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Sensors, Volume 18, Issue 3 (March 2018)

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Open AccessArticle A Study on the Impact of Poly(3-hexylthiophene) Chain Length and Other Applied Side-Chains on the NO2 Sensing Properties of Conducting Graft Copolymers
Sensors 2018, 18(3), 928; https://doi.org/10.3390/s18030928
Received: 22 February 2018 / Revised: 16 March 2018 / Accepted: 19 March 2018 / Published: 20 March 2018
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Abstract
The detection and concentration measurements of low concentrations of nitrogen dioxide (NO2) are important because of its negative effects on human health and its application in many fields of industry and safety systems. In our approach, conducting graft copolymers based on
[...] Read more.
The detection and concentration measurements of low concentrations of nitrogen dioxide (NO2) are important because of its negative effects on human health and its application in many fields of industry and safety systems. In our approach, conducting graft copolymers based on the poly(3-hexylthiophene) (P3HT) conducting polymer and other side-chains, polyethylene glycol (PEG) and dodec-1-en, grafted on a poly(methylhydrosiloxane) backbone, were investigated. The grafts containing PEG (PEGSil) and dodec-1-en (DodecSil) in two variants, namely, fractions with shorter (hexane fraction -H) and longer (chloroform fraction -CH) side-chains of P3HT, were tested as receptor structures in NO2 gas sensors. Their responses to NO2, within the concentration range of 1–20 ppm, were investigated in an nitrogen atmosphere at different operating temperatures—room temperature (RT) = 25 °C, 50 °C, and 100 °C. The results indicated that both of the copolymers with PEG side-chains had higher responses to NO2 than the materials with dodec-1-en side-chains. Furthermore, the results indicated that, in both cases, H fractions were more sensitive than CH fractions. The highest response to 1 ppm of NO2, from the investigated graft copolymers, had PEGSil H, which indicated a response of 1330% at RT and 1980% at 100 °C. The calculated lower-limit of the detection of this material is lower than 300 ppb of NO2 at 100 °C. This research indicated that graft copolymers of P3HT had great potential for low temperature NO2 sensing, and that the proper choice of other side-chains in graft copolymers can improve their gas sensing properties. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Simultaneous Deployment and Tracking Multi-Robot Strategies with Connectivity Maintenance
Sensors 2018, 18(3), 927; https://doi.org/10.3390/s18030927
Received: 30 January 2018 / Revised: 13 March 2018 / Accepted: 19 March 2018 / Published: 20 March 2018
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Abstract
Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper, we propose two Lloyd-based tracking strategies
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Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper, we propose two Lloyd-based tracking strategies to allow the ground robots (agents) to follow the aerial ones (targets), keeping the connectivity between the agents. The first strategy establishes density functions on the environment so that the targets acquire more importance than other zones, while the second one iteratively modifies the virtual limits of the working area depending on the positions of the targets. We consider the connectivity maintenance due to the fact that coverage tasks tend to spread the agents as much as possible, which is addressed by restricting their motions so that they keep the links of a minimum spanning tree of the communication graph. We provide a thorough parametric study of the performance of the proposed strategies under several simulated scenarios. In addition, the methods are implemented and tested using realistic robotic simulation environments and real experiments. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Motor Planning Error: Toward Measuring Cognitive Frailty in Older Adults Using Wearables
Sensors 2018, 18(3), 926; https://doi.org/10.3390/s18030926
Received: 18 January 2018 / Revised: 5 March 2018 / Accepted: 16 March 2018 / Published: 20 March 2018
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Abstract
Practical tools which can be quickly administered are needed for measuring subtle changes in cognitive–motor performance over time. Frailty together with cognitive impairment, or ‘cognitive frailty’, are shown to be strong and independent predictors of cognitive decline over time. We have developed an
[...] Read more.
Practical tools which can be quickly administered are needed for measuring subtle changes in cognitive–motor performance over time. Frailty together with cognitive impairment, or ‘cognitive frailty’, are shown to be strong and independent predictors of cognitive decline over time. We have developed an interactive instrumented trail-making task (iTMT) platform, which allows quantification of motor planning error (MPE) through a series of ankle reaching tasks. In this study, we examined the accuracy of MPE in identifying cognitive frailty in older adults. Thirty-two older adults (age = 77.3 ± 9.1 years, body-mass-index = 25.3 ± 4.7 kg/m2, female = 38%) were recruited. Using either the Mini-Mental State Examination or Montreal Cognitive Assessment (MoCA), 16 subjects were classified as cognitive-intact and 16 were classified as cognitive-impaired. In addition, 12 young-healthy subjects (age = 26.0 ± 5.2 years, body-mass-index = 25.3 ± 3.9 kg/m2, female = 33%) were recruited to establish a healthy benchmark. Subjects completed the iTMT, using an ankle-worn sensor, which transforms ankle motion into navigation of a computer cursor. The iTMT task included reaching five indexed target circles (including numbers 1-to-3 and letters A&B placed in random order) on the computer-screen by moving the ankle-joint while standing. The ankle-sensor quantifies MPE through analysis of the pattern of ankle velocity. MPE was defined as percentage of time deviation between subject’s maximum ankle velocity and the optimal maximum ankle velocity, which is halfway through the reaching pathway. Data from gait tests, including single task and dual task walking, were also collected to determine cognitive–motor performance. The average MPE in young-healthy, elderly cognitive-intact, and elderly cognitive-impaired groups was 11.1 ± 5.7%, 20.3 ± 9.6%, and 34.1 ± 4.2% (p < 0.001), respectively. Large effect sizes (Cohen’s d = 1.17–4.56) were observed for discriminating between groups using MPE. Significant correlations were observed between the MPE and MoCA score (r = −0.670, p < 0.001) as well as between the MPE and dual task stride velocity (r = −0.584, p < 0.001). This study demonstrated feasibility and efficacy of estimating MPE from a practical wearable platform with promising results in identifying cognitive–motor impairment and potential application in assessing cognitive frailty. The proposed platform could be also used as an alternative to dual task walking test, where gait assessment may not be practical. Future studies need to confirm these observations in larger samples. Full article
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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Open AccessFeature PaperArticle Generic Sensor Failure Modeling for Cooperative Systems
Sensors 2018, 18(3), 925; https://doi.org/10.3390/s18030925
Received: 20 February 2018 / Revised: 12 March 2018 / Accepted: 14 March 2018 / Published: 20 March 2018
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Abstract
The advent of cooperative systems entails a dynamic composition of their components. As this contrasts current, statically composed systems, new approaches for maintaining their safety are required. In that endeavor, we propose an integration step that evaluates the failure model of shared information
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The advent of cooperative systems entails a dynamic composition of their components. As this contrasts current, statically composed systems, new approaches for maintaining their safety are required. In that endeavor, we propose an integration step that evaluates the failure model of shared information in relation to an application’s fault tolerance and thereby promises maintainability of such system’s safety. However, it also poses new requirements on failure models, which are not fulfilled by state-of-the-art approaches. Consequently, this work presents a mathematically defined generic failure model as well as a processing chain for automatically extracting such failure models from empirical data. By examining data of an Sharp GP2D12 distance sensor, we show that the generic failure model not only fulfills the predefined requirements, but also models failure characteristics appropriately when compared to traditional techniques. Full article
(This article belongs to the Special Issue Dependable Monitoring in Wireless Sensor Networks)
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Open AccessArticle Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles
Sensors 2018, 18(3), 924; https://doi.org/10.3390/s18030924
Received: 11 February 2018 / Revised: 14 March 2018 / Accepted: 15 March 2018 / Published: 20 March 2018
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Abstract
Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication
[...] Read more.
Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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Open AccessArticle An Energy-Efficient Algorithm for Wearable Electrocardiogram Signal Processing in Ubiquitous Healthcare Applications
Sensors 2018, 18(3), 923; https://doi.org/10.3390/s18030923
Received: 21 January 2018 / Revised: 24 February 2018 / Accepted: 26 February 2018 / Published: 20 March 2018
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Abstract
Rapid progress and emerging trends in miniaturized medical devices have enabled the un-obtrusive monitoring of physiological signals and daily activities of everyone’s life in a prominent and pervasive manner. Due to the power-constrained nature of conventional wearable sensor devices during ubiquitous sensing (US),
[...] Read more.
Rapid progress and emerging trends in miniaturized medical devices have enabled the un-obtrusive monitoring of physiological signals and daily activities of everyone’s life in a prominent and pervasive manner. Due to the power-constrained nature of conventional wearable sensor devices during ubiquitous sensing (US), energy-efficiency has become one of the highly demanding and debatable issues in healthcare. This paper develops a single chip-based wearable wireless electrocardiogram (ECG) monitoring system by adopting analog front end (AFE) chip model ADS1292R from Texas Instruments. The developed chip collects real-time ECG data with two adopted channels for continuous monitoring of human heart activity. Then, these two channels and the AFE are built into a right leg drive right leg drive (RLD) driver circuit with lead-off detection and medical graded test signal. Human ECG data was collected at 60 beats per minute (BPM) to 120 BPM with 60 Hz noise and considered throughout the experimental set-up. Moreover, notch filter (cutoff frequency 60 Hz), high-pass filter (cutoff frequency 0.67 Hz), and low-pass filter (cutoff frequency 100 Hz) with cut-off frequencies of 60 Hz, 0.67 Hz, and 100 Hz, respectively, were designed with bilinear transformation for rectifying the power-line noise and artifacts while extracting real-time ECG signals. Finally, a transmission power control-based energy-efficient (ETPC) algorithm is proposed, implemented on the hardware and then compared with the several conventional TPC methods. Experimental results reveal that our developed chip collects real-time ECG data efficiently, and the proposed ETPC algorithm achieves higher energy savings of 35.5% with a slightly larger packet loss ratio (PLR) as compared to conventional TPC (e.g., constant TPC, Gao’s, and Xiao’s methods). Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
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Open AccessArticle A Low-Cost Tracking System for Running Race Applications Based on Bluetooth Low Energy Technology
Sensors 2018, 18(3), 922; https://doi.org/10.3390/s18030922
Received: 28 February 2018 / Revised: 14 March 2018 / Accepted: 14 March 2018 / Published: 20 March 2018
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Abstract
Timing points used in running races and other competition events are generally based on radio-frequency identification (RFID) technology. Athletes’ times are calculated via passive RFID tags and reader kits. Specifically, the reader infrastructure needed is complex and requires the deployment of a mat
[...] Read more.
Timing points used in running races and other competition events are generally based on radio-frequency identification (RFID) technology. Athletes’ times are calculated via passive RFID tags and reader kits. Specifically, the reader infrastructure needed is complex and requires the deployment of a mat or ramps which hide the receiver antennae under them. Moreover, with the employed tags, it is not possible to transmit additional and dynamic information such as pulse or oximetry monitoring, alarms, etc. In this paper we present a system based on two low complex schemes allowed in Bluetooth Low Energy (BLE): the non-connectable undirected advertisement process and a modified version of scannable undirected advertisement process using the new capabilities present in Bluetooth 5. After fully describing the system architecture, which allows full real-time position monitoring of the runners using mobile phones on the organizer side and BLE sensors on the participants’ side, we derive the mobility patterns of runners and capacity requirements, which are determinant for evaluating the performance of the proposed system. They have been obtained from the analysis of the real data measured in the last Barcelona Marathon. By means of simulations, we demonstrate that, even under disadvantageous conditions (50% error ratio), both schemes perform reliably and are able to detect the 100% of the participants in all the cases. The cell coverage of the system needs to be adjusted when non-connectable process is considered. Nevertheless, through simulation and experimental, we show that the proposed scheme based on the new events available in Bluetooth 5 is clearly the best implementation alternative for all the cases, no matter the coverage area and the runner speed. The proposal widely exceeds the detection requirements of the real scenario, surpassing the measured peaks of 20 sensors per second incoming in the coverage area, moving at speeds that range from 1.5 m/s to 6.25 m/s. The designed real test-bed shows that the scheme is able to detect 72 sensors below 600 ms, fulfilling comfortably the requirements determined for the intended application. The main disadvantage of this system would be that the sensors are active, but we have proved that its consumption can be so low (9.5 µA) that, with a typical button cell, the sensor battery life would be over 10,000 h of use. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Enhanced Moisture-Reactive Hydrophilic-PTFE-Based Flexible Humidity Sensor for Real-Time Monitoring
Sensors 2018, 18(3), 921; https://doi.org/10.3390/s18030921
Received: 11 February 2018 / Revised: 10 March 2018 / Accepted: 16 March 2018 / Published: 20 March 2018
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Abstract
Flexible sensors connected to cell phones are a promising technology that can aid in continuously monitoring signals in our daily lives, such as an individual’s health status and information from buildings, farms, and industry. Among such signals, real-time humidity monitoring is crucial to
[...] Read more.
Flexible sensors connected to cell phones are a promising technology that can aid in continuously monitoring signals in our daily lives, such as an individual’s health status and information from buildings, farms, and industry. Among such signals, real-time humidity monitoring is crucial to a comfortable life, as human bodies, plants, and industrial environments require appropriate humidity to be maintained. We propose a hydrophilic polytetrafluoroethylene (H-PTFE)-based flexible humidity sensor integrated with readout circuitry, wireless communication, and a mobile battery. To enhance its sensitivity, linearity, and reliability, treatment with sodium hydroxide implements additional hydroxyl (OH) groups, which further enhance the sensitivity, create a strong linearity with respect to variations in relative humidity, and produce a relatively free hysteresis. Furthermore, to create robust mechanical stability, cyclic upward bending was performed for up to 3000 cycles. The overall electrical and mechanical results demonstrate that the flexible real-time H-PTFE humidity sensor system is suitable for applications such as wearable smart devices. Full article
(This article belongs to the Special Issue Thin-Film Transistors for Biomedical and Chemical Sensing)
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Open AccessArticle Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor
Sensors 2018, 18(3), 920; https://doi.org/10.3390/s18030920
Received: 6 January 2018 / Revised: 2 March 2018 / Accepted: 19 March 2018 / Published: 20 March 2018
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Abstract
Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation
[...] Read more.
Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation of cardiopulmonary-signal-and-detection-related abnormal cardiopulmonary events (e.g., tachycardia, bradycardia, tachypnea, bradypnea, and central apnoea) in many possible sleeping postures within varying environmental settings including in total darkness and whether the subject is covered by a blanket or not. The proposed system extracts the signal from the abdominal-thoracic region where cardiopulmonary activity is most pronounced, using a real-time image sequence captured by Kinect v2 sensor. The proposed system shows promising results in any sleep posture, regardless of illumination conditions and unclear ROI even in the presence of a blanket, whilst being reliable, safe, and cost-effective. Full article
(This article belongs to the Special Issue Sensor Applications in Medical Monitoring and Assistive Devices)
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Open AccessArticle Measuring Gait Quality in Parkinson’s Disease through Real-Time Gait Phase Recognition
Sensors 2018, 18(3), 919; https://doi.org/10.3390/s18030919
Received: 16 February 2018 / Revised: 10 March 2018 / Accepted: 19 March 2018 / Published: 20 March 2018
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Abstract
Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model,
[...] Read more.
Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, were compared. The methods were tested on 26 PD patients, both in OFF and ON levodopa conditions, and 11 healthy subjects, during walking tasks. All subjects were equipped with inertial sensors placed on feet. Force resistive sensors were used to assess reference time sequence of gait phases. Goodness Index (G) was evaluated to assess accuracy in gait phases estimation. A novel synthetic index called Gait Phase Quality Index (GPQI) was proposed for gait quality assessment. Results revealed optimum performance (G < 0.25) for three tested methods and good performance (0.25 < G < 0.70) for one threshold method. The GPQI resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score. Furthermore, in patients with severe gait impairment, GPQI was found higher in OFF than in ON state. Our results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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Open AccessArticle Arc-Induced Long Period Gratings from Standard to Polarization-Maintaining and Photonic Crystal Fibers
Sensors 2018, 18(3), 918; https://doi.org/10.3390/s18030918
Received: 26 February 2018 / Revised: 15 March 2018 / Accepted: 18 March 2018 / Published: 20 March 2018
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Abstract
In this work, we report about our recent results concerning the fabrication of Long Period Grating (LPG) sensors in several optical fibers, through the Electric Arc Discharge (EAD) technique. In particular, the following silica fibers with both different dopants and geometrical structures are
[...] Read more.
In this work, we report about our recent results concerning the fabrication of Long Period Grating (LPG) sensors in several optical fibers, through the Electric Arc Discharge (EAD) technique. In particular, the following silica fibers with both different dopants and geometrical structures are considered: standard Ge-doped, photosensitive B/Ge codoped, P-doped, pure-silica core with F-doped cladding, Panda type Polarization-maintaining, and Hollow core Photonic crystal fiber. An adaptive platform was developed and the appropriate “recipe” was identified for each fiber, in terms of both arc discharge parameters and setup arrangement, for manufacturing LPGs with strong and narrow attenuation bands, low insertion losses, and short length. As the fabricated devices have appealing features from the application point of view, the sensitivity characteristics towards changes in different external perturbations (i.e., surrounding refractive index, temperature, and strain) are investigated and compared, highlighting the effects of different fiber composition and structure. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Italy 2017)
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Open AccessArticle Access Control Mechanism for IoT Environments Based on Modelling Communication Procedures as Resources
Sensors 2018, 18(3), 917; https://doi.org/10.3390/s18030917
Received: 27 February 2018 / Revised: 15 March 2018 / Accepted: 18 March 2018 / Published: 20 March 2018
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Abstract
Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access
[...] Read more.
Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to obtain a unified access control scheme between heterogeneous devices (IoT devices, Internet-based services, etc.). To achieve this, we have analysed the most relevant communication protocols for these kinds of environments and then we have proposed a methodology which allows the modelling of communication actions as resources. Then, we can protect these resources using access control mechanisms. The validation of our proposal has been carried out by selecting a communication protocol based on message exchange, specifically Message Queuing Telemetry Transport (MQTT). As an access control scheme, we have selected User-Managed Access (UMA), an existing Open Authorization (OAuth) 2.0 profile originally developed for the protection of Internet services. We have performed tests focused on validating the proposed solution in terms of the correctness of the access control system. Finally, we have evaluated the energy consumption overhead when using our proposal. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle Measurement of Temperature and Relative Humidity with Polymer Optical Fiber Sensors Based on the Induced Stress-Optic Effect
Sensors 2018, 18(3), 916; https://doi.org/10.3390/s18030916
Received: 14 February 2018 / Revised: 9 March 2018 / Accepted: 14 March 2018 / Published: 20 March 2018
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Abstract
This paper presents a system capable of measuring temperature and relative humidity with polymer optical fiber (POF) sensors. The sensors are based on variations of the Young’s and shear moduli of the POF with variations in temperature and relative humidity. The system comprises
[...] Read more.
This paper presents a system capable of measuring temperature and relative humidity with polymer optical fiber (POF) sensors. The sensors are based on variations of the Young’s and shear moduli of the POF with variations in temperature and relative humidity. The system comprises two POFs, each with a predefined torsion stress that resulted in a variation in the fiber refractive index due to the stress-optic effect. Because there is a correlation between stress and material properties, the variation in temperature and humidity causes a variation in the fiber’s stress, which leads to variations in the fiber refractive index. Only two photodiodes comprise the sensor interrogation, resulting in a simple and low-cost system capable of measuring humidity in the range of 5–97% and temperature in the range of 21–46 °C. The root mean squared errors (RMSEs) between the proposed sensors and the reference were 1.12 °C and 1.36% for the measurements of temperature and relative humidity, respectively. In addition, fiber etching resulted in a sensor with a 2 s response time for a relative humidity variation of 10%, which is one of the lowest recorded response times for intrinsic POF humidity sensors. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Twin-Core Fiber-Based Mach Zehnder Interferometer for Simultaneous Measurement of Strain and Temperature
Sensors 2018, 18(3), 915; https://doi.org/10.3390/s18030915
Received: 9 February 2018 / Revised: 12 March 2018 / Accepted: 18 March 2018 / Published: 20 March 2018
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Abstract
In this paper we present an all-fiber interferometric sensor for the simultaneous measurement of strain and temperature. It is composed of a specially fabricated twin-core fiber spliced between two pieces of a single-mode fiber. Due to the refractive index difference between the two
[...] Read more.
In this paper we present an all-fiber interferometric sensor for the simultaneous measurement of strain and temperature. It is composed of a specially fabricated twin-core fiber spliced between two pieces of a single-mode fiber. Due to the refractive index difference between the two cores in a twin-core fiber, a differential interference pattern is produced at the sensor output. The phase response of the interferometer to strain and temperature is measured in the 850–1250 nm spectral range, showing zero sensitivity to strain at 1000 nm. Due to the significant difference in sensitivities to both parameters, our interferometer is suitable for two-parameter sensing. The simultaneous response of the interferometer to strain and temperature was studied using the two-wavelength interrogation method and a novel approach based on the spectral fitting of the differential phase response. As the latter technique uses all the gathered spectral information, it is more reliable and yields the results with better accuracy. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Assessing and Mapping of Road Surface Roughness based on GPS and Accelerometer Sensors on Bicycle-Mounted Smartphones
Sensors 2018, 18(3), 914; https://doi.org/10.3390/s18030914
Received: 7 February 2018 / Revised: 12 March 2018 / Accepted: 12 March 2018 / Published: 19 March 2018
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Abstract
The surface roughness of roads is an essential road characteristic. Due to the employed carrying platforms (which are often cars), existing measuring methods can only be used for motorable roads. Until now, there has been no effective method for measuring the surface roughness
[...] Read more.
The surface roughness of roads is an essential road characteristic. Due to the employed carrying platforms (which are often cars), existing measuring methods can only be used for motorable roads. Until now, there has been no effective method for measuring the surface roughness of un-motorable roads, such as pedestrian and bicycle lanes. This hinders many applications related to pedestrians, cyclists and wheelchair users. In recognizing these research gaps, this paper proposes a method for measuring the surface roughness of pedestrian and bicycle lanes based on Global Positioning System (GPS) and accelerometer sensors on bicycle-mounted smartphones. We focus on the International Roughness Index (IRI), as it is the most widely used index for measuring road surface roughness. Specifically, we analyzed a computing model of road surface roughness, derived its parameters with GPS and accelerometers on bicycle-mounted smartphones, and proposed an algorithm to recognize potholes/humps on roads. As a proof of concept, we implemented the proposed method in a mobile application. Three experiments were designed to evaluate the proposed method. The results of the experiments show that the IRI values measured by the proposed method were strongly and positively correlated with those measured by professional instruments. Meanwhile, the proposed algorithm was able to recognize the potholes/humps that the bicycle passed. The proposed method is useful for measuring the surface roughness of roads that are not accessible for professional instruments, such as pedestrian and cycle lanes. This work enables us to further study the feasibility of crowdsourcing road surface roughness with bicycle-mounted smartphones. Full article
(This article belongs to the Special Issue Crowd-Sensing and Remote Sensing Technologies for Smart Cities)
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