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Geomatics and Soft Computing Techniques for Infrastructural Monitoring

Author

Listed:
  • Vincenzo Barrile

    (DICEAM—Civil, Energy, Environmental and Material, Engineering Department, Mediterranean University, 89124 Reggio Calabria, Italy)

  • Antonino Fotia

    (DICEAM—Civil, Energy, Environmental and Material, Engineering Department, Mediterranean University, 89124 Reggio Calabria, Italy)

  • Giovanni Leonardi

    (DICEAM—Civil, Energy, Environmental and Material, Engineering Department, Mediterranean University, 89124 Reggio Calabria, Italy)

  • Raffaele Pucinotti

    (PAU—Heritage-Architecture-Urbanism, Mediterranean University, 89124 Reggio Calabria, Italy)

Abstract

Structural Health Monitoring (SHM) allows us to have information about the structure under investigation and thus to create analytical models for the assessment of its state or structural behavior. Exceeded a predetermined danger threshold, the possibility of an early warning would allow us, on the one hand, to suspend risky activities and, on the other, to reduce maintenance costs. The system proposed in this paper represents an integration of multiple traditional systems that integrate data of a different nature (used in the preventive phase to define the various behavior scenarios on the structural model), and then reworking them through machine learning techniques, in order to obtain values to compare with limit thresholds. The risk level depends on several variables, specifically, the paper wants to evaluate the possibility of predicting the structure behavior monitoring only displacement data, transmitted through an experimental transmission control unit. In order to monitor and to make our cities more “sustainable”, the paper describes some tests on road infrastructure, in this contest through the combination of geomatics techniques and soft computing.

Suggested Citation

  • Vincenzo Barrile & Antonino Fotia & Giovanni Leonardi & Raffaele Pucinotti, 2020. "Geomatics and Soft Computing Techniques for Infrastructural Monitoring," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1606-:d:323314
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    Citations

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    Cited by:

    1. Clyde Zhengdao Li & Zhenchao Guo & Dong Su & Bing Xiao & Vivian W. Y. Tam, 2022. "The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance," Sustainability, MDPI, vol. 14(13), pages 1-28, June.
    2. Xiaoming Lei & Limin Sun & Ye Xia & Tiantao He, 2020. "Vibration-Based Seismic Damage States Evaluation for Regional Concrete Beam Bridges Using Random Forest Method," Sustainability, MDPI, vol. 12(12), pages 1-18, June.

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