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19 pages, 4547 KiB

Open AccessArticle

Spatial-Temporal Analysis of PM_2.5 and NO₂ Concentrations Collected Using Low-Cost Sensors in Peñuelas, Puerto Rico

by Stephen Reece, Ron Williams, Maribel Colón, David Southgate, Evelyn Huertas, Marie O’Shea, Ariel Iglesias and Patricia Sheridan

Sensors 2018, 18(12), 4314; https://doi.org/10.3390/s18124314 - 7 Dec 2018

Cited by 7 | Viewed by 5436

Abstract

The U.S. Environmental Protection Agency (EPA) is involved in the discovery, evaluation, and application of low-cost air quality (AQ) sensors to support citizen scientists by directly engaging with them in the pursuit of community-based interests. The emergence of low-cost (<$2500) sensors have allowed [...] Read more.

The U.S. Environmental Protection Agency (EPA) is involved in the discovery, evaluation, and application of low-cost air quality (AQ) sensors to support citizen scientists by directly engaging with them in the pursuit of community-based interests. The emergence of low-cost (<$2500) sensors have allowed a wide range of stakeholders to better understand local AQ conditions. Here we present results from the deployment of the EPA developed Citizen Science Air Monitor (CSAM) used to conduct approximately five months (October 2016–February 2017) of intensive AQ monitoring in an area of Puerto Rico (Tallaboa-Encarnación, Peñuelas) with little historical data on pollutant spatial variability. The CSAMs were constructed by combining low-cost particulate matter size fraction 2.5 micron (PM_2.5) and nitrogen dioxide (NO₂) sensors and distributed across eight locations with four collocated weather stations to measure local meteorological parameters. During this deployment 1 h average concentrations of PM_2.5 and NO₂ ranged between 0.3 to 33.6 µg/m³ and 1.3 to 50.6 ppb, respectively. Peak concentrations were observed for both PM_2.5 and NO₂ when conditions were dominated by coastal-originated winds. These results advanced the community’s understanding of pollutant concentrations and trends while improving our understanding of the limitations and necessary procedures to properly interpret measurements produced by low-cost sensors. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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18 pages, 6377 KiB

Open AccessArticle

Integration of Autonomous Wireless Sensor Networks in Academic School Gardens

by Peio Lopez-Iturri, Mikel Celaya-Echarri, Leyre Azpilicueta, Erik Aguirre, José J. Astrain, Jesús Villadangos and Francisco Falcone

Sensors 2018, 18(11), 3621; https://doi.org/10.3390/s18113621 - 25 Oct 2018

Cited by 7 | Viewed by 4244

Abstract

In this work, the combination of capabilities provided by Wireless Sensor Networks (WSN) with parameter observation in a school garden is employed in order to provide an environment for school garden integration as a complementary educational activity in primary schools. Wireless transceivers with [...] Read more.

In this work, the combination of capabilities provided by Wireless Sensor Networks (WSN) with parameter observation in a school garden is employed in order to provide an environment for school garden integration as a complementary educational activity in primary schools. Wireless transceivers with energy harvesting capabilities are employed in order to provide autonomous system operation, combined with an ad-hoc implemented application called MySchoolGardenApp, based on a modular software architecture. The system enables direct parameter observation, data analysis and processing capabilities, which can be employed by students in a cloud based platform. Providing remote data access allows the adaptation of content to specific classroom/homework needs. The proposed monitoring WSN has been deployed in an orchard located in the schoolyard of a primary school, which has been built with EnOcean’s energy harvesting modules, providing an optimized node device as well network layout. For the assessment of the wireless link quality and the deployment of the modules, especially the central module which needs to receive directly the signals of all the sensor modules, simulation results obtained by an in-house developed 3D Ray Launching deterministic method have been used, providing coverage/capacity estimations applicable to the specific school environment case. Preliminary trials with MySchoolGardenApp have been performed, showing the feasibility of the proposed platform as an educational resource in schools, with application in specific natural science course content, development of technological skills and the extension of monitoring capabilities to new context-aware applications. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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15 pages, 54085 KiB

Open AccessArticle

Evaluation of Water Indices for Surface Water Extraction in a Landsat 8 Scene of Nepal

by Tri Dev Acharya, Anoj Subedi and Dong Ha Lee

Sensors 2018, 18(8), 2580; https://doi.org/10.3390/s18082580 - 7 Aug 2018

Cited by 219 | Viewed by 14205

Abstract

Accurate and frequent updates of surface water have been made possible by remote sensing technology. Index methods are mostly used for surface water estimation which separates the water from the background based on a threshold value. Generally, the threshold is a fixed value, [...] Read more.

Accurate and frequent updates of surface water have been made possible by remote sensing technology. Index methods are mostly used for surface water estimation which separates the water from the background based on a threshold value. Generally, the threshold is a fixed value, but can be challenging in the case of environmental noise, such as shadow, forest, built-up areas, snow, and clouds. One such challenging scene can be found in Nepal where no such evaluation has been done. Taking that in consideration, this study evaluates the performance of the most widely used water indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Automated Water Extraction Index (AWEI) in a Landsat 8 scene of Nepal. The scene, ranging from 60 m to 8848 m, contains various types of water bodies found in Nepal with different forms of environmental noise. The evaluation was conducted based on measures from a confusion matrix derived using validation points. Comparing visually and quantitatively, not a single method was able to extract surface water in the entire scene with better accuracy. Upon selecting optimum thresholds, the overall accuracy (OA) and kappa coefficient (kappa) was improved, but not satisfactory. NDVI and NDWI showed better results for only pure water pixels, whereas MNDWI and AWEI were unable to reject snow cover and shadows. Combining NDVI with NDWI and AWEI with shadow improved the accuracy but inherited the NDWI and AWEI characteristics. Segmenting the test scene with elevations above and below 665 m, and using NDVI and NDWI for detecting water, resulted in an OA of 0.9638 and kappa of 0.8979. The accuracy can be further improved with a smaller interval of categorical characteristics in one or multiple scenes. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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22 pages, 2870 KiB

Open AccessArticle

Real-Time Distributed Architecture for Remote Acoustic Elderly Monitoring in Residential-Scale Ambient Assisted Living Scenarios

by Joan Navarro, Ester Vidaña-Vila, Rosa Ma Alsina-Pagès and Marcos Hervás

Sensors 2018, 18(8), 2492; https://doi.org/10.3390/s18082492 - 1 Aug 2018

Cited by 38 | Viewed by 7555

Abstract

Ambient Assisted Living (AAL) has become a powerful alternative to improving the life quality of elderly and partially dependent people in their own living environments. In this regard, tele-care and remote surveillance AAL applications have emerged as a hot research topic in this [...] Read more.

Ambient Assisted Living (AAL) has become a powerful alternative to improving the life quality of elderly and partially dependent people in their own living environments. In this regard, tele-care and remote surveillance AAL applications have emerged as a hot research topic in this domain. These services aim to infer the patients’ status by means of centralized architectures that collect data from a set of sensors deployed in their living environment. However, when the size of the scenario and number of patients to be monitored increase (e.g., residential areas, retirement homes), these systems typically struggle at processing all associated data and providing a reasonable output in real time. The purpose of this paper is to present a fog-inspired distributed architecture to collect, analyze and identify up to nine acoustic events that represent abnormal behavior or dangerous health conditions in large-scale scenarios. Specifically, the proposed platform collects data from a set of wireless acoustic sensors and runs an automatic two-stage audio event classification process to decide whether or not to trigger an alarm. Conducted experiments over a labeled dataset of 7116 s based on the priorities of the Fundació Ave Maria health experts have obtained an overall accuracy of 94.6%. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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14 pages, 4589 KiB

Open AccessArticle

Alignment Method for Linear-Scale Projection Lithography Based on CCD Image Analysis

by Dongxu Ren, Zexiang Zhao, Jianpu Xi, Bin Li, Zhengfeng Li, Huiying Zhao, Lujun Cui and Hang Xu

Sensors 2018, 18(8), 2442; https://doi.org/10.3390/s18082442 - 27 Jul 2018

Cited by 3 | Viewed by 5130

Abstract

This paper presents a method to improve the alignment accuracy of a mask in linear scale projection lithography, in which the adjacent pixel gray square variance method is applied to a charge-coupled device (CCD) image to obtain the best position of the focal [...] Read more.

This paper presents a method to improve the alignment accuracy of a mask in linear scale projection lithography, in which the adjacent pixel gray square variance method is applied to a charge-coupled device (CCD) image to obtain the best position of the focal length of the motherboard and then realize the alignment of the focal plane. Two image positions in the focal plane of the CCD are compared with the traits overlap according to the image splicing principle, and four typical errors are corrected on the basis of the total grating errors. Simultaneously, the rotation error of the mask is used to summarize the grayscale variation function of the CCD image. Threshold functions are employed to express the factors including the wave crests of the amplitude, period error, and phase error, which govern the rotation accuracy and weight alignment accuracy expression of the established four error factors. Finally, in the experiment, the slope of the mask is corrected and adjusted to the same direction as the slide plate with the assistance of a dual-frequency laser interferometer. The effect of the alignment error on the lithography accuracy is discussed and verified in the static case, and it is found that the CCD maximum resolution pixel is 0.1 μm and accuracy of the scale is 0.79 μm in only a 200-mm-measurement range. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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15 pages, 3430 KiB

Open AccessArticle

Narrowband Characterization of Near-Ground Radio Channel for Wireless Sensors Networks at 5G-IoT Bands

by Hicham Klaina, Ana Vazquez Alejos, Otman Aghzout and Francisco Falcone

Sensors 2018, 18(8), 2428; https://doi.org/10.3390/s18082428 - 26 Jul 2018

Cited by 34 | Viewed by 4712

Abstract

In this contribution, a narrowband radio channel model is proposed for rural scenarios in which the radio link operates under near-ground conditions for application in wireless sensor networks dedicated to smart agriculture. The received power attenuation was measured for both transmitter and receiver [...] Read more.

In this contribution, a narrowband radio channel model is proposed for rural scenarios in which the radio link operates under near-ground conditions for application in wireless sensor networks dedicated to smart agriculture. The received power attenuation was measured for both transmitter and receiver antennas placed at two different heights above ground: 0.2 and 0.4 m. Three frequency ranges, proposed for future 5G-IoT use case in agriculture, were chosen: 868 MHz, 2.4 GHz and 5.8 GHz. Three ground coverings were tested in a rural scenario: soil, short and tall grass fields. The path loss was then estimated as dependent of the radio link range and a three-slope log-normal path loss model was tailored. Results are explained in terms of the first Fresnel zone obstruction. Commercial Zigbee sensor nodes operating at 2.4 GHz were used in a second experiment to estimate the link quality from the experimental Radio Signal Strength Indicator (RSSI) received values. Two sensor nodes were placed at the same elevation above ground as in the previous experiment, only for short grass field case. The Quality of Service performance was determined in terms of theoretical bit error rate achieved for different digital modulations—BPSK, 8PSK and 16QAM—concluding remarkable results for an obstructed radio link. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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22 pages, 7983 KiB

Open AccessArticle

A Wearable Textile Thermograph

by Pasindu Lugoda, Theodore Hughes-Riley, Rob Morris and Tilak Dias

Sensors 2018, 18(7), 2369; https://doi.org/10.3390/s18072369 - 21 Jul 2018

Cited by 29 | Viewed by 7567

Abstract

In medicine, temperature changes can indicate important underlying pathologies such as wound infection. While thermographs for the detection of wound infection exist, a textile substrate offers a preferable solution to the designs that exist in the literature, as a textile is very comfortable [...] Read more.

In medicine, temperature changes can indicate important underlying pathologies such as wound infection. While thermographs for the detection of wound infection exist, a textile substrate offers a preferable solution to the designs that exist in the literature, as a textile is very comfortable to wear. This work presents a fully textile, wearable, thermograph created using temperature-sensing yarns. As described in earlier work, temperature-sensing yarns are constructed by encapsulating an off-the-shelf thermistor into a polymer resin micro-pod and then embedding this within the fibres of a yarn. This process creates a temperature-sensing yarn that is conformal, drapeable, mechanically resilient, and washable. This work first explored a refined yarn design and characterised its accuracy to take absolute temperature measurements. The influence of contact errors with the refined yarns was explored seeing a 0.24 ± 0.03 measurement error when the yarn was held just 0.5 mm away from the surface being measured. Subsequently, yarns were used to create a thermograph. This work characterises the operation of the thermograph under a variety of simulated conditions to better understand the functionality of this type of textile temperature sensor. Ambient temperature, insulating material, humidity, moisture, bending, compression and stretch were all explored. This work is an expansion of an article published in The 4th International Conference on Sensor and Applications. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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13 pages, 4392 KiB

Open AccessArticle

Cost-Effective Technologies to Study the Arctic Ocean Environment ^†

by Viviana Piermattei, Alice Madonia, Simone Bonamano, Riccardo Martellucci, Gabriele Bruzzone, Roberta Ferretti, Angelo Odetti, Maurizio Azzaro, Giuseppe Zappalà and Marco Marcelli

Sensors 2018, 18(7), 2257; https://doi.org/10.3390/s18072257 - 13 Jul 2018

Cited by 21 | Viewed by 5060

Abstract

The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets [...] Read more.

The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to monitor the Arctic marine ecosystem and validate high-resolution satellite observations (e.g., Sentinel), which are necessary to feed climatic and biogeochemical forecasting models. However, the Global Observing System needs to complete its geographic coverage, particularly for the harsh, extreme environment of the Arctic Region. In this scenario, autonomous systems are proving to be valuable tools for increasing the resolution of existing data. To this end, a low-cost, miniaturized and flexible probe, ArLoC (Arctic Low-Cost probe), was designed, built and installed on an innovative unmanned marine vehicle, the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys), during a preliminary scientific campaign in the Svalbard Archipelago within the UVASS project. This study outlines the instrumentation used and its design features, its preliminary integration on PROTEUS and its test results. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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10 pages, 996 KiB

Open AccessArticle

Graphene-Based Raman Spectroscopy for pH Sensing of X-rays Exposed and Unexposed Culture Media and Cells

by Carlo Camerlingo, Alessandro Verde, Lorenzo Manti, Roberta Meschini, Ines Delfino and Maria Lepore

Sensors 2018, 18(7), 2242; https://doi.org/10.3390/s18072242 - 12 Jul 2018

Cited by 13 | Viewed by 4137

Abstract

Graphene provides a unique way of sensing the local pH level of substances on the micrometric scale, with important implications for the monitoring of cellular metabolic activities where proton excretion could occur. Accordingly, an innovative biosensing approach for the quantification of the pH [...] Read more.

Graphene provides a unique way of sensing the local pH level of substances on the micrometric scale, with important implications for the monitoring of cellular metabolic activities where proton excretion could occur. Accordingly, an innovative biosensing approach for the quantification of the pH value of biological fluids, to be used also with small amounts of fluids, was realized and tested. It is based on the use of micro-Raman spectroscopy to detect the modifications of the graphene doping level induced by the contact of the graphene with the selected fluids. The approach was preliminarily tested on aqueous solutions of known pH values. It was then used to quantify the pH values of cell culture media directly exposed to different doses of X-ray radiation and to media exposed to X-ray-irradiated cells. The Raman response of cells placed on graphene layers was also examined. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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22 pages, 831 KiB

Open AccessArticle

Cost–Benefit Optimization of Structural Health Monitoring Sensor Networks

by Giovanni Capellari, Eleni Chatzi and Stefano Mariani

Sensors 2018, 18(7), 2174; https://doi.org/10.3390/s18072174 - 6 Jul 2018

Cited by 44 | Viewed by 5692

Abstract

Structural health monitoring (SHM) allows the acquisition of information on the structural integrity of any mechanical system by processing data, measured through a set of sensors, in order to estimate relevant mechanical parameters and indicators of performance. Herein we present a method to [...] Read more.

Structural health monitoring (SHM) allows the acquisition of information on the structural integrity of any mechanical system by processing data, measured through a set of sensors, in order to estimate relevant mechanical parameters and indicators of performance. Herein we present a method to perform the cost–benefit optimization of a sensor network by defining the density, type, and positioning of the sensors to be deployed. The effectiveness (benefit) of an SHM system may be quantified by means of information theory, namely through the expected Shannon information gain provided by the measured data, which allows the inherent uncertainties of the experimental process (i.e., those associated with the prediction error and the parameters to be estimated) to be accounted for. In order to evaluate the computationally expensive Monte Carlo estimator of the objective function, a framework comprising surrogate models (polynomial chaos expansion), model order reduction methods (principal component analysis), and stochastic optimization methods is introduced. Two optimization strategies are proposed: the maximization of the information provided by the measured data, given the technological, identifiability, and budgetary constraints; and the maximization of the information–cost ratio. The application of the framework to a large-scale structural problem, the Pirelli tower in Milan, is presented, and the two comprehensive optimization methods are compared. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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11 pages, 3188 KiB

Open AccessArticle

Acoustic Parametric Signal Generation for Underwater Communication

by María Campo-Valera, Miguel Ardid, Dídac D. Tortosa, Ivan Felis, Juan A. Martínez-Mora, Carlos D. Llorens and Pablo Cervantes

Sensors 2018, 18(7), 2149; https://doi.org/10.3390/s18072149 - 4 Jul 2018

Cited by 6 | Viewed by 3856

Abstract

This paper presents a study of different types of parametric signals with application to underwater acoustic communications. In all the signals, the carrier frequency is 200 kHz, which corresponds to the resonance frequency of the transducer under study and different modulations are presented [...] Read more.

This paper presents a study of different types of parametric signals with application to underwater acoustic communications. In all the signals, the carrier frequency is 200 kHz, which corresponds to the resonance frequency of the transducer under study and different modulations are presented and compared. In this sense, we study modulations with parametric sine sweeps (4 to 40 kHz) that represent binary codes (zeros and ones), getting closer to the application in acoustic communications. The different properties of the transmitting signals in terms of bit rate reconstruction, directivity, efficiency, and power needed are discussed as well. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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28 pages, 12652 KiB

Open AccessArticle

Deterministic Propagation Modeling for Intelligent Vehicle Communication in Smart Cities

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

Sensors 2018, 18(7), 2133; https://doi.org/10.3390/s18072133 - 3 Jul 2018

Cited by 12 | Viewed by 4356

Abstract

Vehicular Ad Hoc Networks (VANETs) are envisaged to be a critical building block of Smart Cities and Intelligent Transportation System (ITS) where applications for pollution, congestion reduction, vehicle mobility improvement, accident prevention and safer roads are some of the VANETs expected benefits towards [...] Read more.

Vehicular Ad Hoc Networks (VANETs) are envisaged to be a critical building block of Smart Cities and Intelligent Transportation System (ITS) where applications for pollution, congestion reduction, vehicle mobility improvement, accident prevention and safer roads are some of the VANETs expected benefits towards Intelligent Vehicle Communications. Although there is a significant research effort in Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communication radio channel characterization, the use of a deterministic approach as a complement of theoretical and empirical models is required to understand more accurately the propagation phenomena in urban environments. In this work, a deterministic computational tool based on an in-house 3D Ray-Launching algorithm is used to represent and analyze large-scale and small-scale urban radio propagation phenomena, including vehicle movement effects on each of the multipath components. In addition, network parameters such as throughput, packet loss and jitter, have been obtained by means of a set of experimental measurements for different V2I and V2V links. Results show the impact of factors such as distance, frequency, location of antenna transmitters (TX), obstacles and vehicle speed. These results are useful for radio-planning Wireless Sensor Networks (WSNs) designers and deployment of urban Road Side Units (RSUs). Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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15 pages, 14200 KiB

Open AccessArticle

Smart Sensing of Pavement Temperature Based on Low-Cost Sensors and V2I Communications

by Jorge Godoy, Rodolfo Haber, Juan Jesús Muñoz, Fernando Matía and Álvaro García

Sensors 2018, 18(7), 2092; https://doi.org/10.3390/s18072092 - 29 Jun 2018

Cited by 16 | Viewed by 6326

Abstract

Nowadays, the preservation, maintenance, rehabilitation, and improvement of road networks are key issues. Pavement condition is highly affected by environmental factors such as temperature and humidity, hence the importance of building databases enriched with real-time information from monitoring systems that enable the analysis [...] Read more.

Nowadays, the preservation, maintenance, rehabilitation, and improvement of road networks are key issues. Pavement condition is highly affected by environmental factors such as temperature and humidity, hence the importance of building databases enriched with real-time information from monitoring systems that enable the analysis and modeling of the road properties. Information and communication technologies, and specifically wireless sensor networks and computational intelligence methods, are enabling the design of new monitoring systems. The main goal of this work is the design of a pavement monitoring system for measuring temperature at internal layers. The proposed solution is based on low-cost and robust temperature sensors, vehicle-to-infrastructure communications, allowing one to transmit information directly from probes to a moving auscultation vehicle, and a neural network-based model for prediction pavement temperature. User requirements drive probes’ design to a modular device, with easy installation, low cost, and reduced energy consumption. Results of the test and validation experiments show both the benefits and viability of the proposed system, which reflect in an accuracy improvement and reduction in routine test duration. Finally, data collected over a year is applied to assess the performance of BELLS3 models and the suggested neural network for predicting pavement temperature. The dynamic behavior of the predicted temperature and the mean absolute error of the neural network-based model are better than the BELL3 model, demonstrating the suitability of the proposed pavement monitoring system. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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19 pages, 7422 KiB

Open AccessArticle

Elastic MCF Rubber with Photovoltaics and Sensing on Hybrid Skin (H-Skin) for Artificial Skin by Utilizing Natural Rubber: Third Report on Electric Charge and Storage under Tension and Compression

by Kunio Shimada

Sensors 2018, 18(6), 1853; https://doi.org/10.3390/s18061853 - 6 Jun 2018

Cited by 5 | Viewed by 3466

Abstract

In the series of studies on new types of elastic and compressible artificial skins with hybrid sensing functions, photovoltaics, and battery, we have proposed a hybrid skin (H-Skin) by utilizing an electrolytically polymerized magnetic compound fluid (MCF) made of natural rubber latex (NR-latex). [...] Read more.

In the series of studies on new types of elastic and compressible artificial skins with hybrid sensing functions, photovoltaics, and battery, we have proposed a hybrid skin (H-Skin) by utilizing an electrolytically polymerized magnetic compound fluid (MCF) made of natural rubber latex (NR-latex). By using the experimental results in the first and second reports, we have clarified the feasibility of electric charge at irradiation, and that without illumination under compression and elongation. The former was explained in a wet-type MCF rubber solar cell by developing a tunneling theory together with an equivalent electric circuit model. The latter corresponds to the battery rather than to the solar cell. As for the MCF rubber battery, depending on the selected agent type, we can make the MCF rubber have higher electricity and lighter weight. Therefore, the MCF rubber has an electric charge and storage whether at irradiation or not. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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23 pages, 12379 KiB

Open AccessArticle

Elastic MCF Rubber with Photovoltaics and Sensing on Hybrid Skin (H-Skin) for Artificial Skin by Utilizing Natural Rubber: 2nd Report on the Effect of Tension and Compression on the Hybrid Photo- and Piezo-Electricity Properties in Wet-Type Solar Cell Rubber

by Kunio Shimada

Sensors 2018, 18(6), 1848; https://doi.org/10.3390/s18061848 - 6 Jun 2018

Cited by 8 | Viewed by 3649

Abstract

In contrast to ordinary solid-state solar cells, a flexible, elastic, extensible and light-weight solar cell has the potential to be extremely useful in many new engineering applications, such as in the field of robotics. Therefore, we propose a new type of artificial skin [...] Read more.

In contrast to ordinary solid-state solar cells, a flexible, elastic, extensible and light-weight solar cell has the potential to be extremely useful in many new engineering applications, such as in the field of robotics. Therefore, we propose a new type of artificial skin for humanoid robots with hybrid functions, which we have termed hybrid skin (H-Skin). To realize the fabrication of such a solar cell, we have continued to utilize the principles of ordinary solid-state wet-type or dye-sensitized solar rubber as a follow-up study to the first report. In the first report, we dealt with both photovoltaic- and piezo-effects for dry-type magnetic compound fluid (MCF) rubber solar cells, which were generated because the polyisoprene, oleic acid of the magnetic fluid (MF), and water served as p- and n- semiconductors. In the present report, we deal with wet-type MCF rubber solar cells by using sensitized dyes and electrolytes. Photoreactions generated through the synthesis of these components were investigated by an experiment using irradiation with visible and ultraviolet light. In addition, magnetic clusters were formed by the aggregation of Fe₃O₄ in the MF and the metal particles created the hetero-junction structure of the semiconductors. In the MCF rubber solar cell, both photo- and piezo-electricity were generated using a physical model. The effects of tension and compression on their electrical properties were evaluated. Finally, we experimentally demonstrated the effect of the distance between the electrodes of the solar cell on photoelectricity and built-in electricity. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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16 pages, 4515 KiB

Open AccessArticle

Elastic MCF Rubber with Photovoltaics and Sensing for Use as Artificial or Hybrid Skin (H-Skin): 1st Report on Dry-Type Solar Cell Rubber with Piezoelectricity for Compressive Sensing

by Kunio Shimada

Sensors 2018, 18(6), 1841; https://doi.org/10.3390/s18061841 - 5 Jun 2018

Cited by 12 | Viewed by 4398

Abstract

Ordinary solar cells are very difficult to bend, squash by compression, or extend by tensile strength. However, if they were to possess elastic, flexible, and extensible properties, in addition to piezo-electricity and resistivity, they could be put to effective use as artificial skin [...] Read more.

Ordinary solar cells are very difficult to bend, squash by compression, or extend by tensile strength. However, if they were to possess elastic, flexible, and extensible properties, in addition to piezo-electricity and resistivity, they could be put to effective use as artificial skin installed over human-like robots or humanoids. Further, it could serve as a husk that generates electric power from solar energy and perceives any force or temperature changes. Therefore, we propose a new type of artificial skin, called hybrid skin (H-Skin), for a humanoid robot having hybrid functions. In this study, a novel elastic solar cell is developed from natural rubber that is electrolytically polymerized with a configuration of magnetic clusters of metal particles incorporated into the rubber, by applying a magnetic field. The material thus produced is named magnetic compound fluid rubber (MCF rubber) that is elastic, flexible, and extensible. The present report deals with a dry-type MCF rubber solar cell that uses photosensitized dye molecules. First, the photovoltaic mechanism in the material is investigated. Next, the changes in the photovoltaic properties of its molecules due to irradiation by visible light are measured under compression. The effect of the compression on its piezoelectric properties is investigated. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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18 pages, 2532 KiB

Open AccessArticle

Integrated Method for Personal Thermal Comfort Assessment and Optimization through Users’ Feedback, IoT and Machine Learning: A Case Study ^†

by Francesco Salamone, Lorenzo Belussi, Cristian Currò, Ludovico Danza, Matteo Ghellere, Giulia Guazzi, Bruno Lenzi, Valentino Megale and Italo Meroni

Sensors 2018, 18(5), 1602; https://doi.org/10.3390/s18051602 - 17 May 2018

Cited by 84 | Viewed by 9492

Abstract

Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV [...] Read more.

Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones. Following this perspective, the paper describes the results of an in-field investigation of thermal conditions through the use of nearable and wearable solutions, parametric models and machine learning techniques. The aim of the research is the exploration of the reliability of IoT-based solutions combined with advanced algorithms, in order to create a replicable framework for the assessment and improvement of user thermal satisfaction. For this purpose, an experimental test in real offices was carried out involving eight workers. Parametric models are applied for the assessment of thermal comfort; IoT solutions are used to monitor the environmental variables and the users’ parameters; the machine learning CART method allows to predict the users’ profile and the thermal comfort perception respect to the indoor environment. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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16 pages, 2522 KiB

Open AccessArticle

Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers

by Guillermo Robles, José Manuel Fresno and Juan Manuel Martínez-Tarifa

Sensors 2018, 18(5), 1410; https://doi.org/10.3390/s18051410 - 3 May 2018

Cited by 6 | Viewed by 4121

Abstract

Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied [...] Read more.

Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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23 pages, 1592 KiB

Open AccessArticle

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN

by Rosa Ma Alsina-Pagès, Francesc Alías, Joan Claudi Socoró and Ferran Orga

Sensors 2018, 18(4), 1272; https://doi.org/10.3390/s18041272 - 20 Apr 2018

Cited by 19 | Viewed by 7465

Abstract

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started [...] Read more.

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on

μ

Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around

\frac{1}{6}

of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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19 pages, 15232 KiB

Open AccessArticle

An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Nanotubes for SHM of Large Structures

by Andrea Meoni, Antonella D’Alessandro, Austin Downey, Enrique García-Macías, Marco Rallini, A. Luigi Materazzi, Luigi Torre, Simon Laflamme, Rafael Castro-Triguero and Filippo Ubertini

Sensors 2018, 18(3), 831; https://doi.org/10.3390/s18030831 - 9 Mar 2018

Cited by 78 | Viewed by 8601

Abstract

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and [...] Read more.

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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Review

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29 pages, 1865 KiB

Open AccessReview

Application of Electronic-Nose Technologies and VOC-Biomarkers for the Noninvasive Early Diagnosis of Gastrointestinal Diseases

by Alphus Dan Wilson

Sensors 2018, 18(8), 2613; https://doi.org/10.3390/s18082613 - 9 Aug 2018

Cited by 130 | Viewed by 11642

Abstract

Conventional methods utilized for clinical diagnosis of gastrointestinal (GI) diseases have employed invasive medical procedures that cause stress, anxiety and pain to patients. These methods are often expensive, time-consuming, and require sophisticated chemical-analysis instruments and advanced modeling procedures to achieve diagnostic interpretations. This [...] Read more.

Conventional methods utilized for clinical diagnosis of gastrointestinal (GI) diseases have employed invasive medical procedures that cause stress, anxiety and pain to patients. These methods are often expensive, time-consuming, and require sophisticated chemical-analysis instruments and advanced modeling procedures to achieve diagnostic interpretations. This paper reviews recent applications of simpler, electronic-nose (e-nose) devices for the noninvasive early diagnosis of a wide range of GI diseases by collective analysis of headspace volatile organic compound (VOC)-metabolites from clinical samples to produce disease-specific aroma signatures (VOC profiles). A different “metabolomics” approach to GI disease diagnostics, involving identifications and quantifications of disease VOC-metabolites, are compared to the electronic-nose approach based on diagnostic costs, accuracy, advantages and disadvantages. The importance of changes in gut microbiome composition that result from disease are discussed relative to effects on disease detection. A new diagnostic approach, which combines the use of e-nose instruments for early rapid prophylactic disease-screenings with targeted identification of known disease biomarkers, is proposed to yield cheaper, quicker and more dependable diagnostic results. Some priority future research needs and coordination for bringing e-nose instruments into routine clinical practice are summarized. Full article

(This article belongs to the Special Issue Selected Papers from the 4th International Electronic Conference on Sensors and Applications)

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