Gas sensors have attracted a lot of attention for real-time, low-cost, detection and measurement of gas concentrations for both understanding and monitoring a variety of gas phenomena, from industrial processes to env...
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More than 1.35 million lives are lost due to traffic accidents, with 94% of these accidents caused by human error. In order to significantly improve the traffic safety and efficiency, automated driving systems, includ...
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Considering the issues of the filter order in a signal processing channel with sensors, through the serial link of the same type filters with low order. New approach to define cutoff frequency of such link was obtaine...
Considering the issues of the filter order in a signal processing channel with sensors, through the serial link of the same type filters with low order. New approach to define cutoff frequency of such link was obtained. This solution allows quickly change the order and bandwidth of bandpass filters in robotic mobile platforms with limited computing resources. Proposed using a preliminary calculation of such frequencies, depending on the number of serial links of the same type of filters. This allows quickly rebuild the sensor signal processing channel.
We designed a ultrasensitive textile-based strain sensing choker to accurately monitor the slight strain changes caused by activities such as speech and breathing at the throat. The ordered cracks, which are induced b...
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ISBN:
(数字)9798350395136
ISBN:
(纸本)9798350395143
We designed a ultrasensitive textile-based strain sensing choker to accurately monitor the slight strain changes caused by activities such as speech and breathing at the throat. The ordered cracks, which are induced by the textile structure, endow the strain sensor with superior sensitivity and repeatability. This sensor can utilize advanced machine learning algorithms to decode signals from speech into corresponding words and sentences for integration into silent speech interface systems, or link signals from sleep to various sleep conditions like sleep apnea for integration into sleep monitoring systems.
A metal diaphragm-based airflow sensor based on fiber-optic Fabry-Perot (F-P) interference has been proposed and experimentally demonstrated. The sensor is composed of glass sleeving, ceramic ferrule and metal diaphra...
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ISBN:
(数字)9781510646520
ISBN:
(纸本)9781510646520;9781510646513
A metal diaphragm-based airflow sensor based on fiber-optic Fabry-Perot (F-P) interference has been proposed and experimentally demonstrated. The sensor is composed of glass sleeving, ceramic ferrule and metal diaphragm. Through data calibration, a practical airflow sensor has been fabricated. As a result of the stainless steel diaphragm and open F-P cavity, the durability of the sensor is ensured, and it can be used in poor air quality environments. Experimental results in the airflow field show that the sensor has the potential to estimate the air quantity of high-speed airflow in various air conduit.
In many applications using wireless sensor networks, the reliability of monitored data is crucial to analyze situations and take decisions. Compressed sensing methods are effective to ensure durability of a wireless s...
In many applications using wireless sensor networks, the reliability of monitored data is crucial to analyze situations and take decisions. Compressed sensing methods are effective to ensure durability of a wireless sensor network installation and to overcome communication failures by drastically lowering the amount of data to transmit. The method proposed in this paper aims to perform an abstraction of the signals sparsity model required by compressed sensing in order to use a deep learning-based approach. This method is designed to be effective for all kinds of transient or temporally dynamic signals sufficiently regular to be predictable, that is to say signals that can be implicitly modelled by a sparse representation. Through the collaboration of two recurrent neural networks and signal processing algorithms, our temporal method outperforms, in terms of accuracy, state-of-art methods, including distributed compressed sensing, time series imputation and forecasting deep learning methods. Thus, high compression rates up to 95% can be reached while leading to an error of less than 0.5°C in reconstructing temperature signals.
The paper investigates the problem of optimizing a sensor network for monitoring a continuous area, considering the bounded coverage areas of sensors. This task is formulated in terms of the maximum coverage location ...
The paper investigates the problem of optimizing a sensor network for monitoring a continuous area, considering the bounded coverage areas of sensors. This task is formulated in terms of the maximum coverage location problem. A mathematical model is proposed as a two-criteria optimization problem. The objective functions are the maximum area of the covered part of the region and the minimum total overlapping of sensor coverage areas. This model is transformed into an elastic (quasi-physical quasi-human) model, which differs from the known one in forming the extrusion potential energy function. To solve the problem, an original approach was implemented, combining local and global optimization stages. At the stage of local optimization, the Broyden-Fletcher-Goldfarb-Shanno method was used, in which the gradients were calculated analytically or from first-order differences depending on the shape of sensor coverage areas. At the stage of local optimization, the multistart method was used. The implementation of the approach has been tested for the polygonal shape of the region and elliptical shapes of the sensor coverage areas.
This work is aimed at research in the field of developing methods for the diagnosis of rolling bearings. This paper evaluates the influence of a number of measuring points of a multipoint temperature sensor on the per...
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ISBN:
(数字)9798331518752
ISBN:
(纸本)9798331518769
This work is aimed at research in the field of developing methods for the diagnosis of rolling bearings. This paper evaluates the influence of a number of measuring points of a multipoint temperature sensor on the performance of a rolling bearing diagnostic method. The study considers a rolling bearing diagnosis method based on analyzing a bearing temperature field and applying a neural network with an “autoencoder” architecture. The research of efficiency of the method is made on the temperature field data of the rolling bearing, which is a part of the technical equipment of the metal rolling line. As a result of this work, the hypothesis that the efficiency of the diagnostic model increases with the increase in the number of measuring points was confirmed.
This paper investigates the application of Industrial IoT (IIoT) systems for rapid development and deployment of control systems. We present a case study of a smart plant irrigation system implemented using Volapu IIo...
ISBN:
(数字)9781837242252
This paper investigates the application of Industrial IoT (IIoT) systems for rapid development and deployment of control systems. We present a case study of a smart plant irrigation system implemented using Volapu IIoT Suite, highlighting its advantages for low-cost and rapid development. The system leverages real-time sensor data (soil moisture, temperature) for rule-based control with the option to integrate weather forecasts for more informed decision-making. Volapu’s data interface enables the future incorporation of advanced data processing modules, facilitating the construction of higher-order control models. This study demonstrates the effectiveness of Volapu IIoT Suite in facilitating the development of cost-effective and scalable IIoT control systems.
Landslides are one of the major global geohazards, contributing to significant economic and social losses to private and public properties. In this paper, we deployed a Brillouin optical time-domain analysis (BOTDA) i...
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