sensors-logo

Journal Browser

Journal Browser

Special Issue "State-of-the-Art Sensors Technology in Poland 2021-2022"

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

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 5474

Special Issue Editor

Prof. Dr. Krzysztof Kulpa
E-Mail Website
Guest Editor
Institute of Electronic Systems, Faculty of Electronics and Information Technology, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland
Interests: radar imaging; novel radar technologies; noise and passive radars; sparse processing ; cognitive radars

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to provide a comprehensive overview of state-of-the-art sensor technology in Poland. Research articles and reviews are sought that provide insight into any aspect of novel sensor development and application in Poland. Topics of interest include, but are not limited to, the following:

  • Physical sensors
  • Chemical sensors
  • Biosensors
  • Lab-on-a-chip
  • Remote sensors
  • Sensor networks
  • Smart/Intelligent sensors
  • Sensor devices
  • Sensor technology and application
  • Sensing principles
  • Optoelectronic and photonic sensors
  • Optomechanical sensors
  • Sensor arrays and chemometrics
  • Micro and nanosensors
  • Internet of Things
  • Signal processing, data fusion and deep learning in sensor systems
  • Sensor interface
  • Human–computer interaction
  • Advanced materials for sensing
  • Sensing systems
  • MEMS/NEMS
  • Localization and object tracking
  • Sensing and imaging
  • Image sensors
  • Vision/camera based sensors
  • Action recognition
  • Machine/deep learning and artificial intelligence in sensing and imaging
  • 3D sensing
  • Communications and signal processing
  • Wearable sensors, devices, and electronics

Prof. Dr. Krzysztof Kulpa
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 (7 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Investigations of Hydrodynamic Force Generated on the Rotating Cylinder Implemented as a Bow Rudder on a Large-Scale Ship Model
Sensors 2022, 22(23), 9137; https://doi.org/10.3390/s22239137 - 24 Nov 2022
Viewed by 220
Abstract
This paper presents experimental studies of the force generated on the rotating cylinder implemented as a bow rudder on a large-scale ship model. The research focused on the maneuverability of the unit equipped with a rotating cylinder (RC) in the front part of [...] Read more.
This paper presents experimental studies of the force generated on the rotating cylinder implemented as a bow rudder on a large-scale ship model. The research focused on the maneuverability of the unit equipped with a rotating cylinder (RC) in the front part of the model and its future use as a steering device on small draft river barges. The study presented in this paper is a continuation of the research carried out using the small physical model of a river push train in 1:20 geometric scale equipped with two bow RCs and open water tests of separated rotating cylinders carried out in a flume tank. The experimental test setup with RC installed on the model in 1:24 geometric scale allowed to compare the parameters of standard maneuvers performed with the use of RC and without it. The proposed method based on the measurement of the ship model trajectory during maneuvers allowed to compare the hydrodynamic steering force generated by RC with the steering force generated by the conventional stern spade rudder. The results of the experiments compared with empirical models show a similar trend. RC dynamics was tested for rotational speeds up to 570 RPM (revolutions per minute) and ship model velocity up to 1 m/s. The rotating cylinder generated velocity field is presented and phenomena influencing the generated hydrodynamic force are discussed. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Article
The Hybrid System for the Magnetic Characterization of Superparamagnetic Nanoparticles
Sensors 2022, 22(22), 8879; https://doi.org/10.3390/s22228879 - 17 Nov 2022
Viewed by 264
Abstract
The characterization of nanoparticles is crucial in several medical applications, such as hyperthermic therapy, which heats superparamagnetic nanoparticles with an external electromagnetic field. The knowledge of heating ability (magnetic losses) in AC magnetic field frequency function allows for selecting the optimal excitation. A [...] Read more.
The characterization of nanoparticles is crucial in several medical applications, such as hyperthermic therapy, which heats superparamagnetic nanoparticles with an external electromagnetic field. The knowledge of heating ability (magnetic losses) in AC magnetic field frequency function allows for selecting the optimal excitation. A hybrid system for the characterization of superparamagnetic nanoparticles was designed and tested. The proposed setup consists of an excitation coil and two sensing probes: calorimetric and magnetic. The measurements of the imaginary part of the complex magnetic susceptibility of superparamagnetic nanoparticles are possible in the kilohertz range. The system was verified using a set of nanoparticles with different diameters. The measurement procedure was described and verified. The results confirmed that an elaborated sensor system and measuring procedures could properly characterize the magnetic characteristics of nanoparticles. The main advantage of this system is the ability to compare both characteristics and confirm the selection of optimal excitation parameters. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Show Figures

Figure 1

Article
Biometric Identification Based on Keystroke Dynamics
Sensors 2022, 22(9), 3158; https://doi.org/10.3390/s22093158 - 20 Apr 2022
Cited by 1 | Viewed by 566
Abstract
The purpose of the paper is to study how changes in neural network architecture and its hyperparameters affect the results of biometric identification based on keystroke dynamics. The publicly available dataset of keystrokes was used, and the models with different parameters were trained [...] Read more.
The purpose of the paper is to study how changes in neural network architecture and its hyperparameters affect the results of biometric identification based on keystroke dynamics. The publicly available dataset of keystrokes was used, and the models with different parameters were trained using this data. Various neural network layers—convolutional, recurrent, and dense—in different configurations were employed together with pooling and dropout layers. The results were compared with the state-of-the-art model using the same dataset. The results varied, with the best-achieved accuracy equal to 82% for the identification (1 of 20) task. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Show Figures

Figure 1

Article
Real-Time Object Detection and Classification by UAV Equipped With SAR
Sensors 2022, 22(5), 2068; https://doi.org/10.3390/s22052068 - 07 Mar 2022
Cited by 1 | Viewed by 1323
Abstract
The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural networks (YOLOv5). The research resulted in a new method that [...] Read more.
The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural networks (YOLOv5). The research resulted in a new method that combines YOLOv5 with post-processing using classic image analysis. It is shown that the new system improves both the classification accuracy and the location of the identified object. The algorithms were implemented and tested on a mobile platform installed on a military-class UAV as the primary unit for online image analysis. The usage of objective low-computational complexity detection algorithms on SAR scans can reduce the size of the scans sent to the ground control station. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Show Figures

Figure 1

Article
The Prototype Monitoring System for Pollution Sensing and Online Visualization with the Use of a UAV and a WebRTC-Based Platform
Sensors 2022, 22(4), 1578; https://doi.org/10.3390/s22041578 - 17 Feb 2022
Cited by 4 | Viewed by 815
Abstract
Nowadays, we observe a great interest in air pollution, including exhaust fumes. This interest is manifested in both the development of technologies enabling the limiting of the emission of harmful gases and the development of measures to detect excessive emissions. The latter includes [...] Read more.
Nowadays, we observe a great interest in air pollution, including exhaust fumes. This interest is manifested in both the development of technologies enabling the limiting of the emission of harmful gases and the development of measures to detect excessive emissions. The latter includes IoT systems, the spread of which has become possible thanks to the use of low-cost sensors. This paper presents the development and field testing of a prototype pollution monitoring system, allowing for both online and off-line analyses of environmental parameters. The system was built on a UAV and WebRTC-based platform, which was the subject of our previous paper. The platform was retrofitted with a set of low-cost environmental sensors, including a gas sensor able to measure the concentration of exhaust fumes. Data coming from sensors, video metadata captured from 4K camera, and spatiotemporal metadata are put in one situational context, which is transmitted to the ground. Data and metadata are received by the ground station, processed (if needed), and visualized on a dashboard retrieving situational context. Field studies carried out in a parking lot show that our system provides the monitoring operator with sufficient situational awareness to easily detect exhaust emissions online, and delivers enough information to enable easy detection during offline analyses as well. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Show Figures

Figure 1

Article
Modeling and Verification of Asynchronous Systems Using Timed Integrated Model of Distributed Systems
Sensors 2022, 22(3), 1157; https://doi.org/10.3390/s22031157 - 03 Feb 2022
Viewed by 539
Abstract
In modern computer systems, distributed systems play an increasingly important role, and modeling and verification are crucial in their development. The specificity of many systems requires taking this into account in real time, as time dependencies significantly affect the system’s behavior, when achieving [...] Read more.
In modern computer systems, distributed systems play an increasingly important role, and modeling and verification are crucial in their development. The specificity of many systems requires taking this into account in real time, as time dependencies significantly affect the system’s behavior, when achieving the goals of its processes or with adverse phenomena such as deadlocks. The natural features of distributed systems include the asynchrony of actions and communication, the autonomy of nodes, and the locality of behavior, i.e., independence from any global or non-local features. Most modeling formalisms are derived from parallel centralized systems, in which the behavior of components depends on the global state or the simultaneous achievement of certain states by components. This approach is unrealistic for distributed systems. This article presents the formalism of a timed integrated model of distributed systems that supports all of the mentioned features. The formalism is based on the relation between the states of the distributed nodes and the messages of distributed computations, called agents. This relation creates system actions. A specification in this formalism can be translated into timed automata, the most popular formalism for specifying and verifying timed parallel systems. The translation rules ensure that the semantics of T-IMDS and timed automata are consistent, allowing use of the Uppaal validator for system verification. The development of general formulas for checking the deadlock freedom and termination efficiency allows for automated verification, without learning temporal logics and time-dependent formulas. An important and rare feature is the finding of partial deadlocks, because in a distributed system a common situation occurs in which some nodes/processes are deadlocked, while others work. Examples of checking timed distributed systems are included. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Show Figures

Figure 1

Article
Deep Learning Neural Modelling as a Precise Method in the Assessment of the Chronological Age of Children and Adolescents Using Tooth and Bone Parameters
Sensors 2022, 22(2), 637; https://doi.org/10.3390/s22020637 - 14 Jan 2022
Cited by 6 | Viewed by 938
Abstract
Dental age is one of the most reliable methods for determining a patient’s age. The timing of teething, the period of tooth replacement, or the degree of tooth attrition is an important diagnostic factor in the assessment of an individual’s developmental age. It [...] Read more.
Dental age is one of the most reliable methods for determining a patient’s age. The timing of teething, the period of tooth replacement, or the degree of tooth attrition is an important diagnostic factor in the assessment of an individual’s developmental age. It is used in orthodontics, pediatric dentistry, endocrinology, forensic medicine, and pathomorphology, but also in scenarios regarding international adoptions and illegal immigrants. The methods used to date are time-consuming and not very precise. For this reason, artificial intelligence methods are increasingly used to estimate the age of a patient. The present work is a continuation of the work of Zaborowicz et al. In the presented research, a set of 21 original indicators was used to create deep neural network models. The aim of this study was to verify the ability to generate a more accurate deep neural network model compared to models produced previously. The quality parameters of the produced models were as follows. The MAE error of the produced models, depending on the learning set used, was between 2.34 and 4.61 months, while the RMSE error was between 5.58 and 7.49 months. The correlation coefficient R2 ranged from 0.92 to 0.96. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)
Show Figures

Figure 1

Back to TopTop