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Special Issue "Smart Sensing and Artificial Intelligence for Civil Infrastructure Monitoring and Management"

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

Deadline for manuscript submissions: 31 March 2023 | Viewed by 624

Special Issue Editors

Dr. Yuguang Fu
E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
Interests: wireless smart sensors; digital twin; artificial intelligence; cyber-physical system; structural health monitoring; digital construction
Dr. Jianxiao Mao
E-Mail Website
Guest Editor
School of Civil Engineering, Southeast University, Nanjing 211189, China
Interests: structural health monitoring; dynamic system identification; long-span bridge; wind engineering
Dr. Peng (Patrick) Sun
E-Mail Website
Guest Editor
Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
Interests: sensor development for structural health monitoring; sensing system development; UAV-based remote sensing; deep learning-based computer vision application
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The monitoring and management of civil infrastructure (e.g., bridges, buildings, tunnels, pipelines, railways, dams) is always an important topic around the world. Smart sensing, accompanied with artificial intelligence (AI), has recently received growing interest for addressing the aforementioned concern. Smart sensing can obtain timely condition or status information about civil infrastructures during their lifecycle, and hence ensure safe construction and efficient operation by providing early warnings of damage or deterioration prior to costly repair or even catastrophic failures.

In recent years, engineers and researchers have witnessed significant advancements in the development of smart sensing technologies, such as wireless smart sensors, mobile sensing, computer vision, and NDT technologies. Their significant potential is further released, with advanced signal processing and data science, which is powered by AI technologies. Meanwhile, these technologies have enabled several full-scale instrumentations of structures under construction or in service. Combined with the collected data stream from these smart sensing systems, researchers take advantage of AI techniques for modelling environmental loadings, detecting construction risks, uncovering the degradation law of structural performance, identifying the surface and interior deficiency of structures, and quickly issuing management instructions.

The focus of this Special Issue is on presenting the latest advances in smart sensing and AI for civil infrastructure monitoring and management. Potential topics include, but are not limited to:

  • Smart sensor development (hardware or software);
  • Digital signal processing and filter design;
  • Sensor fault diagnosis and recovery;
  • Computer vision and image processing;
  • Big data management and mining;
  • Long-term performance monitoring and assessment;
  • Condition assessment or smart upgrading of infrastructure;
  • Surface or interior damage detection of structures;
  • System identification;
  • Construction monitoring and management;
  • Vibration mitigation;
  • Performance improvement of aged infrastructure;
  • Case studies of smart civil infrastructure systems (e.g., bridges, buildings, and tunnels), etc.

Dr. Yuguang Fu
Dr. Jianxiao Mao
Dr. Peng (Patrick) Sun
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 2400 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

  • smart sensing
  • signal processing
  • artificial intelligence
  • structural health monitoring
  • infrastructure inspection
  • full-scale sensor deployment
  • full-field deformation sensing
  • UAV-based sensing application

Published Papers (1 paper)

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Research

Article
xImpact: Intelligent Wireless System for Cost-Effective Rapid Condition Assessment of Bridges under Impacts
Sensors 2022, 22(15), 5701; https://doi.org/10.3390/s22155701 - 29 Jul 2022
Viewed by 275
Abstract
Bridge strikes by over-height vehicles or ships are critical sudden events. Due to their unpredictable nature, many events go unnoticed or unreported, but they can induce structural failures or hidden damage that accelerates the bridge’s long-term degradation. Therefore, always-on monitoring is essential for [...] Read more.
Bridge strikes by over-height vehicles or ships are critical sudden events. Due to their unpredictable nature, many events go unnoticed or unreported, but they can induce structural failures or hidden damage that accelerates the bridge’s long-term degradation. Therefore, always-on monitoring is essential for deployed systems to enhance bridge safety through the reliable detection of such events and the rapid assessment of bridge conditions. Traditional bridge monitoring systems using wired sensors are too expensive for widespread implementation, mainly due to their significant installation cost. In this paper, an intelligent wireless monitoring system is developed as a cost-effective solution. It employs ultralow-power, event-triggered wireless sensor prototypes, which enables on-demand, high-fidelity sensing without missing unpredictable impact events. Furthermore, the proposed system adopts a smart artificial intelligence (AI)-based framework for rapid bridge assessment by utilizing artificial neural networks. Specifically, it can identify the impact location and estimate the peak force and impulse of impacts. The obtained impact information is used to provide early estimation of bridge conditions, allowing the bridge engineers to prioritize resource allocation for the timely inspection of the more severe impacts. The performance of the proposed monitoring system is demonstrated through a full-scale field test. The test results show that the developed system can capture the onset of bridge impacts, provide high-quality synchronized data, and offer a rapid damage assessment of bridges under impact events, achieving the error of around 2 m in impact localization, 1 kN for peak force estimation, and 0.01 kN·s for impulse estimation. Long-term deployment is planned in the future to demonstrate its reliability for real-life impact events. Full article
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