Literatura académica sobre el tema "Multi-sensors integration"
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Artículos de revistas sobre el tema "Multi-sensors integration"
HUGHES, KEN y N. RANGANATHAN. "MODELING SENSOR CONFIDENCE FOR SENSOR INTEGRATION TASKS". International Journal of Pattern Recognition and Artificial Intelligence 08, n.º 06 (diciembre de 1994): 1301–18. http://dx.doi.org/10.1142/s0218001494000656.
Texto completoGiampetruzzi, Lucia, Amilcare Barca, Flavio Casino, Simonetta Capone, Tiziano Verri, Pietro Siciliano y Luca Francioso. "Multi-Sensors Integration in a Human Gut-On-Chip Platform". Proceedings 2, n.º 13 (13 de noviembre de 2018): 1022. http://dx.doi.org/10.3390/proceedings2131022.
Texto completoAn, Boxing, Ying Ma, Wenbo Li, Meng Su, Fengyu Li y Yanlin Song. "Three-dimensional multi-recognition flexible wearable sensor via graphene aerogel printing". Chemical Communications 52, n.º 73 (2016): 10948–51. http://dx.doi.org/10.1039/c6cc05910d.
Texto completoWei, Liang, Yongcheng Li, Zhimei Cui, Baoshi Wang, Guanlang Huang, Zhiming Wang y Jie Wei. "Research and Demonstration of Intelligent Multi-Physical Quantity Integration Sensor for Transmission Lines". Journal of Physics: Conference Series 2215, n.º 1 (1 de febrero de 2022): 012021. http://dx.doi.org/10.1088/1742-6596/2215/1/012021.
Texto completoPapadimitriou, Costas y Evaggelos Ntotsios. "Optimization Algorithms for System Integration". Advances in Science and Technology 56 (septiembre de 2008): 514–23. http://dx.doi.org/10.4028/www.scientific.net/ast.56.514.
Texto completoRetscher, Günther. "Test and Integration of Location Sensors for a Multi-sensor Personal Navigator". Journal of Navigation 60, n.º 1 (15 de diciembre de 2006): 107–17. http://dx.doi.org/10.1017/s037346330700402x.
Texto completoEbel, P., S. Saha y 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 (28 de junio de 2021): 243–49. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-243-2021.
Texto completoLiu, Shijie, Zhaoyou Ma, Xinming Guo, Xucai Zhuang, Yonghong Chen, Jianqing Wu y Jianping Xing. "Research and development of intelligent safety sensor integration devices for autonomous driving". Journal of Physics: Conference Series 2196, n.º 1 (1 de febrero de 2022): 012002. http://dx.doi.org/10.1088/1742-6596/2196/1/012002.
Texto completoLai, Tao, Guang Long Wang, Wen Jie Zhu y Feng Qi Gao. "Attitude Determination by Integration of Multi-Sensors Based on Federated Kalman Filter". Applied Mechanics and Materials 602-605 (agosto de 2014): 2958–61. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2958.
Texto completoWu, Hongsheng y 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.
Texto completoTesis sobre el tema "Multi-sensors integration"
Amerineni, Rajesh. "BRAIN-INSPIRED MACHINE LEARNING CLASSIFICATION MODELS". OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1806.
Texto completoUlbricht, Andreas, Maik Gude, Daniel Barfuß, Michael Birke, Andree Schwaar y 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.
Texto completoLeon, 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.
Texto completoThis 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
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.
Texto completoExcessive 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
Parnian, Neda. "Integration of Local Positioning System & Strapdown Inertial Navigation System for Hand-Held Tool Tracking". Thesis, 2008. http://hdl.handle.net/10012/4043.
Texto completoHuang, Yen-Hsiang y 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.
Texto completo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).
Capítulos de libros sobre el tema "Multi-sensors integration"
Park, Chi-ho y Joong-hee Han. "Development of Low-Cost Sensors Based Multi-sensors Integration Positioning Algorithm for Land Vehicle Tracking and Monitoring Device". En 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.
Texto completoBrambilla, Mattia. "Sensor-Assisted Cooperative Localization and Communication in Multi-agent Networks". En Special Topics in Information Technology, 129–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85918-3_11.
Texto completoMcCloskey, Scott. "Computational Imaging". En Multimedia Forensics, 41–62. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7621-5_3.
Texto completoMusaev, Aibek, De Wang y Calton Pu. "Multi-hazard Detection by Integrating Social Media and Physical Sensors". En Social Media for Government Services, 395–409. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27237-5_17.
Texto completoBraunfelds, Janis, Sandis Spolitis, Jurgis Porins y Vjaceslavs Bobrovs. "Fiber Bragg Grating Sensors Integration in Fiber Optical Systems". En Optical Fiber [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94289.
Texto completoDrwiega, Michał y Elżbieta Roszkowska. "Multi-Robot Mapping Based on 3D Maps Integration". En Autonomous Mobile Mapping Robots [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.107978.
Texto completoZhou, Zude, Huaiqing Wang y Ping Lou. "Sensor Integration and Data Fusion Theory". En Manufacturing Intelligence for Industrial Engineering, 160–88. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-864-2.ch007.
Texto completoLourenço, Patrícia. "Biomass Estimation Using Satellite-Based Data". En Forest Biomass - From Trees to Energy. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.93603.
Texto completoJin, Minhao, Shaojie Luo, Jiabin Huang y Xincheng Zhou. "Efficient Security Detection Strategy Based on K-Means Algorithm in LPWAN". En Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220547.
Texto completoMinke, Anneke y Helmut Lessing. "Environmental Monitoring, Data Mining, and Dynamic Analysis". En Corporate Environmental Management Information Systems, 168–79. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-981-1.ch011.
Texto completoActas de conferencias sobre el tema "Multi-sensors integration"
Huwedi, Ashraf, Peter Steinhaus y Rudiger Dillmann. "Autonomous Feature-Based Exploration using Multi-Sensors". En 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. IEEE, 2006. http://dx.doi.org/10.1109/mfi.2006.265610.
Texto completoZhe Mao, Zhuoran Zhang, Yaling Lu y Shuai Mei. "The data fusion with ANFIS in multi-sensors grain information monitoring system". En 2012 4th Electronic System-Integration Technology Conference (ESTC). IEEE, 2012. http://dx.doi.org/10.1109/estc.2012.6485676.
Texto completoImam, Neena, Jacob Barhen y Charles Glover. "Optimum sensors integration for multi-sensor multi-target environment for ballistic missile defense applications". En 2012 6th Annual IEEE Systems Conference (SysCon). IEEE, 2012. http://dx.doi.org/10.1109/syscon.2012.6189519.
Texto completoSenanayake, S. M. N. Arosha, Owais Ahmed Malik y Mohammad Iskandar. "Wireless Multi-Sensor Integration for ACL Rehabilitation Using Biofeedback Mechanism". En ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-87809.
Texto completoRuser, Heinrich. "Smartlow-cost weather sensor as an example for `multi-component' sensors". En 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. IEEE, 2006. http://dx.doi.org/10.1109/mfi.2006.265675.
Texto completoLatorre, L., J. Miquel y S. Chamaille-Jammes. "MEMS based Low-Power Multi-Sensors device for Bio-Logging Applications". En 2021 Symposium on Design, Test, Integration & Packaging of MEMS and MOEMS (DTIP). IEEE, 2021. http://dx.doi.org/10.1109/dtip54218.2021.9568669.
Texto completoXu, Y., J. Y. Wang, B. X. Cao y J. Yang. "Multi sensors based ultrasonic human face identification: Experiment and analysis". En 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.
Texto completoKaed, Charbel El, Andre Ponnouradjane y Dhaval Shah. "A Semantic Based Multi-Platform IoT Integration Approach from Sensors to Chatbots". En 2018 Global Internet of Things Summit (GIoTS). IEEE, 2018. http://dx.doi.org/10.1109/giots.2018.8534520.
Texto completoLiu, Lu, Ling Xiao y Tingting Liu. "Construction and Integration of under vehicle inspection system based on multi-source sensors". En 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2019. http://dx.doi.org/10.1109/icspcc46631.2019.8960709.
Texto completoNishimura, Yuki, Makoto Sakamoto y Tomoyuki Yamaguchi. "Development of Multi-copter System on Concrete Surfaces with Outer Frame and Wind Speed Sensors*". En 2020 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2020. http://dx.doi.org/10.1109/sii46433.2020.9026215.
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