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The paper deals with the estimation of sensor faults for dynamic systems as well as the assessment of the uncertainty of the resulting estimates. For that purpose, it is assumed that the external disturbances are bounded within an ellipsoidal domain. This allows considering both stochastic and deterministic process and measurement uncertainties. Under such an assumption, a fault diagnosis scheme is developed with a prescribed convergence rate and accuracy. To achieve fault estimation, a conversion into an equivalent descriptor system is utilized. The paper provides a full stability and convergence analysis of the estimator including observability analysis. As a result, a set of complementary fault uncertainty intervals is obtained, which are minimized in such a way as to obtain a minimum detectable sensor fault. The final part of the paper exhibits a numerical example concerning fault estimation of a multi-tank system. The obtained results clearly confirm the performance of the proposed estimator expressed in the minimum detectable fault intervals. [ABSTRACT FROM AUTHOR]

The paper describes the structural design of a laboratory device that allows for presenting operation, simulating work procedures and checking functionality of the elevator "rope sensors" when equalizing different tensile forces in partial ropes of a rope system of traction elevators. The laboratory device is modified for checking operations of commonly used rope sensors. In an overwhelming number of cases, elevator technicians use them for setting up the unequally distributed tensile forces in elevator ropes. The device is equipped with three, mutually attached pulleys, over which the rope is installed. The unknown tensile force in the rope is determined by an "indirect method", i.e. from the resultant of the forces of the rope bent over the pulleys, which have an effect on the force sensor. The tensile force along the rope axis can be determined numerically, but also experimentally, from the inclination angle of the rope installed on the pulleys, diameter of the pulleys, diameter of the rope and the force detected by the force sensor of the stretched rope. The paper presents experimentally obtained tensile force values at the rope sensor, deduced from stretching the rope. The paper also describes the procedure for determining the measured load in the rope by rope sensors of the SWR, SWK and RMT-1 types based on the [ABSTRACT FROM AUTHOR]

Voice Activity Detection (VAD) is a crucial step for speech processing, which detecting accuracy and speed directly affects the effect of subsequent processing. Some voice processing system based phone or in the indoor environment, which need simple and quick method of VAD, for these representative voice signal, this paper proposes a new algorithm which is adaptive and quick based on a major improvement to Dual-Threshold endpoint detection algorithm. First the amplitude normalization is processed to the original voice signal, the characteristic is extracted by means of short-time amplitude, which can simplify operation. Then, large-scale (long frame-length and frame-shift) short-time amplitude is used for rough detection, combining adaptive threshold judgement of consecutive frames, which can find voice areas of start-point and end-point quickly. To these areas, small-scale (short frame-length and frame-shift) short-time amplitude is used for accurate detection, forward scanning is put to start-point area, reverse scanning is put to end-point area, combining adaptive threshold judgement of consecutive frames, start-point and end-point of the effective speech can be accurately located. Experimental results show that the method of this paper can detect endpoints of voice signal more quickly and accurately, which can improve recognition performance dramatically. Largescale can increase detection speed, small-scale can improve detection accuracy, both can be adjusted to satisfy the different requirements. The method of this paper ensures both detection speed and precision, which has more flexibility and applicability. [ABSTRACT FROM AUTHOR]

In the paper, a pressure sensor and a humidity sensor are designed as supplementary components of a textile integrated waveguide (TIW) based on an artificial magnetic conductor (AMC) consisting of hexagonal elements. Thanks to AMC, sewing of electrically conductive side walls can be eliminated. Since operating in the stop-band of TIW, the sensors do not influence transmission parameters of TIW, and provide an additional functionality. For fabrication, a three-dimensional knitted fabric was used as a substrate and conductive surfaces were created from a self-adhesive copper foil. The sensors were simulated, manufactured and measured in the frequency range from 10 GHz to 12 GHz with a reasonable agreement. Since the designed components are sensitive on manufacturing tolerances, a higher measured insertion loss in TIW can be observed compared to simulations. Nevertheless, the insertion loss can be reduced when manufacturing accuracy is improved. [ABSTRACT FROM AUTHOR]

Travel time is a fundamental measure in any transportation system. With the development of technology, travel time can be automatically collected by a variety of advanced sensors. However, limited by objective conditions, it is difficult for any sensor system to cover the whole transportation network in real time. In order to estimate the travel time of the whole transportation network, this paper gives a system of linear equations which is constructed by the user equilibrium (UE) principle and observed data. The travel time of a link which is not covered by a sensor can be calculated by using the observed data collected by sensors. In a typical transportation network, the minimum number and location of sensors to estimate the travel time of the whole network are given based on the properties of the solution of a systems of linear equations. The results show that, in a typical network, the number and location of sensors follow a certain law. The results of this study can provide reference for the development of transportation and provide a scientific basis for transportation planning. [ABSTRACT FROM AUTHOR]

In this paper, we describe our team's data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV dataset contains data from LIDAR, RGB, depth cameras, temperature, moisture, and atmospheric pressure sensors. We describe data transfer from a platform, automatic and manual validation of data quality, conversions to multiple formats, and structuring of the final data. Accurate time offset estimation between sensors achieved in the dataset uses IMU data generated by purposeful movements of the sensor platform. Therefore, we also outline partitioning of the data and time alignment calculation during post-processing. [ABSTRACT FROM AUTHOR]

Accurate detection of gas/odor requires highly selective gas sensor. However, the high-performance classification of gases/odors can be achieved using partial-selective gas sensors. Since 1980s, an array of broadly tuned (partial-selective) gas sensors have been used in several fields of science and engineering, and the resulting gas sensing systems (GSS) are popularly known as electronic noses (e-Noses). The combination of similar or different sensors in the array indirectly compensates for the requirement of high selectivity in GSS. Further, e-Nose's performance inevitably depends on the salient features drawn from the initial responses of the gas sensor array (GSA). So obtained features are referred to as the responses of virtual sensors (VS). In this paper, we have proposed the three-input and three-output (TITO) technique to derive efficient virtual sensor responses (VSRs) which outperform its well-published peer technique. A GSA consisting of four elements is used to demonstrate the proposed technique. Our proposed technique augments the VSRs by four times compared to its peer. The efficacy of our proposed technique has been tested using nine fundamental classifiers, viz., linear support vector machine (100%), decision tree (97.5%), multi-layer perceptron neural network (100%), K-nearest neighbor (85%), logistic regression (100%), Gaussian process with radial basis function (95%), linear discriminant analysis (97.5%), random forest (100%), and AdaBoost (95%). Ten-fold cross-validation has been used to minimize the biasing impact of the intra- and inter-class variance. With the result, four classifiers successfully provide an accuracy of 100 percent. Hence, we have proposed and vindicated an efficient technique. [ABSTRACT FROM AUTHOR]

Increasing the accuracy of position measurement is an intensively addressed issue in engineering practice. Indirect methods provide satisfactory distance information. For more accurate identification of surface geometry or tilt, systems based on image processing are frequently employed, however, these are more expensive in contrast to devices operating on the basis of acoustic principle. This paper deals with the modelling of the impulse functions of ultrasonic sensors under known geometrical conditions of their distribution. The reflecting surface is a metallic surface. Based on the results, a statistically significant non-linear correlation between the complex integral of the impulse function and the front time of the transient characteristic is shown. The change from the parallel to the perpendicular case of the longitudinal axis of ultrasonic transducer distribution due to the change in the tilt angle of reflected surface is also included in the study. The interval of change in the tilt angle of reflecting surface was from 0° to 30°. [ABSTRACT FROM AUTHOR]

The paper focuses on investigation of influence of the volume inserted in the scanning area of the magnetic resonance imaging (MRI) device working with a low magnetic field generated by a pair of permanent magnets on vibration and acoustic noise. In addition, its aim is to evaluate the influence of different types of used scan sequences, different settings of slice orientation and scan parameters on the energy and spectral properties of vibration and noise generated by the gradient coil system of the MRI device. Two basic measurements were performed within this work: mapping of sound pressure levels in the MRI device vicinity and parallel acquisition of vibration signals by sensors mounted on the lower and upper parts of the MRI gradient system. The paper next analyzes changes in properties of the vibration signals for the examined person lying in the scanning area compared with the situation of using only the testing phantom. Spectral characteristics of the recorded vibration signals are then analyzed statistically, and compared visually and numerically. The obtained results of the detailed analysis will be used for improvement of noise suppression algorithms applied to a speech signal recorded simultaneously with scanning of the human vocal tract for its 3D modeling. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports published within the issue which include the use of olfactory sensor, the introduction of the perceptual colour correlogram, and the utilization of a Sick laser scanner.

A new approach for studying the performance of single-mode optical fiber surface plasmon resonance sensor for refractive index sensing is presented. Intensity interrogation technique is used to observe and examine the effect of changing the value of the operating wavelength, within the single-mode operation region, on sensor performance. Effect of changing metal thickness, which is a critical parameter of the sensor structure, is also investigated. The results show that the selected operating wavelength within the mentioned region plays a very important role and has a significant impact on the sensor sensitivity. As the operating wavelength increases beyond the cut-off wavelength, above which the first higher-order mode disappears, the sensitivity increases while the refractive index range, for which the sensitivity is above its half maximum value, becomes narrower. In the proposed sensor structure, for a metal thickness of 25 nm, the maximum sensitivity reaches 2554 RIU−1 for analyte refractive index of 1.439 at a wavelength of 1500 nm. This sensitivity corresponds to a resolution of order 106 RIU by assuming 1% minimum reflectivity variation. The operating wavelength should be carefully selected and changed according to the refractive index values intended to be measured to ensure high sensor sensitivity at these values. The analysis provided in this paper enables to select and change the desired range of the sensed refractive index using low cost technique by just changing the operating wavelength in the single-mode operation region. [ABSTRACT FROM AUTHOR]

Various studies on local crop monitoring are presented in the literature, however there is insufficient research on low-cost IoT weather stations that can obtain weather information over a long period of time. To overcome the difficulties described above, this paper proposes the development of an IoT weather station for low-cost, sustainable and multi-functional agricultural crop monitoring. The objective of the work is to develop a local weather observation device for agricultural crops, to set up a server for storing and providing meteorological information and to perform an analysis of the acquired weather data. The weather station architecture developed and proposed in this project consists of four main blocks: sensor and controller module, power module, local data storage module and data communication module (gateway). [ABSTRACT FROM AUTHOR]

This paper presents a new approach for fabrication of single layer microbolometer detectors featuring pixel level vacuum packaging together with a lens on the pixel. The proposed lens structure can be used to increase the fill factor of the detector so that the pixel size can be decreased without decreasing the minimum feature size in the detector which is a problem in single layer microbolometers. The designs of the lens and the fabrication process of pixel level vacuum packaged microbolometer detector together with this lens are given in the framework of this study. The optical and mechanical simulations of the structure are performed. The radius of curvature of the lens is optimized to be 25 μm and it is shown that the condensing efficiency is 100% for 3 μm lens-detector distance. The deflection in the lens structure is found approximately as 0.8 nm in 1 atm environment pressure, showing that the proposed structure is durable. The proposed structure increases the fill factor to twice of the original value without decreasing the minimum feature size in the fabrication processes, resulting in the same amount of improvement in the performance of the detector. This approach can also be used to increase the yield and decrease the fabrication cost of single layer and also standard microbolometers with small pixel sizes, as it integrates the vacuum packaging in the fabrication steps. [ABSTRACT FROM AUTHOR]

High-performance detection and estimation of gases/odors are challenging, especially in real-time gas sensing applications. Recently, efficient electronic noses (e-noses) are being developed using convolutional neural networks (CNNs). Further, CNNs perform better when they operate on a minimal size of vector response. In this paper, dimensions of the operational vectors have been augmented by using virtual sensor responses. These virtual responses are obtained from the principal components of the physical sensor responses. Accordingly, two sets of data are upscaled as a one-dimensional one. Another level of upscaling is further obtained by using the mirror mosaicking technique. Hence, with our proposed novel approach, the final vector size for CNN operations achieves a new dimension. With this upscaled hybrid dataset, consisting of physical and virtual sensor responses, a simpler CNN has achieved 100 percent correct classification in two different experimental settings. To the best of authors information, it is for the first time that an e-nose has been designed using a principal component-based hybrid, upscaled dataset and achieves 100 percent correct classification of the considered gases/odors. [ABSTRACT FROM AUTHOR]

This paper deals with the determination of the absolute errors of a small time of flight (ToF) distance sensor with respect to coloured surfaces at different illumination intensities. The aim was to determine the absolute error of the measured distance by the VL53L1X sensor when set to short-mode and long-mode at different illumination intensities: 10 lx and 350 lx depending on the coloured surface using regression analysis methods. The research was performed using 7 colour samples with different spectral colours determined according to the CIE Lab colour model. Based on the performed experiments, it was found that the error at different sensor settings, change of colour surface and different illumination intensity is approximated by a linear function only up to a certain measured distance. The process is influenced by proposed factors such as: illumination intensity, coloured surface with different illumination reflectance and signal-noise parameters of the tested sensor during the experiment. [ABSTRACT FROM AUTHOR]

In this paper, we make an attempt to use the QHY174M-GPS camera for the photometry research of fast-rotating artificial objects including debris, satellites and rocket bodies. This device is useful for imaging occultations, eclipses, meteors, and so on due to a highly precise recording of the time (GPS-based) and location of the observation on every frame and fast readout of the CMOS detector. The precision of time registration by the QHY174M-GPS camera is at the level of microseconds. All light curves obtained by studied camera during observations of artificial satellites in this work were carried out at Derenivka Observatory of Uzhhorod National University, Ukraine. The created photometric system with QHY174M-GPS camera as the detector and reflector telescope with parameters D=120 mm, F=114 mm, FOV=2.82°-1.76° was calibrated. For target observations, SharpCap software was used. For the purposes of photometry processing, ccd_phot software was developed using Python 3.8 programming language with astropy and photutils packages. Photometry observations of artificial satellites of the Earth and standard stars were carried out. Over 80 lightcurves of artificial satellites were obtained. Comparing synchronous observations from two sites, separated 15 km from each other, we can conclude that photometry on the QHY174M-GPS camera gave us the same shape of lightcurve and additional advantages, such as time of exposure or simplicity of usage. [ABSTRACT FROM AUTHOR]

The cognitive goal of this paper is to assess whether marker-less motion capture systems provide sufficient data to recognize human postures in the side view. The research goal is to develop a new posture classification method that allows for analysing human activities using data recorded by RGB-D sensors. The method is insensitive to recorded activity duration and gives satisfactory results for the sagittal plane. An improved competitive Neural Network (cNN) was used. The method of preprocessing the data is first discussed. Then, a method for classifying human postures is presented. Finally, classification quality using various distance metrics is assessed. The data sets covering the selection of human activities have been created. Postures typical for these activities have been identified using the classifying neural network. The classification quality obtained using the proposed cNN network and two other popular neural networks were compared. The results confirmed the advantage of cNN network. The developed method makes it possible to recognize human postures by observing movement in the sagittal plane. [ABSTRACT FROM AUTHOR]

Atmospheric corrosivity is classified according to EN ISO 9223 Corrosion of metals and alloys – Corrosivity of atmospheres – Classification, determination and estimation. For the determination and estimation of the corrosivity category, standardized approaches are used. Monitoring of corrosivity with the application of various sensors is an actual trend. The paper gives results of verification of some types of sensors for this monitoring with standardized flat samples at atmospheric test sites in the Czech Republic. The trend of decreasing atmospheric corrosivity is evident in the last decade. Monitoring of the corrosion rate and mapping of the corrosivity become a very important step in preventing failures in long-term atmospheric exposition. This type of monitoring was used on bridge construction to estimate the seasonal effect of de-icing salts deposition, too. [ABSTRACT FROM AUTHOR]

This scientific paper highlights some aspects related to the design and real implementation of a smart miniature camera, which can represent a modern home automation solution. It integrates sensors controlled by the ESP-NOW communication protocol using the ESP32 microcontroller. The miniature camera consists of a living space incorporated with various sensors to measure temperature, humidity, air quality, and other parameters necessary for environmental comfort. The sensors are connected to a development board, which is programmed to collect, process, and interpret data from the sensors. Additionally, a software application has been developed using the C# programming language for a computer, which allows the user to remotely monitor and control the camerațs sensor data. The proposed smart miniature camera can be implemented in various scenarios such as smart homes, offices, and public spaces to provide a comfortable and efficient environment for occupants. [ABSTRACT FROM AUTHOR]

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The attitude detection of 3-DOF actuator is an important technology of 3-DOF spherical actuator control. For the space attitude change of the stator and the traditional detection method is invalid, the relative coordinate transformation is proposed in this paper, through the analysis of the coordinate systems of the spherical actuator. The transformed relative coordinate data is proved by using MATLAB platform. The traditional coordinate transformation and the relative coordinate transformation are compared in this paper. Using the relative coordinate transformation algorithm, the relative position detection system based on the MEMS six-axis sensor is designed. Using two sensors to detect both the attitude of the stator and the rotor, the relative position detection system is realized. The data received from sensor transformed by this method is used to verify the feasibility. [ABSTRACT FROM AUTHOR]

Building structures are extremely sensitive at influence of outdoor conditions. Most often these are the influence of wind, sunshine, temperature changes of the surrounding and at least the influence of the own or other loading. According to resonance of the structure with the surrounding is coming to vibration and oscillation in relative high frequency interval (0.1 Hz - 100.0 Hz). These phenomena significantly affect the static and dynamic characteristics of structures, their safety and functionality. The paper brings example of monitoring these phenomena. The object of monitoring is the Danube Bridge Apollo in Bratislava, which main steel structure was measured by acceleration sensors with frequency up to10 Hz. The main topic of the paper is the analysis of dynamic behavior of structure using spectral analysis method. The usage of Fourier Transform is described, own frequencies and amplitudes of structure oscillation are calculated. [ABSTRACT FROM AUTHOR]

This paper concerns a classification problem of 3D shapes being in motion. The goal is to develop the system with real-time capabilities to distinguish basic shapes (corners, planes, cones, spheres etc.) that are moving in front of RGB-D sensor. It is introduced an improvement of 'SoA al-gorithms (normal vector computation using PC A Principal Component Analysis and SVD Singular Value Decomposi-tion, PFH - Point Feature Histogram) based on GPGPU (General Purpose Graphic Processor Unit) computation. This approach guarantee on-line computation of normal vectors, unfortunately computation time of the PFH for each normal vector is still a challenge to obtain on-line ca-pabilities, therefore in this paper it is shown how to find a region of movement and to perform the classification process assuming the decreased amount of data. Proposed approach can be a starting point for further developments of the systems able to recognize the objects in the dynamic environments. [ABSTRACT FROM AUTHOR]

This paper describes the development of intelligent sensors as part of an integrated systems approach. The integrated systems approach treats the sensor as a complete system with its own sensing hardware (the traditional sensor), A/D converter, processing and storage capabilities, software drivers, self-assessment algorithms and communication protocols. The immediate application is the monitoring of rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done to date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS). The PIS as discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the digital data. If any event, i.e. spike, drift, noise, is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with a confidence factor in the reliability of the data. The VIS discussed here is a virtual implantation of the PIS in C++. The VIS is designed to mirror the operations of the PIS; however, the VIS works on a computer at which digital data is provided as the input and is thus portable to any sensor system. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities. [ABSTRACT FROM AUTHOR]

This paper presents the development of a versatile sensor platform used for autonomous data acquisition. The key advantages of the platform are its compact design, implemented onboard sensors, standard interfaces to connect application specific sensors and subsequently simple installation and low costs for the preparation of a measurement task. The paper provides details of the platform design and key characteristics. Practical exemplary applications in the field of automotive sensing, covering thermal management related and passenger comfort related measurement tasks, are presented. [ABSTRACT FROM AUTHOR]

The paper discusses the derivation of an accurate coordinate measuring system consisting of two, three, or four sensors based on the records of four fixed laser triangulation sensors done for a gauge block in movement. Three-dimensional case is considered. In the simulations, using a set of distances quadruplets, parameters of sensors in a local sensors coordinate system are determined through a least squares minimization process using the Differential Evolution approach. The influence of the measurement and rounding inaccuracy on the identification accuracy using numerical simulation methods are assessed. [ABSTRACT FROM AUTHOR]

This paper describes new technical challenges that arise from networking dynamical systems. In particular, the paper takes a look at the underlying phenomena and the resulting modeling problems that arise in such systems. Special emphasis is placed on the problem of synchronization, since this problem has not received as much attention in the literature as the phenomena of packet drop, delays, etc. The paper then discusses challenges arising in prominent areas such as congestion control, sensor networks, as well as vehicle networks and swarms. [ABSTRACT FROM AUTHOR]

A cost-effective method for resolution increase of a two-stage piecewise linear analog-to-digital converter used for sensor linearization is proposed in this paper. In both conversion stages flash analog-to-digital converters are employed. Resolution increase by one bit per conversion stage is performed by introducing one additional comparator in front of each of two flash analog-to-digital converters, while the converters' resolutions remain the same. As a result, the number of employed comparators, as well as the circuit complexity and the power consumption originating from employed comparators are for almost 50 % lower in comparison to the same parameters referring to the linearization circuit of the conventional design and of the same resolution. Since the number of employed comparators is significantly reduced according to the proposed method, special modifications of the linearization circuit are needed in order to properly adjust reference voltages of employed comparators. [ABSTRACT FROM AUTHOR]

In this paper, novel symmetrical split ring resonator (SSRR) is proposed as a suitable component for performance enhancement of microwave sensors. SSRR has been employed for enhancing the insertion loss of the microwave sensors. Using the same device area, we can achieve a high Q-factor of 141.54 from the periphery enhancement using Quasi-linear coupling SSRR, whereas loose coupling SSRR can achieve a Q-factor of 33.98 only. Using Quasi-linear coupling SSRR, the Q-factor is enhanced 4.16 times the loose coupling SSRR using the same device area. After the optimization was made, the SSRR sensor with loose coupling scheme has achieved a very high Q-factor value around 407.34 while quasi-linear scheme has achieved high Q-factor value of 278.78 at the same operating frequency with smaller insertion loss. Spurious passbands at 1st, 2nd, 3rd, and 4th harmonics have been completely suppressed well above -20 dB rejection level without visible changes in the passband filter characteristics. The most significant of using SSRR is to be used for various industrial applications such as food industry, quality control, bio-sensing medicine and pharmacy. The simulation result that Quasi-linear coupling SSRR is a viable candidate for the performance enhancement of microwave sensors has been verified. [ABSTRACT FROM AUTHOR]

This paper presents the automatic system for the processing of the signals from the frequency modulated interrupted continuous wave (FMICW) radar and describes methods for the primary signal processing. Further, we present methods for the detection of the targets in strong noise. These methods are tested both on the real and simulated signals. The real signals were measured using the developed at the IAP CAS experimental prototype of FMICW radar with operational frequency 35.4 GHz. The measurement campaign took place at the TU Delft, the Netherlands. The obtained results were used for development of the system for the automatic detection and analysis of the targets measured by the FMICW radar. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are composed of set sensor nodes communicating through wireless channels with limited resources. Therefore, several routing protocols and approaches about energy efficient operation of WSNs have been proposed. Clustering algorithm based routing protocols are well used for efficient management of sensing sensor node energy resources. However, many researches were focused on optimization of well-known hierarchical routing approaches of WSNs using fuzzy logic system or heuristic methods. Most of these routing approaches haven't considered the impact of heterogeneity of sensor nodes, in terms of their energy which is equipped with additional energy resources. In this paper, we propose stable election using three fuzzy parameters approach (SEFP) using fuzzy logic system for heterogeneous WSNs. The main purpose of this routing approach is to improve the network lifetime and particularly the stability period of the network. In the SEFP approach, the sensor node with the maximum chance value becomes a cluster head (CH) based in three fuzzy parameters such as residual energy of each sensor node, closeness to base station (BS), and sum of distances between particular sensor node and other sensor nodes (area distance). The Simulation results of heterogeneous WSNs shows that our approach using fuzzy logic system always preserves more energy as compared to well-known protocols such as LEACH and SEP. additionally, we found that our approach SEFP outperforms LEACH and SEP protocols in prolonging the lifetime and the stability period for heterogeneous WSNs. [ABSTRACT FROM AUTHOR]

Today, using intelligent transport systems such as identifying vehicle type for monitoring traffic in urban areas can advantage a lot. In this paper, a new method has been presented to detect vehicle type with only one reference image per class. Our algorithm is based on searching mean gradients and analysing these changes by Daubechies wavelet transformation. Firstly, a feature vector is obtained based on the car boundary changes of the side view image in proposed system. This vector is then analyzed by Daubechies wavelet transformation and three statistical criteria; variance, norm-1 and norm-2 are extracted from wavelet coefficients. Finally, a similarity factor is defined to detect the same type of vehicles. The proposed algorithm is resistant against car edge negligible changes and the experimental results indicate the high performance of system in detecting the vehicle types. [ABSTRACT FROM AUTHOR]

In this paper some procedures for accurately defining the kinematic trajectories described by skid-steering robots by using only the kinematic data of the wheels (or tracks) are presented and discussed. These procedures have been analysed with several experimental tests carried out moving a rover skid-steering robot on different surfaces. The particularity of the skid steering mobile robots is the presence of the high slippage effects that heavily influence the correct kinematic reconstruction by using the classical kinematic equation. For this reason, the possibility of using particular strategies based on the instantaneous centre radiuses is here considered; these strategies use parameters such as the equivalent 'carriageway', the slipping coefficients and the slipping ratio for including the effect of vehicle dynamics. Moreover, the effect of different surfaces is evident on the parameters that characterize the considered strategies for kinematic reconstruction; anyway, the high repeatability of the experiments carried out on the same conditions and a certain trend of the slipping ratio that seems to characterise the different types of surfaces, allow foreseeing positive developments of the considered strategies. The experiments have been carried out on a particular skid-steering robot (rover 4WD1); the generalization of the results for other types of skid-steering robot may be easily foreshadowed. The original value of the paper is related to the systematic experimental validation of the procedures indicated and to the comments that may be very useful in defining the limits of the procedure for the kinematic reconstruction with high slipping effects. [ABSTRACT FROM AUTHOR]

This paper proposes a real-time urban air quality forecasting method based on monitoring sites and Thiessen polygon. Firstly, the concentration of pollutants affecting air quality is obtained through the real-time observations of the monitoring sites deployed in wireless sensor network, according to which the air quality index (AQI) can be calculated and air quality levels and categories can be graded. Then, Thiessen polygons are constructed based on the monitoring sites and the air quality conditions from the only site within any polygon will be the representative to that of any other points within this polygon. Finally, the monitoring sites and Thiessen polygons rendered with standard air quality colors will be visualized on a geographical map for the realization of real-time forecasting method taking Thiessen polygons as forecasting units. Taking Shanghai city as an example, a real-time and visualized air quality prediction platform has been constructed in downtown Shanghai city, the real-time visualization of urban air quality forecasting and early warnings under the constraints of Thiessen polygon have been realized. [ABSTRACT FROM AUTHOR]

A basic tenet of wireless sensor networks is that processing of data is less expensive in terms of power than transmitting data. A data compression method is proposed to limit the amount of data transmitted within the network. In this paper, we propose a novel data compression algorithm suitable for low power computing devices. In our method, a data point density algorithm is used to determine which points to discard in a given data region. This algorithm is applied to uniform sections throughout the entirety of the data set. Regions with the highest data point density will be represented by a single point. The resulting data points then form the compressed data set. The transmission and subsequent processing of this compressed data set will cause less strain on the network than the original data set, while still maintaining the required information of the original data set. A tool is developed to test the method and compare it with other methods. [ABSTRACT FROM AUTHOR]

Recognizing how developing browsing behaviour could result in greater return for service providers through more efficient data usage without compromising Quality of Service (QoS), this paper proposes a new innovative model to describe the distribution and occurrence of behavioural errors in data usage models. We suggest: a) that the statistics of behavioural errors can be described in terms of locomotive inefficiencies, which increases error probability depending on the time elapsed since the last occurrence of an error; b) that the distribution of inter-error intervals can be approximated by power law and the relative number of errors. Comparing immersive similarities of data usage and foraging behaviours according to the Levy-Flight hypothesis, the length of the usage can be feasibly increased with less errors and eventually increase average revenue per user (ARPU). The validity of the concept is demonstrated with the aid of experimental data obtained from test software called Learn-2-Fly which sought to make browsing behaviours more efficient through user responses to stimuli created by an artificially intelligent engine. Although there were limitations on the scope of this test, a noticeable change in the user browse duration occurred over the duration of testing periods, with test subjects spending more time browsing and reacting to intended visual stimuli. The study establishes the opportunity to provide a higher quality of service to the end-user, whilst also offering a dynamic opportunity to increase revenue streams. Further consequences, refinements, and future works of the model are described in the body of the paper. [ABSTRACT FROM AUTHOR]

This paper proposes the Fictitious Reference Iterative Tuning-Particle Swarm Optimization (FRIT-PSO) method to design PID controllers for feedback control systems. The proposed method is an offline PID parameter tuning method. Moreover it is not necessary to derive any mathematical models of objected control systems. The proposed method is demonstrated by comparing with the FRIT method in numerical examples and an experiment. [ABSTRACT FROM AUTHOR]

After the completion of the process of industrialization in the world, a large number of electrified equipment appeared, people's daily life is also more and more dependent on electricity security, electricity consumption has risen sharply. At present, various lights driven by electricity play a crucial role in our daily life, which is also the main cause of electricity consumption. We often notice that even when the room is empty, or during the day, the lights are still on, which is a waste of electricity. The waste of power resources caused by traditional lighting equipment cannot be ignored. Therefore, intelligent home furnishing equipment is the favored object of people. So here for a kind of indoor lighting control system is designed, in order to meet the lighting needs on the basis of more humane, more importantly, can save power resources. With the rapid application of automation in daily life and the continuous development of computer technology, lighting control has become increasingly intelligent and automated. The control function of the system is realized by the STM32F103 chip, the illumination is automatically detected by the BH1750 module, and the time parameters are recorded and fed back by the DS3231 clock module. The infrared reflection sensor is used to detect whether there are people in the room. When there is no one, the light will be automatically turned off to save energy. If there are people, when the ambient light intensity is lower than the set value, the light will be automatically turned on to ensure the comfort of the ambient brightness. And can use OLED module real-time display indoor light intensity, number of people and working time. This indoor lighting control system can not only automatically turn on the light according to the environment, but also detect whether there is a human body in the current environment and turn on or off the light by itself, which has more practical significance. [ABSTRACT FROM AUTHOR]

The development and studies related to carbon nanotubes, due to their physical properties and small sizes, are revealing new applications in the medical field. The present paper is proposing a non-invasive method of patient glycemia measurement by mean of carbon nanotubes based sensor. Due to their small sizes and elastic properties, carbon nanotubes are able to oscillate under the weight of small molecules capable of fixing on their body structure. After piezoelectric activation, the carbon nanotubes sensor based, is able to detect the variation of oscillations produced in nanotubes due to acetone molecules diffused through a selectively permeable membrane from the exhaled air, and attached to the nanotubes. The mathematical model taken into accont shows a linear dependence between the concentration of acetone in blood and glycemia, and makes the carbon nanotube sensor suitable for indirect estimation of the glycemia by noninvasive measurements made on the exhaled air sample, providing zero risk for the patient and absence of stress during the measurements. [ABSTRACT FROM AUTHOR]

In this paper, a new non-contact method for detection of impact damage in carbon fibre-reinforced polymer composites with a complementary split-ring resonator sensor is proposed. The resonance frequency is evaluated as an indicator of the presence of damage. The resonator is made on a printed circuit board, and in the experimental setup it is positioned close to the area of interest. Electromagnetic models are built, and from the resonant responses the appropriate frequency range used for the test is determined. The active sensing element in the resonator is found from the analysis of the magnetic field distribution. The parametric study performed shows that a larger frequency change occurs for a wider impacted region, which is of great use for practical applications. The proposed method is validated by the experimental results, where a frequency shift of 65 MHz was observed for a 0.36 mm deep dent. [ABSTRACT FROM AUTHOR]

This paper deals with the concept, the design and an experimental prototype of a low-cost aerometric sensor system for sport aviation. The performance of an experimental prototype of the sensor system is compared with the performance of a standard system. The possible further development of the system is also mentioned. The system presented here originates from and extends earlier basic work on an aerometric system for general aviation. The extension implements and focuses general designs from the earlier system for real use of the current system in the category of sport airplanes and gliders. The objective of the system is to reduce the cost of aircraft instrumental equipment, and to provide improved measurement performance of the aerometric system using an innovative approach of altitude measurements. In the experimental system, altitude is still determined based on the classic barometric principle. However, for measurements of atmospheric pressure, the differential pressure sensor is used primarily in combination with a low-cost absolute pressure sensor, which also measures in a differential mode. [ABSTRACT FROM AUTHOR]

The paper offers an overview of signal processing approaches that are suitable for monitoring of persons by means of ultrawideband sensors. The "Monitoring of persons" is related to their detection, localization, and tracking and in the case of static persons, also to the monitoring of their vital signs such as the breathing frequency and the heart rate. This paper discusses basic principles in the monitoring of persons who can be moving, static, or changing the character of their movement. In the case of static persons, the paper describes signal processing methods suitable for contactless estimation of their breathing frequency and the heart rate. Monitoring of persons using UWB sensors is attractive in many application scenarios such as emergency, rescue, medical, etc. Therefore, we believe that this comprehensive survey brings a lot of interesting information to researchers and specialists working in the field of contactless monitoring of persons. [ABSTRACT FROM AUTHOR]

Today, the sensing devices play an important role for various system automation and monitoring of different physical and chemical parameters. Nonlinearity is an important long-time issue for most of the sensors, so to compensate nonlinearity, various linearization schemes are reported in the literature. The accuracy of linearization schemes depends on the type and the nonlinearity value of the sensor output. Since it is difficult to find an exact polynomial equation or other functions to represent the response curve; it gives more error when the measurement parameter is determined from the inverse approximation functions. As many sensors are used for different applications, the linearized characteristics will simplify the design, calibration, and accuracy of the measurement. This paper presents a review of different methods applied to linearize sensor characteristics reported in the literature. Due to availability of high-performance analog devices, analog methods are still popular among many researchers. However, due to the advancement of IC technologies, hardware implementation of the software methods can be done easily with reduced time, cost, and more accuracy, so the digital methods combined with software techniques perform the job with better flexibility and efficiency. [ABSTRACT FROM AUTHOR]

An amount of data measured with sensors is increasing year to year. Every sensor has a location and sensor data are mostly measured for long time period, so visualization of location and regular updating of visualized value is necessary. Various characteristics (e.g. meteorological conditions) can be automatically read at frequent intervals and those readings can be aggregated into the interactive map visualization. This map must be not only legible but also understandable also for readers that are experts in their specialisation, however, not in cartography. This paper presents possibilities of using and implementation of adaptive cartography and visual seeking principles for interactive visualization and analysis of sensor based data measured in real time. Our solution is described on experimental application for precise farming that we developed during research project Agrisensor. [ABSTRACT FROM AUTHOR]

Measurement of water content in oil-water mixing flow was restricted by special problems such as narrow measuring range and low accuracy. A simulated multi-sensor measurement system in the laboratory was established, and the influence of multi-factor such as temperature, and salinity content on the measurement was investigated by numerical simulation combined with experimental test. A soft measurement model based on rough set-support vector machine (RS-SVM) classifier and genetic algorithm-neural network (GA-NN) predictors was reported in this paper. Investigation results indicate that RS-SVM classifier effectively realized the pattern identification for water holdup states via fuzzy reasoning and self-learning, and GA-NN predictors are capable of subsection forecasting water content in the different water holdup patterns, as well as adjusting the model parameters adaptively in terms of online measuring range. Compared with the actual laboratory analyzed results, the soft model proposed can be effectively used for estimating the water content in oil-water mixture in all-round measuring range [ABSTRACT FROM AUTHOR]

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Copyright of Annual of Navigation is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An important prerequisite for creation of autonomous robot is the ability to create the map of the environment. Robots need to be able to construct a map of the environment and to use it for navigation. In this paper a multirobot mapping approach is proposed, where artificial landmarks (glyphs) are used for robot localisation and only simple sensors - bumper sensors - are available for obstacle detection. The proposed mapping system creates the map of the environment and allows changing the map rapidly in case of inaccurate robot position measurements or sensor errors. The system has a central server and robots use wireless network to communicate with the server. The mapping implementation takes into account the fact that the network has limited bandwidth and only limited amount of data can be sent. [ABSTRACT FROM AUTHOR]

Multiple sensors fusion plays a major role in situation awareness, especially in modern dynamic security monitoring and tracking applications. In this paper, we focus on a specific effective set of complementary sensors [Laser (for speed measurements), Sonar (for space scanning) and RF (for access rights)]. A novel multi-agent system is obtained by fusing the above types of sensory data taking advantages of similarity and complementarity concepts. Furthermore, Kalman Filter is utilized to track next state estimates of agent(s) in uncertain environment. Finally, our proposed system transforms system state to be able to make a security awareness decision, using type-2 fuzzy logic system to handle exhibited uncertainty, for asset scenery under surveillance. It is shown that the system performance can exhibit promising improvements for this dynamic security monitoring situation as a result of using the above complementary heterogeneous set of sensors. [ABSTRACT FROM AUTHOR]

Pneumatic actuators are highly nonlinear characteristics and uncertainties make it difficult to achieve high performances. The objective of this paper is to present a brief overview of pneumatic actuators based on modeling and control strategies that has been proposed by various researchers. Before the main discussion, some background information will be presented in a relation to pneumatic actuators. This review concludes with a short summary and discussion of modeling and control approaches of pneumatic actuators. The implication of this paper is for further improving the performance of existing pneumatic actuators. [ABSTRACT FROM AUTHOR]