Sensors

13 pages, 4002 KiB

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

by Marcin Procek, Kinga Kepska and Agnieszka Stolarczyk

Sensors 2018, 18(3), 928; https://doi.org/10.3390/s18030928 - 20 Mar 2018

Cited by 18 | Viewed by 5169

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 NO_2, 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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24 pages, 2643 KiB

Open AccessArticle

Simultaneous Deployment and Tracking Multi-Robot Strategies with Connectivity Maintenance

by Javier Tardós, Rosario Aragues, Carlos Sagüés and Carlos Rubio

Sensors 2018, 18(3), 927; https://doi.org/10.3390/s18030927 - 20 Mar 2018

Cited by 11 | Viewed by 4684

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 [...] Read more.

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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14 pages, 4169 KiB

Open AccessArticle

Motor Planning Error: Toward Measuring Cognitive Frailty in Older Adults Using Wearables

by He Zhou, Hyoki Lee, Jessica Lee, Michael Schwenk and Bijan Najafi

Sensors 2018, 18(3), 926; https://doi.org/10.3390/s18030926 - 20 Mar 2018

Cited by 21 | Viewed by 7159

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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31 pages, 747 KiB

Open AccessFeature PaperArticle

Generic Sensor Failure Modeling for Cooperative Systems

by Georg Jäger, Sebastian Zug and António Casimiro

Sensors 2018, 18(3), 925; https://doi.org/10.3390/s18030925 - 20 Mar 2018

Cited by 12 | Viewed by 6130

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 [...] Read more.

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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15 pages, 4304 KiB

Open AccessArticle

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles

by Duona Zhang, Wenrui Ding, Baochang Zhang, Chunyu Xie, Hongguang Li, Chunhui Liu and Jungong Han

Sensors 2018, 18(3), 924; https://doi.org/10.3390/s18030924 - 20 Mar 2018

Cited by 96 | Viewed by 11675

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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21 pages, 5893 KiB

Open AccessArticle

An Energy-Efficient Algorithm for Wearable Electrocardiogram Signal Processing in Ubiquitous Healthcare Applications

by Ali Hassan Sodhro, Arun Kumar Sangaiah, Gul Hassan Sodhro, Sonia Lohano and Sandeep Pirbhulal

Sensors 2018, 18(3), 923; https://doi.org/10.3390/s18030923 - 20 Mar 2018

Cited by 72 | Viewed by 11495

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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17 pages, 9993 KiB

Open AccessArticle

A Low-Cost Tracking System for Running Race Applications Based on Bluetooth Low Energy Technology

by David Perez-Diaz-de-Cerio, Ángela Hernández-Solana, Antonio Valdovinos and Jose Luis Valenzuela

Sensors 2018, 18(3), 922; https://doi.org/10.3390/s18030922 - 20 Mar 2018

Cited by 8 | Viewed by 7975

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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9 pages, 2984 KiB

Open AccessArticle

Enhanced Moisture-Reactive Hydrophilic-PTFE-Based Flexible Humidity Sensor for Real-Time Monitoring

by Heekyeong Park, Sungho Lee, Seok Hwan Jeong, Ui Hyun Jung, Kidong Park, Min Goo Lee, Sunkook Kim and Joonhyung Lee

Sensors 2018, 18(3), 921; https://doi.org/10.3390/s18030921 - 20 Mar 2018

Cited by 31 | Viewed by 7423

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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17 pages, 5655 KiB

Open AccessArticle

Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor

by Ali Al-Naji and Javaan Chahl

Sensors 2018, 18(3), 920; https://doi.org/10.3390/s18030920 - 20 Mar 2018

Cited by 17 | Viewed by 6657

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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16 pages, 1563 KiB

Open AccessArticle

Measuring Gait Quality in Parkinson’s Disease through Real-Time Gait Phase Recognition

by Ilaria Mileti, Marco Germanotta, Enrica Di Sipio, Isabella Imbimbo, Alessandra Pacilli, Carmen Erra, Martina Petracca, Stefano Rossi, Zaccaria Del Prete, Anna Rita Bentivoglio, Luca Padua and Eduardo Palermo

Sensors 2018, 18(3), 919; https://doi.org/10.3390/s18030919 - 20 Mar 2018

Cited by 38 | Viewed by 6976

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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19 pages, 4109 KiB

Open AccessArticle

Arc-Induced Long Period Gratings from Standard to Polarization-Maintaining and Photonic Crystal Fibers

by Flavio Esposito, Rajeev Ranjan, Stefania Campopiano and Agostino Iadicicco

Sensors 2018, 18(3), 918; https://doi.org/10.3390/s18030918 - 20 Mar 2018

Cited by 49 | Viewed by 6785

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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21 pages, 665 KiB

Open AccessArticle

Access Control Mechanism for IoT Environments Based on Modelling Communication Procedures as Resources

by Luis Cruz-Piris, Diego Rivera, Ivan Marsa-Maestre, Enrique De la Hoz and Juan R. Velasco

Sensors 2018, 18(3), 917; https://doi.org/10.3390/s18030917 - 20 Mar 2018

Cited by 60 | Viewed by 9034

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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12 pages, 1723 KiB

Open AccessArticle

Measurement of Temperature and Relative Humidity with Polymer Optical Fiber Sensors Based on the Induced Stress-Optic Effect

by Arnaldo Leal-Junior, Anselmo Frizera-Neto, Carlos Marques and Maria José Pontes

Sensors 2018, 18(3), 916; https://doi.org/10.3390/s18030916 - 20 Mar 2018

Cited by 70 | Viewed by 9128

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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11 pages, 12027 KiB

Open AccessArticle

Twin-Core Fiber-Based Mach Zehnder Interferometer for Simultaneous Measurement of Strain and Temperature

by Dominik Kowal, Waclaw Urbanczyk and Pawel Mergo

Sensors 2018, 18(3), 915; https://doi.org/10.3390/s18030915 - 20 Mar 2018

Cited by 17 | Viewed by 5129

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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17 pages, 8895 KiB

Open AccessArticle

Assessing and Mapping of Road Surface Roughness based on GPS and Accelerometer Sensors on Bicycle-Mounted Smartphones

by Kaiyue Zang, Jie Shen, Haosheng Huang, Mi Wan and Jiafeng Shi

Sensors 2018, 18(3), 914; https://doi.org/10.3390/s18030914 - 19 Mar 2018

Cited by 114 | Viewed by 13109

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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11 pages, 4251 KiB

Open AccessArticle

On-Line Detection and Segmentation of Sports Motions Using a Wearable Sensor

by Woosuk Kim and Myunggyu Kim

Sensors 2018, 18(3), 913; https://doi.org/10.3390/s18030913 - 19 Mar 2018

Cited by 14 | Viewed by 5833

Abstract

In sports motion analysis, observation is a prerequisite for understanding the quality of motions. This paper introduces a novel approach to detect and segment sports motions using a wearable sensor for supporting systematic observation. The main goal is, for convenient analysis, to automatically [...] Read more.

In sports motion analysis, observation is a prerequisite for understanding the quality of motions. This paper introduces a novel approach to detect and segment sports motions using a wearable sensor for supporting systematic observation. The main goal is, for convenient analysis, to automatically provide motion data, which are temporally classified according to the phase definition. For explicit segmentation, a motion model is defined as a sequence of sub-motions with boundary states. A sequence classifier based on deep neural networks is designed to detect sports motions from continuous sensor inputs. The evaluation on two types of motions (soccer kicking and two-handed ball throwing) verifies that the proposed method is successful for the accurate detection and segmentation of sports motions. By developing a sports motion analysis system using the motion model and the sequence classifier, we show that the proposed method is useful for observation of sports motions by automatically providing relevant motion data for analysis. Full article

(This article belongs to the Special Issue Selected Papers from the Eighth International Conference on ICT Convergence (ICTC 2017))

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22 pages, 23990 KiB

Open AccessArticle

Penalized Maximum Likelihood Angular Super-Resolution Method for Scanning Radar Forward-Looking Imaging

by Ke Tan, Wenchao Li, Qian Zhang, Yulin Huang, Junjie Wu and Jianyu Yang

Sensors 2018, 18(3), 912; https://doi.org/10.3390/s18030912 - 19 Mar 2018

Cited by 11 | Viewed by 4807

Abstract

Deconvolution provides an efficient technology to implement angular super-resolution for scanning radar forward-looking imaging. However, deconvolution is an ill-posed problem, of which the solution is not only sensitive to noise, but also would be easily deteriorate by the noise amplification when excessive iterations [...] Read more.

Deconvolution provides an efficient technology to implement angular super-resolution for scanning radar forward-looking imaging. However, deconvolution is an ill-posed problem, of which the solution is not only sensitive to noise, but also would be easily deteriorate by the noise amplification when excessive iterations are conducted. In this paper, a penalized maximum likelihood angular super-resolution method is proposed to tackle these problems. Firstly, a new likelihood function is deduced by separately considering the noise in I and Q channels to enhance the accuracy of the noise modeling for radar imaging system. Afterwards, to conquer the noise amplification and maintain the resolving ability of the proposed method, a joint square-Laplace penalty is particularly formulated by making use of the outlier sensitivity property of square constraint as well as the sparse expression ability of Laplace distribution. Finally, in order to facilitate the engineering application of the proposed method, an accelerated iterative solution strategy is adopted to solve the obtained convex optimal problem. Experiments based on both synthetic data and real data demonstrate the effectiveness and superior performance of the proposed method. Full article

(This article belongs to the Section Remote Sensors)

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16 pages, 5076 KiB

Open AccessArticle

The Smallest Form Factor UWB Antenna with Quintuple Rejection Bands for IoT Applications Utilizing RSRR and RCSRR

by MuhibUr Rahman and Jung-Dong Park

Sensors 2018, 18(3), 911; https://doi.org/10.3390/s18030911 - 19 Mar 2018

Cited by 53 | Viewed by 7133

Abstract

In this paper, we present the smallest form factor microstrip-fed ultra-wideband antenna with quintuple rejection bands for use in wireless sensor networks, mobile handsets, and Internet of things (IoT). Five rejection bands have been achieved at the frequencies of 3.5, 4.5, 5.25, 5.7, [...] Read more.

In this paper, we present the smallest form factor microstrip-fed ultra-wideband antenna with quintuple rejection bands for use in wireless sensor networks, mobile handsets, and Internet of things (IoT). Five rejection bands have been achieved at the frequencies of 3.5, 4.5, 5.25, 5.7, and 8.2 GHz, inseminating four rectangular complementary split ring resonators (RCSRRs) on the radiating patch and placing two rectangular split-ring resonators (RSRR) near the feedline-patch junction of the conventional ultra-wideband (UWB) antenna. The design guidelines of the implemented notched bands are provided at the desired frequency bands and analyzed. The measured results demonstrate that the proposed antenna delivers a wide impedance bandwidth from 3 to 11 GHz with a nearly omnidirectional radiation pattern, high rejection in the multiple notched-bands, and good radiation efficiency over the entire frequency band except at the notched frequencies. Simulated and measured response match well specifically at the stop-bands. Full article

(This article belongs to the Section Remote Sensors)

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12 pages, 3181 KiB

Open AccessArticle

A Compact Microwave Microfluidic Sensor Using a Re-Entrant Cavity

by Hayder Hamzah, Ali Abduljabar, Jonathan Lees and Adrian Porch

Sensors 2018, 18(3), 910; https://doi.org/10.3390/s18030910 - 19 Mar 2018

Cited by 35 | Viewed by 5877

Abstract

A miniaturized 2.4 GHz re-entrant cavity has been designed, manufactured and tested as a sensor for microfluidic compositional analysis. It has been fully evaluated experimentally with water and common solvents, namely methanol, ethanol, and chloroform, with excellent agreement with the expected behaviour predicted [...] Read more.

A miniaturized 2.4 GHz re-entrant cavity has been designed, manufactured and tested as a sensor for microfluidic compositional analysis. It has been fully evaluated experimentally with water and common solvents, namely methanol, ethanol, and chloroform, with excellent agreement with the expected behaviour predicted by the Debye model. The sensor’s performance has also been assessed for analysis of segmented flow using water and oil. The samples’ interaction with the electric field in the gap region has been maximized by aligning the sample tube parallel to the electric field in this region, and the small width of the gap (typically 1 mm) result in a highly localised complex permittivity measurement. The re-entrant cavity has simple mechanical geometry, small size, high quality factor, and due to the high concentration of electric field in the gap region, a very small mode volume. These factors combine to result in a highly sensitive, compact sensor for both pure liquids and liquid mixtures in capillary or microfluidic environments. Full article

(This article belongs to the Special Issue Microfluidic Sensors)

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23 pages, 7438 KiB

Open AccessArticle

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton

by Likun Wang, Zhijiang Du, Wei Dong, Yi Shen and Guangyu Zhao

Sensors 2018, 18(3), 909; https://doi.org/10.3390/s18030909 - 19 Mar 2018

Cited by 13 | Viewed by 5600

Abstract

To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. [...] Read more.

To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human–robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility. Full article

(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)

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16 pages, 7282 KiB

Open AccessArticle

Multi-Residential Activity Labelling in Smart Homes with Wearable Tags Using BLE Technology

by Ghassem Mokhtari, Amjad Anvari-Moghaddam, Qing Zhang and Mohanraj Karunanithi

Sensors 2018, 18(3), 908; https://doi.org/10.3390/s18030908 - 19 Mar 2018

Cited by 26 | Viewed by 5256

Abstract

Smart home platforms show promising outcomes to provide a better quality of life for residents in their homes. One of the main challenges that exists with these platforms in multi-residential houses is activity labeling. As most of the activity sensors do not provide [...] Read more.

Smart home platforms show promising outcomes to provide a better quality of life for residents in their homes. One of the main challenges that exists with these platforms in multi-residential houses is activity labeling. As most of the activity sensors do not provide any information regarding the identity of the person who triggers them, it is difficult to label the sensor events in multi-residential smart homes. To deal with this challenge, individual localization in different areas can be a promising solution. The localization information can be used to automatically label the activity sensor data to individuals. Bluetooth low energy (BLE) is a promising technology for this application due to how easy it is to implement and its low energy footprint. In this approach, individuals wear a tag that broadcasts its unique identity (ID) in certain time intervals, while fixed scanners listen to the broadcasting packet to localize the tag and the individual. However, the localization accuracy of this method depends greatly on different settings of broadcasting signal strength, and the time interval of BLE tags. To achieve the best localization accuracy, this paper studies the impacts of different advertising time intervals and power levels, and proposes an efficient and applicable algorithm to select optimal value settings of BLE sensors. Moreover, it proposes an automatic activity labeling method, through integrating BLE localization information and ambient sensor data. The applicability and effectiveness of the proposed structure is also demonstrated in a real multi-resident smart home scenario. Full article

(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications 2018)

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20 pages, 3326 KiB

Open AccessArticle

How to Improve Fault Tolerance in Disaster Predictions: A Case Study about Flash Floods Using IoT, ML and Real Data

by Gustavo Furquim, Geraldo P. R. Filho, Roozbeh Jalali, Gustavo Pessin, Richard W. Pazzi and Jó Ueyama

Sensors 2018, 18(3), 907; https://doi.org/10.3390/s18030907 - 19 Mar 2018

Cited by 42 | Viewed by 8089

Abstract

The rise in the number and intensity of natural disasters is a serious problem that affects the whole world. The consequences of these disasters are significantly worse when they occur in urban districts because of the casualties and extent of the damage to [...] Read more.

The rise in the number and intensity of natural disasters is a serious problem that affects the whole world. The consequences of these disasters are significantly worse when they occur in urban districts because of the casualties and extent of the damage to goods and property that is caused. Until now feasible methods of dealing with this have included the use of wireless sensor networks (WSNs) for data collection and machine-learning (ML) techniques for forecasting natural disasters. However, there have recently been some promising new innovations in technology which have supplemented the task of monitoring the environment and carrying out the forecasting. One of these schemes involves adopting IP-based (Internet Protocol) sensor networks, by using emerging patterns for IoT. In light of this, in this study, an attempt has been made to set out and describe the results achieved by SENDI (System for dEtecting and forecasting Natural Disasters based on IoT). SENDI is a fault-tolerant system based on IoT, ML and WSN for the detection and forecasting of natural disasters and the issuing of alerts. The system was modeled by means of ns-3 and data collected by a real-world WSN installed in the town of São Carlos - Brazil, which carries out the data collection from rivers in the region. The fault-tolerance is embedded in the system by anticipating the risk of communication breakdowns and the destruction of the nodes during disasters. It operates by adding intelligence to the nodes to carry out the data distribution and forecasting, even in extreme situations. A case study is also included for flash flood forecasting and this makes use of the ns-3 SENDI model and data collected by WSN. Full article

(This article belongs to the Special Issue Security in IoT Enabled Sensors)

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21 pages, 7214 KiB

Open AccessArticle

Compensation of Horizontal Gravity Disturbances for High Precision Inertial Navigation

by Junbo Tie, Juliang Cao, Meiping Wu, Junxiang Lian, Shaokun Cai and Lin Wang

Sensors 2018, 18(3), 906; https://doi.org/10.3390/s18030906 - 18 Mar 2018

Cited by 14 | Viewed by 4354

Abstract

Horizontal gravity disturbances are an important factor that affects the accuracy of inertial navigation systems in long-duration ship navigation. In this paper, from the perspective of the coordinate system and vector calculation, the effects of horizontal gravity disturbance on the initial alignment and [...] Read more.

Horizontal gravity disturbances are an important factor that affects the accuracy of inertial navigation systems in long-duration ship navigation. In this paper, from the perspective of the coordinate system and vector calculation, the effects of horizontal gravity disturbance on the initial alignment and navigation calculation are simultaneously analyzed. Horizontal gravity disturbances cause the navigation coordinate frame built in initial alignment to not be consistent with the navigation coordinate frame in which the navigation calculation is implemented. The mismatching of coordinate frame violates the vector calculation law, which will have an adverse effect on the precision of the inertial navigation system. To address this issue, two compensation methods suitable for two different navigation coordinate frames are proposed, one of the methods implements the compensation in velocity calculation, and the other does the compensation in attitude calculation. Finally, simulations and ship navigation experiments confirm the effectiveness of the proposed methods. Full article

(This article belongs to the Section Physical Sensors)

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19 pages, 1324 KiB

Open AccessArticle

Algorithms for Designing Unimodular Sequences with High Doppler Tolerance for Simultaneous Fully Polarimetric Radar

by Fulai Wang, Chen Pang, Yongzhen Li and Xuesong Wang

Sensors 2018, 18(3), 905; https://doi.org/10.3390/s18030905 - 18 Mar 2018

Cited by 13 | Viewed by 4126

Abstract

Simultaneous fully polarimetric radar uses orthogonal polarization channels to transmit a pair of signals, both of which must have good auto- and cross-correlation characteristics. In this paper, the design of sequences with good correlation properties and Doppler tolerance is investigated. New cyclic algorithms, [...] Read more.

Simultaneous fully polarimetric radar uses orthogonal polarization channels to transmit a pair of signals, both of which must have good auto- and cross-correlation characteristics. In this paper, the design of sequences with good correlation properties and Doppler tolerance is investigated. New cyclic algorithms, namely, Cyclic Algorithm-Gradient I (CAGI) and Cyclic Algorithm-Gradient II (CAGII) are proposed to solve the optimization problem. Meanwhile, the sequences designed in this paper have ultra-low auto- and cross-correlation side-lobes in a specified lag interval. Numerical experiments are conducted to demonstrate and validate the superiority of the proposed cyclic algorithms, especially for the measurement of moving targets. Full article

(This article belongs to the Section Remote Sensors)

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16 pages, 7598 KiB

Open AccessArticle

Urban Area Detection in Very High Resolution Remote Sensing Images Using Deep Convolutional Neural Networks

by Tian Tian, Chang Li, Jinkang Xu and Jiayi Ma

Sensors 2018, 18(3), 904; https://doi.org/10.3390/s18030904 - 18 Mar 2018

Cited by 34 | Viewed by 5626

Abstract

Detecting urban areas from very high resolution (VHR) remote sensing images plays an important role in the field of Earth observation. The recently-developed deep convolutional neural networks (DCNNs), which can extract rich features from training data automatically, have achieved outstanding performance on many [...] Read more.

Detecting urban areas from very high resolution (VHR) remote sensing images plays an important role in the field of Earth observation. The recently-developed deep convolutional neural networks (DCNNs), which can extract rich features from training data automatically, have achieved outstanding performance on many image classification databases. Motivated by this fact, we propose a new urban area detection method based on DCNNs in this paper. The proposed method mainly includes three steps: (i) a visual dictionary is obtained based on the deep features extracted by pre-trained DCNNs; (ii) urban words are learned from labeled images; (iii) the urban regions are detected in a new image based on the nearest dictionary word criterion. The qualitative and quantitative experiments on different datasets demonstrate that the proposed method can obtain a remarkable overall accuracy (OA) and kappa coefficient. Moreover, it can also strike a good balance between the true positive rate (TPR) and false positive rate (FPR). Full article

(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)

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27 pages, 9359 KiB

Open AccessTutorial

Micro/Nanofibre Optical Sensors: Challenges and Prospects

by Limin Tong

Sensors 2018, 18(3), 903; https://doi.org/10.3390/s18030903 - 18 Mar 2018

Cited by 112 | Viewed by 12853

Abstract

Micro/nanofibres (MNFs) are optical fibres with diameters close to or below the vacuum wavelength of visible or near-infrared light. Due to its wavelength- or sub-wavelength scale diameter and relatively large index contrast between the core and cladding, an MNF can offer engineerable waveguiding [...] Read more.

Micro/nanofibres (MNFs) are optical fibres with diameters close to or below the vacuum wavelength of visible or near-infrared light. Due to its wavelength- or sub-wavelength scale diameter and relatively large index contrast between the core and cladding, an MNF can offer engineerable waveguiding properties including optical confinement, fractional evanescent fields and surface intensity, which is very attractive to optical sensing on the micro and nanometer scale. In particular, the waveguided low-loss tightly confined large fractional evanescent fields, enabled by atomic level surface roughness and extraordinary geometric and material uniformity in a glass MNF, is one of its most prominent merits in realizing optical sensing with high sensitivity and great versatility. Meanwhile, the mesoporous matrix and small diameter of a polymer MNF, make it an excellent host fibre for functional materials for fast-response optical sensing. In this tutorial, we first introduce the basics of MNF optics and MNF optical sensors, and review the progress and current status of this field. Then, we discuss challenges and prospects of MNF sensors to some extent, with several clues for future studies. Finally, we conclude with a brief outlook for MNF optical sensors. Full article

(This article belongs to the Special Issue Optical Sensors based on Micro/Nanofibres)

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19 pages, 9927 KiB

Open AccessArticle

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing

by Jun Li, Qiu-hua Lin, Chun-yu Kang, Kai Wang and Xiu-Ting Yang

Sensors 2018, 18(3), 902; https://doi.org/10.3390/s18030902 - 18 Mar 2018

Cited by 36 | Viewed by 5893

Abstract

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is [...] Read more.

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets. Full article

(This article belongs to the Section Sensor Networks)

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26 pages, 3259 KiB

Open AccessReview

Detection of Antibiotics and Evaluation of Antibacterial Activity with Screen-Printed Electrodes

by Florentina-Daniela Munteanu, Ana Maria Titoiu, Jean-Louis Marty and Alina Vasilescu

Sensors 2018, 18(3), 901; https://doi.org/10.3390/s18030901 - 18 Mar 2018

Cited by 69 | Viewed by 11878

Abstract

This review provides a brief overview of the fabrication and properties of screen-printed electrodes and details the different opportunities to apply them for the detection of antibiotics, detection of bacteria and antibiotic susceptibility. Among the alternative approaches to costly chromatographic or ELISA methods [...] Read more.

This review provides a brief overview of the fabrication and properties of screen-printed electrodes and details the different opportunities to apply them for the detection of antibiotics, detection of bacteria and antibiotic susceptibility. Among the alternative approaches to costly chromatographic or ELISA methods for antibiotics detection and to lengthy culture methods for bacteria detection, electrochemical biosensors based on screen-printed electrodes present some distinctive advantages. Chemical and (bio)sensors for the detection of antibiotics and assays coupling detection with screen-printed electrodes with immunomagnetic separation are described. With regards to detection of bacteria, the emphasis is placed on applications targeting viable bacterial cells. While the electrochemical sensors and biosensors face many challenges before replacing standard analysis methods, the potential of screen-printed electrodes is increasingly exploited and more applications are anticipated to advance towards commercial analytical tools. Full article

(This article belongs to the Special Issue Screen-Printed Electrodes)

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26 pages, 8583 KiB

Open AccessArticle

Dielectric Spectroscopy and Optical Density Measurement for the Online Monitoring and Control of Recombinant Protein Production in Stably Transformed Drosophila melanogaster S2 Cells

by Jan Zitzmann, Tobias Weidner, Gerrit Eichner, Denise Salzig and Peter Czermak

Sensors 2018, 18(3), 900; https://doi.org/10.3390/s18030900 - 18 Mar 2018

Cited by 26 | Viewed by 9574

Abstract

The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different [...] Read more.

The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different measurement principles are exploited. We used this combination of techniques to monitor and control the growth and protein production of stably transformed Drosophila melanogaster S2 cells expressing antimicrobial proteins. The in situ monitoring system was suitable in batch, fed-batch and perfusion modes, and was particularly useful for the online determination of cell concentration, specific growth rate (µ) and cell viability. These data were used to pinpoint the optimal timing of the key transitional events (induction and harvest) during batch and fed-batch cultivation, achieving a total protein yield of ~25 mg at the 1-L scale. During cultivation in perfusion mode, the OD₈₈₀ signal was used to control the bleed line in order to maintain a constant cell concentration of 5 × 10⁷ cells/mL, thus establishing a turbidostat/permittistat culture. With this setup, a five-fold increase in productivity was achieved and 130 mg of protein was recovered after 2 days of induced perfusion. Our results demonstrate that both sensors are suitable for advanced monitoring and integration into online control strategies. Full article

(This article belongs to the Special Issue Sensors for Cell Analysis)

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25 pages, 3084 KiB

Open AccessArticle

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks

by Shaobo Wu, Wusheng Chou, Jianwei Niu and Mohsen Guizani

Sensors 2018, 18(3), 899; https://doi.org/10.3390/s18030899 - 18 Mar 2018

Cited by 18 | Viewed by 5681

Abstract

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, [...] Read more.

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio. Full article

(This article belongs to the Collection Smart Industrial Wireless Sensor Networks)

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