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Buildings
Special Issues
Building Structure Health Monitoring and Damage Detection
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Building Structure Health Monitoring and Damage Detection

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: 10 April 2026 | Viewed by 815

Special Issue Editors

Dr. Fidel Lozano

E-Mail Website
Guest Editor
Department of Civil Engineering, Universidad of Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain
Interests: BIM; structural health monitoring; artificial intelligence; Construction 4.0; sensors
Dr. Edison Atencio

E-Mail Website
Guest Editor
School of Civil Engineering, Pontificia Universidad Católica de Valparaíso (PUCV), 2340000 Valparaíso, Chile
Interests: Construction 4.0; project management; enterprise engineering; BIM; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural health monitoring and damage detection are crucial to ensure the safety and durability of buildings. This Special Issue gathers innovative research on the behavior of structures under various conditions, aiming to improve damage prevention and mitigation.

Topics of interest include the analysis of dynamic structural response and the application of artificial intelligence in damage detection, real-time monitoring, and structural integrity assessment. Advanced methods for fault identification and the prediction of structural behavior under extreme events like earthquakes and vibrations are also explored.

This Special Issue welcomes original research and review studies that provide innovative and practical solutions for structural monitoring and damage detection, promoting safety and sustainability in the construction field.

Dr. Fidel Lozano
Dr. Edison Atencio
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural health monitoring
  • damage detection
  • structural integrity
  • dynamic structural response
  • artificial intelligence
  • real-time monitoring

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

20 pages, 6383 KB  
Article
Post-Earthquake Damage Detection and Safety Assessment of the Ceiling Panoramic Area in Large Public Buildings Using Image Stitching
by Lichen Wang, Yapeng Liang and Shihao Yan
Buildings 2025, 15(21), 3922; https://doi.org/10.3390/buildings15213922 - 30 Oct 2025
Viewed by 441
Abstract
With the development of artificial intelligence, intelligent assessment methods have been applied in post-earthquake emergency rescue. These methods enable rapid and accurate identification and localization of earthquake-induced damage to ceilings in large public buildings, which often serve as emergency shelters. However, in practical [...] Read more.
With the development of artificial intelligence, intelligent assessment methods have been applied in post-earthquake emergency rescue. These methods enable rapid and accurate identification and localization of earthquake-induced damage to ceilings in large public buildings, which often serve as emergency shelters. However, in practical applications, challenges remain: damage recognition accuracy is low when using wide-field distant shots, while close-up local shots are unsuitable for identifying panoramic regional damage. As a result, high-precision intelligent safety assessment of the entire ceiling area cannot be achieved. Therefore, this study proposes a panoramic image stitching method based on SIFT feature point detection and registration, optimized by the RANSAC algorithm, to generate high-resolution, wide-angle panoramic images of ceilings in large public buildings. The BRISQUE values of the stitched images range between 20 and 30, indicating good stitching quality. Subsequently, by integrating damage recognition and image stitching techniques, a safety assessment test was conducted on 227 stitched images of earthquake-induced ceiling damage captured in real scenes, using evaluation indicators such as damage type and severity quantification. The safety assessment achieved an overall accuracy of 98.7%, demonstrating the effectiveness of ceiling damage detection technology based on image stitching. This technology enables intelligent post-earthquake safety assessment of ceilings in large public buildings across the entire area. Full article
(This article belongs to the Special Issue Building Structure Health Monitoring and Damage Detection)
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