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Infrastructures
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Advanced Sensing Technologies and Smart Construction Materials for Structural Health...
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Advanced Sensing Technologies and Smart Construction Materials for Structural Health Monitoring

A special issue of Infrastructures (ISSN 2412-3811). This special issue belongs to the section "Smart Infrastructures".

Deadline for manuscript submissions: 30 May 2026 | Viewed by 1331

Special Issue Editors

Dr. Andrea Meoni

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Interests: structural health monitoring; smart materials; seismic engineering; numerical simulations
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Gustavo Henrique Nalon

E-Mail Website
Guest Editor
Department of Applied and Computational Mechanics, Federal University of Juiz de Fora, Juiz de Fora 36036-330, MG, Brazil
Interests: structural health monitoring; structural mechanics; structural masonry; sustainable construction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural Health Monitoring (SHM) plays a crucial role in ensuring the safety, durability, and sustainability of civil infrastructure. Recent advancements in sensing technologies and the development of smart construction materials have provided unprecedented opportunities for the real-time monitoring, predictive maintenance, and resilience assessment of structures.

In this context, we are pleased to invite you to contribute to this Special Issue, entitled “Advanced Sensing Technologies and Smart Construction Materials for Structural Health Monitoring”, which aims to showcase cutting-edge research and innovative applications that leverage advanced sensing technologies and smart materials for the SHM of critical infrastructure. The scope of this Special Issue includes, but is not limited to, novel sensors, self-sensing and self-healing materials, IoT-based sensing solutions, and satellite radar interferometry approaches. We are particularly interested in contributions that address the integration of sensor data with AI-driven SHM strategies and digital twins for damage detection, as well as the challenges associated with the real-world application and large-scale deployment of innovative sensing technologies.

By bridging material science, sensing technology, and digital innovation, this Special Issue seeks to foster interdisciplinary solutions that enhance structural monitoring, optimize maintenance strategies, and improve sustainability in the era of smart cities.

Original research articles and reviews are welcome.

We look forward to receiving your contributions.

Dr. Andrea Meoni
Prof. Dr. Gustavo Henrique Nalon
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. Infrastructures is an international peer-reviewed open access monthly 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 1800 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
  • advanced sensing technologies
  • smart construction materials
  • self-sensing materials
  • self-healing materials
  • satellite radar interferometry
  • iot-based sensing solutions
  • AI and machine learning for SHM
  • digital twin
  • damage detection

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Published Papers (2 papers)

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Research

15 pages, 2375 KB  
Article
Piezoresistive Smart Bricks for Structural Health Monitoring of Masonry Arch Bridges: An Exploratory Numerical Study
by Andrea Meoni, Michele Mattiacci, Alina Elena Eva, Francesco Falini and Filippo Ubertini
Infrastructures 2026, 11(5), 144; https://doi.org/10.3390/infrastructures11050144 - 22 Apr 2026
Viewed by 390
Abstract
Masonry arch bridges are critical assets in aging transportation networks, yet their Structural Health Monitoring (SHM) remains challenging. Smart bricks—piezoresistive sensing units compatible with masonry structures and capable of acting simultaneously as load-bearing components and strain sensors—offer a promising solution for embedding self-sensing [...] Read more.
Masonry arch bridges are critical assets in aging transportation networks, yet their Structural Health Monitoring (SHM) remains challenging. Smart bricks—piezoresistive sensing units compatible with masonry structures and capable of acting simultaneously as load-bearing components and strain sensors—offer a promising solution for embedding self-sensing capability directly within the masonry. While previous work by the authors has investigated their use in masonry walls, their application to arched structures remains unexplored. This gap is particularly significant given that arches, characterized by a predominantly compressive stress state, represent a natural context for smart-brick implementation. This study presents a numerical investigation assessing the potential of smart bricks for strain-based SHM of masonry arch bridges. A Finite Element (FE) model, derived from a validated experimental benchmark representative of typical Italian railway arch bridges, was used to virtually embed smart bricks at selected cross-sections along the arch. Damage progression was simulated through cyclic loading–unloading stages, enabling direct correlation between strain evolution and structural deterioration. Results demonstrate that smart bricks accurately capture damage-driven strain redistributions, closely mirroring both the sequence of damage formation and the associated collapse mechanism. These findings support the use of smart bricks for early detection of localized structural changes in masonry arches, providing a foundation for future experimental validation and real-world deployment of minimally invasive SHM systems. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies and Smart Construction Materials for Structural Health Monitoring)
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25 pages, 5082 KB  
Article
Performance Evaluation of Fixed-Point DFOS Cables for Structural Monitoring of Reinforced Concrete Elements
by Aigerim Buranbayeva, Assel Sarsembayeva, Bun Pin Tee, Iliyas Zhumadilov and Gulizat Orazbekova
Infrastructures 2025, 10(12), 349; https://doi.org/10.3390/infrastructures10120349 - 15 Dec 2025
Cited by 1 | Viewed by 535
Abstract
Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with [...] Read more.
Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with a single-mode DFOS cable incorporating internal anchors at 2 m intervals and bonded externally with structural epoxy. Brillouin time-domain analysis (BOTDA) provided distributed strain measurements at approximately 0.5 m spatial resolution, with all cables calibrated to ±15,000 µε. Under stepwise monotonic loading, the system captured smooth, repeatable strain baselines and clearly resolved localized tensile peaks associated with crack initiation and propagation. Long-gauge averages exhibited a near-linear load–strain response (R2 ≈ 0.99) consistent with discrete foil and vibrating-wire strain gauges. Even after cracking, the DFOS signal remained continuous, while some discrete sensors showed saturation or scatter. Temperature compensation via a parallel fiber ensured thermally stable interpretation during load holds. The fixed-point configuration mitigated local debonding effects and yielded unbiased long-gauge strain data suitable for assessing serviceability and differential settlement. Overall, the results confirm the suitability of fixed-point DFOS as a durable, SHM-ready sensing approach for RC foundation elements and as a dense data source for emerging digital-twin frameworks. Full article
(This article belongs to the Special Issue Advanced Sensing Technologies and Smart Construction Materials for Structural Health Monitoring)
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