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Smart Sensor Technology and Engineering System Monitoring

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

Deadline for manuscript submissions: closed (1 August 2022) | Viewed by 3299

Special Issue Editors


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Guest Editor
Department of Mechanical Engineering, Lakehead University, Thunder Bay, Ontario P7B 5E1, Canada
Interests: mechatronics; smart sensors; artificial intelligence; machine learning; signal processing; diagnostics; prognostics; intelligent control
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Mechanical Engineering, Xi’an Jiaotong University, 28 Xianning Road West, Xi'an 710049, China
Interests: machinery health monitoring; sensor technology; tribology; artificial intelligence; image processing; diagnostics; prognostics; system control

Special Issue Information

Dear Colleagues,

Rapid advances in smart sensing technologies have provided new tools to collect signals for system health monitoring in different engineering sectors, such as mechanical, electrical, civil, and chemical engineering. Reliable monitoring information can be used in predictive maintenance to improve production quality, operation safety, and reliability, as well as to reduce maintenance costs. On the other hand, the application of smart sensor networks can provide a large amount of data with high variety and pose significant challenges on the signal processing side. Artificial intelligence provides a promising approach for effective learning and decision-making for complex and integrated systems. This Special Issue focuses on smart sensor technology and its applications in health condition monitoring across different domains and engineering sectors. We welcome original research contributions and state-of-the-art reviews from academia and industry. The Special Issue topics include but are not limited to the following:

Smart sensor technology (e.g., vibration, temperature, humidity, and electric current);

Sensor networks and internet of things (IOT);

Design, implementation, and testing of sensing systems;

Fault detection and diagnosis of different engineering systems using sensor data;

Prognostics and health management;

Artificial intelligence for health condition monitoring;

Machine learning and deep learning to improve decision-making efficiency;

Intelligent manufacturing and control;

Energy harvesting for sensor networks;

Applications in different engineering disciplines.

Prof. Dr. Wilson Wang
Guest Editor

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

  • Sensing systems
  • Smart sensors
  • Remote sensors
  • Wireless communication
  • IOT
  • Sensor interface
  • Sensor data fusion
  • Artificial intelligence
  • Signal processing and fault detection
  • System state prognosis
  • Sensor technology and application

Published Papers (1 paper)

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Research

17 pages, 7061 KiB  
Article
Power-Saving Design of Radio Frequency Identification Sensor Networks in Bus Seatbelt Monitoring Systems
by Sitong Sun, Wen Yang and Wilson Wang
Sensors 2020, 20(20), 5882; https://doi.org/10.3390/s20205882 - 17 Oct 2020
Cited by 3 | Viewed by 2033
Abstract
Seatbelt state monitoring is important in intercity buses for passenger safety. This paper discusses the issues and challenges in power-saving design of radio frequency identification (RFID) sensor networks in bus seatbelt monitoring. A new design approach is proposed in this work for low-power [...] Read more.
Seatbelt state monitoring is important in intercity buses for passenger safety. This paper discusses the issues and challenges in power-saving design of radio frequency identification (RFID) sensor networks in bus seatbelt monitoring. A new design approach is proposed in this work for low-power layout and parameter setting in RFID sensor nodes in hardware and software design. A one-to-many pairing registration method is suggested between the concentrator and the seat nodes. Unlike using extra computer software to write seat identification (ID) into an integrated circuit (IC) card, the node ID in this project can be stored into the concentrator directly, which can reduce intermediate operations and reduce development costs. The effectiveness of the proposed low-power design approach is verified by some experimental tests. Full article
(This article belongs to the Special Issue Smart Sensor Technology and Engineering System Monitoring)
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