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Recent Advances in Sensing Technologies for Automation, Process and Structural Health Monitoring

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

Deadline for manuscript submissions: 20 September 2025 | Viewed by 1002

Special Issue Editors


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Guest Editor
Department of Aeronautics, Imperial College London, South Kensington Campus, City and Guilds Building, Exhibition Road, London SW7 2AZ, UK
Interests: structural analysis; finite element modeling; reliability engineering; stochastic modeling; digital twinning; optimization; machine learning; artificial intelligence

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Guest Editor Assistant
School of Automation, Beijing Institute of Technology, No. 5, Zhongguancun South Street, Haidian District, Beijing, China
Interests: structural integrity and health monitoring; fiber optic sensing; dada-driven structural digital twin; internet of things; inverse finite element method

Special Issue Information

Dear Colleagues,

Recent advancements in sensing technologies are reshaping automation, process and structural health monitoring, making the integration of intelligent sensing networks practical, feasible and scalable. These developments have far-reaching applications, enabling unprecedented levels of adaptability across industries.

These sensing technologies have made possible advancements in automation that would otherwise be impossible, leading to the development of autonomous systems such as drones for infrastructure inspection, robotics for precision tasks in hazardous environments, and wearable devices that provide real-time data on human performance. Sensing solutions are also revolutionizing how industrial processes are managed, monitored, and optimized, allowing for greater efficiency and reliability. Process monitoring has made it possible to achieve continuous, real-time oversight of complex operations. In manufacturing, they have facilitated the shift toward zero-defect production, enabling early detection of anomalies and reducing waste through data-driven decision-making. Beyond manufacturing, process monitoring solutions have become critical in sectors such as wastewater treatment, oil refineries, and energy production. It is now possible to accurately monitor flow rates, temperature fluctuations, and chemical compositions in real time, allowing operators to optimize processes, improve resource efficiency, and minimize environmental impacts. At the same time, the safety and resilience of aging infrastructure remains a pressing challenge, particularly in critical sectors such as aerospace, civil engineering, and transportation. Emerging sensing technologies, such as fiber optic sensors and guided wave systems, enable on-demand reliability assessments of structures, allowing stakeholders to detect damage early, optimize maintenance intervals, and extend asset remaining life. It is therefore possible to transition away from traditional manual inspection practices that are costly and time-consuming and promoting sustainability in infrastructure management (material optimization, reduced downtime, and improved safety).

Implementation of such approaches significantly contribute to recent sustainability goals by reducing environmental footprints (e.g., through lighter structures and energy-efficient systems), optimizing costs (e.g., maintenance scheduling, energy use, material waste minimization), and improving societal resilience and reliability. Sensors—ranging from fiber optic and micro-electromechanical system (MEMS)-based devices to smart materials that act as integrated sensors—offer higher sensitivity, durability, and cost-effectiveness, making them suitable for a wide range of applications.

This Special Issue invites contributions on the latest sensing technologies and frameworks for efficient monitoring of processes and structures across multiple sectors. We seek state-of-the-art sensing solutions, smart materials with embedded sensing capabilities, novel signal processing algorithms, and cross-disciplinary case studies that demonstrate practical implementation in real scale problems. Submissions focusing on real-world applications and their implications for sustainability, resilience, and Industry 4.0 are particularly encouraged. Potential topics include (but are not limited to) the following:

  • Intelligent Sensor Networks
  • Internet of Things (IoT) Enabled Sensing Solutions
  • Embedded and Energy-Efficient Sensors
  • Multi-Sensor Data Fusion
  • Smart Materials with Integrated Sensing Elements
  • Predictive Maintenance and Condition Assessment
  • Probabilistic Methods, Deep Learning and Signal Processing for Uncertainty Quantification and Propagation
  • Fiber Optic Sensors
  • Damage Detection and Imaging Algorithms
  • Reliability and Safety Engineering
  • Guided Waves for Structural and Process Monitoring
  • Acoustic and Temperature Sensors

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Dr. Ilias Giannakeas
Guest Editor

Dr. Yingwu Li
Guest Editor Assistant

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

  • intelligent sensor networks
  • Internet of Things (IoT)-enabled sensing solutions
  • embedded and energy-efficient sensors
  • multi-sensor data fusion
  • smart materials with integrated sensing elements
  • predictive maintenance and condition assessment
  • probabilistic methods, deep learning, and signal processing for uncertainty quantification and propagation
  • optical fiber and fiber Bragg grating sensors
  • damage detection and imaging algorithms
  • reliability and safety engineering
  • guided waves for structural and process monitoring
  • acoustic and temperature sensors

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (1 paper)

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Research

29 pages, 8416 KiB  
Article
WSN-Based Multi-Sensor System for Structural Health Monitoring
by Fatih Dagsever, Zahra Sharif Khodaei and M. H. Ferri Aliabadi
Sensors 2025, 25(14), 4407; https://doi.org/10.3390/s25144407 - 15 Jul 2025
Viewed by 738
Abstract
Structural Health Monitoring (SHM) is an essential technique for continuously assessing structural conditions using integrated sensor systems during operation. SHM technologies have evolved to address the increasing demand for efficient maintenance strategies in advanced engineering fields, such as civil infrastructure, aerospace, and transportation. [...] Read more.
Structural Health Monitoring (SHM) is an essential technique for continuously assessing structural conditions using integrated sensor systems during operation. SHM technologies have evolved to address the increasing demand for efficient maintenance strategies in advanced engineering fields, such as civil infrastructure, aerospace, and transportation. However, developing a miniaturized, cost-effective, and multi-sensor solution based on Wireless Sensor Networks (WSNs) remains a significant challenge, particularly for SHM applications in weight-sensitive aerospace structures. To address this, the present study introduces a novel WSN-based Multi-Sensor System (MSS) that integrates multiple sensing capabilities onto a 3 × 3 cm flexible Printed Circuit Board (PCB). The proposed system combines a Piezoelectric Transducer (PZT) for impact detection; a strain gauge for mechanical deformation monitoring; an accelerometer for capturing dynamic responses; and an environmental sensor measuring temperature, pressure, and humidity. This high level of functional integration, combined with real-time Data Acquisition (DAQ) and precise time synchronization via Bluetooth Low Energy (LE), distinguishes the proposed MSS from conventional SHM systems, which are typically constrained by bulky hardware, single sensing modalities, or dependence on wired communication. Experimental evaluations on composite panels and aluminum specimens demonstrate reliable high-fidelity recording of PZT signals, strain variations, and acceleration responses, matching the performance of commercial instruments. The proposed system offers a low-power, lightweight, and scalable platform, demonstrating strong potential for on-board SHM in aircraft applications. Full article
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