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In machinery condition monitoring, it is often vital to consider information from multiple sources due to possible sensor failure or signal distortion, which may result in misclassification of the health status. An issue with multiple sensor data fusion, however, is that the classification can be affected by conflicting results between sensor signals. The proposed method uses a novel three-module approach to information fusion in order to address the problem. Features corresponding to signal integrity are extracted and employed for training a one-class support vector machine to detect unwanted distortions or sensor failures. Different classifiers are trained for the different sensor types available and each signal recorded is used to determine machine health. Decision-level fusion is conducted through a majority voting system using the integrity scores derived from the OCSVMs and the separate classification results. From this, a dynamically weighted fault diagnosis based on sensor signal quality is obtained. Experimental verification using vibration and acoustic emission signals show that the framework is viable and allows for an increased reliability in machinery health diagnosis. [ABSTRACT FROM AUTHOR]

The design and usage of the addressed combined fiber-optic sensors (ACFOSs) and the multisensory control systems of the greenhouse gas concentration on their basis are investigated herein. The main development trend of the combined fiber-optic sensors (CFOSs), which consists of the fiber Bragg grating (FBG) and the Fabry–Perot resonator (FPR), which are successively formed at the optical fiber end, is highlighted. The use of the addressed fiber Bragg structures (AFBSs) instead of the FBG in the CFOSs not only leads to the significant cheapening of the sensor system due to microwave photonics interrogating methods, but also increasing its metrological characteristics. The structural scheme of the multisensory gas concentration monitoring system is suggested. The suggested scheme allows detecting four types of greenhouse gases (CO2, NO2, CH4 and Ox) depending on the material and thickness of the polymer film, which is the FPR sensitive element. The usage of the Karhunen–Loève transform (KLT), which allows separating each component contribution to the reflected spectrum according to its efficiency, is proposed. In the future, this allows determining the gas concentration at the AFBS address frequencies. The estimations show that the ACFOS design in the multisensory system allows measuring the environment temperature in the range of −60...+300 °C with an accuracy of 0.1–0.01 °C, and the gas concentration in the range of 10...90% with an accuracy of 0.1–0.5%. [ABSTRACT FROM AUTHOR]

Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring. Within the scope of the joint science and sports event "Elbschwimmstaffel" (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality. The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation. An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers. [ABSTRACT FROM AUTHOR]

Due to the fact that single sensor data contains only partial information about complex systems, multiple sensors are often embedded to simultaneously monitor the health state and predict the remaining useful life (RUL). This brings new challenges to traditional approaches that focus on single sensor in terms of data fusion, optimization, and uncertainty management. To address these challenges, this article proposes a novel RUL prediction and uncertainty management framework for multisensor systems. In this framework, a composite 1-D health indicator (1-D HI) is obtained from multiple sensors by optimizing some HI characteristics, including monotonicity, robustness, fitting error, and range information, to better describe the underlying degradation process. A multiobjective grasshopper optimization algorithm is used to achieve the optimal weight vector of the fusion model. Then, an unscented particle filter is introduced to predict the RUL by combining the degradation model constructed from HI and the composite 1-D HI as measurement. To manage the uncertainty in prognosis, a probability distribution of failure threshold and noise parameter adjustment are developed. Experimental results on aircraft turbine engine degradation and comparison with state-of-the-art methods are presented to demonstrate the effectiveness of the proposed framework in RUL prediction of multisensor systems. [ABSTRACT FROM AUTHOR]

A portable multisensor frequency modulated continuous radar (FMCW) networked radar concept is presented for the localization of persons trapped in debris in building collapse scenarios. A 2-D localization algorithm is evaluated in a field test to demonstrate successful localization detection of respiration micromovements. [ABSTRACT FROM AUTHOR]

We propose a robust attitude estimation method for multisensor systems with heavy-tailed noise. The attitude model is represented by a quaternion, and the propagation process in the filter is based on a gyro-based model. To avoid the constraint of quaternion, the quaternion is converted to modified Rodrigues parameters during the prediction and update process. Instead of the minimum mean square error principle, the maximum correntropy criterion is applied in the update process, which is robust to heavy-tailed noises. Considering the linear form in the update process, the information filtering algorithm is applied in the proposed method to simplify the calculation of multisensor information fusion. Moreover, the application of information filtering algorithm can also avoid the numerical problem that zero weight functions cannot be incorporated into the Gaussian filtering framework. Simulations for several cases are performed, and the simulation results indicate the robustness and efficiency of the proposed filter. [ABSTRACT FROM AUTHOR]

The problem of multisensor multitarget state estimation in the presence of constant but unknown sensor biases is investigated. The classical approach to this problem is to augment the state vector to include the states of all the targets and the sensor biases, and then implement an augmented state Kalman filter (ASKF). In this article, we propose a novel decoupled Kalman filtering algorithm. The decoupled Kalman filtering first processes each target in a separate branch, namely the single-target Kalman filtering branch, where the single-target states and the sensor biases are estimated. Then the bias estimate is refined by fusing the former bias estimates across all the single-target Kalman filtering branches. Finally, the refined bias estimate is fed back to each single-target Kalman filtering branch to improve the target state estimation. We prove that the proposed decoupled Kalman filtering is exactly equivalent to the ASKF in terms of the estimation results under a usual initial condition. The equivalence is also confirmed via the numerical example. Moreover, we further validate the proposed algorithm using the field experimental data of a multistatic passive radar. [ABSTRACT FROM AUTHOR]

Medium dense hardwoods (HWs) show higher tensile strength (TS) values than softwoods (SWs). These advantages cannot be utilised effectively because HW grading is not well developed. The aim of the present paper was to analyse the utilisation potential of European ash (Fraxinus spp.) and maple (Acer spp.) grown in Central Europe, which were graded by different methods. The visual grading characteristics of 869 HW boards were determined and the dynamic modulus of elasticity (MOEdyn) and X-ray attenuation (XRA) were measured by an industrial scanner. The specimens were subsequently tested in tension according to EN 408:2010 and according to German visual grading rules show strength values of 28 MPa and 30 MPa, respectively. Machine strength grading and for a combination of manually assessed boards and MOEdyn give rise to higher strength data. MOEdyn, in particular, results in lamella data with 62 MPa for ash and 42 MPa for maple. There is good agreement with recently presented HW tensile profiles. Machine grading with a multisensor system allows better strength prediction compared to the MOEdyn or visual strength grading. Best performance is achieved by a combined grading approach. [ABSTRACT FROM AUTHOR]

The aim of the project presented in this article was to design a system which allows for assessment of indoor environmental conditions, with a special consideration regarding the comfort of occupants. The system consists of two microprocessor devices with numerous sensors, as well as a PC application which includes fuzzy inference module. Fuzzy inference algorithm allows for comfort assessment based on data gathered by sensors. It can also help to analyse the efficiency of HVAC systems. The article includes description of the system's functions and selection criteria for sensors taking into account of measurands. Also described in this paper is the construction of knowledge base, based on information from environmental standards and experts' statements. The constructed system was tested and examined, to confirm its application in practical comfort assessment and to highlight the advantages of using fuzzy logic in the process of analysing measured parameters and inference, which captures the way living beings process data. [ABSTRACT FROM AUTHOR]

Abstract: In the paper, the percolation model (PM) developed earlier for description of data associated with complex fluids was successfully applied. As an example, we analyzed the virgin olive oil electrochemical data. In spite of the fact that this complex fluid as olive oil contains more than 100 different chemical components, it becomes possible to describe the dependencies J(U) (defined in electrochemistry as the voltammograms (VAGs)) in terms of the percolation model. This model takes into account the behavior of the conducting/percolation currents in meso‐region and dependencies of the fractal dimension versus applied potential U. It was proved that this model was applicable for three basic regions: cathode region (where positive charges are mainly concentrated), capacitor (Faraday) region and anode region (where negative charges were mainly located). For these three basic conventional regions known in electrochemistry, we obtained the excellent coincidence of the fitting function obtained in the frame of PM with experimental data. These results prove that this meso‐model can be applicable for description of wide set of data including different complex solutions and fluids. [ABSTRACT FROM AUTHOR]

This paper focuses on the linear optimal recursive sequential fusion filter design for multisensor systems subject to stochastic parameter perturbations, fading measurements, and correlated noises. The stochastic parameter perturbations existing in the state model are described by white multiplicative noises. The fading measurement phenomena for different sensors are described by independent random variables with known statistical properties. Moreover, the measurement noises of different sensors are correlated with each other and also correlated with the system noise at the same time step. First, a model equivalent to the original system is established by transferring the multiplicative noises into the additive noises. Then, based on the equivalent model and an innovation analysis method, a sequential fusion filter in the linear minimum variance sense is proposed to solve the linear optimal state estimation problem in real time according to the arriving order of measurements from different sensors. Finally, the equivalence on estimation accuracy of the proposed sequential fusion filter and the centralized fusion filter is strictly proven, which shows the optimality of the proposed sequential fusion algorithm. Moreover, the proposed sequential fusion filter has a reduced computational burden. Compared with the distributed matrix-weighted fusion filter, the computation of cross-covariance matrices is avoided and the estimation accuracy is improved. Finally, a simulation example verifies the effectiveness of the proposed sequential fusion filtering algorithm. [ABSTRACT FROM AUTHOR]

The possibility of using solid-state and liquid PVC-membrane electrodes based on ionic liquids to design a potentiometric multisensor system is assessed. Ionic liquids with 1,3-dihexadecylimidazolium cation and chloride, bromide, iodide, and nitrate anions are used. The sensitivity parameters of the sensors are determined. A multisensor array is applied to detect chloride and iodide anions in the multicomponent mixture. The designed system is used to discriminate between mineral waters of different compositions by applying the method of principal component analysis (PCA). [ABSTRACT FROM AUTHOR]

The results of studying characteristics of potentiometric DP-sensors (sensors with the Donnan potential as their analytical signal) are presented for alkaline solutions of a sulfur-containing amino acid with perfluorosulfonic cation exchange membranes subjected to thermal treatment and mechanical deformation at different relative humidity. Correlation between the distribution of sensitivity of DP-sensors towards cations and anions and diffusion permeability of membranes was found. A multisensor system including two DP-sensors based on membranes with optimized properties and a glass electrode for codetermination of potassium cations and amino acid anions and zwitterions in solutions at pH > 7 are developed. [ABSTRACT FROM AUTHOR]

Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of landcover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach. [ABSTRACT FROM AUTHOR]

A resolution‐reconfigurable, bandwidth‐scalable analogue‐to‐digital converter (ADC) with programmable‐gain (PG) functionality for a multi‐sensor system, which encompasses various signals such as bio‐signals and battery‐level, is presented. In PG and low‐power mode, a PG first‐order noise‐shaping (NS) successive‐approximation register (SAR) ADC achieves 8.4‐to‐10.2‐bit operating up to 16 kHz while providing a gain of 1/2/4. The PG NS SAR ADC can be reconfigured as an adder and a quantiser in a delta‐sigma (ΔΣ) modulator enhancing the order of the modulator for high‐resolution. The third‐order ΔΣ modulator achieves 16.1 bits in a bandwidth of 1 kHz. The work is implemented in a 0.18 μm CMOS process with a 1.8 V power supply. [ABSTRACT FROM AUTHOR]

Inertial navigation system (INS)/global navigation satellite system (GNSS)/ celestial navigation system (CNS) integration is a promising solution to improve the performance of navigation due to the complementary characteristics of INS, GNSS, and CNS. Nevertheless, the information fusion involved in INS/GNSS/CNS integration is still an open issue. This paper presents a matrix weighted multisensor data fusion methodology with two-level structure for INS/GNSS/CNS integrated navigation system. On the first level, GNSS and CNS are integrated with INS by two local filters respectively to obtain local optimal state estimations. On the second level, two different matrix weighted data fusion algorithms, one based on generic weighting matrices and the other based on diagonal weighting matrices, are developed to fuse the local state estimations for generating the global optimal state estimation. These two algorithms are derived in the sense of linear minimum variance, which provide unbiased fusion results no matter whether the local state estimations are mutually independent or not. Thus, they overcome the limitations of the federated Kalman filter by refraining from the use of the upper bound technique. Compared with the data fusion algorithm based on generic weighting matrices, the computational load involved in the one based on diagonal weighting matrices is significantly reduced, even though its accuracy is slightly lower due to the disregard of the coupled relationship between the components of the local state estimations. The effectiveness of the proposed matrix weighted multisensor data fusion methodology is verified through Monte Carlo simulations and practical experiments in comparison with the federated Kalman filter. [ABSTRACT FROM AUTHOR]

Retail price of food products is a complex interplay between multiple factors. Overall product quality has got one of the most serious impacts on the price in many situations. In the present study, an artificial sensory system (potentiometric electronic tongue) was employed for the analysis of black tea samples purchased in the retail stores in Spain and Russia. It was possible to relate the response of a potentiometric sensor system with retail prices of various black tea samples by means of partial least squares (PLS) regression. PLS regression models are allowed for the prediction of retail price with mean relative errors of about 15 and 25 % for Spain's tea bags and for loose-packed tea from Russia, respectively. The suggested approach shows a promise for the development of an instrumental analytical technique for regulatory authorities to fight with counterfeits and for commercial purposes to evaluate market space. [ABSTRACT FROM AUTHOR]

The design and performance of potentiometric multisensor system made in solid-contact technology is described. Both, the measuring electrodes as well as the reference electrode are in a compact cell. The system allows for simultaneous measurement of various ions. The characteristics of the electrodes for Na+, K+ and Ca2+ ions were determined using the designed system and compared with ISEs of the same membrane composition in classical system. The potentiometric cells were used to determine the concentration of the ions in synthetic and real human sweat samples. The obtained results for synthetic samples were compared to the expected values and for collected real sample of sweat were compared to the results obtained by flame photometry (Na+, K+) and by AAS (Ca2+). [ABSTRACT FROM AUTHOR]

This paper presents an alternative method utilizing real-time measurements of existing rotor magnetic field in the feedback loop for multi degree-of-freedom (DOF) orientation control of a permanent-magnet spherical motor (PMSM) characterized with redundant inputs. As the direct field-feedback control (DFC) system requires only measured magnetic fields, it eliminates the need of an external orientation sensing system and its major components can operate independently and permit parallel processing. The DFC method greatly reduces accumulated errors and time delay due to serial computations commonly encountered in existing methods that rely on orientation-dependent models for feedback control of a multi-DOF PMSM. In this paper, the method for determining the bijective relationship between the rotor orientation and measured magnetic field is presented, which enables the replacement of the orientation error by the magnetic field error in the control law. Using analytical magnetic field and torque models, the DFC design method is illustrated with two examples: a one-DOF motion system and a three-DOF PMSM; the latter has been experimentally implemented, for which an embedded multisensor system with connected bijective domains is designed. Excellent trajectory control results were obtained validating the concept feasibility of the DFC method for the PMSM. [ABSTRACT FROM PUBLISHER]

In this study, an effective wavelet packet decomposition (WPD)‐based robust transcale decentralised estimation fusion algorithm is proposed for multisensor systems. The standard state‐space models of wavelet packet coefficients at the coarsest scale decomposition layer are established by Haar WPD. Based on the above models, the decentralised H∞ filtering fusion formulae is employed to obtain the fusion estimates at the coarsest scale decomposition layer, and these estimates are then used to reconstruct the estimates at the finest scale by an inverse WPD transform. At last, the feasibility analysis of the proposed algorithm is given. Two simulation examples are presented to illustrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Assistive Devices are employed in various applications, ranging from in-home monitoring of medical symptoms to support in reminding activities of daily living. In these devices, crucial characteristics are non-obtrusiveness, low-maintenance, and simplicity for the user, for data extraction as well as for application development. The Set for Intuitive Movement and Proximity Logging for Everyday (SIMPLE) use focuses on the research and development of applications related to the detection and measurement of movement and interaction, i.e., proximity to objects of daily use. It encompasses the sensors themselves, charging stations, as well as devices for online and offline data collection, forwarding, and extraction. It also supports the adjustment of basic recording parameters as well as changing the device's firmware needing only a memory card reader. Basic power saving and movement detection algorithms are already implemented. SIMPLE-use closes a gap, offering both movement and interaction acquisition in one easy to use sensor set. [ABSTRACT FROM PUBLISHER]

Advances in electronics, sensor technology, information science, electrical and computer engineering give rise to emerging technologies, some of which could be applied to the inspection, monitoring, and condition assessment of buried water mains. This paper presents a state of the review of sensor technologies used for monitoring indicators pointing to pipe structural deterioration. The potential for multi-sensor system and sensor data fusion for condition-based maintenance are also discussed. [ABSTRACT FROM PUBLISHER]

An important prerequisite for successful multisensor integration is that the data from the reporting sensors are transformed to a common reference frame free of systematic or registration bias errors. If not properly corrected, the registration errors can seriously degrade the global surveillance system performance by increasing tracking errors and even introducing ghost tracks. The relative sensor registration (or grid-locking) process aligns remote data to local data under the assumption that the local data are bias free and that all biases reside with the remote sensor. In this paper, we consider all registration errors involved in the grid-locking problem, i.e., attitude, measurement, and position biases. A linear least squares (LS) estimator of these bias terms is derived and its statistical performance compared to the hybrid Cramér–Rao lower bound (HCRLB) as a function of sensor locations, sensors number, and accuracy of sensor measurements. [ABSTRACT FROM AUTHOR]

Force estimation plays a very important role in many application areas. The disturbance observer is significantly becoming the preferred approach since it offers distinct advantages of improving the robustness of force control and the accuracy of force estimation. However, one of the main disadvantages is the limitation from white Gaussian noise. This paper proposes an improved design methodology for the disturbance observer. The main contribution of the work described in this paper is the design of disturbance observers combined with a Kalman filter with a multisensor system. From the experimental results, white Gaussian noise was reduced and fast response in contact motion was achieved. The effectiveness of the proposed disturbance observer has been confirmed through comparisons with conventional methods in 1-d.o.f. linear motor systems. [ABSTRACT FROM AUTHOR]

Basic principles of a new potentiometric sensor are considered. Its analytical signal is the Donnan potential at the ion-exchange polymer/studied solution of electrolyte interface. Assessments of potential drops at individual interfaces are presented, same as estimates of diffusion potentials in the electrochemical circuit for measurement of the sensor response. It is shown that the overall contribution of the values of all potentials to EMF of the electrochemical circuit, except for the Donnan potential, at the ion-exchange polymer/studied solution interface are negligibly low as compared to the experimental values of the circuit EMF in the studied systems. Certain regularities of the Donnan potential formation are studied in the systems with the polymers of different structure and solutions containing inorganic ions and organic electrolytes in different ionic forms. The possibility is shown of using a sensor with such an analytical signal as the Donnan potential for assay of amino acids, vitamins, and drug substances in aqueous solutions. The sensor was used as a selective electrode for determination of lysine in aqueous solutions with neutral amino acids in the range of pH 5.0-7.0 and glycine in aqueous alkali solutions in the range of pH 9.00-11.00. The developed sensor is introduced as a cross-sensitive electrode into the array of multisensor systems for multicomponent quantitative analysis of the lysine monohydrochloride, thiamine chloride, novocaine hydrochloride, lidocaine hydrochloride solutions containing potassium and sodium chlorides. The measurement error of electrolytes in aqueous solutions did not exceed 10%. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop a system for reconstructing an image of two parameters, e.g., temperature and body composition, in the same region of a living body. In this paper, a new multifunctional sensor for simultaneous measurements of the ultrasonic and electrical properties of an object is proposed. The proposed sensor, which uses a pair of piezoelectric ceramic transducers, measures not only the ultrasonic property of the object but also its electrical property by using the sur- face electrodes of each piezoelectric ceramic transducer. In the experiment, the propagation time and conductance of a simple cell model for the living body are simultaneously measured by the proposed sensor. The sodium chloride (NaCI) concentration, which is the composition that determines the conductivity of the model, and temperature are estimated from the measurements. It was found that the ultrasonic and electrical properties could simultaneously be measured. In addition, two parameters of the model could be estimated from these measured values. Therefore, it is suggested that the proposed sensor has the potential for application, although there are some problems that must be solved. [ABSTRACT FROM AUTHOR]

A cross-layered slotted ALOHA protocol is proposed and analyzed for distributed estimation in sensor networks. Suppose that the sensors in the network record local measurements of a common event and report the data back to the fusion center through direct transmission links. We employ a channel-aware transmission control where the transmission probability of each sensor is chosen according to the quality of its local observation and transmission channels. As opposed to maximizing the system throughput, our goal is to design transmission control policies that optimize the estimation performance. Two transmission control strategies are proposed: the maximum mean-square-error (MSE) reduction (MMR) scheme and the suboptimal two-mode MSE-reduction (TMMR) scheme. The MMR maximizes the MSE-reduction of the estimate after each time slot. However, this method requires knowledge of the number of active sensors and the accumulated estimation performance in each time slot, which must be provided through feedback from the fusion center. In TMMR, the sensors switch between two predetermined transmission control functions without explicit knowledge of the estimation performance and the number of active sensors in each time slot. Moreover, we notice that, if new observations are made by the sensors in each time slot, diversity combining techniques can be employed to fully exploit the data that the sensors measure over their idle time slots. Specifically, we perform selective combining on the observations that are made in between transmissions. As a result, we are able to exploit both the spatial and temporal diversity gains inherent in the multisensor system. [ABSTRACT FROM PUBLISHER]

In this paper, a new electronic system for gas detection is presented. Particular attention is focused on electronic noses that employ several resistive sensors. New resistive sensors may have high value due to new substances (TiO2) or to low-cost fabrication process and, supposing to use these sensors together with traditional ones (SnO2), a novel instrument to manage high-value resistive sensors varying over a wide range, from kilohms to gigohms is required. The proposed hardware approach is a modular architecture which takes advantage from an improved resistance-to-period converter, where sensors are DC powered. Experimental results show a relative standard deviation below 0.01% and a relative displacement to the reference line less than 1% over six decades if commercial resistors are considered. A prototype has been realized to manage up to eight sensors, detect and estimate substance concentrations, and communicate results to the Internet. [ABSTRACT FROM PUBLISHER]

This paper concerns the sequential estimation of a hidden state vector from noisy observations delivered by several sensors. Different from the standard framework, we assume here that the sensors may switch autonomously between different sensor states, that is, between different observation models. This includes sensor failure or sensor functioning conditions change. In our model, sensor states are represented by discrete latent variables, whose prior probabilities are Markovian. We propose a family of efficient particle filters, for both synchronous and asynchronous sensor observations as well as for important special cases. Moreover, we discuss connections with previous works. Lastly, we study thoroughly a wheel land vehicle positioning problem where the GPS information may be unreliable because of multipath/masking effects [ABSTRACT FROM PUBLISHER]

We present a new geomagnetic field measurement system for the detection of archaeological signatures in the soil. The system provides a unique fast mapping of large areas with high magnetic field gradient resolution as well as lateral precision. The data acquired by the device are geographically referenced and suitable for embedding in a Geographic Information System (GIS). [ABSTRACT FROM AUTHOR]

Prior knowledge of the noise present in a color image acquisition device is very important in estimating colorimetric values or in recovering the spectral reflectances of pixels of objects being imaged, since these values are greatly influenced by the noise. In this paper, a new model is proposed for the determination of the noise variance of a multispectral color image acquisition system and experimental results to demonstrate its accuracy are presented. It is demonstrated that the noise variance of an actual multispectral color image acquisition system computed by the proposal agrees fairly well with the variance which minimizes the mean-square error of the recovered reflectances by the Wiener filter. As an application of the proposal, it is shown that spectral reflectances of an art painting are recovered accurately by the use of sensor responses without prior knowledge of objects being imaged and noise present in an image acquisition system. [ABSTRACT FROM AUTHOR]

This letter explores the distributed multisensor dynamic system, which has uniform sampling velocity and asynchronous sampling data for different sensors, and puts forward a new gradation fusion algorithm of multisensor dynamic system. As the total forecasted increment value between the two adjacent moments is the forecasted estimate value of the corresponding state increment in the fusion center, the new algorithm models the state and the forecasted estimate value of every moment. Kalman filter and all measurements arriving sequentially in the fusion period are employed to update the evaluation of target state step by step, on the condition that the system has obtained the target state evaluation that is based on the overall information in the previous fusion period. Accordingly, in the present period, the fusion evaluation of the target state at each sampling point on the basis of the overall information can be obtained. This letter elaborates the form of this new algorithm. Computer simulation demonstrates that this new algorithm owns greater precision in estimating target state than the present asynchronous fusion algorithm calibrated in time does. [ABSTRACT FROM AUTHOR]

In the present work, the use of the cluster analysis method in the "fuzzy logic" concept for the optimization of the cross-selective sensor arrays ("electronic nose", EN) is considered. This approach enables to purposefully form the sensor arrays with definite chemical functionality optimized for the solution of the specific applied problems. The criteria of the optimization of the sensor response, number and type of the sensor elements are considered with the goal to improve the classification of widely used pharmaceutical products. The optimization of EN array in the kinetic mode and selection of the most informative part of the sensor response enabled to reduce the analysis time, and also the number of sensors in array, to improve the discriminatory capability of the whole array. Being based on the analysis of response kinetic peculiarities, the physical mechanisms determining the peculiarities of adsorption-desorption processes at the interface have been considered. [ABSTRACT FROM AUTHOR]

The field of air-quality monitoring is gaining increasing interest, with regard to both indoor environment and air-pollution control in open space. This work introduces a pattern recognition technique based on adaptive K-nn applied to a multisensor system, optimized for the recognition of some relevant tracers for air pollution in outdoor environment, namely benzene, toluene, and xylene (BTX), NO2, and CO. The pattern-recognition technique employed aims at recognizing the target gases within an air sample of unknown composition and at estimating their concentrations. It is based on PCA and K-nn classification with an adaptive vote technique based on the gas concentrations of the training samples associated to the K-neighbors. The system is tested in a controlled environment composed of synthetic air with a fixed humidity rate (30%) at concentrations in the ppm range for BTX and NO2, in the range of 10 ppm for CO. The pattern recognition technique is experimented on a knowledge base composed of a limited number of samples (130), with the adoption of a leave-one-out procedure in order to estimate the classification probability. In these conditions, the system demonstrates the capability to recognize the presence of the target gases in controlled conditions with a high hit-rate. Moreover, the concentrations of the individual components of the test samples are successfully estimated for BTX and NO2 in more than 80% of the considered cases, while a lower hit-rate (69%) is reached for CO. [ABSTRACT FROM PUBLISHER]

We report on the development of a simple and cost-effective potentiometric sensor array that is based on manual "drawing" on the polymeric support with the pencils composed of graphite and different types of zeolites. The sensor array demonstrates distinct sensitivity towards a variety of inorganic ions in aqueous media. This multisensor system has been successfully applied to quantitative analysis of 100 real-life surface waters sampled in Mahananda and Hooghly rivers in the West Bengal state (India). Partial least squares regression has been utilized to relate responses of the sensors to the values of different water quality parameters. It has been found that the developed sensor array, or electronic tongue, is capable of quantifying total hardness, total alkalinity, and calcium content in the samples, with the mean relative errors below 18%. [ABSTRACT FROM AUTHOR]

The significant improvement of quality of life achieved over the last decades has stimulated the development of new approaches in medicine to take into account the personal needs of each patient. Precision medicine, providing healthcare customization, opens new horizons in the diagnosis, treatment and prevention of numerous diseases. As a consequence, there is a growing demand for novel analytical devices and methods capable of addressing the challenges of precision medicine. For example, various types of sensors or their arrays are highly suitable for simultaneous monitoring of multiple analytes in complex biological media in order to obtain more information about the health status of a patient or to follow the treatment process. Besides, the development of sustainable sensors based on natural chemicals allows reducing their environmental impact. This review is concerned with the application of such analytical platforms in various areas of medicine: analysis of body fluids, wearable sensors, drug manufacturing and screening. The importance and role of naturally-occurring compounds in the development of electrochemical multisensor systems and arrays are discussed. [ABSTRACT FROM AUTHOR]

Water quality is one of the most critical indicators of environmental pollution and it affects all of us. Water contamination can be accidental or intentional and the consequences are drastic unless the appropriate measures are adopted on the spot. This review provides a critical assessment of the applicability of various technologies for real-time water quality monitoring, focusing on those that have been reportedly tested in real-life scenarios. Specifically, the performance of sensors based on molecularly imprinted polymers is evaluated in detail, also giving insights into their principle of operation, stability in real on-site applications and mass production options. Such characteristics as sensing range and limit of detection are given for the most promising systems, that were verified outside of laboratory conditions. Then, novel trends of using microwave spectroscopy and chemical materials integration for achieving a higher sensitivity to and selectivity of pollutants in water are described. [ABSTRACT FROM AUTHOR]

The paper describes the substance image formation based on the measurements by multisensor systems and the possibility of the development of a gas analysis device like an electronic nose. Classification of gas sensors and the need for their application for the recognition of difficult images of multicomponent air environments are considered. The image is formed based on stochastic transformations, calculations of correlation, and fractal dimensions of reconstruction attractors. The paper shows images created for substances with various structures that were received with the help of a multisensor system under fixed measurement conditions. [ABSTRACT FROM AUTHOR]

"Electronic tongues", "taste sensors", and similar devices (further named as "multisensor systems", or MSS) have been studied and applied mostly for the analysis of edible analytes. This is not surprising, since the MSS development was sometimes inspired by the mainstream idea that they could substitute human gustatory tests. However, the basic principle behind multisensor systems—a combination of an array of cross-sensitive chemical sensors for liquid analysis and a machine learning engine for multivariate data processing—does not imply any limitations on the application of such systems for the analysis of inedible media. This review deals with the numerous MSS applications for the analysis of inedible analytes, among other things, for agricultural and medical purposes. [ABSTRACT FROM AUTHOR]

Multisensor systems can overcome the limitation of measurement range of single-sensor systems, but often require complex calibration and data fusion. In this study, a three-dimensional (3D) measurement method of four-view stereo vision based on Gaussian process (GP) regression is proposed. Two sets of point cloud data of the measured object are obtained by gray-code phase-shifting technique. On the basis of the characteristics of the measured object, specific composite kernel functions are designed to obtain the initial GP model. In view of the difference of noise in each group of point cloud data, the weight idea is introduced to optimize the GP model, which is the data fusion based on Bayesian inference method for point cloud data. The proposed method does not require strict hardware constraints. Simulations for the curve and the high-order surface and experiments of complex 3D objects have been designed to compare the reconstructing accuracy of the proposed method and the traditional methods. The results show that the proposed method is superior to the traditional methods in measurement accuracy and reconstruction effect. [ABSTRACT FROM AUTHOR]

Rapid industrialization has significantly influenced people's lifestyles in the recent decades, and the influence of traditional culture is diminishing. Recently, several studies attempted to simultaneously utilize various sensors to record delicate and sophisticated performances of intangible cultural heritage (ICH). Although painting is one of the most common ICH of human history, few research studies have recorded traditional painting work. In this paper, we aim to lay the groundwork for reviving Korean painting, even if there would be no painters to produce these traditional Korean paintings in the future. We propose a novel multisensor-based acquisition system that records traditional Korean painting work while minimizing interference in the work. The proposed system captures real-time data originating from the painter, brushes, pigments, and canvas, which are the essential components of the painting work. We utilized the proposed system to capture the painting work by two experts, and we visualize the captured data. We showed the various results of statistical analysis, and also discussed the usability. [ABSTRACT FROM AUTHOR]

In different disciplines of science, the knowledge of the resulting pressures in the subsoil can help to understand physical phenomena of mass exchange between the atmosphere and the terrain. The measurement of lower differential pressures is complicated given the low range of detected values. In this paper, a multisensor system has been designed and developed to measure differential pressures in radon gas transport studies. The adequacy of this system has been proven using a purpose-built pressure chamber and an automatic motion system developed by the authors. The temporal response frequencies, the pressure values measured by the sensors, and their ability to link in series were analyzed to offer a multisensor spatial and temporal mapping. At the same time, the influence of the components required for a real deployment were studied using different tube lengths and diameters, connectors, and obstructions across the operating range of the pressure sensors. The system has also been tested for measuring differential pressures in a real model with a concrete slab above the soil and a pressure generator system below. It was found that this system is very suitable for outdoor measurements that demand a quick temporal response and accuracy. [ABSTRACT FROM AUTHOR]

This research is devoted to the development and study of novel cross-sensitive sensors based on modified extracting ligands. According to the previous results of liquid extraction studies, the chemical modification of membrane active components would change the analytical characteristics of a sensor comprising them. The sensing elements of the studied sensors consisted of various derivatives of N,N,N′,N′-tetraoctyldiamide of diglycolic acid (TODGA) and di-phenyl-N,N-di-i-sobutylcarbamoylmethylen phoshine oxide (CMPO) used as neutral carriers, CCD (chlorinated cobalt dicarbollide) as a lipophilic additive, different plasticizers, and poly(vinyl chloride) (PVC) as a polymer. TODGA-based sensors demonstrated a stable and reproducible response towards rare earth cations in acidic media (pH = 2). Changing the concentrations and ratio of neutral carriers and the lipophilic additive, it is possible to modify the sensitivity and selectivity of the sensors towards the same target ions. Bonded ligands, such as cobalt dicarbollide covalently attached to TODGA and CMPO, exhibited lower selectivity and sensitivity to rare earth cations. A possibility to vary the cross-sensitivity patterns of the sensors in a wide range might be of great interest for the development of multisensor systems allowing the simultaneous determination of several analytes in multicomponent solutions. [ABSTRACT FROM AUTHOR]

The paper describes a wide-range practical application of the potentiometric multisensor system (MS) (1) for integral safety evaluation of a variety of natural waters at multiple locations, under various climatic conditions and anthropogenic stress and (2) for close to real consistency evaluation of waste water purification processes at urban water treatment plants. In total, 25 natural surface water samples were collected around St. Petersburg (Russia), analyzed as is, and after ultrasonic treatment. Toxicity of the samples was evaluated using bioassay and MS. Relative errors of toxicity assessment with MS in these samples were below 20%. The system was also applied for fast determination of integral water quality using chemical oxygen demand (COD) values in 20 samples of water from river and ponds in Kolkata (India) and performed with an acceptable precision of 20% to 22% in this task. Furthermore, the MS was applied for fast simultaneous evaluation of COD, biochemical oxygen demand, inorganic phosphorous, ammonia, and nitrate nitrogen at two waste water treatment plants (over 320 samples). Reasonable precision (within 25%) of such analysis is acceptable for rapid water safety evaluation and enables fast control of the purification process. MS proved to be a practicable analytical instrument for various real-world tasks related to water safety monitoring. [ABSTRACT FROM AUTHOR]