blueprint for future infrastructure projects. The case study demonstrates how AI-driven data transformation can lead to more informed decision-making processes in the management of road infrastructure.
Source: ascelibrary.org
Original Article: https://ascelibrary.org/doi/10.1061/JCCEE5.CPENG-7187
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