Advancements in the Use of Distributed Sensing and Edge/Cloud Diagnostics in Structural Health Monitoring Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 2
Special Issue Editors
Interests: structural health monitoring; nondestructive testing; load monitoring; smart structures; ultrasounds and material testingstructural health monitoring; nondestructive testing; load monitoring; smart structures; ultrasounds and material testing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Structural health monitoring (SHM) based on distributed sensing is increasingly being investigated in many engineering fields with the aim to turn preventive maintenance into the predictive lifecycle management of structures. In this context, the advances in the Industry 5.0 paradigm and the Internet of Things in recent years, including improvements in communication, miniaturization and protocols, contributed to bringing computing as close as possible to where data are produced, thereby reducing the typical latency, especially when big data are streamed. This has been exacerbated by the evolution of artificial intelligence (AI) and machine learning, which are promising yet data-demanding. Hence, deploying AI algorithms at the edge of the network is crucial to process data in real time and efficiently make decisions. In this view, edge/cloud computing and optimization in SHM systems are of outmost importance, with strong emphasis to be placed on trustworthiness and reliability assessment thereof.
Potential applications include aviation and the maritime industry, but also pipeworks, bridges and other technical structures.
It is expected that distributed sensing and edge/cloud analysis related to the field of SHM is described thoroughly and demonstrated in a relevant environment. Numerical investigations may also help to provide additional insights. In any case, it is mandatory to show experimental results with permanently installed sensors from a dedicated laboratory experiment, possibly combined with a demonstration in the field.
Dr. Vittorio Memmolo
Dr. Jochen Moll
Guest Editors
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Keywords
- fault diagnostics
- damage detection
- edge detection
- predictive maintenance
- artificial intelligence
- inspection
- continuous monitoring
- real-time diagnosis
- safety
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