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IntelliSense and Its Application in Engineering
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Topic Editors

Faculty of Construction and Environment, Hong Kong Polytechnic University, Kowloon 100872, Hong Kong
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
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IntelliSense and Its Application in Engineering

Abstract submission deadline
closed (31 December 2023)
Manuscript submission deadline
closed (31 March 2024)
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2167

Topic Information

Dear Colleagues,

Intellisense refers to the intelligent ability to sense and identify environments, objects, and people using technologies such as sensors, computer vision, and machine learning. Intelligent sensing technology has emerged as a powerful tool in engineering, enabling the development of advanced systems that can sense, process, and respond to complex environmental stimuli. Intelligent sensing can be applied to various application scenarios such as automation control, intelligent monitoring, intelligent interaction and manufacturing. With the development of these technologies, engineers can create systems that are more agile, efficient, and adaptable to changing conditions, thus adding value to engineering projects in many ways.

The aim of this topic "IntelliSensing and Its Application in Engineering" is to collect the latest research on the development and application of intelligent sensing technology in the engineering field. We welcome manuscripts on intelligent sensing-based control systems, smart sensors, data analytics, and decision-making. Additionally, we are interested in research on the application of sensing in areas such as robotics, automation, energy systems, and environmental monitoring.

We believe that this topic will promote the application of intelligent sensing technology in the engineering field, and contribute to the advancement of engineering practices. We look forward to receiving your submissions and sharing the latest research findings in this exciting field.

The topics of interest include, but are not limited to, the following:

  • Remote sensing
  • Wearable sensors
  • Civil engineering
  • Geological engineering
  • Hydraulic engineering
  • Smart construction
  • Smart city
  • Structural safety monitoring
  • Environmental quality monitoring
  • Artificial intelligence
  • Internet of thing
  • Digital twin
  • Robotics
  • 3D printing

Dr. Shuai Han
Dr. Yantao Yu
Topic Editors

Keywords

  • sensing technology
  • artificial intelligence
  • engineering application
  • construction
  • smart sensor
  • computer vision
  • big data
  • environment perception

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci 		2.5 5.3 2011 17.8 Days CHF 2400
Buildings
buildings 		3.1 3.4 2011 17.2 Days CHF 2600
CivilEng
civileng 		- 2.8 2020 35.5 Days CHF 1200
Geosciences
geosciences 		2.4 5.3 2011 26.2 Days CHF 1800
Infrastructures
infrastructures 		2.7 5.2 2016 16.8 Days CHF 1800
Materials
materials 		3.1 5.8 2008 15.5 Days CHF 2600
Remote Sensing
remotesensing 		4.2 8.3 2009 24.7 Days CHF 2700
Smart Cities
smartcities 		7.0 11.2 2018 25.8 Days CHF 2000

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Published Papers (1 paper)

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16 pages, 6209 KiB  
Article
Fast Cable-Force Measurement for Large-Span Cable-Stayed Bridges Based on the Alignment Recognition Method and Smartphone-Captured Video
by Hongxia Lu, Wenwei Fu, Yi Chen, Bingchun Li and Yang Li
Buildings 2024, 14(7), 1941; https://doi.org/10.3390/buildings14071941 - 26 Jun 2024
Viewed by 1123
Abstract
The accurate measurement of cable force plays an important role in the structural form, structural behavior, and safety evaluation of large-span cable-stayed bridges. A fast cable-force estimation method is proposed based on the alignment recognition method and smartphone-captured video. This method can realize [...] Read more.
The accurate measurement of cable force plays an important role in the structural form, structural behavior, and safety evaluation of large-span cable-stayed bridges. A fast cable-force estimation method is proposed based on the alignment recognition method and smartphone-captured video. This method can realize real-time, non-contact, and non-destructive force measurements. Videos of bridge cables were collected using a portable smartphone, and an alignment recognition method was employed to obtain the lateral displacement along the cable, followed by numerical differentiation of the lateral displacement of the cable to acquire the acceleration time history. Based on the fundamental dynamic equation of beam elements, a unified explicit formula for cable-force calculation considering service characteristics was established in the frequency method. Finally, the method was applied to the cable-force measurement during the operation and maintenance stage of the Gengcun Dou Bridge. The measured cable forces were compared with the values obtained from the on-site monitoring system. The results show that the proposed method can accurately identify the acceleration time history at different positions of the cable, and the corresponding frequency components are essentially consistent. The average relative deviation of the measured cable forces from the reference method is within 3%. The proposed cable-force measurement method is simple as regards equipment, convenient for operation, and high in efficiency, providing a new method for the measurement of cable forces in large-span cable-stayed bridges, which can offer reliable measured cable-force data for structural analysis during bridge operation and the maintenance stage. Full article
(This article belongs to the Topic IntelliSense and Its Application in Engineering)
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