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Sensors Young Investigators’ Contributions Collection

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

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 22510

Special Issue Editor

Dipartimento di Ingegneria Elettrica e dell'Informazione (Department of Electrical and Information Engineering), Politecnico di Bari, Via Edoardo Orabona n. 4, 70125 Bari, Italy
Interests: optoelectronic technologies; photonic devices and sensors; nanophotonic integrated sensors; non linear integrated optics; microelectronic and nanoelectronic technologies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The collection of Sensors 2022 Young Investigator Award aims to compile the current trends and research directions of internationally renowned and successful young scientists. In this way, we hope to create a platform for young scientists to exchange knowledge and increase the visibility of their studies in the scholarly community of sensor technology. All accepted papers in the special issue will be offered a 20% discount on the article processing charge (APC) to support the work of young scientists.

Young scientists (under 40 years old who have obtained a Ph.D. degree) produce ground-breaking research and have made significant contributions to the advancement of sensors and sensing-related topics.

Along with their submission, we request that any young authors who are interested in this opportunity send a short biography, including a photograph, their education experience, and current research interests or scientific background. With this new initiative, we hope to strengthen the networking of young scientists, encouraging them to pursue their research careers and assisting them in surmounting the challenges and hurdles they may face on this journey.

For any questions about the special issue, please contact the Editorial Office <>.

Prof. Dr. Vittorio Passaro
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.

Published Papers (9 papers)

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Research

16 pages, 7244 KiB  
Article
Low-Cost Online Monitoring System for the Etching Process in Fiber Optic Sensors by Computer Vision
by Wenceslao Eduardo Rodríguez-Rodríguez, Jesús Abraham Puente-Sujo, Adolfo Josué Rodríguez-Rodríguez, Ignacio R. Matias, David Tomás Vargas-Requena and Luis Antonio García-Garza
Sensors 2023, 23(13), 5951; https://doi.org/10.3390/s23135951 - 27 Jun 2023
Cited by 1 | Viewed by 1321
Abstract
The present research exposes a novel methodology to manufacture fiber optic sensors following the etching process by Hydrofluoric Acid deposition through a real-time monitoring diameter measurement by computer vision. This is based on virtual instrumentation developed with the National Instruments® technology and [...] Read more.
The present research exposes a novel methodology to manufacture fiber optic sensors following the etching process by Hydrofluoric Acid deposition through a real-time monitoring diameter measurement by computer vision. This is based on virtual instrumentation developed with the National Instruments® technology and a conventional digital microscope. Here, the system has been tested proving its feasibility by the SMS structure diameter reduction from its original diameter of 125 μ until approximately 42.5 μm. The results obtained have allowed us to demonstrate a stable state behavior of the developed system during the etching process through diameter measurement at three different structure sections. Therefore, this proposal will contribute to the etched fiber optic sensor development that requires reaching an enhanced sensitivity. Finally, to demonstrate the previously mentioned SMS without chemical corrosion, and the etched manufactured SMS, both have been applied as glucose concentration sensors. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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12 pages, 8610 KiB  
Article
Design and Development of a Family of Integrated Devices to Monitor Animal Movement in the Wild
by Laila Daniela Kazimierski, Andrés Oliva Trevisan, Erika Kubisch, Karina Laneri and Nicolás Catalano
Sensors 2023, 23(7), 3684; https://doi.org/10.3390/s23073684 - 02 Apr 2023
Viewed by 1485
Abstract
Monitoring the tortoise Chelonoidis chilensis in the wild, currently in a vulnerable state of conservation in southern Argentina, is essential to gather movement information to elaborate guidelines for the species preservation. We present here the electronic circuit design as well as the associated [...] Read more.
Monitoring the tortoise Chelonoidis chilensis in the wild, currently in a vulnerable state of conservation in southern Argentina, is essential to gather movement information to elaborate guidelines for the species preservation. We present here the electronic circuit design as well as the associated firmware for animal monitoring that was entirely designed by our interdisciplinary research team to allow the extension of device features in the future. Our development stands out for being a family of low-cost and low-power devices, that could be easily adaptable to other species and contexts. Each device is composed of a sub 1 GHz radiofrequency IoT-compatible transceiver, a global navigation satellite system (GNSS) receiver, a magnetometer, and temperature and inertial sensors. The device does not exceed 5% of the animal’s weight to avoid disturbance in their behavior. The board was designed to work as a monitoring device as well as a collecting data station and a tracker, by adding only small pieces of hardware. We performed field measurements to assess the autonomy and range of the radiofrequency link, as well as the power consumption and the associated positioning error. We report those values and discuss the device’s limitations and advantages. The weight of the PCB including battery and GNSS receiver is 44.9 g, its dimensions are 48.7 mm × 63.7 mm, and it has an autonomy that can vary between a week and a month, depending on the sampling rates of the sensors and the rate of the RF signal and that of the GNSS receiver. The characterization of the device parameters will favor the open use of this development by other research groups working on similar projects. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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18 pages, 4749 KiB  
Article
Effective Ransomware Detection Using Entropy Estimation of Files for Cloud Services
by Kyungroul Lee, Jaehyuk Lee, Sun-Young Lee and Kangbin Yim
Sensors 2023, 23(6), 3023; https://doi.org/10.3390/s23063023 - 10 Mar 2023
Cited by 1 | Viewed by 1555
Abstract
A variety of data-based services such as cloud services and big data-based services have emerged in recent times. These services store data and derive the value of the data. The reliability and integrity of the data must be ensured. Unfortunately, attackers have taken [...] Read more.
A variety of data-based services such as cloud services and big data-based services have emerged in recent times. These services store data and derive the value of the data. The reliability and integrity of the data must be ensured. Unfortunately, attackers have taken valuable data as hostage for money in attacks called ransomware. It is difficult to recover original data from files in systems infected by ransomware because they are encrypted and cannot be accessed without keys. There are cloud services to backup data; however, encrypted files are synchronized with the cloud service. Therefore, the original file cannot be restored even from the cloud when the victim systems are infected. Therefore, in this paper, we propose a method to effectively detect ransomware for cloud services. The proposed method detects infected files by estimating the entropy to synchronize files based on uniformity, one of the characteristics of encrypted files. For the experiment, files containing sensitive user information and system files for system operation were selected. In this study, we detected 100% of the infected files in all file formats, with no false positives or false negatives. We demonstrate that our proposed ransomware detection method was very effective compared to other existing methods. Based on the results of this paper, we expect that this detection method will not synchronize with a cloud server by detecting infected files even if the victim systems are infected with ransomware. In addition, we expect to restore the original files by backing up the files stored on the cloud server. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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15 pages, 4089 KiB  
Article
State of Charge Estimation Model Based on Genetic Algorithms and Multivariate Linear Regression with Applications in Electric Vehicles
by Carlos Gustavo Manriquez-Padilla, Isaias Cueva-Perez, Aurelio Dominguez-Gonzalez, David Alejandro Elvira-Ortiz, Angel Perez-Cruz and Juan Jose Saucedo-Dorantes
Sensors 2023, 23(6), 2924; https://doi.org/10.3390/s23062924 - 08 Mar 2023
Cited by 4 | Viewed by 1626
Abstract
Nowadays, the use of renewable, green/eco-friendly technologies is attracting the attention of researchers, with a view to overcoming recent challenges that must be faced to guarantee the availability of Electric Vehicles (EVs). Therefore, this work proposes a methodology based on Genetic Algorithms (GA) [...] Read more.
Nowadays, the use of renewable, green/eco-friendly technologies is attracting the attention of researchers, with a view to overcoming recent challenges that must be faced to guarantee the availability of Electric Vehicles (EVs). Therefore, this work proposes a methodology based on Genetic Algorithms (GA) and multivariate regression for estimating and modeling the State of Charge (SOC) in Electric Vehicles. Indeed, the proposal considers the continuous monitoring of six load-related variables that have an influence on the SOC (State of Charge), specifically, the vehicle acceleration, vehicle speed, battery bank temperature, motor RPM, motor current, and motor temperature. Thus, these measurements are evaluated in a structure comprised of a Genetic Algorithm and a multivariate regression model in order to find those relevant signals that better model the State of Charge, as well as the Root Mean Square Error (RMSE). The proposed approach is validated under a real set of data acquired from a self-assembly Electric Vehicle, and the obtained results show a maximum accuracy of approximately 95.5%; thus, this proposed method can be applied as a reliable diagnostic tool in the automotive industry. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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18 pages, 11167 KiB  
Article
UAV’s Status Is Worth Considering: A Fusion Representations Matching Method for Geo-Localization
by Runzhe Zhu, Mingze Yang, Ling Yin, Fei Wu and Yuncheng Yang
Sensors 2023, 23(2), 720; https://doi.org/10.3390/s23020720 - 08 Jan 2023
Cited by 8 | Viewed by 2058
Abstract
Visual geo-localization plays a crucial role in positioning and navigation for unmanned aerial vehicles, whose goal is to match the same geographic target from different views. This is a challenging task due to the drastic variations in different viewpoints and appearances. Previous methods [...] Read more.
Visual geo-localization plays a crucial role in positioning and navigation for unmanned aerial vehicles, whose goal is to match the same geographic target from different views. This is a challenging task due to the drastic variations in different viewpoints and appearances. Previous methods have been focused on mining features inside the images. However, they underestimated the influence of external elements and the interaction of various representations. Inspired by multimodal and bilinear pooling, we proposed a pioneering feature fusion network (MBF) to address these inherent differences between drone and satellite views. We observe that UAV’s status, such as flight height, leads to changes in the size of image field of view. In addition, local parts of the target scene act a role of importance in extracting discriminative features. Therefore, we present two approaches to exploit those priors. The first module is to add status information to network by transforming them into word embeddings. Note that they concatenate with image embeddings in Transformer block to learn status-aware features. Then, global and local part feature maps from the same viewpoint are correlated and reinforced by hierarchical bilinear pooling (HBP) to improve the robustness of feature representation. By the above approaches, we achieve more discriminative deep representations facilitating the geo-localization more effectively. Our experiments on existing benchmark datasets show significant performance boosting, reaching the new state-of-the-art result. Remarkably, the recall@1 accuracy achieves 89.05% in drone localization task and 93.15% in drone navigation task in University-1652, and shows strong robustness at different flight heights in the SUES-200 dataset. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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17 pages, 3210 KiB  
Article
Combined Effect of Ultrasound and Low-Heat Treatments on E. coli in Liquid Egg Products and Analysis of the Inducted Structural Alterations by NIR Spectroscopy
by Dávid Nagy, László Baranyai, Lien Le Phuong Nguyen, Andrea Taczman Brückner, Tamás Zsom, Csaba Németh, József Felföldi and Viktória Zsom-Muha
Sensors 2022, 22(24), 9941; https://doi.org/10.3390/s22249941 - 16 Dec 2022
Cited by 1 | Viewed by 1333
Abstract
In this study, sonication with mild heat treatment was used to reduce the E. coli count in inoculated liquid whole egg, egg yolk and albumen. Ultrasonic equipment (20/40 kHz, 180/300 W) has been used for 30/60 min with a 55 °C water bath. [...] Read more.
In this study, sonication with mild heat treatment was used to reduce the E. coli count in inoculated liquid whole egg, egg yolk and albumen. Ultrasonic equipment (20/40 kHz, 180/300 W) has been used for 30/60 min with a 55 °C water bath. The combination of sonication and low-heat treatment was able to reduce the concentration of E. coli from 5-log CFU × mL−1 below 10 CFU × mL−1 at 300 W, 40 kHz and 60 min of sonication in liquid egg products. The 60 min treatment was able to reduce the E. coli concentration below 10 CFU × mL−1 in the case of egg yolk regardless of the applied frequency, absorbed power or applied energy dose. The 30 min treatment of sonication and heating was able to reduce significantly the number of E. coli in the egg products, as well. Our results showed that sonication with mild heat treatment can be a useful technique to decrease the number of microorganisms in liquid egg products to a very low level. Near-infrared spectroscopy was used to investigate structural changes in the samples, induced by the combined treatment. Principal component analysis showed that this method can alter the C-H, C-N, -OH and -NH bonds in these egg products. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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20 pages, 5991 KiB  
Article
Digital Forensic Case Studies for In-Vehicle Infotainment Systems Using Android Auto and Apple CarPlay
by Yeonghun Shin, Sungbum Kim, Wooyeon Jo and Taeshik Shon
Sensors 2022, 22(19), 7196; https://doi.org/10.3390/s22197196 - 22 Sep 2022
Cited by 6 | Viewed by 4231
Abstract
Vehicle systems have been one of the fastest-growing fields in recent years. Vehicles are extremely helpful for understanding driver behaviors and have received significant attention from a forensic perspective. Extensive forensic research was previously conducted on on-board vehicle systems, such as an event [...] Read more.
Vehicle systems have been one of the fastest-growing fields in recent years. Vehicles are extremely helpful for understanding driver behaviors and have received significant attention from a forensic perspective. Extensive forensic research was previously conducted on on-board vehicle systems, such as an event data recorders, located in the electronic control unit or manufacturer-based infotainment systems. However, unlike previous vehicles that used only manufacturer-based infotainment systems, most vehicles today are equipped with infotainment systems such as Android Auto and Apple CarPlay. These in-vehicle infotainment (IVI) systems connect to mobile devices such as smartphones and tablets. The vehicle can periodically communicate with a smartphone and thus a network outside the vehicle. Drivers can use more services in their vehicles than ever before. Accordingly, an increasing number of diverse data are being stored in vehicles, with mobile devices connected to both the vehicle and the cloud. Such data include information that can be of significant help to investigators in solving problems during forensic investigations. Therefore, forensics of IVI systems such as Android Auto and Apple CarPlay are becoming increasingly important. We analyzed various forensic studies conducted on Android Auto and Apple CarPlay. Most of the research was mainly focused on mobile devices connected through a wired USB connection. The use of wireless-based IVI systems has recently been increasing. However, the analysis of Android Auto and Apple CarPlay from this point of view is insufficient. Therefore, we proposed a forensic methodology that fully considers such limitations. A forensic analysis was conducted on various IVI systems. We also developed an IVI system forensics tool that works based on the proposed methodology. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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17 pages, 6153 KiB  
Article
Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements
by Manuela Gomez-Correa and David Cruz-Ortiz
Sensors 2022, 22(16), 5931; https://doi.org/10.3390/s22165931 - 09 Aug 2022
Cited by 7 | Viewed by 4124
Abstract
Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the [...] Read more.
Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section’s diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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15 pages, 4375 KiB  
Article
Ultrasensitive Electrochemical Detection and Plasmon-Enhanced Photocatalytic Degradation of Rhodamine B Based on Dual-Functional, 3D, Hierarchical Ag/ZnO Nanoflowers
by Neethu Sebastian, Wan-Chin Yu and Deepak Balram
Sensors 2022, 22(13), 5049; https://doi.org/10.3390/s22135049 - 05 Jul 2022
Cited by 5 | Viewed by 1980
Abstract
The sensitive detection and degradation of synthetic dyes are pivotal to maintain safety owing to the adverse side effects they impart on living beings. In this work, we developed a sensitive electrochemical sensor for the nanomolar-level detection of rhodamine B (RhB) using a [...] Read more.
The sensitive detection and degradation of synthetic dyes are pivotal to maintain safety owing to the adverse side effects they impart on living beings. In this work, we developed a sensitive electrochemical sensor for the nanomolar-level detection of rhodamine B (RhB) using a dual-functional, silver-decorated zinc oxide (Ag/ZnO) composite-modified, screen-printed carbon electrode. The plasmon-enhanced photocatalytic degradation of organic pollutant RhB was also performed using this nanocomposite prepared by embedding different weight percentages (1, 3, and 5 wt%) of Ag nanoparticles on the surface of a three-dimensional (3D), hierarchical ZnO nanostructure based on the photoreduction approach. The structure and morphology of an Ag/ZnO nanocomposite were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), elemental mapping, ultraviolet-visible (UV-vis) spectroscopy, and X-ray diffraction (XRD). The electrochemical sensor exhibited a very high sensitivity of 151.44 µAµM−1cm−2 and low detection limit of 0.8 nM towards RhB detection. The selectivity, stability, repeatability, reproducibility, and practical feasibility were also analyzed to prove their reliability. Furthermore, the photocatalysis results revealed that 3 wt% of the Ag/ZnO hybrid nanostructure acquired immense photostability, reusability, and 90.5% degradation efficiency under visible light. Additionally, the pseudo-first-order rate constant of Ag-3/ZnO is 2.186 min−1 suggested promising activity in visible light photocatalysis. Full article
(This article belongs to the Special Issue Sensors Young Investigators’ Contributions Collection)
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