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Special Issue "Feature Papers in Optical Sensors 2023"

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

Deadline for manuscript submissions: 31 December 2023 | Viewed by 9121

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Prof. Dr. Vittorio M. N. Passaro

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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
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Prof. Dr. Yuliya Semenova

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School of Electrical and Electronic Engineering, Photonics Research Centre, Technological University Dublin, Grangegorman, D07 ADY7 Dublin, Ireland
Interests: optical sensing; whispering gallery mode effects in microfibre based resonators for chemical and bio-sensing; smart optical sensors for engineering applications; sensing of volatile organic compounds in environmental monitoring, medical diagnostics and industrial control; optics and applications of liquid crystals in photonics
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Prof. Dr. Nikolay Kazanskiy

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1. Image Processing Systems Institute of the RAS—Branch of the FSRC “Crystallography and Photonics” RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia
2. Technical Cybernetics Department, Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia
Interests: computer optics; diffractive nanophotonics; computer vision; plasmonic sensors; optical sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Optical sensors are the subject of a huge number of studies and applications. Many well-established technologies, including free-space optics, integrated photonics, and fiber optics approaches, have been developed in recent decades to fabricate and develop increasingly more-efficient optical sensors for applications ranging from industrial control to monitoring the environment, biomedical use, and even as part of the Internet of Things.

The purpose of this Special Issue is to publish a set of papers that typify the very most insightful and influential original articles where our section’s EBMs discuss key topics in the field, particularly review contributions that demonstrate the advancement of optical sensing technology and successfully present new and consolidated application areas. Areas of interest include the evaluation of new sensors, new sensing principles, new applications, and new technologies, as well as review papers on the state of the art of well-established technologies for sensing. Topics of interest include Group IV photonic sensors, optomechanical sensors, fiber optic sensors, silicon photonics, plasmonic sensors, and metasurfaces and related topics.

Prof. Dr. Vittorio Passaro
Prof. Dr. Yuliya Semenova
Prof. Dr. Nikolay Kazanskiy
Guest Editors

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 (10 papers)

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Research

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Open AccessArticle

Crime Light Imaging (CLI): A Novel Sensor for Stand-Off Detection and Localization of Forensic Traces

Cristina Cano-Trujillo

Gemma Montalvo

and

Violeta Lazic

Sensors 2023, 23(18), 7736; https://doi.org/10.3390/s23187736 - 07 Sep 2023

Viewed by 388

Abstract

Stand-off detection of latent traces avoids the scene alteration that might occur during close inspection by handheld forensic lights. Here, we describe a novel sensor, named Crime Light Imaging (CLI), designed to perform high-resolution photography of targets at a distance of 2–10 m and to visualize some common latent traces. CLI is based on four high-power illumination LEDs and one color CMOS camera with a motorized objective plus frontal filters; the LEDs and camera could be synchronized to obtain short-exposure images weakly dependent on the ambient light. The sensor is integrated into a motorized platform, providing the target scanning and necessary information for 3D scene reconstruction. The whole system is portable and equipped with a user-friendly interface. The preliminary tests of CLI on fingerprints at distance of 7 m showed an excellent image resolution and drastic contrast enhancement under green LED light. At the same distance, a small (1 µL) blood droplet on black tissue was captured by CLI under NIR LED, while a trace from 15 µL semen on white cotton became visible under UV LED illumination. These results represent the first demonstration of true stand-off photography of latent traces, thus opening the way for a completely new approach in crime scene forensic examination. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

“GeSn Rule-23”—The Performance Limit of GeSn Infrared Photodiodes

Guo-En Chang

Shui-Qing Yu

and

Greg Sun

Sensors 2023, 23(17), 7386; https://doi.org/10.3390/s23177386 - 24 Aug 2023

Viewed by 295

Abstract

Group-IV GeSn photodetectors (PDs) compatible with standard complementary metal–oxide-semiconductor (CMOS) processing have emerged as a new and non-toxic infrared detection technology to enable a wide range of infrared applications. The performance of GeSn PDs is highly dependent on the Sn composition and operation temperature. Here, we develop theoretical models to establish a simple rule of thumb, namely “GeSn−rule 23”, to describe GeSn PDs’ dark current density in terms of operation temperature, cutoff wavelength, and Sn composition. In addition, analysis of GeSn PDs’ performance shows that the responsivity, detectivity, and bandwidth are highly dependent on operation temperature. This rule provides a simple and convenient indicator for device developers to estimate the device performance at various conditions for practical applications. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors

Abdulkadir Eryildirim

and

Sensors 2023, 23(15), 6891; https://doi.org/10.3390/s23156891 - 03 Aug 2023

Viewed by 511

Abstract

In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error

d_{e r r o r}

of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

Proximal Active Optical Sensing Operational Improvement for Research Using the CropCircle ACS-470, Implications for Measurement of Normalized Difference Vegetation Index (NDVI)

Matthew M. Conley

Alison L. Thompson

and

Reagan Hejl

Sensors 2023, 23(11), 5044; https://doi.org/10.3390/s23115044 - 24 May 2023

Viewed by 743

Abstract

Active radiometric reflectance is useful to determine plant characteristics in field conditions. However, the physics of silicone diode-based sensing are temperature sensitive, where a change in temperature affects photoconductive resistance. High-throughput plant phenotyping (HTPP) is a modern approach using sensors often mounted to proximal based platforms for spatiotemporal measurements of field grown plants. Yet HTPP systems and their sensors are subject to the temperature extremes where plants are grown, and this may affect overall performance and accuracy. The purpose of this study was to characterize the only customizable proximal active reflectance sensor available for HTPP research, including a 10 °C increase in temperature during sensor warmup and in field conditions, and to suggest an operational use approach for researchers. Sensor performance was measured at 1.2 m using large titanium-dioxide white painted field normalization reference panels and the expected detector unity values as well as sensor body temperatures were recorded. The white panel reference measurements illustrated that individual filtered sensor detectors subjected to the same thermal change can behave differently. Across 361 observations of all filtered detectors before and after field collections where temperature changed by more than one degree, values changed an average of 0.24% per 1 °C. Recommendations based on years of sensor control data and plant field phenotyping agricultural research are provided to support ACS-470 researchers by using white panel normalization and sensor temperature stabilization. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

Bi-Directional Free-Space Visible Light Communication Supporting Multiple Moveable Clients Using Light Diffusing Optical Fiber

and

Sensors 2023, 23(10), 4725; https://doi.org/10.3390/s23104725 - 13 May 2023

Cited by 1 | Viewed by 836

Abstract

In this work, we put forward and demonstrate a bi-direction free-space visible light communication (VLC) system supporting multiple moveable receivers (Rxs) using a light-diffusing optical fiber (LDOF). The downlink (DL) signal is launched from a head-end or central office (CO) far away to the LDOF at the client side via a free-space transmission. When the DL signal is launched to the LDOF, which acts as an optical antenna to re-transmit the DL signal to different moveable Rxs. The uplink (UL) signal is sent via the LDOF towards the CO. In a proof-of-concept demonstration, the LDOF is 100 cm long, and the free space VLC transmission between the CO and the LDOF is 100 cm. 210 Mbit/s DL and 850 Mbit/s UL transmissions meet the pre-forward-error-correction bit error rate (pre-FEC BER = 3.8 × 10⁻³) threshold. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

Evaluation of Spatial Gas Temperature and Water Vapor Inhomogeneities in TDLAS in Circular Multipass Absorption Cells Used for the Analysis of Dynamic Tube Flows

Felix Witt

Henning Bohlius

and

Volker Ebert

Sensors 2023, 23(9), 4345; https://doi.org/10.3390/s23094345 - 27 Apr 2023

Viewed by 781

Abstract

The use of optical circular multipass absorption cells (CMPAC) in an open-path configuration enables the sampling free analysis of cylindrical gas flows with high temporal resolution and only minimal disturbances to the sample gas in the pipe. Combined with their robust unibody design, CMPACs are a good option for many applications in atmospheric research and industrial process monitoring. When deployed in an open-path configuration, the effects of inhomogeneities in the gas temperature and composition have to be evaluated to ensure that the resulting measurement error is acceptable for a given application. Such an evaluation needs to consider the deviations caused by spectroscopic effects, e.g., nonlinear effects of temperature variations on the intensity of the spectral line, as well as the interaction of the temperature and concentration field with the characteristic laser beam pattern of the CMPAC. In this work we demonstrate this novel combined evaluation approach for the CMPAC used as part of the tunable diode laser absorption spectroscopy (TDLAS) reference hygrometer in PTB’s dynH₂O setup for the characterization of the dynamic response behavior of hygrometers. For this, we measured spatially resolved, 2D temperature and H₂O concentration distributions, and combined them with spatially resolved simulated spectra to evaluate the inhomogeneity effects on the line area of the used H₂O spectral line at 7299.43 cm⁻¹. Our results indicate that for dynH₂O, the deviations caused by the interaction between large concentration heterogeneities and the characteristic sampling of the beam pattern of the CMPAC are three orders of magnitude larger than deviations caused by small temperature heterogeneity induced spectroscopic effects. We also deduce that the assumption that the “path-integrated” H₂O concentration derived with the open-path CMPAC setup represents an accurate H₂O area average in the flow section covered by the CMPAC in fact shows significant differences of up to 16% and hence does not hold true when large H₂O concentration gradients are present. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

Long-Range Traffic Monitoring Based on Pulse-Compression Distributed Acoustic Sensing and Advanced Vehicle Tracking and Classification Algorithm

and

Sensors 2023, 23(6), 3127; https://doi.org/10.3390/s23063127 - 15 Mar 2023

Viewed by 1196

Abstract

We introduce a novel long-range traffic monitoring system for vehicle detection, tracking, and classification based on fiber-optic distributed acoustic sensing (DAS). High resolution and long range are provided by the use of an optimized setup incorporating pulse compression, which, to our knowledge, is the first time that is applied to a traffic-monitoring DAS system. The raw data acquired with this sensor feeds an automatic vehicle detection and tracking algorithm based on a novel transformed domain that can be regarded as an evolution of the Hough Transform operating with non-binary valued signals. The detection of vehicles is performed by calculating the local maxima in the transformed domain for a given time-distance processing block of the detected signal. Then, an automatic tracking algorithm, which relies on a moving window paradigm, identifies the trajectory of the vehicle. Hence, the output of the tracking stage is a set of trajectories, each of which can be regarded as a vehicle passing event from which a vehicle signature can be extracted. This signature is unique for each vehicle, allowing us to implement a machine-learning algorithm for vehicle classification purposes. The system has been experimentally tested by performing measurements using dark fiber in a telecommunication fiber cable running in a buried conduit along 40 km of a road open to traffic. Excellent results were obtained, with a general classification rate of 97.7% for detecting vehicle passing events and 99.6% and 85.7% for specific car and truck passing events, respectively. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

Performance Evaluation of MEMS-Based Automotive LiDAR Sensor and Its Simulation Model as per ASTM E3125-17 Standard

and

Sensors 2023, 23(6), 3113; https://doi.org/10.3390/s23063113 - 14 Mar 2023

Cited by 1 | Viewed by 1774

Abstract

Measurement performance evaluation of real and virtual automotive light detection and ranging (LiDAR) sensors is an active area of research. However, no commonly accepted automotive standards, metrics, or criteria exist to evaluate their measurement performance. ASTM International released the ASTM E3125-17 standard for the operational performance evaluation of 3D imaging systems commonly referred to as terrestrial laser scanners (TLS). This standard defines the specifications and static test procedures to evaluate the 3D imaging and point-to-point distance measurement performance of TLS. In this work, we have assessed the 3D imaging and point-to-point distance estimation performance of a commercial micro-electro-mechanical system (MEMS)-based automotive LiDAR sensor and its simulation model according to the test procedures defined in this standard. The static tests were performed in a laboratory environment. In addition, a subset of static tests was also performed at the proving ground in natural environmental conditions to determine the 3D imaging and point-to-point distance measurement performance of the real LiDAR sensor. In addition, real scenarios and environmental conditions were replicated in the virtual environment of a commercial software to verify the LiDAR model’s working performance. The evaluation results show that the LiDAR sensor and its simulation model under analysis pass all the tests specified in the ASTM E3125-17 standard. This standard helps to understand whether sensor measurement errors are due to internal or external influences. We have also shown that the 3D imaging and point-to-point distance estimation performance of LiDAR sensors significantly impacts the working performance of the object recognition algorithm. That is why this standard can be beneficial in validating automotive real and virtual LiDAR sensors, at least in the early stage of development. Furthermore, the simulation and real measurements show good agreement on the point cloud and object recognition levels. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Open AccessArticle

Exploring the Effects of LED-Based Visible Light Communication on Reading and Color Perception in Indoor Environments: An Experimental Study

and

Sensors 2023, 23(6), 2949; https://doi.org/10.3390/s23062949 - 08 Mar 2023

Cited by 1 | Viewed by 1014

Abstract

Visible light communications (VLC) is a technology that enables the transmission of digital information with a light source. VLC is nowadays seen as a promising technology for indoor applications, helping WiFi to handle the spectrum crunch. Possible indoor applications range from Internet connection at home/office to multimedia content delivery in a museum. Despite the vast interest of researchers in both theoretical analysis and experimentation on VLC technology, no studies have been carried out on the human perceptions of objects illuminated by VLC-based lamps. It is important to define if a VLC lamp decreases the reading capability or modifies the color perception in order to make VLC a technology appropriate for everyday life use. This paper describes the results of psychophysical tests on humans to define if VLC lamps modify the perception of colors or the reading speed. The results of the reading speed test showed a

0.97

correlation coefficient between tests with and without VLC modulated light, leading us to conclude that there is no difference in the reading speed capability with and without VLC-modulated light. The results of the color perception test showed a Fisher exact test p-value of

0.2351

, showing that the perception of color is not influenced by the presence of the VLC modulated light. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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Review

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Open AccessReview

Machine Learning Approaches in Brillouin Distributed Fiber Optic Sensors

Christos Karapanagiotis

and

Katerina Krebber

Sensors 2023, 23(13), 6187; https://doi.org/10.3390/s23136187 - 06 Jul 2023

Viewed by 877

Abstract

This paper presents reported machine learning approaches in the field of Brillouin distributed fiber optic sensors (DFOSs). The increasing popularity of Brillouin DFOSs stems from their capability to continuously monitor temperature and strain along kilometer-long optical fibers, rendering them attractive for industrial applications, such as the structural health monitoring of large civil infrastructures and pipelines. In recent years, machine learning has been integrated into the Brillouin DFOS signal processing, resulting in fast and enhanced temperature, strain, and humidity measurements without increasing the system’s cost. Machine learning has also contributed to enhanced spatial resolution in Brillouin optical time domain analysis (BOTDA) systems and shorter measurement times in Brillouin optical frequency domain analysis (BOFDA) systems. This paper provides an overview of the applied machine learning methodologies in Brillouin DFOSs, as well as future perspectives in this area. Full article

(This article belongs to the Special Issue Feature Papers in Optical Sensors 2023)

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