The infrastructure industry is currently not taking full advantage of the potential of artificial intelligence (AI) and machine learning, primarily because of a lack of reusable infrastructure project data. According to consulting firm FMI Corporation, 96% of infrastructure project data is never reused, often because data generated in one phase of an asset lifecycle is incompatible with the data structure in the next phase. As a result of this issue, stakeholders within the industry are making decisions based on incomplete data, and siloed data is leading to obsolescence. A cohesive and complete dataset can help to drive sustainable outcomes and ensure accurate design intent. To achieve this, the industry requires open platforms for creating and maintaining rich datasets, interoperability among tools, and standard data requirements throughout the lifecycle. The use of digital twin technology will also be critical in combining different data sources. By adopting these measures, stakeholders can leverage machine learning to gain insights into data for more sustainable and efficient outcomes.
FMI Corporation is a consulting firm that focuses on the US engineering and construction industry.
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