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Selected Papers from the 7th International Electronic Conference on Sensors and Applications

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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 27101

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Dr. Stefano Mariani

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Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy
Interests: MEMS; smart materials; micromechanics; machine learning-driven materials modeling
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Dr. Thomas B. Messervey

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CEO and Co-Founder, Research to Market Solution s.r.l., Pavia, Italy
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Dr. Alberto Vallan

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Politecnico di Torino, Department of Electronics and Telecommunications, corso Duca degli Abruzzi, 24, I-10129 Torino, Italy
Interests: measurement instruments; sensors; optical fiber sensors; plastic optical fibers
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Dr. Stefan Bosse

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Department of Computer Science, University of Bremen, and Faculty Computer Science, University of Koblenz-Landau, Mainz, Germany
Interests: artificial intelligence; machine learning; distributed systems; parallel systems; programming languages; self-organizing systems; multi-agent systems
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Prof. Dr. Francisco Falcone

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1. Department of Electrical, Electronic and Communication Engineering & Institute for Smart Cities (ISC), Public University of Navarre, 31006 Pamplona, Spain
2. School of Engineering and Science, Tecnologico de Monterrey, Monterrey 64849, Mexico
Interests: wireless networks; performance evaluation; distributed systems; context-aware environments; IoT; next-generation wireless systems
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Special Issue Information

Dear Colleagues,

This Special Issue comprises extended and expanded versions of proceedings papers from the 7th International Electronic Conference on Sensors and Applications, held 15–30 November 2020, on sciforum.net. In this 7th edition of e-conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Selected papers which attracted the most interest on the web, or that provided a particularly innovative contribution, have been gathered for publication. These papers have been subjected to peer review and are published with the aim of rapid and wide dissemination of research results, developments and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications.

Dr. Stefano Mariani
Dr. Thomas B. Messervey
Dr. Alberto Vallan
Dr. Stefan Bosse
Prof. Dr. Francisco Falcone
Guest Editors

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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

Biosensors
chemical sensors
physical sensors
sensor networks
applications
smart cities
structural health monitoring technologies and sensor networks
wearable sensors
optical fiber sensors
nanosensors
pathogen sensors

Published Papers (10 papers)

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Research

14 pages, 1805 KiB

Open AccessArticle

Comprehensive Optimization of the Tripolar Concentric Ring Electrode Based on Its Finite Dimensions Model and Confirmed by Finite Element Method Modeling

by Oleksandr Makeyev, Yiyao Ye-Lin, Gema Prats-Boluda and Javier Garcia-Casado

Sensors 2021, 21(17), 5881; https://doi.org/10.3390/s21175881 - 31 Aug 2021

Cited by 2 | Viewed by 2063

Abstract

The optimization performed in this study is based on the finite dimensions model of the concentric ring electrode as opposed to the negligible dimensions model used in the past. This makes the optimization problem comprehensive, as all of the electrode parameters including, for the first time, the radius of the central disc and individual widths of concentric rings, are optimized simultaneously. The optimization criterion used is maximizing the accuracy of the surface Laplacian estimation, as the ability to estimate the Laplacian at each electrode constitutes primary biomedical significance of concentric ring electrodes. For tripolar concentric ring electrodes, the optimal configuration was compared to previously proposed linearly increasing inter-ring distances and constant inter-ring distances configurations of the same size and based on the same finite dimensions model. The obtained analytic results suggest that previously proposed configurations correspond to almost two-fold and more than three-fold increases in the Laplacian estimation error compared with the optimal configuration proposed in this study, respectively. These analytic results are confirmed using finite element method modeling, which was adapted to the finite dimensions model of the concentric ring electrode for the first time. Moreover, the finite element method modeling results suggest that optimal electrode configuration may also offer improved sensitivity and spatial resolution. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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16 pages, 3843 KiB

Open AccessArticle

Intention Prediction and Human Health Condition Detection in Reaching Tasks with Machine Learning Techniques

by Federica Ragni, Leonardo Archetti, Agnès Roby-Brami, Cinzia Amici and Ludovic Saint-Bauzel

Sensors 2021, 21(16), 5253; https://doi.org/10.3390/s21165253 - 04 Aug 2021

Cited by 7 | Viewed by 2551

Abstract

Detecting human motion and predicting human intentions by analyzing body signals are challenging but fundamental steps for the implementation of applications presenting human–robot interaction in different contexts, such as robotic rehabilitation in clinical environments, or collaborative robots in industrial fields. Machine learning techniques (MLT) can face the limit of small data amounts, typical of this kind of applications. This paper studies the illustrative case of the reaching movement in 10 healthy subjects and 21 post-stroke patients, comparing the performance of linear discriminant analysis (LDA) and random forest (RF) in: (i) predicting the subject’s intention of moving towards a specific direction among a set of possible choices, (ii) detecting if the subject is moving according to a healthy or pathological pattern, and in the case of discriminating the damage location (left or right hemisphere). Data were captured with wearable electromagnetic sensors, and a sub-section of the acquired signals was required for the analyses. The possibility of detecting with which arm (left or right hand) the motion was performed, and the sensitivity of the MLT to variations in the length of the signal sub-section were also evaluated. LDA and RF prediction accuracies were compared: Accuracy improves when only healthy subjects or longer signals portions are considered up to 11% and at least 10%, respectively. RF reveals better estimation performance both as intention predictor (on average 59.91% versus the 62.19% of LDA), and health condition detector (over 90% in all the tests). Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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11 pages, 3002 KiB

Open AccessCommunication

Optical-Fiber Microsphere-Based Temperature Sensors with ZnO ALD Coating—Comparative Study

by Paulina Listewnik, Mikhael Bechelany, Paweł Wierzba and Małgorzata Szczerska

Sensors 2021, 21(15), 4982; https://doi.org/10.3390/s21154982 - 22 Jul 2021

Viewed by 1754

Abstract

This study presents the microsphere-based fiber-optic sensor with the ZnO Atomic Layer Deposition coating thickness of 100 nm and 200 nm for temperature measurements. Metrological properties of the sensor were investigated over the temperature range from 100 °C to 300 °C, with a 10 °C step. The interferometric signal was used to monitor the integrity of the microsphere and its attachment to the connecting fiber. For the sensor with a 100 nm coating, a spectrum shift of the reflected signal and the optical power of the reflected signal were used to measure temperature, while only the optical power of the reflected signal was used in the sensor with a 200 nm coating. The R² coefficient of the discussed sensors indicates a linear fit of over 0.99 to the obtained data. The sensitivity of the sensors, investigated in this study, equals 103.5 nW/°C and 19 pm/°C or 11.4 nW/°C for ZnO thickness of 200 nm and 100 nm, respectively. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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14 pages, 524 KiB

Open AccessArticle

FBG-Based Temperature Sensors for Liquid Identification and Liquid Level Estimation via Random Forest

by Katiuski Pereira, Wagner Coimbra, Renan Lazaro, Anselmo Frizera-Neto, Carlos Marques and Arnaldo Gomes Leal-Junior

Sensors 2021, 21(13), 4568; https://doi.org/10.3390/s21134568 - 03 Jul 2021

Cited by 27 | Viewed by 2930

Abstract

This paper proposed a liquid level measurement and classification system based on a fiber Bragg grating (FBG) temperature sensor array. For the oil classification, the fluids were dichotomized into oil and nonoil, i.e., water and emulsion. Due to the low variability of the classes, the random forest (RF) algorithm was chosen for the classification. Three different fluids, namely water, mineral oil, and silicone oil (Kryo 51), were identified by three FBGs located at 21.5 cm, 10.5 cm, and 3 cm from the bottom. The fluids were heated by a Peltier device placed at the bottom of the beaker and maintained at a temperature of 318.15 K during the entire experiment. The fluid identification by the RF algorithm achieved an accuracy of 100%. An average root mean squared error (RMSE) of 0.2603 cm, with a maximum RMSE lower than 0.4 cm, was obtained in the fluid level measurement also using the RF algorithm. Thus, the proposed method is a feasible tool for fluid identification and level estimation under temperature variation conditions and provides important benefits in practical applications due to its easy assembly and straightforward operation. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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17 pages, 3127 KiB

Open AccessArticle

Modelling and Evaluation of the Absorption of the 866 MHz Electromagnetic Field in Humans Exposed near to Fixed I-RFID Readers Used in Medical RTLS or to Monitor PPE

by Patryk Zradziński, Jolanta Karpowicz, Krzysztof Gryz, Grzegorz Owczarek and Victoria Ramos

Sensors 2021, 21(12), 4251; https://doi.org/10.3390/s21124251 - 21 Jun 2021

Cited by 5 | Viewed by 2722

Abstract

The aim of this study was to model and evaluate the Specific Energy Absorption Rate (SAR) values in humans in proximity to fixed multi-antenna I-RFID readers of passive tags under various scenarios mimicking exposure when they are incorporated in Real-Time Location Systems (RTLS), or used to monitor Personal Protective Equipment (PPE). The sources of the electromagnetic field (EMF) in the modelled readers were rectangular microstrip antennas at a resonance frequency in free space of 866 MHz from the ultra-high frequency (UHF) RFID frequency range of 865–868 MHz. The obtained results of numerical modelling showed that the SAR values in the body 5 cm away from the UHF RFID readers need consideration with respect to exposure limits set by international guidelines to prevent adverse thermal effects of exposure to EMF: when the effective radiated power exceeds 5.5 W with respect to the general public/unrestricted environments exposure limits, and with respect to occupational/restricted environments exposure limits, when the effective radiated power exceeds 27.5 W. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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16 pages, 5780 KiB

Open AccessArticle

Deterministic and Empirical Approach for Millimeter-Wave Complex Outdoor Smart Parking Solution Deployments

by Fidel Alejandro Rodríguez-Corbo, Leyre Azpilicueta, Mikel Celaya-Echarri, Peio Lopez-Iturri, Ana V. Alejos, Raed M. Shubair and Francisco Falcone

Sensors 2021, 21(12), 4112; https://doi.org/10.3390/s21124112 - 15 Jun 2021

Cited by 10 | Viewed by 2165

Abstract

The characterization of different vegetation/vehicle densities and their corresponding effects on large-scale channel parameters such as path loss can provide important information during the deployment of wireless communications systems under outdoor conditions. In this work, a deterministic analysis based on ray-launching (RL) simulation and empirical measurements for vehicle-to-infrastructure (V2I) communications for outdoor parking environments and smart parking solutions is presented. The study was carried out at a frequency of 28 GHz using directional antennas, with the transmitter raised above ground level under realistic use case conditions. Different radio channel impairments were weighed in, considering the progressive effect of first, the density of an incremental obstructed barrier of trees, and the effect of different parked vehicle densities within the parking lot. On the basis of these scenarios, large-scale parameters and temporal dispersion characteristics were obtained, and the effect of vegetation/vehicle density changes was assessed. The characterization of propagation impairments that different vegetation/vehicle densities can impose onto the wireless radio channel in the millimeter frequency range was performed. Finally, the results obtained in this research can aid communication deployment in outdoor parking conditions. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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14 pages, 3942 KiB

Open AccessArticle

Electrospun PEO/PEDOT:PSS Nanofibers for Wearable Physiological Flex Sensors

by Eve Verpoorten, Giulia Massaglia, Candido Fabrizio Pirri and Marzia Quaglio

Sensors 2021, 21(12), 4110; https://doi.org/10.3390/s21124110 - 15 Jun 2021

Cited by 5 | Viewed by 2657

Abstract

Flexible sensors are fundamental devices for human body monitoring. The mechanical strain and physiological parameters coupled sensing have attracted increasing interest in this field. However, integration of different sensors in one platform usually involves complex fabrication process-flows. Simplification, even if essential, remains a challenge. Here, we investigate a piezoresistive and electrochemical active electrospun nanofibers (NFs) mat as the sensitive element of the wearable physiological flex sensing platform. The use of one material sensitive to the two kinds of stimuli reduces the process-flow to two steps. We demonstrate that the final NFs pH-Flex Sensor can be used to monitor the deformation of a human body joint as well as the pH of the skin. A unique approach has been selected for pH sensing, based on Electrochemical Impedance Spectroscopy (EIS). A linear dependence of the both the double layer capacitance and charge transfer re-sistance with the pH value was obtained by EIS, as well as a linear trend of the electrical resistance with the bending deformation. Gauge factors values calculated after the bending test were 45.84 in traction and 208.55 in compression mode, reflecting the extraordinary piezoresistive behavior of our nanostructured NFs. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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12 pages, 20495 KiB

Open AccessCommunication

Flexible and Transparent Polymer-Based Optical Humidity Sensor

by Katerina Lazarova, Silvia Bozhilova, Sijka Ivanova, Darinka Christova and Tsvetanka Babeva

Sensors 2021, 21(11), 3674; https://doi.org/10.3390/s21113674 - 25 May 2021

Cited by 8 | Viewed by 3436

Abstract

Thin spin-coated polymer films of amphiphilic copolymer obtained by partial acetalization of poly (vinyl alcohol) are used as humidity-sensitive media. They are deposited on polymer substrate (PET) in order to obtain a flexible humidity sensor. Pre-metallization of substrate is implemented for increasing the optical contrast of the sensor, thus improving the sensitivity. The morphology of the sensors is studied by surface profiling, while the transparency of the sensor is controlled by transmittance measurements. The sensing behavior is evaluated through monitoring of transmittance values at different levels of relative humidity gradually changing in the range 5–95% and the influence of up to 1000 bending deformations is estimated by determining the hysteresis and sensitivity of the flexible sensor after each set of deformations. The successful development of a flexible sensor for optical monitoring of humidity in a wide humidity range is demonstrated and discussed. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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22 pages, 683 KiB

Open AccessArticle

Systematic Performance Evaluation of a Novel Optimized Differential Localization Method for Capsule Endoscopes

by Samuel Zeising, Kivanc Ararat, Angelika Thalmayer, Daisuke Anzai, Georg Fischer and Jens Kirchner

Sensors 2021, 21(9), 3180; https://doi.org/10.3390/s21093180 - 03 May 2021

Cited by 8 | Viewed by 2707

Abstract

Capsule endoscopy is a well-established diagnostic tool for the gastrointestinal tract. However, the reliable tracking of capsule endoscopes needs further investigation. Recently, the static magnetic differential method for the localization of capsule endoscopes has shown promising results. This method was experimentally validated by investigating the difference in the measured values of the geomagnetic flux density of a representative sensor pair. In the measurements, it was revealed that misalignment of the sensors and ferromagnetic material near the sensor pair had the most significant impact on the differential approach. Besides, a systematical simulation-based study was conducted. Herein, the position and alignment of all sensors of the localization system were randomly varied. Furthermore, root-mean-squared noise was added to the sensor measurements, and the influence of nearby ferromagnetic material was evaluated. Subsequently, non-idealities were applied simultaneously on the proposed localization system, and the entire system was rotated. The proposed method was significantly better than state-of-the-art geomagnetic compensation methods for the localization of capsule endoscopes with mean position and orientation errors of approximately 2 mm and 1°, respectively. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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21 pages, 2743 KiB

Open AccessArticle

Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios

by Paula Verde, Javier Díez-González, Rubén Ferrero-Guillén, Alberto Martínez-Gutiérrez and Hilde Perez

Sensors 2021, 21(7), 2458; https://doi.org/10.3390/s21072458 - 02 Apr 2021

Cited by 14 | Viewed by 2161

Abstract

Local Positioning Systems (LPS) have become an active field of research in the last few years. Their application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization, or low-level flights in restricted environments. LPS consists of ad-hoc deployments of sensors which meets the design requirements of each activity. Among LPS, those based on temporal measurements are attracting higher interest due to their trade-off among accuracy, robustness, availability, and costs. The Time Difference of Arrival (TDOA) is extended in the literature for LPS applications and consequently we perform, in this paper, an analysis of the optimal sensor deployment of this architecture for achieving practical results. This is known as the Node Location Problem (NLP) and has been categorized as NP-Hard. Therefore, heuristic solutions such as Genetic Algorithms (GA) or Memetic Algorithms (MA) have been applied in the literature for the NLP. In this paper, we introduce an adaptation of the so-called MA-Solis Wets-Chains (MA-SW-Chains) for its application in the large-scale discrete discontinuous optimization of the NLP in urban scenarios. Our proposed algorithm MA-Variable Neighborhood Descent-Chains (MA-VND-Chains) outperforms the GA and the MA of previous proposals for the NLP, improving the accuracy achieved by 17% and by 10% respectively for the TDOA architecture in the urban scenario introduced. Full article

(This article belongs to the Special Issue Selected Papers from the 7th International Electronic Conference on Sensors and Applications)

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