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Special Issue "Vision-Based Sensing in Engineering Structures"
Deadline for manuscript submissions: 31 December 2019.
Tel. +1-(212) 367-2824
Interests: computer vision; structural health monitoring; bridge engineering; data analytics; machine learning
Tel. +1-(212) 854-3143
Interests: remote sensing; computer vision; sensor application for structural health monitoring; sustainability of civil infrastructural systems; smart structures
Interests: structural health monitoring; post-disaster evaluation; vibration control; seismic isolation and control; smart structures
The rapid advances in digital cameras and computer vision techniques make computer vision-based sensing a promising next-generation monitoring technology for engineering structures to complement traditional structural health monitoring (SHM) and nondestructive evaluation. Compared with conventional sensors, computer vision sensors are far more cost-effective and agile to set up, and provide significantly higher spatial-density measurements where each pixel could represent a measurement point.
Currently, computer vision sensing has been drawing attention and gaining popularity in two major areas: (1) vision-based sensors for dynamic response measurement and their SHM applications for modal/parameter identification, damage detection, force estimation, and model validation and updating; and (2) visual monitoring for structural surface defect detection and condition assessment. Despite the progress made in various state-of-the-art vision sensing methods for a wide range of applications, technical and practical issues arise when they are employed for the continuous monitoring of large-scale structures with complex geometries in difficult environments (e.g., changes in illumination/background, heat haze-induced image distortions, object occlusions, camera vibration, varying camera poses and distances, etc.).
This Special Issue is aimed at addressing the open research challenges and unsolved problems related to the vision-based sensing of engineering structures. Manuscripts are solicited that present new vision-based sensing systems useful in highly unstructured and dynamic environments, and innovative and efficient methods for interpreting and transforming monitoring results into actionable data for informed decision-making. Both original research articles and reviews are welcome.
Topics of interest include, but are not limited to:
- Development of accurate vision-based displacement sensors;
- SHM using computer vision and machine learning techniques;
- Automated defect/damage detection and condition assessment of engineering structures via unmanned aerial vehicles;
- Computer vision and artificial intelligence applications in defect/damage detection, quantification and localization;
- Post-disaster assessment through vision data analytics;
- Other new emerging vision-based sensing technologies.
Dr. Dongming Feng
Dr. Maria Q. Feng
Dr. Aiqun Li
Dr. Xiaowei Ye
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 papers will be 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. Remote Sensing 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 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.
- computer vision
- vision sensor
- remote sensing
- dynamic response measurement
- damage detection
- structural health monitoring
- unmanned aerial vehicles
- machine learning
- artificial intelligence
- engineering structure