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Enhancing the Accuracy of Low-Cost Inclinometers with Artificial Intelligence

Authors :
Fidel Lozano
Seyyedbehrad Emadi
Seyedmilad Komarizadehasl
Jesús González Arteaga
Ye Xia
Source :
Buildings, Vol 14, Iss 2, p 519 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

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.

Details

Language :
English
ISSN :
20755309
Volume :
14
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Buildings
Publication Type :
Academic Journal
Accession number :
edsdoj.4591fe036d084abbb6259181e2642a80
Document Type :
article
Full Text :
https://doi.org/10.3390/buildings14020519