Search

Microwave gas sensors have been rapidly expanding in the recent past to meet the ever-increasing demands of wireless sensing devices in the market, thus opening new frontiers but also posing new challenges. This article provides a thorough overview of the state-of-art and future trends in the interdisciplinary and timely research field related to the development of microwave transducers for gas sensing, going from the theoretical background to practical applications. To gain a clear understanding of this type of sensors, the fundamentals and a few experimental case studies are described. [ABSTRACT FROM AUTHOR]

This work addresses the adoption of Machine Learning classifiers and Convolutional Neural Networks to improve the performance of highly wearable, single-channel instrumentation for Brain-Computer Interfaces. The proposed measurement system is based on the classification of Steady- State Visually Evoked Potentials (SSVEPs). In particular, Head-Mounted Displays for Augmented Reality are used to generate and display the flickering stimuli for the SSVEPs elicitation. Four experiments were conducted by employing, in turn, a different Head-Mounted Display. For each experiment, two different algorithms were applied and compared with the state-of-the-art-techniques. Furthermore, the impact of different Augmented Reality technologies in the elicitation and classification of SSVEPs was also explored. The experimental metrological characterization demonstrates (i) that the proposed Machine Learning-based processing strategies providea significantenhancement of theSSVEPclassification accuracy with respect to the state of the art, and (ii) that choosing an adequate Head-Mounted Display is crucial to obtain acceptable performance. Finally, it is also shown that the adoption of inter-subjective validation strategies such as the Leave-One-Subject-Out Cross Validation successfully leads to an increase in the inter-individual 1- $\sigma$ reproducibility: this, in turn, anticipates an easier development of ready-to-use systems. [ABSTRACT FROM AUTHOR]

Wireless sensor elements integrated with miniaturized antennas are useful in various applications such as wearable chemical and environmental sensors and Internet-of-Things (IoT) sensor nodes. A major problem in antenna operation is detuning of the antenna bandwidth due to loading by the sensor element. In this article, we report on the integration of an interdigitated capacitor (IDC), acting as a sensor, into an aperture coupled patch (ACP) antenna, such that weak coupling is established between the IDC and the rectangular patch resonator. Because of low mutual coupling, during the sensing process the antenna is not detuned out of its operational bandwidth and its performance is not compromised by the presence of the sensor and vice versa. A sensing material (barium titanate film) is deposited on the IDC located at the edge of the microstrip line used to slot-feed the ACP antenna. A change in the material permittivity is transduced into a variation of resonant frequency of the antenna. We describe the design and fabrication of the IDC sensor-integrated ACP antenna and demonstrate the measured sensing performance at different temperatures and relative humidity concentrations. [ABSTRACT FROM AUTHOR]

In this article, the electrochemical monitoring of phenol (Ph) in water by using a nanostructured MnO2-modified screen-printed carbon electrode (MnO2-SPCE) is reported. MnO2 nanoparticles were synthesized by the redox-precipitation method. Morphological, textural, and microstructural characteristics were investigated by scanning electron microscopy (SEM), X-ray diffraction, Raman, Brunauer–Emmett–Teller (BET) surface area, and pore volume analyses. Electrochemical properties of the modified MnO2-SPCE electrode have been investigated by cyclic voltammetry and linear sweep voltammetry. The detection of Ph in water by the developed sensor was exploited using square wave voltammetry and chronoamperometry. The sensor showed good characteristics, such as simple fabrication, low cost, good sensitivity, stability, reproducibility, and selectivity, against inorganic analytes and other phenolic compounds. The reported results demonstrated the great potential of nanostructured MnO2 in developing high performances electrochemical sensors to be utilized in the field of environmental pollution monitoring. [ABSTRACT FROM AUTHOR]

In this article, we present a novel autocorrelation-based frequency estimation algorithm for single-tone sinusoidal signals. In comparison to other state-of-the-art frequency estimation methods, the proposed one provides a better tradeoff between accuracy, complexity, and estimation range. In particular, the algorithm is able to achieve the Cramer–Rao lower bound for moderate and high signal-to-noise ratio, and its implementation is feasible even in resource-constrained microcontrollers, as those commonly used in the Industrial Internet-of-Things (IIoT) applications and low-cost instrumentation. Finally, we investigate the performance of the algorithm in the case of a practical IIoT application, i.e., frequency estimation of unbalanced three-phase power systems, showing that it outperforms several other autocorrelation-based estimators. [ABSTRACT FROM AUTHOR]

This article provides for the first time a very extensive experimental characterization coupled with a fully analytical modeling in order to investigate, in a systematic and comprehensive way, the sensing performance of a two-port surface acoustic wave (SAW) resonator from room down to cryogenic temperatures. The motivation behind this work is twofold: to quantitatively assess the temperature sensitivity of the SAW technology for cryogenic applications and to gain a better understanding of the underlying physics in terms of the equivalent-circuit elements. Although the measurement-based analysis is developed by focusing on a SAW from Murata as a case study, the developed investigation methodology is independent of the considered technology and extensible to other SAW types. A cryogenic system based on a closed-loop helium refrigerator is used to cool the tested SAW from 300 K down to 20 K with a step of 10 K. At each studied temperature, the scattering parameters are measured using a vector network analyzer over a narrow frequency band around the nominal resonant frequency of 423.2 MHz, spanning from 420 MHz to 425 MHz with a small step of 3.125 kHz. The measured scattering parameters are then transformed into the admittance ones, as they are more useful for sensing performance assessment and for equivalent-circuit model extraction. The extracted model is successfully validated through the achieved good agreement between measurements and simulations of the temperature- and frequency-dependent behavior of the studied resonator. [ABSTRACT FROM AUTHOR]

Here, this article reports about the design of a soft sensor (SS) able to monitor the hazardous gases in industrial plants. The SS is designed to estimate the gas concentrations by means of the measurements coming from an array of sensors, avoiding at the same time the humidity and temperature influence on array outputs. The SS has been designed with a data-driven approach, using a set of experimental data acquired in a laboratory. The design methodologies of two different SSs are compared, with the aim of obtaining both the good performance and a low computational complexity. As a first approach, a principal component analysis (PCA) has been performed to exploit the high correlation among some of the measures coming from the sensor array. A classical multilayer perceptron neural network is then trained to estimate the relationships between the PCA outputs and the gas concentrations. As a second approach, a deep belief network (DBN) has been considered. The data here reported show a good accuracy in the evaluation of several gas concentrations, even in the presence of noised measurements, allowing an efficient risk warning. Even if both the methods gave a similar performance, a lower number of model parameters and a lower noise sensitivity are obtained when using DBNs. [ABSTRACT FROM AUTHOR]