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New Trends in Sensing and Structural Health Monitoring for New and Existing Structures

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 20 March 2026 | Viewed by 67

Special Issue Editors


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Guest Editor Assistant
Department of Civil & Environmental Engineering, Embry Riddle Aeronautical University, Daytona Beach, FL 32114, USA
Interests: structural reliability; structural resilience; aging infrastructure; material deterioration; structural health monitoring

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Guest Editor
Department of Civil and Environment Engineering, Universitat Politècnica de Catalunya, BarcelonaTech. C/Jordi Girona 1-3, 08034 Barcelona, Spain
Interests: low-cost sensor; structural health monitoring applications; bridge structure; operational modal analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue highlights the latest advancements and developments in the field of sensing and structural health monitoring (SHM) for both new and existing infrastructure. In the context of climate change and frequent natural hazards, these new trends are being developed towards a safer, more resilient, and more sustainable infrastructure.  

Over the last decades, sensing and structural health monitoring underwent rapid innovation in both sensor technologies and methodologies. This Special Issue covers several key themes, including the development and integration of advanced sensor technologies such as distributed fiber optic sensors, MEMS-based systems, smart structures, and wireless sensor networks. Another theme is the application of artificial intelligence (AI) and machine learning (ML) for data interpretation, anomaly detection, and predictive maintenance, enabling more accurate and autonomous decision-making. The issue also covers new algorithmic frameworks for damage detection, localization, and quantification in complex structures. These algorithms leverage signal processing, statistical analysis, and data fusion to enhance the reliability and efficiency of SHM systems.

Overall, this Special Issue provides a comprehensive overview of the transformative trends shaping the future of structural monitoring and underscores the role of new methodologies in promoting infrastructure resilience, safety, and performance.

Dr. Dan Su
Guest Editor Assistant

Dr. Komarizadehasl Seyedmilad
Dr. Ye Xia
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sensors 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
  • acoustic sensing 
  • defect imaging 
  • thermal imaging 
  • sensor development 
  • machine learning 
  • signal processing 
  • non-destructive testing 
  • composite inspection 
  • material characterization 
  • real-time monitoring

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Published Papers

This special issue is now open for submission.
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