Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.9
Journals
Sensors
Special Issues
State-of-the-Art Sensors Technology
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

State-of-the-Art Sensors Technology

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

Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 15477

Special Issue Editor

Prof. Dr. Alexander Sutor

E-Mail Website
Guest Editor
UMIT - Private University for Health Sciences, Medical Informatics and Technology GmbH, Department of Biomedical Informatics and Mechatronics, Institute for Measurement and Sensor Technology, Eduard-Wallnöfer-Zentrum 1, 6060 Hall in Tirol, Austria
Interests: mechanical sensors; optical sensors; acoustic sensors; biomedical applications; wireless sensor application

Special Issue Information

Dear colleagues,

Sensors provide the primary environmental information necessary for the control of many processes. In the automation processes enrolled in Industry 4.0, many observations rely on information gained by sensors. Many sensor principles are well known, but their applicability depends on factors such as ease of use, robustness, accuracy, repeatability, wireless applicability, energy supply and consumption, and last but not least, cost.
This Special Issue focused on state-of-the-art sensor principles which address those tasks. The topic is open, but special focus will be given to biomedical applications, sensors for special processes, measurement by imaging technologies, optical measurement regarding selective spectroscopy, acoustic sensors and imaging, industrial applications, and wireless technologies.

Prof. Dr. Alexander Sutor
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

  • mechanical sensors
  • optical sensors
  • acoustic sensors
  • image-based measurements
  • industrial sensors
  • wireless sensors

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 4402 KiB  
Article
Progressive Early Image Recognition for Wireless Vision Sensor Networks
by AlKhzami AlHarami, Abubakar Abubakar, Bo Zhang and Amine Bermak
Sensors 2022, 22(17), 6348; https://0-doi-org.brum.beds.ac.uk/10.3390/s22176348 - 24 Aug 2022
Viewed by 1267
Abstract
A wireless vision sensor network (WVSN) is built by using multiple image sensors connected wirelessly to a central server node performing video analysis, ultimately automating different tasks such as video surveillance. In such applications, a large deployment of sensors in the same way [...] Read more.
A wireless vision sensor network (WVSN) is built by using multiple image sensors connected wirelessly to a central server node performing video analysis, ultimately automating different tasks such as video surveillance. In such applications, a large deployment of sensors in the same way as Internet-of-Things (IoT) devices is required, leading to extreme requirements in terms of sensor cost, communication bandwidth and power consumption. To achieve the best possible trade-off, we propose in this paper a new concept that attempts to achieve image compression and early image recognition leading to lower bandwidth and smart image processing integrated at the sensing node. A WVSN implementation is proposed to save power consumption and bandwidth utilization by processing only part of the acquired image at the sensor node. A convolutional neural network is deployed at the central server node for the purpose of progressive image recognition. The proposed implementation is capable of achieving an average recognition accuracy of 88% with an average confidence probability of 83% for five subimages, while minimizing the overall power consumption at the sensor node as well as the bandwidth utilization between the sensor node and the central server node by 43% and 86%, respectively, compared to the traditional sensor node. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

16 pages, 3851 KiB  
Article
Sensing Method Using Multiple Quantities for Diagnostic of Insulators in Different Ambient Conditions
by Bystrík Dolník, Ľuboš Šárpataky, Iraida Kolcunová and Peter Havran
Sensors 2022, 22(4), 1376; https://0-doi-org.brum.beds.ac.uk/10.3390/s22041376 - 11 Feb 2022
Cited by 6 | Viewed by 1589
Abstract
Insulators are one of the many components responsible for the reliability of electricity supply as part of transmission and distribution lines. Failure of the insulator can cause considerable economic problems that are much greater than the insulator cost. When the failure occurs on [...] Read more.
Insulators are one of the many components responsible for the reliability of electricity supply as part of transmission and distribution lines. Failure of the insulator can cause considerable economic problems that are much greater than the insulator cost. When the failure occurs on the transmission line, a large area can be without electricity supply or other transmission lines will be overloaded. Because of the consequences of the insulator’s failure, diagnostics of the insulator plays a significant role in the reliability of the power supply. Basic diagnostic methods require experienced personnel, and inspection requires moving in the field. New diagnostic methods require online measurement if it is possible. Diagnostic by measuring the leakage current flowing on the surface of the insulator is well known. However, many other quantities can be used as a good tool for diagnostics of insulators. We present in this article results obtained on the investigated porcelain insulators that are one of the most used insulation materials for housing the insulator’s core. Leakage current, dielectric loss factor, capacity, and electric charge are used as diagnostic quantities to investigate porcelain insulators in different pollution conditions and different ambient relative humidity. Pollution and humidity are the main factors that decrease the insulator´s electric strength and reliability. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

29 pages, 1586 KiB  
Article
One-Dimensional Systemic Modeling of Thermal Sensors Based on Miniature Bead-Type Thermistors
by Rodolphe Heyd
Sensors 2021, 21(23), 7866; https://0-doi-org.brum.beds.ac.uk/10.3390/s21237866 - 26 Nov 2021
Viewed by 1679
Abstract
Accurate measurements of thermal properties is a major concern, for both scientists and the industry. The complexity and diversity of current and future demands (biomedical applications, HVAC, smart buildings, climate change adapted cities, etc.) require making the thermal characterization methods used in laboratory [...] Read more.
Accurate measurements of thermal properties is a major concern, for both scientists and the industry. The complexity and diversity of current and future demands (biomedical applications, HVAC, smart buildings, climate change adapted cities, etc.) require making the thermal characterization methods used in laboratory more accessible and portable, by miniaturizing, automating, and connecting them. Designing new materials with innovative thermal properties or studying the thermal properties of biological tissues often require the use of miniaturized and non-invasive sensors, capable of accurately measuring the thermal properties of small quantities of materials. In this context, miniature electro-thermal resistive sensors are particularly well suited, in both material science and biomedical instrumentation, both in vitro and in vivo. This paper presents a one-dimensional (1D) electro-thermal systemic modeling of miniature thermistor bead-type sensors. A Godunov-SPICE discretization scheme is introduced, which allows for very efficient modeling of the entire system (control and signal processing circuits, sensors, and materials to be characterized) in a single workspace. The present modeling is applied to the thermal characterization of different biocompatible liquids (glycerol, water, and glycerol–water mixtures) using a miniature bead-type thermistor. The numerical results are in very good agreement with the experimental ones, demonstrating the relevance of the present modeling. A new quasi-absolute thermal characterization method is then reported and discussed. The multi-physics modeling described in this paper could in the future greatly contribute to the development of new portable instrumental approaches. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

20 pages, 8489 KiB  
Article
Inductive Tracking Methodology for Wireless Sensors in Photoreactors
by David Demetz and Alexander Sutor
Sensors 2021, 21(12), 4201; https://0-doi-org.brum.beds.ac.uk/10.3390/s21124201 - 18 Jun 2021
Cited by 2 | Viewed by 1658
Abstract
In this paper, we present a methodology for locating wireless sensors for the use in photoreactors. Photoreactors are, e.g., used to cultivate photosynthetic active microorganisms. For measuring important parameters like, e.g., the temperature inside the reactor, sensors are needed. Wireless locatable floating sensors [...] Read more.
In this paper, we present a methodology for locating wireless sensors for the use in photoreactors. Photoreactors are, e.g., used to cultivate photosynthetic active microorganisms. For measuring important parameters like, e.g., the temperature inside the reactor, sensors are needed. Wireless locatable floating sensors would enable it to measure the data anywhere inside the reactor and to get a spatial resolution of the registered data. Due to the well defined propagation properties of magnetic fields and the fact that they are not significantly influenced in underwater environments when using low frequencies, a magnetic induction (MI) system is chosen for the data transmission as well as for the localization task. We designed an inductive transmitter and a receiver capable of measuring the magnetic field in every three spatial directions. The transmitting frequency is set at approx. 300kHz. This results in a wavelength of approx. 1km which clearly exceeds the dimensions of our measurement setup where the transmitter–receiver distances in general are lower than one meter. Due to this fact, only the quasi-static field component has to be considered and the location of the transmitter is calculated by measuring its magnetic field at defined positions and in using the magnetic dipole field equation in order to model its magnetic field geometry. The used measurement setup consists of a transmitter and two receivers. The first measurements were performed without a water filled photoreactor since no differences in the propagation criteria of magnetic fields are expected due to the negligibly low differences in the relative magnetic permeability of water and air. The system is calibrated and validated by using a LIDAR depth camera that is also used to locate the transmitter. The transmitter positions measured with the camera are therefore compared with the inductively measured ones. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

23 pages, 13001 KiB  
Article
A Quasi-Static Quantitative Ultrasound Elastography Algorithm Using Optical Flow
by Raphael Lamprecht, Florian Scheible, Marion Semmler and Alexander Sutor
Sensors 2021, 21(9), 3010; https://0-doi-org.brum.beds.ac.uk/10.3390/s21093010 - 25 Apr 2021
Cited by 8 | Viewed by 2717
Abstract
Ultrasound elastography is a constantly developing imaging technique which is capable of displaying the elastic properties of tissue. The measured characteristics could help to refine physiological tissue models, but also indicate pathological changes. Therefore, elastography data give valuable insights into tissue properties. This [...] Read more.
Ultrasound elastography is a constantly developing imaging technique which is capable of displaying the elastic properties of tissue. The measured characteristics could help to refine physiological tissue models, but also indicate pathological changes. Therefore, elastography data give valuable insights into tissue properties. This paper presents an algorithm that measures the spatially resolved Young’s modulus of inhomogeneous gelatin phantoms using a CINE sequence of a quasi-static compression and a load cell measuring the compressing force. An optical flow algorithm evaluates the resulting images, the stresses and strains are computed, and, conclusively, the Young’s modulus and the Poisson’s ratio are calculated. The whole algorithm and its results are evaluated by a performance descriptor, which determines the subsequent calculation and gives the user a trustability index of the modulus estimation. The algorithm shows a good match between the mechanically measured modulus and the elastography result—more precisely, the relative error of the Young’s modulus estimation with a maximum error 35%. Therefore, this study presents a new algorithm that is capable of measuring the elastic properties of gelatin specimens in a quantitative way using only the image data. Further, the computation is monitored and evaluated by a performance descriptor, which measures the trustability of the results. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

19 pages, 17056 KiB  
Article
Dynamic Biomechanical Analysis of Vocal Folds Using Pipette Aspiration Technique
by Florian Scheible, Raphael Lamprecht, Marion Semmler and Alexander Sutor
Sensors 2021, 21(9), 2923; https://0-doi-org.brum.beds.ac.uk/10.3390/s21092923 - 21 Apr 2021
Cited by 8 | Viewed by 1946
Abstract
The voice producing process is a complex interplay between glottal pressure, vocal folds, their elasticity and tension. The material properties of vocal folds are still insufficiently studied, because the determination of material properties in soft tissues is often difficult and connected to extensive [...] Read more.
The voice producing process is a complex interplay between glottal pressure, vocal folds, their elasticity and tension. The material properties of vocal folds are still insufficiently studied, because the determination of material properties in soft tissues is often difficult and connected to extensive experimental setups. To shed light on this less researched area, in this work, a dynamic pipette aspiration technique is utilized to measure the elasticity in a frequency range of 100–1000 Hz. The complex elasticity could be assessed with the phase shift between exciting pressure and tissue movement. The dynamic pipette aspiration setup has been miniaturized with regard to a future in-vivo application. The techniques were applied on 3 different porcine larynges 4 h and 1 d postmortem, in order to investigate the deterioration of the tissue over time and analyze correlation in elasticity values between vocal fold pairs. It was found that vocal fold pairs do have different absolute elasticity values but similar trends. This leads to the assumption that those trends are more important for phonation than having same absolute values. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

15 pages, 22313 KiB  
Article
Tensor Decomposition for Spatial—Temporal Traffic Flow Prediction with Sparse Data
by Funing Yang, Guoliang Liu, Liping Huang and Cheng Siong Chin
Sensors 2020, 20(21), 6046; https://0-doi-org.brum.beds.ac.uk/10.3390/s20216046 - 24 Oct 2020
Cited by 5 | Viewed by 2609
Abstract
Urban transport traffic surveillance is of great importance for public traffic control and personal travel path planning. Effective and efficient traffic flow prediction is helpful to optimize these real applications. The main challenge of traffic flow prediction is the data sparsity problem, meaning [...] Read more.
Urban transport traffic surveillance is of great importance for public traffic control and personal travel path planning. Effective and efficient traffic flow prediction is helpful to optimize these real applications. The main challenge of traffic flow prediction is the data sparsity problem, meaning that traffic flow on some roads or of certain periods cannot be monitored. This paper presents a transport traffic prediction method that leverages the spatial and temporal correlation of transportation traffic to tackle this problem. We first propose to model the traffic flow using a fourth-order tensor, which incorporates the location, the time of day, the day of the week, and the week of the month. Based on the constructed traffic flow tensor, we either propose a model to estimate the correlation in each dimension of the tensor. Furthermore, we utilize the gradient descent strategy to design a traffic flow prediction algorithm that is capable of tackling the data sparsity problem from the spatial and temporal perspectives of the traffic pattern. To validate the proposed traffic prediction method, case studies using real-work datasets are constructed, and the results demonstrate that the prediction accuracy of our proposed method outperforms the baselines. The accuracy decreases the least with the percentage of missing data increasing, including the situation of data being missing on neighboring roads in one or continuous multi-days. This certifies that the proposed prediction method can be utilized for sparse data-based transportation traffic surveillance. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop