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Special Issue "Selected Papers from 5th International Conference on Sensors and Electronic Instrumentation Advances (SEIA 2019)"

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

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 7561

Special Issue Editor

Dr. Sergey Y. Yurish
E-Mail Website
Guest Editor
International Frequency Sensor Association (IFSA), Barcelona, Spain
Interests: smart sensors; intelligent sensors; frequency-to-digital converters; frequency measurements
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 5th Annual International Conference on Sensors and Electronic Instrumentation Advances (SEIA' 2019) is a forum for the presentation, discussion, and exchange of information and the latest research and development results in both theoretical and experimental research in sensors, transducers, and their related fields. It will bring together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the field of sensors and measurements.

The SEIA conference will focus on any significant breakthroughs and innovations in sensors, electronics, measuring instrumentation, and transducers engineering advances and their applications with the broadest concepts. The conference is organized by the International Frequency Sensor Association (IFSA), a professional association, which celebrates its 20th anniversary in 2019.

Topics of interest include, but not limited to, the following:

Sensors and Sensing Technology

  • Accelerometers;
  • Inclinometers;
  • Gyroscopes;
  • Mechanical sensors;
  • Optical sensors;
  • Optical fiber sensors;
  • Photonic sensors;
  • Chemical sensors;
  • Biosensors;
  • Immunosensors;
  • BioMEMS;
  • Temperature sensors;
  • Pressure sensors;
  • Acoustic sensors;
  • Electromagnetic sensors;
  • Gas sensors;
  • Humidity sensors;
  • Infrared sensors, devices, and thermography;
  • Radiation sensors;
  • Multi sensor fusion;
  • Smart sensors;
  • Intelligent sensors;
  • Virtual sensors;
  • Sensor interfacing and signal conditioning;
  • Sensor calibration;
  • Nanomaterials and electronics technology for sensors;
  • Semiconductor materials for sensors;
  • Polymer materials for sensors;
  • MEMS and NEMS;
  • Remote sensors and telemetry;
  • Sensor applications.

Sensor Instrumentation and Measuring Technology

  • Metrology and measurement science;
  • Methods of measurements;
  • Calibrations and standards;
  • Measurement of electrical quantities;
  • Time and frequency measurements;
  • Measurement of force, mass, torque, inclination, and acceleration;
  • Magnetic measurements;
  • Hardness measurements;
  • Measurement of geometrical quantities;
  • Temperature and thermal measurements;
  • Pressure and vacuum measurements;
  • Vibration and noise measurement;
  • Flow measurements;
  • Chemical measurements;
  • Quantum measurements and photonics;
  • Acoustics and the ultrasonic measurements;
  • Environmental measurements;
  • Power and energy measurements;
  • Measurement of human functions;
  • Measurements in biology and medicine;
  • Mathematical tools for measurements;
  • Optical and radiation measurements;
  • Microwave measurements;
  • Virtual instruments and data acquisition systems;
  • Software measurements;
  • Measurement systems;
  • Distributed measurements;
  • Analog-to-digital converters, digital and mixed signal processing;
  • Waveform analysis and measurements;
  • Scientific and industrial instrumentation;
  • Cyber-physical systems and IoT;
  • Experimental mechanics;
  • Measurement in robotics;
  • Metrology in food and nutrition;
  • Intelligent and computer vision instruments;
  • Reliability of instrument and measurement systems;
  • Nanometrology;
  • Technical diagnostics and testing;
  • Nondestructive testing;
  • Education and training in measurement and instrumentation.

Prof. Dr. Sergey Y. Yurish
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 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.

Published Papers (6 papers)

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Research

Article
Wireless Measuring System for Monitoring the Condition of Devices Designed to Protect Line Structures
Sensors 2020, 20(9), 2512; https://doi.org/10.3390/s20092512 - 29 Apr 2020
Cited by 3 | Viewed by 960
Abstract
A large number of rock formations in the Czech Republic and abroad directly threaten to damage objects or traffic along the roads located beneath these formations. For this reason, many such rock formations are stabilized using protective fences or dynamic barriers. There are [...] Read more.
A large number of rock formations in the Czech Republic and abroad directly threaten to damage objects or traffic along the roads located beneath these formations. For this reason, many such rock formations are stabilized using protective fences or dynamic barriers. There are several special sensors available on the market. However, there is no comprehensive monitoring system, including remote threshold settings, data processing, and alarm conditions. This statement is supported by extensive research in this area as well as information from major geotechnical companies that are interested in such a system and want to include it in their portfolio. The aim of the article is to describe the unique wireless monitoring system used to measure the geotechnical quantities we have developed. The design and implementation of systems used to measure protective fence states with accelerometers and slope shift with load anchor cells are presented. Wireless accelerometric sensors and load anchor cell sensors are proposed for both systems. To transfer data from the accelerometer sensor to a superior system, IQRF® technology is applied for the communication between the wireless nodes and the network coordinator under the IQMESH topology. The article includes a detailed description of the development of the accelerometric wireless sensor node and load anchor cell wireless sensor node. Three case studies are also discussed. The first case study focuses on the data implementation and assessment at a testing polygon at the village of Málkov. The second case study describes the data implementation and an assessment of the measuring system under operating conditions in Zbraslav, a municipality near Prague. The third case study describes the implementation and assessment of data from load anchor cell wireless nodes installed in realistic conditions on a supporting gabion wall next to a road. All communication between the sensors and with the IQMESH network coordinator and database was executed wirelessly. The data were archived in a MySQL database and it provides a data source for the assessment and visualizations using the Grafana SW system. Full article
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Article
Design, Implementation and Data Analysis of an Embedded System for Measuring Environmental Quantities
Sensors 2020, 20(8), 2304; https://doi.org/10.3390/s20082304 - 17 Apr 2020
Cited by 6 | Viewed by 1088
Abstract
The article describes the development and implementation of a complex monitoring system for measuring the concentration of carbon dioxide, ambient temperature, relative humidity and atmospheric pressure. The presented system was installed at two locations. The first was in the rooms at the Department [...] Read more.
The article describes the development and implementation of a complex monitoring system for measuring the concentration of carbon dioxide, ambient temperature, relative humidity and atmospheric pressure. The presented system was installed at two locations. The first was in the rooms at the Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava. The second was in the classrooms of the Grammar School and Secondary School of Electrical Engineering and Computer Science in Frenštát pod Radhoštěm. The article contains a detailed description of the entire measurement network, whose basic component was a device for measuring carbon dioxide concentration, temperature and relative humidity in ambient air and atmospheric pressure via wireless data transmission using IQRF® technology. Measurements were conducted continuously for several months. The data were archived in a database. The article also describes the methods for processing the data with statistical analysis. Carbon dioxide concentration was selected for data analysis. Data were selected from at least two different rooms at each location. The processed results represent the time periods for the given carbon dioxide concentrations. The graphs display in percent how much of the time students or employees spent exposed to safe or dangerous concentrations of carbon dioxide. The collected data were used for the future improvement of air quality in the rooms. Full article
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Article
Observation of CO Detection Using Aluminum-Doped ZnO Nanorods on Microcantilever
Sensors 2020, 20(7), 2013; https://doi.org/10.3390/s20072013 - 03 Apr 2020
Cited by 4 | Viewed by 1055
Abstract
An oscillating piezoresistive microcantilever (MC) coated with an aluminum (Al)-doped zinc oxide (ZnO) nanorods was used to detect carbon monoxide (CO) in air at room temperature. Al-doped ZnO nanorods were grown on the MC surface using the hydrothermal method, and a response to [...] Read more.
An oscillating piezoresistive microcantilever (MC) coated with an aluminum (Al)-doped zinc oxide (ZnO) nanorods was used to detect carbon monoxide (CO) in air at room temperature. Al-doped ZnO nanorods were grown on the MC surface using the hydrothermal method, and a response to CO gas was observed by measuring a resonant frequency shift of vibrated MC. CO gas response showed a significant increase in resonant frequency, where sensitivity in the order of picogram amounts was obtained. An increase in resonant frequency was also observed with increasing gas flow rate, which was simultaneously followed by a decrease in relative humidity, indicating that the molecular interface between ZnO and H2O plays a key role in CO absorption. The detection of other gases of carbon compounds such as CO2 and CH4 was also performed; the sensitivity of CO was found to be higher than those gases. The results demonstrate the reversibility and reproducibility of the proposed technique, opening up future developments of highly sensitive CO-gas detectors with a fast response and room temperature operation. Full article
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Article
Frequency Response Stabilization and Comparative Studies of MET Hydrophone at Marine Seismic Exploration Systems
Sensors 2020, 20(7), 1944; https://doi.org/10.3390/s20071944 - 30 Mar 2020
Cited by 8 | Viewed by 1341
Abstract
Low frequency hydrophone with a frequency range of 1−300 Hz for marine seismic exploration systems has been developed. The operation principle of the hydrophone bases on the molecular electronic transfer that allows high sensitivity and low level self-noise at low frequencies (<10 Hz) [...] Read more.
Low frequency hydrophone with a frequency range of 1−300 Hz for marine seismic exploration systems has been developed. The operation principle of the hydrophone bases on the molecular electronic transfer that allows high sensitivity and low level self-noise at low frequencies (<10 Hz) to be achieved. The paper presents a stabilization method of the frequency response within the frequency range at a depth up to 30 m. Laboratory and marine tests confirmed the stated characteristics as well as the possibility of using this sensor in bottom marine seismic systems. An experimental sample of the hydrophone successfully passed a comparative marine test at Gelendzhik Bay (Black Sea) with the technical support of Joint-Stock Company (JSC) “Yuzhmorgeologiya”. One of the main results is the possibility of obtaining high-quality information in the field of low frequencies, which was demonstrated in the course of field tests. Full article
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Article
Love Wave Sensors with Silver Modified Polypyrrole Nanoparticles for VOCs Monitoring
Sensors 2020, 20(5), 1432; https://doi.org/10.3390/s20051432 - 06 Mar 2020
Cited by 12 | Viewed by 1353
Abstract
Love wave sensors with silver-modified polypyrrole nanoparticles are developed in this work. These systems prove functional at room temperature with enhanced response, sensitivity and response time, as compared to other state-of-the-art surface acoustic wave (SAW) sensors, towards volatile organic compounds (VOCs). Results demonstrate [...] Read more.
Love wave sensors with silver-modified polypyrrole nanoparticles are developed in this work. These systems prove functional at room temperature with enhanced response, sensitivity and response time, as compared to other state-of-the-art surface acoustic wave (SAW) sensors, towards volatile organic compounds (VOCs). Results demonstrate the monitoring of hundreds of ppb of compounds such as acetone, ethanol and toluene with low estimated limits of detection (~3 ppb for acetone). These results are attributed to the use of silver-modified polypyrrole as a second guiding/sensitive layer in the Love wave sensor structure, which provides further chemically active sites for the gas-solid interactions. The sensing of low VOCs concentrations by micro sensing elements as those presented here could be beneficial in future systems for air quality control, food quality control or disease diagnosis via exhaled breath as the limits of detection obtained are within those required in these applications. Full article
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Article
Development of Invisible Sensors and a Machine-Learning-Based Recognition System Used for Early Prediction of Discontinuous Bed-Leaving Behavior Patterns
Sensors 2020, 20(5), 1415; https://doi.org/10.3390/s20051415 - 05 Mar 2020
Cited by 4 | Viewed by 1351
Abstract
This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recognizer based on machine learning. [...] Read more.
This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recognizer based on machine learning. The linear characteristic between loads and output was obtained from a load test to evaluate sensor output characteristics. Moreover, the output values change linearly concomitantly with speed to attain the sensor with the equivalent load. We obtained benchmark datasets of continuous and discontinuous behavior patterns from ten subjects. Recognition targets using our sensor prototype and their monitoring system comprise five behavior patterns: sleeping, longitudinal sitting, lateral sitting, terminal sitting, and leaving the bed. We compared machine learning algorithms of five types to recognize five behavior patterns. The experimentally obtained results revealed that the proposed sensor system improved recognition accuracy for both datasets. Moreover, we achieved improved recognition accuracy after integration of learning datasets as a general discriminator. Full article
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