Defect digital twinning: A technical framework to integrate robotics, AI and BIM for facility management and renovation

Abstract

Abstract Buildings and infrastructure are aging around the world, calling for proper management and renovation. Awareness of defects occurred to the facilities is a prerequisite to make informed decisions. Despite extensive research in defect detection, it remains unclear how to timely update the dynamically changing defect condition at scale and with ease. This study aims to develop a technical framework that integrates robotics, artificial intelligence (AI), and building information modeling (BIM) to enable defect digital twinning. The framework establishes a mechanism to bridge defects in the physical world with their digital representations in the virtual world. It extends existing defect information modeling with a means to capture accurate and up-to-date as-damaged information in a timely manner. The proposed framework was evaluated with a 10-story residential building in Hong Kong. The case study demonstrates the effectiveness of the framework in twinning defects concerning their positions, geometry and dimensions. The research opens new possibilities to twin facility defects at street block or even city level to support urban renewal.