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the framework of “Assessment and observation of the structural behaviour of historical built assets resorting to artificial intelligence techniques”, financed by the Faculty of Engineering of University
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solution will utilize information collected through specific sensors installed in the infrastructure, which will be processed by advanced Artificial Intelligence algorithms. The works listed for this grant
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the identification of innovations within the project’s thematic area, as well as the development of advanced tools for railway track monitoring, condition inspection, and maintenance planning supported by artificial
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