SISTEMA DE ALARMA PARA SISTEMAS DE GESTION DE PUENTES CON GEMELOS DIGITALES BIM UTILIZANDO INTELIGENCIA ARTIFICIAL

PID2021-126405OB-C32

Nombre agencia financiadora Agencia Estatal de Investigación
Acrónimo agencia financiadora AEI
Programa Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia
Subprograma Subprograma Estatal de Generación de Conocimiento
Convocatoria Proyectos de I+D+I (Generación de Conocimiento y Retos Investigación)
Año convocatoria 2021
Unidad de gestión Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023
Centro beneficiario UNIVERSIDAD DE CASTILLA-LA MANCHA
Identificador persistente http://dx.doi.org/10.13039/501100011033

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Enhancing the accuracy of low-cost inclinometers with artificial intelligence

UPCommons. Portal del coneixement obert de la UPC
  • Lozano Galant, Fidel|||0000-0001-9272-6172
  • Emadi, Seyyedbehrad
  • Komarizadehasl, Seyedmilad|||0000-0002-9010-2611
  • González-Arteaga, Jesús
  • Xia, Ye
The development of low-cost structural and environmental sensors has sparked a transformation across numerous fields, offering cost-effective solutions for monitoring infrastructures and buildings. However, the affordability of these solutions often comes at the expense of accuracy. To enhance precision, the LARA (Low-cost Adaptable Reliable Anglemeter) system averaged the measurements of a set of five different accelerometers working as inclinometers. However, it is worth noting that LARA’s sensitivity still falls considerably short of that achieved by other high-accuracy commercial solutions. There are no works presented in the literature to enhance the accuracy, precision, and resolution of low-cost inclinometers using artificial intelligence (AI) tools for measuring structural deformation. To fill these gaps, artificial intelligence (AI) techniques are used to elevate the precision of the LARA system working as an inclinometer. The proposed AI-driven tool uses Multilayer Perceptron (MLP) to glean insight from high-accuracy devices’ responses. The efficacy and practicality of the proposed tools are substantiated through the structural and environmental monitoring of a real steel frame located in Cuenca, Spain., This research was funded by FEDER, grant number PID2021-126405OB-C31 and PID2021-126405OB-C32—A Way to Make Europe and Spanish Ministry of Economy and Competitiveness MICIN/AEI/10.13039/501100011033/, National Natural Science Foundation of China (52278313), and a grant provided by the Polytechnic University of Catalonia with a reference of ALECTORS-2023., Peer Reviewed