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Mixed Reality procedures for the maintenance of existing bridges and retaining walls

Author(s): (Construction Technologies Institute, National Research Council L'Aquila Italy)
(Construction Technologies Institute, National Research Council L'Aquila Italy)
(Department of Biosciences and Territory, StreGa Lab University of Molise Campobasso Italy)
(Department of Biosciences and Territory, StreGa Lab University of Molise Campobasso Italy)
(Construction Technologies Institute, National Research Council L'Aquila Italy)
Medium: journal article
Language(s): English
Published in: ce/papers, , n. 5, v. 6
Page(s): 1382-1390
DOI: 10.1002/cepa.2110
Abstract:

National and International road networks are made of structures and infrastructures that often exhibit poor performance due to a lack of maintenance. In this context, Italy recently renewed the legislation regarding existing infrastructure analysis to support knowledge and facilitate a homogeneous data acquisition process. Thus a key component of the process consists of the visual inspection protocols complemented by physical and mechanical measures. This applies to all the structures built for the road network operation, including those classified as geotechnical whose deterioration is often neglected or appropriately surveyed. Along with the definition of a data form for collecting datasets on these aspects, a relevant aspect of the process is the implementation of a collaborative environment for the information management and analysis systems supporting the interested parties in the field. The paper reports the design of a base geotechnical inspection form for Retaining Wall and illustrates some aspects of its implementation in a digital environment. Mixed Reality techniques in combination with web‐based tools for data collection are investigated to increase the feasibility and reliability of the visual inspection of existing road networks.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1002/cepa.2110.
  • About this
    data sheet
  • Reference-ID
    10767302
  • Published on:
    17/04/2024
  • Last updated on:
    17/04/2024
 
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