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Статті в журналах з теми "Multi-sensors integration"
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HUGHES, KEN, and N. RANGANATHAN. "MODELING SENSOR CONFIDENCE FOR SENSOR INTEGRATION TASKS." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 06 (December 1994): 1301–18. http://dx.doi.org/10.1142/s0218001494000656.
Повний текст джерелаАнотація:
This paper addresses the problem of determining the reliability of individual sensors in a multi-sensor robotic system in an unknown environment. The inherent difficulty in this problem is that the decision must be based solely upon the data from the sensors themselves. While some previous research has considered unstructured environments (see Refs. 1 and 2 for examples) little if any consideration has been given to totally unknown environments. This problem has usually been avoided by assuming that the sensors would not provide erroneous data or ignoring sensors when they appeared to provide erroneous data. We believe a more robust solution is to consider each sensor’s performance over time compared to other sensors, and from this determine a measure of confidence in each sensor. This allows sensors which temporarily provide erroneous data to be accommodated. A system which can determine the reliability of its sensors is more robust since it can wisely decide which sensors are most appropriate for a given task and can also determine whether sensor conflicts are the result of poorly performing sensors.
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Giampetruzzi, Lucia, Amilcare Barca, Flavio Casino, Simonetta Capone, Tiziano Verri, Pietro Siciliano, and Luca Francioso. "Multi-Sensors Integration in a Human Gut-On-Chip Platform." Proceedings 2, no. 13 (November 13, 2018): 1022. http://dx.doi.org/10.3390/proceedings2131022.
Повний текст джерелаАнотація:
In the conventional culture systems in vitro, the challenging organoid approach have recently been overcome by the development of microfluidic Organ Chip models of human intestine. The potential future applications of Intestine-on-Chips in disease modelling, drug development and personalized medicine are leading research to identify and investigate limitations of modern chip-based systems and to focus the attention on the gut epithelium and its specific barrier function playing a significant role in many human disorders and diseases. In this paper, we propose and discuss the importance to implement a multi-parameter analysis on an engineered platform for developing an Epithelial Gut On Chip model.
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An, Boxing, Ying Ma, Wenbo Li, Meng Su, Fengyu Li, and Yanlin Song. "Three-dimensional multi-recognition flexible wearable sensor via graphene aerogel printing." Chemical Communications 52, no. 73 (2016): 10948–51. http://dx.doi.org/10.1039/c6cc05910d.
Повний текст джерела
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Wei, Liang, Yongcheng Li, Zhimei Cui, Baoshi Wang, Guanlang Huang, Zhiming Wang, and Jie Wei. "Research and Demonstration of Intelligent Multi-Physical Quantity Integration Sensor for Transmission Lines." Journal of Physics: Conference Series 2215, no. 1 (February 1, 2022): 012021. http://dx.doi.org/10.1088/1742-6596/2215/1/012021.
Повний текст джерелаАнотація:
Abstract The digital grid requires sensors to be widely deployed, safe, and reliable. At present, the single functional sensors suffered from redundant sensing system, repeated construction and low utilization rate. Therefore, this paper researched the multi-physical quantity integration sensor for a quad-bundle spacer on 500kV transmission lines. The sensor was composed of self-supplying rings and the monitoring host. Based on the non-contact current measurement technology, energy supply technology, intelligent sensing technology, low power consumption technology, reliability design technology, and other advanced technologies, this paper designed the hardware, software, and protective structure of the sensor, which can monitor the current and temperature of bubbles, channel side image and infrared image on transmission lines, ambient temperature, humidity, and air pressure. Finally, the multi-physical quantity integration sensors have been used on transmission lines in China Southern Power Grid, and the functions were verified. The sensors promote the automation, information, and digitization of monitoring transmission lines.
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Papadimitriou, Costas, and Evaggelos Ntotsios. "Optimization Algorithms for System Integration." Advances in Science and Technology 56 (September 2008): 514–23. http://dx.doi.org/10.4028/www.scientific.net/ast.56.514.
Повний текст джерелаАнотація:
This work outlines the optimization algorithms involved in integrating system analysis and measured data collected from a network of sensors. The integration is required for structural health monitoring problems arising in structural dynamics and related to (1) model parameter estimation used for finite element model updating, (2) model-based damage detection in structures and (3) optimal sensor location for parameter estimation and damage detection. These problems are formulated as single- and multi-objective optimization problems of continuous or discrete-valued variables. Gradient-based, evolutionary, hybrid and heuristic algorithms are presented that effectively address issues related to the estimation of multiple local/global solutions and computational complexity arising in single and multi-objective optimization involving continuous and discrete variables.
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Retscher, Günther. "Test and Integration of Location Sensors for a Multi-sensor Personal Navigator." Journal of Navigation 60, no. 1 (December 15, 2006): 107–17. http://dx.doi.org/10.1017/s037346330700402x.
Повний текст джерелаАнотація:
In the work package “Integrated Positioning” of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environments) we are dealing with the navigation and guidance of visitors to our University. The start points are the public transport stops in the surroundings of the Vienna University of Technology and the system users should be guided to certain office rooms or persons. For the user's position determination different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors, such as a digital compass and gyro for heading determination, accelerometers for the determination of the distance travelled, a barometric pressure sensor for altitude determination and, for indoor areas, location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter. An optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the senors in the stochastic filter model, the sensor characteristics and performance were investigated in several tests. The tests were performed in different environments either with free satellite visibility, in urban canyons or inside buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach are presented in the paper.
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Ebel, P., S. Saha, and X. X. Zhu. "FUSING MULTI-MODAL DATA FOR SUPERVISED CHANGE DETECTION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 243–49. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-243-2021.
Повний текст джерелаАнотація:
Abstract. With the rapid development of remote sensing technology in the last decade, different modalities of remote sensing data recorded via a variety of sensors are now easily accessible. Different sensors often provide complementary information and thus a more detailed and accurate Earth observation is possible by integrating their joint information. While change detection methods have been traditionally proposed for homogeneous data, combining multi-sensor multi-temporal data with different characteristics and resolution may provide a more robust interpretation of spatio-temporal evolution. However, integration of multi-temporal information from disparate sensory sources is challenging. Moreover, research in this direction is often hindered by a lack of available multi-modal data sets. To resolve these current shortcomings we curate a novel data set for multi-modal change detection. We further propose a novel Siamese architecture for fusion of SAR and optical observations for multi-modal change detection, which underlines the value of our newly gathered data. An experimental validation on the aforementioned data set demonstrates the potentials of the proposed model, which outperforms common mono-modal methods compared against.
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Liu, Shijie, Zhaoyou Ma, Xinming Guo, Xucai Zhuang, Yonghong Chen, Jianqing Wu, and Jianping Xing. "Research and development of intelligent safety sensor integration devices for autonomous driving." Journal of Physics: Conference Series 2196, no. 1 (February 1, 2022): 012002. http://dx.doi.org/10.1088/1742-6596/2196/1/012002.
Повний текст джерелаАнотація:
Abstract Grasping the status of vehicles timely and accurately is the key to avoid traffic accidents and collecting data from multi-sensors is significant for development of road-side intelligent sensor technology. In this paper, LiDAR (Light Detection and Ranging) and camera sensors are tested, and the sensor data can be processed and analyzed, and the display can be integrated. In this paper, a multi-sensor data acquisition integration device based on Raspberry Pi is proposed, which can realize the optimal processing of data and simultaneous acquisition display function. This method avoids the tedium of using an IPC and improves the efficiency of data acquisition and sensor integration.
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Lai, Tao, Guang Long Wang, Wen Jie Zhu, and Feng Qi Gao. "Attitude Determination by Integration of Multi-Sensors Based on Federated Kalman Filter." Applied Mechanics and Materials 602-605 (August 2014): 2958–61. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2958.
Повний текст джерелаАнотація:
Micro inertial measurement unit integration storage test system is a typical multi-sensor information fusion system consists of microsensors. The Federated Kalman filter is applied to micro inertial measurement unit integration storage test system. The general structure and characteristics of Federated Kalman filter is expounded. The four-order Runge-Kutta method based on quaternion differential equation was used to dispose the output angular rate data from gyroscope, and the recurrence expressions was established too. The control system based ARM Cortex-M4 master-slave structure is adopted in this paper. The result shown that the dimensionality reduced algorithm significantly reduces implementation complexity of the method and the amount computation. The filtering effect and real-time performance have much increased than traditionally method.
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Wu, Hongsheng, and Junwang Hu. "Artificial Intelligence Platform Construction and Integration Based on Multi-sensor Fusion." MATEC Web of Conferences 359 (2022): 01028. http://dx.doi.org/10.1051/matecconf/202235901028.
Повний текст джерелаАнотація:
Sensor is an important source of data transmission, through the integration of mechanical radar, inertial measurement unit and other sensors, building an artificial intelligence platform, will effectively save data information. By taking advantage of sensor fusion, the data of gyroscope and accelerometer are transferred to the background, and then the time stamp of artificial intelligence platform is aligned to get useful and usable information. By combining the mechanical radar and millimeter wave radar, an artificial intelligence platform is built, which makes full use of the synergetic advantage of the related sensors, captures the data information independently and saves it according to the time stamp. This paper focuses on the construction and integration of artificial intelligence platform based on multi-sensor fusion.
Дисертації з теми "Multi-sensors integration"
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Amerineni, Rajesh. "BRAIN-INSPIRED MACHINE LEARNING CLASSIFICATION MODELS." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1806.
Повний текст джерелаАнотація:
This dissertation focuses on the development of three classes of brain-inspired machine learning classification models. The models attempt to emulate (a) multi-sensory integration, (b) context-integration, and (c) visual information processing in the brain.The multi-sensory integration models are aimed at enhancing object classification through the integration of semantically congruent unimodal stimuli. Two multimodal classification models are introduced: the feature integrating (FI) model and the decision integrating (DI) model. The FI model, inspired by multisensory integration in the subcortical superior colliculus, combines unimodal features which are subsequently classified by a multimodal classifier. The DI model, inspired by integration in primary cortical areas, classifies unimodal stimuli independently using unimodal classifiers and classifies the combined decisions using a multimodal classifier. The multimodal classifier models are be implemented using multilayer perceptrons and multivariate statistical classifiers. Experiments involving the classification of noisy and attenuated auditory and visual representations of ten digits are designed to demonstrate the properties of the multimodal classifiers and to compare the performances of multimodal and unimodal classifiers. The experimental results show that the multimodal classification systems exhibit an important aspect of the “inverse effectiveness principle” by yielding significantly higher classification accuracies when compared with those of the unimodal classifiers. Furthermore, the flexibility offered by the generalized models enables the simulations and evaluations of various combinations of multimodal stimuli and classifiers under varying uncertainty conditions. The context-integrating model emulates the brain’s ability to use contextual information to uniquely resolve the interpretation of ambiguous stimuli. A deep learning neural network classification model that emulates this ability by integrating weighted bidirectional context into the classification process is introduced. The model, referred to as the CINET, is implemented using a convolution neural network (CNN), which is shown to be ideal for combining target and context stimuli and for extracting coupled target-context features. The CINET parameters can be manipulated to simulate congruent and incongruent context environments and to manipulate target-context stimuli relationships. The formulation of the CINET is quite general; consequently, it is not restricted to stimuli in any particular sensory modality nor to the dimensionality of the stimuli. A broad range of experiments are designed to demonstrate the effectiveness of the CINET in resolving ambiguous visual stimuli and in improving the classification of non-ambiguous visual stimuli in various contextual environments. The fact that the performance improves through the inclusion of context can be exploited to design robust brain-inspired machine learning algorithms. It is interesting to note that the CINET is a classification model that is inspired by a combination of brain’s ability to integrate contextual information and the CNN, which is inspired by the hierarchical processing of visual information in the visual cortex. A convolution neural network (CNN) model, inspired by the hierarchical processing of visual information in the brain, is introduced to fuse information from an ensemble of multi-axial sensors in order to classify strikes such as boxing punches and taekwondo kicks in combat sports. Although CNNs are not an obvious choice for non-array data nor for signals with non-linear variations, it will be shown that CNN models can effectively classify multi-axial multi-sensor signals. Experiments involving the classification of three-axis accelerometer and three-axes gyroscope signals measuring boxing punches and taekwondo kicks showed that the performance of the fusion classifiers were significantly superior to the uni-axial classifiers. Interestingly, the classification accuracies of the CNN fusion classifiers were significantly higher than those of the DTW fusion classifiers. Through training with representative signals and the local feature extraction property, the CNNs tend to be invariant to the latency shifts and non-linear variations. Moreover, by increasing the number of network layers and the training set, the CNN classifiers offer the potential for even better performance as well as the ability to handle a larger number of classes. Finally, due to the generalized formulations, the classifier models can be easily adapted to classify multi-dimensional signals of multiple sensors in various other applications.
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Ulbricht, Andreas, Maik Gude, Daniel Barfuß, Michael Birke, Andree Schwaar, and Andrzej Czulak. "Potential and application fields of lightweight hydraulic components in multi-material design." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-200294.
Повний текст джерелаАнотація:
Hydraulic systems are used in many fields of applications for different functions like energy storage in hybrid systems. Generally the mass of hydraulic systems plays a key role especially for mobile hydraulics (construction machines, trucks, cars) and hydraulic aircraft systems. The main product properties like energy efficiency or payload can be improved by reducing the mass. In this connection carbon fiber reinforced plastics (CFRP) with their superior specific strength and stiffness open up new chances to acquire new lightweight potentials compared to metallic components. However, complex quality control and failure identification slow down the substitution of metals by fiber-reinforced plastics (FRP). But the lower manufacturing temperatures of FRP compared to metals allow the integration of sensors within FRP-components. These sensors then can be advantageously used for many functions like quality control during the manufacturing process or structural health monitoring (SHM) for failure detection during their life cycle. Thus, lightweight hydraulic components made of composite materials as well as sensor integration in composite components are a main fields of research and development at the Institute of Lightweight Engineering and Polymer Technology (ILK) of the TU Dresden as well as at the Leichtbau-Zentrum Sachsen GmbH (LZS).
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Leon, Perez Edgar. "Matrice de nanofils piézoélectriques interconnectés pour des applications capteur haute résolution : défis et solutions technologiques." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT015/document.
Повний текст джерелаАнотація:
Ce projet de thèse aborde la question de l’intégration hétérogène de nanofils interconnectés sur des puces microélectroniques à destination de dispositifs de type MEMS et NEMS. Ces dispositifs visent à adresser la problématique globale qu’est le « More than Moore », c’est-à-dire la transformation des filières CMOS classiques pour permettre le développement de nouveaux micro et nano-composants intégrés.En particulier, ces dernières années, une variété de dispositifs à base de nanomatériaux ont vu le jour, conférant à des dispositifs de type micro-actionneurs et micro-capteurs de nouvelles fonctionnalités et/ou des performances accrues, e.g. en termes de résolution, sensibilité, sélectivité. Nous nous intéresserons ici à un certain type de nanostructures, les nanofils d’oxyde de zinc (ZnO), qui ont surtout été utilisés pour concevoir des dispositifs dont le principe de fonctionnement exploite l’effet piézoélectrique, souvent astucieusement combiné avec leurs propriétés semiconductrices. En effet, sous l’effet d’une contrainte mécanique ou d’un déplacement, les nanofils piézoélectriques génèrent un potentiel électrique (piézopotentiel). Si, en outre, les nanofils sont semiconducteurs, le piézopotentiel peut être utilisé pour contrôler un courant externe en fonction de la contrainte mécanique imposée au nanofil (effet piézotronique). L’avantage d’utiliser des nanostructures unidimensionnelles réside dans la modularité de leurs propriétés mécaniques et piézoélectriques en comparaison avec le matériau massif. Par ailleurs, leur intégration est aujourd’hui possible par des voies de croissance compatibles avec les procédés microélectroniques (CMOS/MEMS). Toutes ces considérations rendent possibles la conception de dispositifs très haute performance combinant la faible dimension des éléments fonctionnels (et donc une forte densité d’intégration synonyme de haute résolution spatiale) et leur sensibilité à des phénomènes d’échelle nanoscopique.Dans ce projet de thèse, on adoptera une vision très technologique de la conception de capteurs matriciels à base de nanofils piézoélectriques verticaux en ZnO. S’appuyant sur la prédiction des performances théoriques et la levée des verrous technologiques associés à la conception et la fabrication du capteur, cette étude s’attache à fournir des prototypes faisant la preuve de concept de ces dispositifs haute performance. Dans un premier temps, la réflexion s’articule autour de modèles multi-physiques par éléments finis (FEM) de la réponse piézoélectrique d’un seul nanofil en flexion, modèle que nous avons fait évoluer vers des pixels complets représentatifs d’un nanofil interconnecté dans une matrice. Sur la base de ces considérations, nous avons imaginé des moyens de caractérisation de la réponse piézoélectrique d’un fil, puis d’un pixel. Le banc de caractérisation mis en place a mis en évidence la complexité d’une mesure piézoélectrique systématique, calibrée et décorrélée des éléments environnants du pixel. Des solutions technologiques adéquates ont pu être imaginées et mises en œuvre à travers la réalisation de pixels élémentaires caractérisables et dont la réponse piézoélectrique peut être prédite théoriquement.Cette réalisation a fait appel à un développement en plusieurs étapes, incluant la croissance par voie chimique des nanofils en ZnO, puis la conception de la matrice d’électrodes contactant individuellement les nanofils. La première se découpe en deux étapes : d’abord le choix d’une couche de germination favorisant la croissance sur puce silicium et compatible avec les procédés de salle blanche ; ensuite le développement d’un procédé de croissance permettant la localisation des nanofils au sein d’une matrice d’électrodes. La seconde moitié du travail de fabrication a consisté à définir et à optimiser l’empilement technologique respectant toutes les considérations abordées jusqu’alors, et à définir les procédés technologiques aboutissant à la fabrication de la matrice finaleThis thesis project deals with the question of heterogeneous integration of interconnected nanowires on microelectronics chips in a view to MEMS and NEMS type devices. These devices aim to address the global problematic of “More than Moore”, that is the transformation of classical CMOS microelectronics processes to enable the development of new integrated micro and nanocomponents.In particular, over the past few years, a variety of nanomaterial-based devices have arisen, revealing micro-actuators and micro-sensors with new functionalities and/or improved performances, e.g. in terms of resolution, sensitivity, selectivity. Here we will focus on a certain type of nanostructures, Zinc Oxide (ZnO) nanowires, which have mostly been used so far to design devices whose working principle exploits the piezoelectric effect, often judiciously combined with their semiconducting properties. Indeed, when submitted to a mechanical constraint or displacement, piezoelectric nanowires generate an electrical potential (piezopotential). If, in addition to this, nanowires are also semiconducting, the piezopotential can be exploited to control an external current as a function of the mechanical constraint imposed to the nanowire (piezotronic effect). The advantage of using one-dimensional nanostructures lies into the modularity of both their mechanical and piezoelectric properties, in comparison with the bulk material. Moreover, their integration is now possible thanks to growth processes compatible with microelectronic processes (CMOS/MEMS). All these considerations make it possible to design very high performance devices combining the very small dimension of their functional unit elements (hence a high integration density which implies a high spatial resolution) and their sensitivity to nanoscale phenomena.In this project, we will adopt a very technology-oriented vision of the design of vertically-aligned ZnO-piezoelectric-nanowire matrix-type sensors. Relying on theoretical performance predictions and technological choices to solve device design and fabrication issues, this study aims to produce proof-of-concept prototypes of these high performance devices. First of all, the design process is elaborated based on finite element multiphysics models (FEM) of the piezoelectric response of a single bent nanowire, which we upgraded towards complete pixels, representative of an interconnected nanowire within a matrix. Following these considerations, we have imagined means of characterization of the piezoelectric response of a wire, then of a pixel. The implemented characterization experiment highlighted the complexity of carrying out a systematic, calibrated piezoelectric measurement, decorrelated from the environment of the pixel. Adequate technological solutions could then be implemented through the fabrication of elementary pixels suitable for characterization and whose piezoelectric response could be predictively modeled.This technological part of the work encompassed several development stages, including the chemical growth of ZnO nanowires and the design of the electrode matrix contacting the nanowires individually. The former splits into two steps: first choosing a clean-room compatible seed layer which will favor growth on a Silicon chip; secondly developing a selective growth process enabling the localization of nanowires within a predefined matrix of electrodes. The second part of the fabrication work focused on defining and optimizing the technological stack with respect to all the above mentioned considerations, and implementing the technological processes yielding the final targeted matrix
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Joly, Matthieu. "Conception d'un système d'analyse multi-capteur ISFET pour la surveillance in-situ de l'azote minéral. Application à la culture du blé dur." Thesis, Toulouse, INSA, 2018. http://www.theses.fr/2018ISAT0043.
Повний текст джерелаАнотація:
L'usage excessif de fertilisants azotés dans les pratiques agricoles modernes est préoccupant car il aboutit, entre autres, à la pollution des nappes phréatiques et à l’eutrophisation des eaux douces et marines. L’analyse du sol peut faciliter la mise en place de nouvelles pratiques agricoles qui tiennent davantage compte des variations temporelles et locales du sol et des plantes. Ces travaux visent donc le développement d’un système d’analyse in-situ, autonome et communicant pour le suivi en temps réel des teneurs en azote minéral du sol. Notre système est basé sur la technologie de microcapteur chimique en silicium lon-Sensitive Field Effect Transistor (ISFET). Une première phase de son développement a été dédiée à la fabrication de microcapteurs génériques pH-ISFET. La problématique de la détermination du pH du sol en insérant les pH-ISFET directement dans le sol a été considérée. Les résultats obtenus par cette méthode in-situ ont été comparés avec la méthode standard et nous avons examiné l’influence de paramètres propres au sol (humidité, texture, pH) et à l’ISFET (durée de vie, dérive temporelle). Dans un second temps, des puces pNH,-ISFET et pNO;-ISFET ont été obtenues en fonctionnalisant les puces génériques pH-ISFET grâce à l'intégration de membranes ionosensibles. La composition de ces membranes a été optimisée jusqu’à obtention de propriétés de détection (sensibilité, sélectivité, stabilité...) en adéquation avec les teneurs en ions ammonium et nitrates typiques des sols cultivés. Des premières caractérisations en conditions in-situ ont alors été effectuées. Finalement, les'capteurs ont été intégrés à un système permettant l’insertion des capteurs dans le sol, leur protection, l’alimentation électrique par batterie et la communication à distance des données de mesure. De premiers résultats, prometteurs, ont été obtenusExcessive use of nitrogen fertilizers in modern agricultural practices is a concern as it leads to groundwater pollution and eutrophication of fresh and marine waters. Soil testing can enable the introduction of new agricultural practices that take more into account temporal and local variations of soil and plants. This work therefore aims at the development of an in situ, autonomous and communicating analysis system for real-time monitoring of the mineral nitrogen contents of soils.Our system is based on the Ion-sensitive Field Effect Transistor (ISFET) microsensor technology. A first step of its development was dedicated to the fabrication of generic pH-ISFET microsensors. The problem of determining soil pH by inserting pH-ISFETs directly into the soil was considered. Results obtained by this in situ method were compared with the standard method and we examined the influence of soil ( moisture, texture, pH) and IFSET parameters (lifetime, time drift). In a second step, pNH4-ISFET and pNO3-ISFET chips were obtained by functionalizing the generic pH-ISFET chips with ionosensitive membrane. The composition of these membranes has been optimized until detection properties ( sensitivity, selectivity, stability, etc.) were in good accordance with the ammonium and nitrate ion contents of cultivated soils. Characterizations under in situ conditions were then carried out.Finally, the integration in the ground, the protection, the power supply and the remote communication of the sensors were made possible by the integration in a dedicated system. We obtained promising results
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Parnian, Neda. "Integration of Local Positioning System & Strapdown Inertial Navigation System for Hand-Held Tool Tracking." Thesis, 2008. http://hdl.handle.net/10012/4043.
Повний текст джерелаАнотація:
This research concerns the development of a smart sensory system for tracking a hand-held moving device to millimeter accuracy, for slow or nearly static applications over extended periods of time. Since different operators in different applications may use the system, the proposed design should provide the accurate position, orientation, and velocity of the object without relying on the knowledge of its operation and environment, and based purely on the motion that the object experiences. This thesis proposes the design of the integration a low-cost Local Positioning System (LPS) and a low-cost StrapDown Inertial Navigation System (SDINS) with the association of the modified EKF to determine 3D position and 3D orientation of a hand-held tool within a required accuracy.
A hybrid LPS/SDINS combines and complements the best features of two different navigation systems, providing a unique solution to track and localize a moving object more precisely. SDINS provides continuous estimates of all components of a motion, but SDINS loses its accuracy over time because of inertial sensors drift and inherent noise. LPS has the advantage that it can possibly get absolute position and velocity independent of operation time; however, it is not highly robust, is computationally quite expensive, and exhibits low measurement rate.
This research consists of three major parts: developing a multi-camera vision system as a reliable and cost-effective LPS, developing a SDINS for a hand-held tool, and developing a Kalman filter for sensor fusion.
Developing the multi-camera vision system includes mounting the cameras around the workspace, calibrating the cameras, capturing images, applying image processing algorithms and features extraction for every single frame from each camera, and estimating the 3D position from 2D images.
In this research, the specific configuration for setting up the multi-camera vision system is proposed to reduce the loss of line of sight as much as possible. The number of cameras, the position of the cameras with respect to each other, and the position and the orientation of the cameras with respect to the center of the world coordinate system are the crucial characteristics in this configuration. The proposed multi-camera vision system is implemented by employing four CCD cameras which are fixed in the navigation frame and their lenses placed on semicircle. All cameras are connected to a PC through the frame grabber, which includes four parallel video channels and is able to capture images from four cameras simultaneously.
As a result of this arrangement, a wide circular field of view is initiated with less loss of line-of-sight. However, the calibration is more difficult than a monocular or stereo vision system. The calibration of the multi-camera vision system includes the precise camera modeling, single camera calibration for each camera, stereo camera calibration for each two neighboring cameras, defining a unique world coordinate system, and finding the transformation from each camera frame to the world coordinate system.
Aside from the calibration procedure, digital image processing is required to be applied into the images captured by all four cameras in order to localize the tool tip. In this research, the digital image processing includes image enhancement, edge detection, boundary detection, and morphologic operations. After detecting the tool tip in each image captured by each camera, triangulation procedure and optimization algorithm are applied in order to find its 3D position with respect to the known navigation frame.
In the SDINS, inertial sensors are mounted rigidly and directly to the body of the tracking object and the inertial measurements are transformed computationally to the known navigation frame. Usually, three gyros and three accelerometers, or a three-axis gyro and a three-axis accelerometer are used for implementing SDINS. The inertial sensors are typically integrated in an inertial measurement unit (IMU). IMUs commonly suffer from bias drift, scale-factor error owing to non-linearity and temperature changes, and misalignment as a result of minor manufacturing defects. Since all these errors lead to SDINS drift in position and orientation, a precise calibration procedure is required to compensate for these errors.
The precision of the SDINS depends not only on the accuracy of calibration parameters but also on the common motion-dependent errors. The common motion-dependent errors refer to the errors caused by vibration, coning motion, sculling, and rotational motion. Since inertial sensors provide the full range of heading changes, turn rates, and applied forces that the object is experiencing along its movement, accurate 3D kinematics equations are developed to compensate for the common motion-dependent errors. Therefore, finding the complete knowledge of the motion and orientation of the tool tip requires significant computational complexity and challenges relating to resolution of specific forces, attitude computation, gravity compensation, and corrections for common motion-dependent errors.
The Kalman filter technique is a powerful method for improving the output estimation and reducing the effect of the sensor drift. In this research, the modified EKF is proposed to reduce the error of position estimation. The proposed multi-camera vision system data with cooperation of the modified EKF assists the SDINS to deal with the drift problem. This configuration guarantees the real-time position and orientation tracking of the instrument. As a result of the proposed Kalman filter, the effect of the gravitational force in the state-space model will be removed and the error which results from inaccurate gravitational force is eliminated. In addition, the resulting position is smooth and ripple-free.
The experimental results of the hybrid vision/SDINS design show that the position error of the tool tip in all directions is about one millimeter RMS. If the sampling rate of the vision system decreases from 20 fps to 5 fps, the errors are still acceptable for many applications.
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Huang, Yen-Hsiang, and 黃彥翔. "Preparation of Amperometric Phenol Sensors by Integrating Multi-Walled Carbon Nanotubes with Silver Nanoparticles (Ag@MWCNTs) and Potential to Apply in the Flow Injection Analysis (FIA) System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/44898325366478909414.
Повний текст джерелаАнотація:
碩士國立臺灣科技大學
化學工程系
103
This study is comprised of two parts: the first part focused on the synthesis of the complexes of Ag@carbon nanotubes (Ag@CNTs) and preparation of horseradish peroxidase (HRP) biosensor. Carbon nanotubes (CNTs) have drawn considerable attention in recent years because of their superior properties that include the larger specific surface area and more electrocatalytic activity, which can significantly enhance the amperometric anodic signal. In this study, the incorporation of Ag nanoparticles on CNTs aimed to enhance the electrical conductivity and reduce the contact resistance. Moreover, various analytical tools were employed to verify the physical-chemical and morphology characteristics of the prepared Ag@CNTs. An amperometric biosensor base on HRP and chitosan- Ag@carbon nanotubes (Ch-Ag@CNTs) on screen printed carbon electrode (SPE). The current responses were detected by phenolic compound at applied voltage -50 mV. The results showed that two sensitivity of phenol detection were 2.37 μA/μM cm2 (0.75 - 100 μM, R2:0.976) and 0.749 μA/μM cm2 (100 - 400 μM, R2:0.979) and limitation of detection was 0.375 μM. It retained 80% of its initial current response after 30 days. For the second part, a custom-made flow channel was applied which mainly plays the role of minimize the required components for reactions and further facilitated the integration, automation, and parallelization for the designated biochemical processes. In addition, the prepared Ch-Ag@CNTs in the first part and HRP were incorporated on SPE for the detection of phenol, which was further combined with a custom-made flow channel, to form “Flow Injection Analysis” (FIA). The FIA designed in this study allows the manipulation of small fluid volume, from micro- down to pico- liter, with exceptional accuracy. In summary, the proposed FIA would have the advantages including low price, rapid response time, high accuracy, and smaller reaction volume that can reduce the thickness of the diffusion layer and effectively convey electronic signals between solid-liquid phases when compared with the conventional system, and could be utilized for a wider range of applications. The results showed that the sensitivity of phenol detection were 2.77 μA/μM cm2 (0.5 - 20 μM, R2:0.974).
Частини книг з теми "Multi-sensors integration"
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Park, Chi-ho, and Joong-hee Han. "Development of Low-Cost Sensors Based Multi-sensors Integration Positioning Algorithm for Land Vehicle Tracking and Monitoring Device." In Internet of Vehicles. Technologies and Services Toward Smart Cities, 101–8. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38651-1_10.
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Brambilla, Mattia. "Sensor-Assisted Cooperative Localization and Communication in Multi-agent Networks." In Special Topics in Information Technology, 129–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85918-3_11.
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AbstractThis brief highlights research advances on cooperative techniques for localization and communication. These two macro trends are investigated in the general context of mobile multi-agent networks for situational awareness applications, where time-varying agents of unknown locations are asked to fulfill positioning and information sharing tasks. Cooperative localization is conceived for both active and passive agents, i.e., targets to be detected and localized, and it is analyzed in vehicular and maritime environments. Communication is investigated for vehicular scenarios, where vehicles are requested to share massive data in the perspective development of connected and automated mobility systems. Both research areas rely on the integration of heterogeneous sensors and communication. Specifically, it is studied how to improve localization by exploring communication techniques as well as how to enhance communication performances by extracting information from perception sensors. The dynamic environment of multi-agent systems calls for robust, flexible and adaptive techniques, capable of profitably fuse different types of information, and the outcomes of these researches show how a statistical approach based on cooperation guarantees higher resilience, reliability and confidence.
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McCloskey, Scott. "Computational Imaging." In Multimedia Forensics, 41–62. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7621-5_3.
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AbstractSince the advent of smartphones, photography is increasingly being done with small, portable, multi-function devices. Relative to the purpose-built cameras that dominated previous eras, smartphone cameras must overcome challenges related to their small form factor. Smartphone cameras have small apertures that produce a wide depth of field, small sensors with rolling shutters that lead to motion artifacts, and small form factors which lead to more camera shake during exposure. Along with these challenges, smartphone cameras have the advantage of tight integration with additional sensors and the availability of significant computational resources. For these reasons, the field of computational imaging has advanced significantly in recent years, with academic groups and researchers from smartphone manufacturers helping these devices become more capable replacements for purpose-built cameras.
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Musaev, Aibek, De Wang, and Calton Pu. "Multi-hazard Detection by Integrating Social Media and Physical Sensors." In Social Media for Government Services, 395–409. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27237-5_17.
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Braunfelds, Janis, Sandis Spolitis, Jurgis Porins, and Vjaceslavs Bobrovs. "Fiber Bragg Grating Sensors Integration in Fiber Optical Systems." In Optical Fiber [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94289.
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Fiber Bragg grating (FBG) sensors are a progressive passive optical components, and used for temperature, strain, water level, humidity, etc. monitoring. FBG sensors network can be integrated into existing optical fiber network infrastructure and realized structural health monitoring of roads, bridges, buildings, etc. In this chapter, the FBG sensor network integration in a single-channel and multi-channel spectrum sliced wavelength division multiplexed passive optical network (SS-WDM-PON) is presented and assessed. The operation of both the sensors and data transmission system, over a shared optical distribution network (ODN), is a challenging task and should be evaluated to provide stable, high-performance mixed systems in the future. Therefore, we have investigated the influence of FBG temperature sensors on 10 Gbit/s non-return-to-zero on–off keying (NRZ-OOK) modulated data channels optical transmission system. Results show that the crosstalk between both systems is negligible. The successful operation of both systems (with BER < 2 × 10−3 for communication system) can be achieved over ODN distances up to 40 km.
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Drwiega, Michał, and Elżbieta Roszkowska. "Multi-Robot Mapping Based on 3D Maps Integration." In Autonomous Mobile Mapping Robots [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.107978.
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An unknown environment could be mapped more efficiently by a group of robots than a single robot. The time reduction due to parallelization is crucial in complex area mapping. There are two general solutions used in the multi-robot mapping. In the first one, robots exchange raw data from sensors. The second approach assumes that each robot creates a local map independently that is exchanged with other robots and integrated. In this chapter, we present a 3D maps integration algorithm that utilizes overlapping regions in the feature-based alignment process. The algorithm does not need any initial guess about the transformation between local maps. However, for successful integration, maps need to have a common area. We showed that the implemented method is effective in various environments. The approach has been verified in experiments with wheeled mobile robots and using public datasets with octree-based maps.
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Zhou, Zude, Huaiqing Wang, and Ping Lou. "Sensor Integration and Data Fusion Theory." In Manufacturing Intelligence for Industrial Engineering, 160–88. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-864-2.ch007.
Повний текст джерелаАнотація:
In previous chapters, the engineering scientific foundations of manufacturing intelligence (such as the knowledge-based system, Multi-Agent system, data mining and knowledge discovery, and computing intelligence) have been discussed in detail. Sensor integration and data fusion is another important theory of manufacturing intelligence. With the development of integrated systems, there is an urgent requirement for improving system automaticity and intelligence. Without improvement, the complexity and scale of systems are increased. Such systems need to be more sensitive to their work environment and independent state, and obviously, single sensor technology hardly meets these requirements. Multi-sensor and data fusion technology are therefore employed in automatic and intelligent manufacturing as it is more comprehensive and accurate than traditional single sensor technology if the information redundancy and complementarity are used reasonably. In theory, the outputs of multi-sensors are mutually validated. Multi-sensor integration is a brand new concept for intelligent manufacturing, and without doubt, sensor integration-based intelligent manufacturing is the development orientation of manufacturing in the future. With reference to the information fusion problem of the multi-sensor integration system, the development state, technical background, application scope and basic meaning of the multi-sensor integration and the data fusion are first reviewed in this chapter. Secondly the classification, level, system structure and function model of the data fusion system is discussed. The theoretical method of the data fusion is then introduced, and finally, attention is paid to cutting tool condition detection, machine thermal error compensation and online detection and error compensation because those are the main applications of multi-sensor data fusion technology in intelligent manufacturing.
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Lourenço, Patrícia. "Biomass Estimation Using Satellite-Based Data." In Forest Biomass - From Trees to Energy. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.93603.
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Comprehensive measurements of global forest aboveground biomass (AGB) are crucial information to promote the sustainable management of forests to mitigate climate change and preserve the multiple ecosystem services provided by forests. Optical and radar sensors are available at different spatial, spectral, and temporal scales. The integration of multi-sources sensor data with field measurements, using appropriated algorithms to identify the relationship between remote sensing predictors and reference measurements, is important to improve forest AGB estimation. This chapter aims to present different types of predicted variables derived from multi-sources sensors, such as original spectral bands, transformed images, vegetation indices, textural features, and different regression algorithms used (parametric and non-parametric) that contribute to a more robust, practical, and cost-effective approach for forest AGB estimation at different levels.
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Jin, Minhao, Shaojie Luo, Jiabin Huang, and Xincheng Zhou. "Efficient Security Detection Strategy Based on K-Means Algorithm in LPWAN." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220547.
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With the development of multi-element integration and high elastic power grid construction, digital sensing of transmission, transformation and distribution equipment in many new energy sources, virtual power plants and load aggregators will be widely used. In this environment, it is urgent to build a reliable sensing network to support its digital sensing applications such as operation state sensing, data collection and demand management. However, due to the large number and wide distribution of distribution equipment, there may be errors in the uploading results of sensors. This paper proposes an efficient security detection strategy based on K-Means algorithm, which greatly improves the information integration and decision ability of the data center.
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Minke, Anneke, and Helmut Lessing. "Environmental Monitoring, Data Mining, and Dynamic Analysis." In Corporate Environmental Management Information Systems, 168–79. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-981-1.ch011.
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Online-monitoring systems as well as systems regarding environmental observation have evolved from classic analytic methods on the laboratory scale. Still, they are structured mainly medially and sectorally. At this point, the multi-sensorial array-technology opens up new possibilities. Today, the integration of these multi-sensorial chips into mobile units of the automotive domain or into cell phones and the transmission of empirical data to an integrated network are possible; there are no fundamental technological barriers. Nevertheless, the examination of this data collected by mobile sensors which are often in motion and the extraction of reliable, supra-regional information yield a new class of problems. In this chapter, an implementation concept will be described which will be evaluated within a pilot scheme.
Тези доповідей конференцій з теми "Multi-sensors integration"
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Huwedi, Ashraf, Peter Steinhaus, and Rudiger Dillmann. "Autonomous Feature-Based Exploration using Multi-Sensors." In 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. IEEE, 2006. http://dx.doi.org/10.1109/mfi.2006.265610.
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Zhe Mao, Zhuoran Zhang, Yaling Lu, and Shuai Mei. "The data fusion with ANFIS in multi-sensors grain information monitoring system." In 2012 4th Electronic System-Integration Technology Conference (ESTC). IEEE, 2012. http://dx.doi.org/10.1109/estc.2012.6485676.
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Imam, Neena, Jacob Barhen, and Charles Glover. "Optimum sensors integration for multi-sensor multi-target environment for ballistic missile defense applications." In 2012 6th Annual IEEE Systems Conference (SysCon). IEEE, 2012. http://dx.doi.org/10.1109/syscon.2012.6189519.
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Senanayake, S. M. N. Arosha, Owais Ahmed Malik, and Mohammad Iskandar. "Wireless Multi-Sensor Integration for ACL Rehabilitation Using Biofeedback Mechanism." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-87809.
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The objective of this study is to propose an integrated motion analysis system for monitoring and assisting the rehabilitation process for athletes based on biofeedback mechanism, particularly for human subjects already undergone Anterior Cruciate Ligament (ACL) injury operations and thus about to start the rehabilitation process. For this purpose, different types of parameters (kinematics and neuromuscular signals) from multi-sensors integration are combined to analyze the motion of affected athletes. Signals acquired from sensors are pre-processed in order to prepare the pattern set for intelligent algorithms to be integrated for possible implementation of effective assistive rehabilitation processing tools for athletes and sports orthopedic surgeons. Based on the characteristics of different signals invoked during the rehabilitation process, two different intelligent approaches (Elman RNN and Fuzzy Logic) have been tested. The newly introduced integrated multi-sensors approach will assist in identifying the clinical stage of the recovery process of athletes after ACL repair and will facilitate clinical decision-making during the rehabilitation process. The use of wearable wireless miniature sensors will provide an un-obstructive assessment of the kinematics and neuromuscular changes occurring after ACL reconstruction in an athlete.
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Ruser, Heinrich. "Smartlow-cost weather sensor as an example for `multi-component' sensors." In 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. IEEE, 2006. http://dx.doi.org/10.1109/mfi.2006.265675.
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Latorre, L., J. Miquel, and S. Chamaille-Jammes. "MEMS based Low-Power Multi-Sensors device for Bio-Logging Applications." In 2021 Symposium on Design, Test, Integration & Packaging of MEMS and MOEMS (DTIP). IEEE, 2021. http://dx.doi.org/10.1109/dtip54218.2021.9568669.
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Xu, Y., J. Y. Wang, B. X. Cao, and J. Yang. "Multi sensors based ultrasonic human face identification: Experiment and analysis." In 2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2012). IEEE, 2012. http://dx.doi.org/10.1109/mfi.2012.6343000.
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Kaed, Charbel El, Andre Ponnouradjane, and Dhaval Shah. "A Semantic Based Multi-Platform IoT Integration Approach from Sensors to Chatbots." In 2018 Global Internet of Things Summit (GIoTS). IEEE, 2018. http://dx.doi.org/10.1109/giots.2018.8534520.
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Liu, Lu, Ling Xiao, and Tingting Liu. "Construction and Integration of under vehicle inspection system based on multi-source sensors." In 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2019. http://dx.doi.org/10.1109/icspcc46631.2019.8960709.
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Nishimura, Yuki, Makoto Sakamoto, and Tomoyuki Yamaguchi. "Development of Multi-copter System on Concrete Surfaces with Outer Frame and Wind Speed Sensors*." In 2020 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2020. http://dx.doi.org/10.1109/sii46433.2020.9026215.
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