Research

1792 KiB

Open AccessArticle

A Highly Sensitive Nonenzymatic Glucose Biosensor Based on the Regulatory Effect of Glucose on Electrochemical Behaviors of Colloidal Silver Nanoparticles on MoS₂

by Kash Anderson, Benjamin Poulter, John Dudgeon, Shu-En Li and Xiang Ma

Sensors 2017, 17(8), 1807; https://doi.org/10.3390/s17081807 - 05 Aug 2017

Cited by 47 | Viewed by 7281

Abstract

A novel and highly sensitive nonenzymatic glucose biosensor was developed by nucleating colloidal silver nanoparticles (AgNPs) on MoS₂. The facile fabrication method, high reproducibility (97.5%) and stability indicates a promising capability for large-scale manufacturing. Additionally, the excellent sensitivity (9044.6 µA•mM⁻¹ [...] Read more.

A novel and highly sensitive nonenzymatic glucose biosensor was developed by nucleating colloidal silver nanoparticles (AgNPs) on MoS₂. The facile fabrication method, high reproducibility (97.5%) and stability indicates a promising capability for large-scale manufacturing. Additionally, the excellent sensitivity (9044.6 µA•mM⁻¹•cm⁻²), low detection limit (0.03 μM), appropriate linear range of 0.1–1000 μM, and high selectivity suggests that this biosensor has a great potential to be applied for noninvasive glucose detection in human body fluids, such as sweat and saliva. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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1983 KiB

Open AccessArticle

A Multiscale Approach to the Smart Deployment of Micro-Sensors over Lightweight Structures

by Giovanni Capellari, Francesco Caimmi, Matteo Bruggi and Stefano Mariani

Sensors 2017, 17(7), 1632; https://doi.org/10.3390/s17071632 - 15 Jul 2017

Cited by 3 | Viewed by 3677

Abstract

A topology optimization approach has been recently proposed to maximize the sensitivity to damage of measurements, collected through a network of sensors to be deployed over thin plates for structural health monitoring purposes. Within such a frame, damage is meant as a change [...] Read more.

A topology optimization approach has been recently proposed to maximize the sensitivity to damage of measurements, collected through a network of sensors to be deployed over thin plates for structural health monitoring purposes. Within such a frame, damage is meant as a change in the structural health characterized by a reduction of relevant stiffness and load-carrying properties. The sensitivity to a damage of unknown amplitude and location is computed by comparing the response to the external actions of the healthy structure and of a set of auxiliary damaged structures, each one featuring reduced mechanical properties in a small region only. The topology optimization scheme has been devised to properly account for the information coming from all of the sensors to be placed on the structure and for damage depending on its location. In this work, we extend the approach within a multiscale frame to account for three different length scales: a macroscopic one, linked to the dimensions of the whole structure to be monitored; a mesoscopic one, linked to the characteristic size of the damaged region; a microscopic one, linked to the size of inertial microelectromechanical systems (MEMS) to be used within a marginally-invasive health monitoring system. Results are provided for a square plate and for a section of fuselage with stiffeners, to show how the micro-sensors have to be deployed to maximize the capability to detect a damage, to assess the sensitivity of the results to the measurement noise and to also discuss the speedup in designing the network topology against a standard single-scale approach. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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15793 KiB

Open AccessArticle

Challenges in Wireless System Integration as Enablers for Indoor Context Aware Environments

by Peio López-Iturri, Erik Aguirre, Leyre Azpilicueta, José Javier Astrain, Jesús Villandangos and Francisco Falcone

Sensors 2017, 17(7), 1616; https://doi.org/10.3390/s17071616 - 12 Jul 2017

Cited by 8 | Viewed by 4110

Abstract

The advent of fully interactive environments within Smart Cities and Smart Regions requires the use of multiple wireless systems. In the case of user-device interaction, which finds multiple applications such as Ambient Assisted Living, Intelligent Transportation Systems or Smart Grids, among others, large [...] Read more.

The advent of fully interactive environments within Smart Cities and Smart Regions requires the use of multiple wireless systems. In the case of user-device interaction, which finds multiple applications such as Ambient Assisted Living, Intelligent Transportation Systems or Smart Grids, among others, large amount of transceivers are employed in order to achieve anytime, anyplace and any device connectivity. The resulting combination of heterogeneous wireless network exhibits fundamental limitations derived from Coverage/Capacity relations, as a function of required Quality of Service parameters, required bit rate, energy restrictions and adaptive modulation and coding schemes. In this context, inherent transceiver density poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. In this work, a deterministic based analysis applied to variable density wireless sensor network operation within complex indoor scenarios is presented, as a function of topological node distribution. The extensive analysis derives interference characterizations, both for conventional transceivers as well as wearables, which provide relevant information in terms of individual node configuration as well as complete network layout. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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7748 KiB

Open AccessArticle

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

by Abhijeet Ravankar, Ankit A. Ravankar, Yukinori Kobayashi and Takanori Emaru

Sensors 2017, 17(7), 1581; https://doi.org/10.3390/s17071581 - 05 Jul 2017

Cited by 34 | Viewed by 5533

Abstract

Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for [...] Read more.

Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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10223 KiB

Open AccessArticle

Instrumented Compliant Wrist with Proximity and Contact Sensing for Close Robot Interaction Control

by Pascal Laferrière and Pierre Payeur

Sensors 2017, 17(6), 1384; https://doi.org/10.3390/s17061384 - 14 Jun 2017

Viewed by 4684

Abstract

Compliance has been exploited in various forms in robotic systems to allow rigid mechanisms to come into contact with fragile objects, or with complex shapes that cannot be accurately modeled. Force feedback control has been the classical approach for providing compliance in robotic [...] Read more.

Compliance has been exploited in various forms in robotic systems to allow rigid mechanisms to come into contact with fragile objects, or with complex shapes that cannot be accurately modeled. Force feedback control has been the classical approach for providing compliance in robotic systems. However, by integrating other forms of instrumentation with compliance into a single device, it is possible to extend close monitoring of nearby objects before and after contact occurs. As a result, safer and smoother robot control can be achieved both while approaching and while touching surfaces. This paper presents the design and extensive experimental evaluation of a versatile, lightweight, and low-cost instrumented compliant wrist mechanism which can be mounted on any rigid robotic manipulator in order to introduce a layer of compliance while providing the controller with extra sensing signals during close interaction with an object’s surface. Arrays of embedded range sensors provide real-time measurements on the position and orientation of surfaces, either located in proximity or in contact with the robot’s end-effector, which permits close guidance of its operation. Calibration procedures are formulated to overcome inter-sensor variability and achieve the highest available resolution. A versatile solution is created by embedding all signal processing, while wireless transmission connects the device to any industrial robot’s controller to support path control. Experimental work demonstrates the device’s physical compliance as well as the stability and accuracy of the device outputs. Primary applications of the proposed instrumented compliant wrist include smooth surface following in manufacturing, inspection, and safe human-robot interaction. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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4384 KiB

Open AccessArticle

An FPGA-Based WASN for Remote Real-Time Monitoring of Endangered Species: A Case Study on the Birdsong Recognition of Botaurus stellaris

by Marcos Hervás, Rosa Ma Alsina-Pagès, Francesc Alías and Martí Salvador

Sensors 2017, 17(6), 1331; https://doi.org/10.3390/s17061331 - 08 Jun 2017

Cited by 12 | Viewed by 5999

Abstract

Fast environmental variations due to climate change can cause mass decline or even extinctions of species, having a dramatic impact on the future of biodiversity. During the last decade, different approaches have been proposed to track and monitor endangered species, generally based on [...] Read more.

Fast environmental variations due to climate change can cause mass decline or even extinctions of species, having a dramatic impact on the future of biodiversity. During the last decade, different approaches have been proposed to track and monitor endangered species, generally based on costly semi-automatic systems that require human supervision adding limitations in coverage and time. However, the recent emergence of Wireless Acoustic Sensor Networks (WASN) has allowed non-intrusive remote monitoring of endangered species in real time through the automatic identification of the sound they emit. In this work, an FPGA-based WASN centralized architecture is proposed and validated on a simulated operation environment. The feasibility of the architecture is evaluated in a case study designed to detect the threatened Botaurus stellaris among other 19 cohabiting birds species in The Parc Natural dels Aiguamolls de l’Empord Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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5978 KiB

Open AccessArticle

Development and Testing of a Dual Accelerometer Vector Sensor for AUV Acoustic Surveys

by Agni Mantouka, Paulo Felisberto, Paulo Santos, Friedrich Zabel, Mário Saleiro, Sérgio M. Jesus and Luís Sebastião

Sensors 2017, 17(6), 1328; https://doi.org/10.3390/s17061328 - 08 Jun 2017

Cited by 15 | Viewed by 5212

Abstract

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of the WiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used [...] Read more.

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of the WiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS has the potential to contribute to this aim in various ways, for example, owing to its spatial filtering capability, it may reduce the amount of post processing by discriminating the bottom from the surface reflections. Additionally, its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The present paper is focused on results related to acoustic wave azimuth estimation as an example of its spatial filtering capabilities. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. Sensitivity and directionality of these three sensors were measured in a tank, whilst the direction estimation capabilities of the accelerometers paired with the hydrophone, forming a vector sensor, were evaluated on a Medusa Class AUV, which was sailing around a deployed sound source. Results of these measurements are presented in this paper. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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7313 KiB

Open AccessArticle

Spatial Characterization of Radio Propagation Channel in Urban Vehicle-to-Infrastructure Environments to Support WSNs Deployment

by Fausto Granda, Leyre Azpilicueta, Cesar Vargas-Rosales, Peio Lopez-Iturri, Erik Aguirre, Jose Javier Astrain, Jesus Villandangos and Francisco Falcone

Sensors 2017, 17(6), 1313; https://doi.org/10.3390/s17061313 - 07 Jun 2017

Cited by 21 | Viewed by 4526

Abstract

Vehicular ad hoc Networks (VANETs) enable vehicles to communicate with each other as well as with roadside units (RSUs). Although there is a significant research effort in radio channel modeling focused on vehicle-to-vehicle (V2V), not much work has been done for vehicle-to-infrastructure (V2I) [...] Read more.

Vehicular ad hoc Networks (VANETs) enable vehicles to communicate with each other as well as with roadside units (RSUs). Although there is a significant research effort in radio channel modeling focused on vehicle-to-vehicle (V2V), not much work has been done for vehicle-to-infrastructure (V2I) using 3D ray-tracing tools. This work evaluates some important parameters of a V2I wireless channel link such as large-scale path loss and multipath metrics in a typical urban scenario using a deterministic simulation model based on an in-house 3D Ray-Launching (3D-RL) algorithm at 5.9 GHz. Results show the high impact that the spatial distance; link frequency; placement of RSUs; and factors such as roundabout, geometry and relative position of the obstacles have in V2I propagation channel. A detailed spatial path loss characterization of the V2I channel along the streets and avenues is presented. The 3D-RL results show high accuracy when compared with measurements, and represent more reliably the propagation phenomena when compared with analytical path loss models. Performance metrics for a real test scenario implemented with a VANET wireless sensor network implemented ad-hoc are also described. These results constitute a starting point in the design phase of Wireless Sensor Networks (WSNs) radio-planning in the urban V2I deployment in terms of coverage. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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1890 KiB

Open AccessArticle

Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework

by Juan Carlos Davila, Ana-Maria Cretu and Marek Zaremba

Sensors 2017, 17(6), 1287; https://doi.org/10.3390/s17061287 - 07 Jun 2017

Cited by 28 | Viewed by 7292

Abstract

The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, [...] Read more.

The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, data losses, and noise, among other experimental constraints, deteriorate data quality and model accuracy. To tackle these issues, this paper presents a data-driven iterative learning framework to classify human locomotion activities such as walk, stand, lie, and sit, extracted from the Opportunity dataset. Data acquired by twelve 3-axial acceleration sensors and seven inertial measurement units are initially de-noised using a two-stage consecutive filtering approach combining a band-pass Finite Impulse Response (FIR) and a wavelet filter. A series of statistical parameters are extracted from the kinematical features, including the principal components and singular value decomposition of roll, pitch, yaw and the norm of the axial components. The novel interactive learning procedure is then applied in order to minimize the number of samples required to classify human locomotion activities. Only those samples that are most distant from the centroids of data clusters, according to a measure presented in the paper, are selected as candidates for the training dataset. The newly built dataset is then used to train an SVM multi-class classifier. The latter will produce the lowest prediction error. The proposed learning framework ensures a high level of robustness to variations in the quality of input data, while only using a much lower number of training samples and therefore a much shorter training time, which is an important consideration given the large size of the dataset. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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5191 KiB

Open AccessArticle

Amorphous SiC/c-ZnO-Based Quasi-Lamb Mode Sensor for Liquid Environments

by Cinzia Caliendo, Muhammad Hamidullah and Farouk Laidoudi

Sensors 2017, 17(6), 1209; https://doi.org/10.3390/s17061209 - 25 May 2017

Cited by 7 | Viewed by 4215

Abstract

The propagation of the quasi-Lamb modes along a-SiC/ZnO thin composite plates was modeled and analysed with the aim to design a sensor able to detect the changes in parameters of a liquid environment, such as added mass and viscosity changes. The modes propagation [...] Read more.

The propagation of the quasi-Lamb modes along a-SiC/ZnO thin composite plates was modeled and analysed with the aim to design a sensor able to detect the changes in parameters of a liquid environment, such as added mass and viscosity changes. The modes propagation was modeled by numerically solving the system of coupled electro-mechanical field equations in three media. The mode shape, the power flow, the phase velocity, and the electroacoustic coupling efficiency (K²) of the modes were calculated, specifically addressing the design of enhanced-coupling, microwave frequency sensors for applications in probing the solid/liquid interface. Three modes were identified that have predominant longitudinal polarization, high phase velocity, and quite good K²: the fundamental quasi symmetric mode (qS₀) and two higher order quasi-longitudinal modes (qL₁ and qL₂) with a dominantly longitudinal displacement component in one plate side. The velocity and attenuation of these modes were calculated for different liquid viscosities and added mass, and the gravimetric and viscosity sensitivities of both the phase velocity and attenuation were theoretically calculated. The present study highlights the feasibility of the a-SiC/ZnO acoustic waveguides for the development of high-frequency, integrated-circuit compatible electroacoustic devices suitable for working in a liquid environment. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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6117 KiB

Open AccessArticle

Multimodal Bio-Inspired Tactile Sensing Module for Surface Characterization

by Thiago Eustaquio Alves de Oliveira, Ana-Maria Cretu and Emil M. Petriu

Sensors 2017, 17(6), 1187; https://doi.org/10.3390/s17061187 - 23 May 2017

Cited by 22 | Viewed by 6709

Abstract

Robots are expected to recognize the properties of objects in order to handle them safely and efficiently in a variety of applications, such as health and elder care, manufacturing, or high-risk environments. This paper explores the issue of surface characterization by monitoring the [...] Read more.

Robots are expected to recognize the properties of objects in order to handle them safely and efficiently in a variety of applications, such as health and elder care, manufacturing, or high-risk environments. This paper explores the issue of surface characterization by monitoring the signals acquired by a novel bio-inspired tactile probe in contact with ridged surfaces. The tactile module comprises a nine Degree of Freedom Microelectromechanical Magnetic, Angular Rate, and Gravity system (9-DOF MEMS MARG) and a deep MEMS pressure sensor embedded in a compliant structure that mimics the function and the organization of mechanoreceptors in human skin as well as the hardness of the human skin. When the modules tip slides over a surface, the MARG unit vibrates and the deep pressure sensor captures the overall normal force exerted. The module is evaluated in two experiments. The first experiment compares the frequency content of the data collected in two setups: one when the module is mounted over a linear motion carriage that slides four grating patterns at constant velocities; the second when the module is carried by a robotic finger in contact with the same grating patterns while performing a sliding motion, similar to the exploratory motion employed by humans to detect object roughness. As expected, in the linear setup, the magnitude spectrum of the sensors’ output shows that the module can detect the applied stimuli with frequencies ranging from 3.66 Hz to 11.54 Hz with an overall maximum error of ±0.1 Hz. The second experiment shows how localized features extracted from the data collected by the robotic finger setup over seven synthetic shapes can be used to classify them. The classification method consists on applying multiscale principal components analysis prior to the classification with a multilayer neural network. Achieved accuracies from 85.1% to 98.9% for the various sensor types demonstrate the usefulness of traditional MEMS as tactile sensors embedded into flexible substrates. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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4241 KiB

Open AccessArticle

Acquisition and Neural Network Prediction of 3D Deformable Object Shape Using a Kinect and a Force-Torque Sensor

by Bilal Tawbe and Ana-Maria Cretu

Sensors 2017, 17(5), 1083; https://doi.org/10.3390/s17051083 - 11 May 2017

Cited by 10 | Viewed by 5013

Abstract

The realistic representation of deformations is still an active area of research, especially for deformable objects whose behavior cannot be simply described in terms of elasticity parameters. This paper proposes a data-driven neural-network-based approach for capturing implicitly and predicting the deformations of an [...] Read more.

The realistic representation of deformations is still an active area of research, especially for deformable objects whose behavior cannot be simply described in terms of elasticity parameters. This paper proposes a data-driven neural-network-based approach for capturing implicitly and predicting the deformations of an object subject to external forces. Visual data, in the form of 3D point clouds gathered by a Kinect sensor, is collected over an object while forces are exerted by means of the probing tip of a force-torque sensor. A novel approach based on neural gas fitting is proposed to describe the particularities of a deformation over the selectively simplified 3D surface of the object, without requiring knowledge of the object material. An alignment procedure, a distance-based clustering, and inspiration from stratified sampling support this process. The resulting representation is denser in the region of the deformation (an average of 96.6% perceptual similarity with the collected data in the deformed area), while still preserving the object’s overall shape (86% similarity over the entire surface) and only using on average of 40% of the number of vertices in the mesh. A series of feedforward neural networks is then trained to predict the mapping between the force parameters characterizing the interaction with the object and the change in the object shape, as captured by the fitted neural gas nodes. This series of networks allows for the prediction of the deformation of an object when subject to unknown interactions. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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14393 KiB

Open AccessArticle

Design and Development of a Nearable Wireless System to Control Indoor Air Quality and Indoor Lighting Quality

by Francesco Salamone, Lorenzo Belussi, Ludovico Danza, Theodore Galanos, Matteo Ghellere and Italo Meroni

Sensors 2017, 17(5), 1021; https://doi.org/10.3390/s17051021 - 04 May 2017

Cited by 73 | Viewed by 11414

Abstract

The article describes the results of the project “open source smart lamp” aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following [...] Read more.

The article describes the results of the project “open source smart lamp” aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following a do-it-yourself (DIY) approach using a microcontroller, an integrated temperature and relative humidity sensor, and techniques of additive manufacturing, allows the adjustment of the indoor thermal comfort quality (ICQ), by interacting directly with the air conditioner. As is well known, the IEQ is a holistic concept including indoor air quality (IAQ), indoor lighting quality (ILQ) and acoustic comfort, besides thermal comfort. The upgrade of the smart lamp bridges the gap of the first version of the device providing the possibility of interaction with the air exchange unit and lighting system in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in a real office equipped with mechanical ventilation and an air conditioning system. This office was occupied by four workers. The experiment is compared with a baseline scenario and the results show how the application of the nearable device effectively optimizes both IAQ and ILQ. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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8582 KiB

Open AccessArticle

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

by Antonio Artuñedo, Raúl M. Del Toro and Rodolfo E. Haber

Sensors 2017, 17(5), 953; https://doi.org/10.3390/s17050953 - 26 Apr 2017

Cited by 15 | Viewed by 7350

Abstract

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through [...] Read more.

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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3124 KiB

Open AccessArticle

Fructose and Pectin Detection in Fruit-Based Food Products by Surface-Enhanced Raman Spectroscopy

by Carlo Camerlingo, Marianna Portaccio, Rosarita Tatè, Maria Lepore and Ines Delfino

Sensors 2017, 17(4), 839; https://doi.org/10.3390/s17040839 - 11 Apr 2017

Cited by 22 | Viewed by 6473

Abstract

Surface-Enhanced Raman Spectroscopy (SERS) enables the investigation of samples with weak specific Raman signals, such as opaque samples, including fruit juices and pulp. In this paper, biological apple juices and apple/pear pulp have been studied in order to evidence the presence of fructose [...] Read more.

Surface-Enhanced Raman Spectroscopy (SERS) enables the investigation of samples with weak specific Raman signals, such as opaque samples, including fruit juices and pulp. In this paper, biological apple juices and apple/pear pulp have been studied in order to evidence the presence of fructose and pectin, which are components of great relevance for quality assessment of these kinds of products. In order to perform SERS measurements a low-cost home-made substrate consisting of a glass slide decorated with 30-nm-sized gold nanoparticles has been designed and used. By employing a conventional micro-Raman spectroscopy set-up and a suitable data treatment based on “wavelet” denoising algorithms and background subtraction, spectra of pectin and fructose with clear Raman features have been obtained. The results have confirmed the potential of SERS in the food industry for product characterization, also considering the low-cost and the relative ease of the fabrication process of the employed SERS substrate. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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5106 KiB

Open AccessArticle

A Low-Cost Environmental Monitoring System: How to Prevent Systematic Errors in the Design Phase through the Combined Use of Additive Manufacturing and Thermographic Techniques

by Francesco Salamone, Ludovico Danza, Italo Meroni and Maria Cristina Pollastro

Sensors 2017, 17(4), 828; https://doi.org/10.3390/s17040828 - 11 Apr 2017

Cited by 36 | Viewed by 9101

Abstract

nEMoS (nano Environmental Monitoring System) is a 3D-printed device built following the Do-It-Yourself (DIY) approach. It can be connected to the web and it can be used to assess indoor environmental quality (IEQ). It is built using some low-cost sensors connected to an [...] Read more.

nEMoS (nano Environmental Monitoring System) is a 3D-printed device built following the Do-It-Yourself (DIY) approach. It can be connected to the web and it can be used to assess indoor environmental quality (IEQ). It is built using some low-cost sensors connected to an Arduino microcontroller board. The device is assembled in a small-sized case and both thermohygrometric sensors used to measure the air temperature and relative humidity, and the globe thermometer used to measure the radiant temperature, can be subject to thermal effects due to overheating of some nearby components. A thermographic analysis was made to rule out this possibility. The paper shows how the pervasive technique of additive manufacturing can be combined with the more traditional thermographic techniques to redesign the case and to verify the accuracy of the optimized system in order to prevent instrumental systematic errors in terms of the difference between experimental and actual values of the above-mentioned environmental parameters. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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10936 KiB

Open AccessArticle

Accurate Determination of the Frequency Response Function of Submerged and Confined Structures by Using PZT-Patches†

by Alexandre Presas, David Valentin, Eduard Egusquiza, Carme Valero, Mònica Egusquiza and Matias Bossio

Sensors 2017, 17(3), 660; https://doi.org/10.3390/s17030660 - 22 Mar 2017

Cited by 45 | Viewed by 8361

Abstract

To accurately determine the dynamic response of a structure is of relevant interest in many engineering applications. Particularly, it is of paramount importance to determine the Frequency Response Function (FRF) for structures subjected to dynamic loads in order to avoid resonance and fatigue [...] Read more.

To accurately determine the dynamic response of a structure is of relevant interest in many engineering applications. Particularly, it is of paramount importance to determine the Frequency Response Function (FRF) for structures subjected to dynamic loads in order to avoid resonance and fatigue problems that can drastically reduce their useful life. One challenging case is the experimental determination of the FRF of submerged and confined structures, such as hydraulic turbines, which are greatly affected by dynamic problems as reported in many cases in the past. The utilization of classical and calibrated exciters such as instrumented hammers or shakers to determine the FRF in such structures can be very complex due to the confinement of the structure and because their use can disturb the boundary conditions affecting the experimental results. For such cases, Piezoelectric Patches (PZTs), which are very light, thin and small, could be a very good option. Nevertheless, the main drawback of these exciters is that the calibration as dynamic force transducers (relationship voltage/force) has not been successfully obtained in the past. Therefore, in this paper, a method to accurately determine the FRF of submerged and confined structures by using PZTs is developed and validated. The method consists of experimentally determining some characteristic parameters that define the FRF, with an uncalibrated PZT exciting the structure. These parameters, which have been experimentally determined, are then introduced in a validated numerical model of the tested structure. In this way, the FRF of the structure can be estimated with good accuracy. With respect to previous studies, where only the natural frequencies and mode shapes were considered, this paper discuss and experimentally proves the best excitation characteristic to obtain also the damping ratios and proposes a procedure to fully determine the FRF. The method proposed here has been validated for the structure vibrating in air comparing the FRF experimentally obtained with a calibrated exciter (impact Hammer) and the FRF obtained with the described method. Finally, the same methodology has been applied for the structure submerged and close to a rigid wall, where it is extremely important to not modify the boundary conditions for an accurate determination of the FRF. As experimentally shown in this paper, in such cases, the use of PZTs combined with the proposed methodology gives much more accurate estimations of the FRF than other calibrated exciters typically used for the same purpose. Therefore, the validated methodology proposed in this paper can be used to obtain the FRF of a generic submerged and confined structure, without a previous calibration of the PZT. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd International Electronic Conference on Sensors and Applications)

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