Relevant bibliographies by topics / Sensor information

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sensor information'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Sensor information"

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Lee, Eun-Taik, and Hee-Chang Eun. "Optimal sensor placements using modified Fisher information matrix and effective information algorithm." International Journal of Distributed Sensor Networks 17, no. 6 (2021): 155014772110230. http://dx.doi.org/10.1177/15501477211023022.

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This article presents an optimal sensor placement algorithm for modifying the Fisher information matrix and effective information. The modified Fisher information matrix and effective information are expressed using a dynamic equation constrained by the condensed relationship of the incomplete mode shape matrix. The mode shape matrix row corresponding to the master degree of freedom of the lowest-contribution Fisher information matrix and effective information indices is moved to the slave degree of freedom during each iteration to obtain an updated shape matrix, which is then used in subseque
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FABRE, S., A. APPRIOU, and X. BRIOTTET. "SENSOR FUSION INTEGRATING CONTEXTUAL INFORMATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 09, no. 03 (2001): 369–409. http://dx.doi.org/10.1142/s0218488501000855.

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The application of multi-sensor fusion, which aims at recogizing a state among a set of hypotheses for object classification, is of major interest as regards the performance improvement brought by the sensor complementarily. Nevertheless this needs to take into account the more accurate as possible information and take advantage of the statistical learning of the previous measurements acquired by sensors. The classical probabilistic fusion methods lack of performance when the previous learning is not representative of the real measurements provided by sensors. The theory of evidence is then in
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Petrivskyi, V. Y., V. L. Shevchenko, O. S. Bychkov, and I. P. Sinitsyn. "Information technology to ensure the survivability of sensor networks." PROBLEMS IN PROGRAMMING, no. 4 (December 2021): 062–69. http://dx.doi.org/10.15407/pp2021.04.062.

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In the modern technological world, sensors and sensor networks are widely used in the all spheres of human activity. One of the key engineering tasks in the design of sensor networks is to ensure the survivability of the network. The article presents algorithms for ensuring the survivability of sensor networks based on a preliminary assessment of this property. Estimation of survivability depends on the network topology. Increasing the survivability of the sensor network is achieved by including additional sensors in the network. An algorithm for finding the position of additional sensors in t
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WANG, BANG. "SENSOR PLACEMENT FOR COMPLETE INFORMATION COVERAGE IN DISTRIBUTED SENSOR NETWORKS." Journal of Circuits, Systems and Computers 17, no. 04 (2008): 627–36. http://dx.doi.org/10.1142/s0218126608004575.

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The sensor placement problem for complete information coverage in a distributed sensor network is studied. Sensors are assumed to be placed on the grid points of a grid in the sensor field and complete information coverage is claimed if all the grid points are information covered. This sensor placement problem is formulated as a constrained optimization problem where the objective is to minimize the total cost while guaranteeing certain coverage requirement. We propose a greedy algorithm to solve this problem. Computational results show that the proposed algorithm can efficiently obtain a good
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Luo, Yuxuan, Panhao Xu, Qinghai Dong, and Boyuan Qiao. "Remote Information Interaction and Software based on Sensor Recognition." Scientific Journal of Technology 5, no. 1 (2023): 1–5. http://dx.doi.org/10.54691/sjt.v5i1.3455.

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Sensor network integrates sensor technology, embedded computing technology, distributed information processing technology and wireless communication technology, and can cooperate in field monitoring, sensing, collecting and processing the information of monitoring objects.wireless sensor network technology has the advantages of self-organization, rapid deployment, high fault tolerance and concealment. At present, sensor technology is frequently used in various fields, but there are many kinds of sensors. It is inefficient to combine the information measured by each sensor to obtain the accurat
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Ehlenbröker, Jan-Friedrich, Uwe Mönks, and Volker Lohweg. "Sensor defect detection in multisensor information fusion." Journal of Sensors and Sensor Systems 5, no. 2 (2016): 337–53. http://dx.doi.org/10.5194/jsss-5-337-2016.

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Abstract. In industrial processes a vast variety of different sensors is increasingly used to measure and control processes, machines, and logistics. One way to handle the resulting large amount of data created by hundreds or even thousands of different sensors in an application is to employ information fusion systems. Information fusion systems, e.g. for condition monitoring, combine different sources of information, like sensors, to generate the state of a complex system. The result of such an information fusion process is regarded as a health indicator of a complex system. Therefore, inform
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Kim, Hyun Jun, Man Bok Park, and Meong Hyun Lee. "Journal of Knowledge Information Technology and Systems)." Korean Institute of Smart Media 12, no. 10 (2023): 55–62. http://dx.doi.org/10.30693/smj.2023.12.10.55.

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Innovation and change are occurring rapidly in the agriculture and livestock industry, and new technologies such as smart barns are being introduced, and data that can be used to control equipment is being collected by utilizing various sensors. However, there are various challenges in the operation of barns, and virtual sensor technology is needed to solve these challenges. In this paper, we define various data items and sensor data types used in livestock farms, study cases that utilize virtual sensors in other fields, and implement and design a virtual sensor system for the final smart live
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Odeberg, Hans. "Fusing sensor information using fuzzy measures." Robotica 12, no. 5 (1994): 465–72. http://dx.doi.org/10.1017/s0263574700018026.

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SUMMARYIn a measurement system with intelligent, distributed sensor processes, complementary observations from different sensor need be combined with each other. This paper describes a method based on fuzzy measures, in which a global ‘fusion algorithm’ questions the sensors as to their support and opinion of a hypothesis. The sensor opinions are clustered into groups based on their support of each others' opinions, and fused using a new fuzzy operator.
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Williams, Simon, Arthur George Suvorov, Zengfu Wang, and Bill Moran. "The Information Geometry of Sensor Configuration." Sensors 21, no. 16 (2021): 5265. http://dx.doi.org/10.3390/s21165265.

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In problems of parameter estimation from sensor data, the Fisher information provides a measure of the performance of the sensor; effectively, in an infinitesimal sense, how much information about the parameters can be obtained from the measurements. From the geometric viewpoint, it is a Riemannian metric on the manifold of parameters of the observed system. In this paper, we consider the case of parameterized sensors and answer the question, “How best to reconfigure a sensor (vary the parameters of the sensor) to optimize the information collected?” A change in the sensor parameters results i
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Yan, Qingli, and Jianfeng Chen. "Sensor Selection via Maximizing Hybrid Bayesian Fisher Information and Mutual Information in Unreliable Sensor Networks." Electronics 9, no. 2 (2020): 283. http://dx.doi.org/10.3390/electronics9020283.

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The sensor selection problem is addressed for unreliable sensor networks. The Bayesian Fisher information (BFI) matrix, mutual information (MI) and their relationship are investigated under Gaussian mixture noise conditions. To overcome the flaw that the sensor selection methods based on either BFI matrix or MI could not provide coincident results, the multiple objective optimal (MOP) -based sensor selection approach is developed via minimizing the number of selected sensors while maximizing corresponding BFI matrix and MI. The variable weight decision making (VWDM) and technique for order of
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Dissertations / Theses on the topic "Sensor information"

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Williams, Jason L. "Information theoretic sensor management." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/38534.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 195-203).<br>Sensor management may be defined as those stochastic control problems in which control values are selected to influence sensing parameters in order to maximize the utility of the resulting measurements for an underlying detection or estimation problem. While problems of this ty
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Oreshkin, Boris. "Distributed information fusion in sensor networks." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86916.

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This thesis addresses the problem of design and analysis of distributed in-network signal processing algorithms for effcient aggregation and fusion of information in wireless sensor networks. The distributed in-network signal processing algorithms alleviate a number of drawbacks of the centralized fusion approach. The single point of failure, complex routing protocols, uneven power consumption in sensor nodes, ineffcient wireless channel utilization, and poor scalability are among these drawbacks. These drawbacks of the centralized approach lead to reduced network lifetime, poor robustness to
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Lowery, Paul. "Information processing in multi sensor systems." Thesis, University of Derby, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322505.

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Fox, Elizabeth Lynn. "Cognitive Analysis of Multi-sensor Information." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1435681970.

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Barua, Shaibal. "Multi-sensor Information Fusion for Classification of Driver's Physiological Sensor Data." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-18880.

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Physiological sensor signals analysis is common practice in medical domain for diagnosis andclassification of various physiological conditions. Clinicians’ frequently use physiologicalsensor signals to diagnose individual’s psychophysiological parameters i.e., stress tiredness,and fatigue etc. However, parameters obtained from physiological sensors could vary becauseof individual’s age, gender, physical conditions etc. and analyzing data from a single sensorcould mislead the diagnosis result. Today, one proposition is that sensor signal fusion canprovide more reliable and efficient outcome tha
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Sonbul, O., M. Byamukama, S. Alzebda, and A. N. Kalashnikov. "Autonomous intrusion detection information system." Thesis, Сумський державний університет, 2012. http://essuir.sumdu.edu.ua/handle/123456789/28777.

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Abstract – Implementation of security arrangements for insecure premises, for example, for temporary exhibitions or infrequent public events, usually results in substantial security personnel costs which can be potentially reduced by employing an easily installable ad hoc intrusion detection information system. In the paper we described the architecture, design and experimental results for a fully prototyped information system that utilizes ultrasonic sensors operating in the pulse echo mode for the perimeter control and ZigBee transceivers for wireless networking. The system consists of inexp
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Tang, Zhijun. "Information-theoretic management of mobile sensor agents." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1126882086.

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Thesis (Ph. D.)--Ohio State University, 2005.<br>Title from first page of PDF file. Document formatted into pages; contains xiii, 170 p.; also includes graphics (some col.). Includes bibliographical references (p. 162-170). Available online via OhioLINK's ETD Center
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Skordylis, Antonios. "Information propagation in traffic monitoring sensor networks." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558548.

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This work investigates the problem of efficiently monitoring and disseminating road traffic information in urban settings using fixed and mobile sensor networks. A key challenge in outdoor urban environments is that bandwidth is a scarce resource. It is thus vital to reduce the communication cost of forwarding traffic data from source sensor nodes through the wireless network to the traffic monitoring center. This thesis proposes two distinct approaches to reducing the communication cost of traffic monitoring: 1) in-network data reduction in the context of fixed sensor networks, and 2) efficie
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Grocholsky, Ben. "Information-Theoretic Control of Multiple Sensor Platforms." Thesis, The University of Sydney, 2002. http://hdl.handle.net/2123/796.

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This thesis is concerned with the development of a consistent, information-theoretic basis for understanding of coordination and cooperation decentralised multi-sensor multi-platform systems. Autonomous systems composed of multiple sensors and multiple platforms potentially have significant importance in applications such as defence, search and rescue mining or intelligent manufacturing. However, the effective use of multiple autonomous systems requires that an understanding be developed of the mechanisms of coordination and cooperation between component systems in pursuit of a common goal. A
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Grocholsky, Ben. "Information-Theoretic Control of Multiple Sensor Platforms." University of Sydney. School of Aerospace, Mechanical and Mechatronic Engineering, 2002. http://hdl.handle.net/2123/796.

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This thesis is concerned with the development of a consistent, information-theoretic basis for understanding of coordination and cooperation decentralised multi-sensor multi-platform systems. Autonomous systems composed of multiple sensors and multiple platforms potentially have significant importance in applications such as defence, search and rescue mining or intelligent manufacturing. However, the effective use of multiple autonomous systems requires that an understanding be developed of the mechanisms of coordination and cooperation between component systems in pursuit of a common goal. A
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Books on the topic "Sensor information"

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Zhao, Feng, and Leonidas Guibas, eds. Information Processing in Sensor Networks. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36978-3.

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Durrant-Whyte, Hugh F. Information and multi-sensor coordination. University of Pennsylvania, Dept. of Computer and Information Science, School of Engineering and Applied Science, 1987.

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J, Guibas Leonidas, ed. Wireless sensor networks: An information processing approach. Morgan Kaufmann, 2004.

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Zhao, Feng. Wireless sensor networks: An information processing approach. Morgan Kaufmann Publishers, 2005.

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Zhao, Feng. Wireless sensor networks: An information processing approach. Morgan Kaufmann, 2004.

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Guang-Zhong, Yang, ed. Body sensor networks. Springer, 2006.

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Aggarwal, Charu C. Managing and Mining Sensor Data. Springer US, 2013.

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Foody, Giles, Peter Mooney, Cidália Costa Fonte, Ana Maria Olteanu Raimond, Steffen Fritz, and Linda See, eds. Mapping and the Citizen Sensor. Ubiquity Press, 2017.

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Michel, Grothe, Kooijman Jan, and Nederlandse Commissie voor Geodesie, eds. Sensor web enablement. NCG, 2008.

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Michel, Grothe, Kooijman Jan, and Nederlandse Commissie voor Geodesie, eds. Sensor web enablement. NCG, 2008.

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Book chapters on the topic "Sensor information"

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Rashid, Md Mamunur, Joarder Kamruzzaman, Iqbal Gondal, and Rafiul Hassan. "Periodic Associated Sensor Patterns Mining from Wireless Sensor Networks." In Neural Information Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70139-4_25.

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Iyengar, Sitharama S. "Embedded Sensor Networks." In Information Systems, Technology and Management. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00405-6_1.

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Becker, Anna Maria, Carolin Helbig, Abdelrhman Mohamdeen, Torsten Masson, and Uwe Schlink. "Environmental Tracking for Healthy Mobility." In Volunteered Geographic Information. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35374-1_11.

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AbstractEnvironmental stressors in city traffic are a relevant health threat to urban cyclists and pedestrians. These stressors are multifaceted and include noise pollution, heat, and air pollution such as particulate matter. In the present chapter, we describe the use of wearable sensors carried by volunteers to capture their exposure to environmental stressors on their everyday routes. These wearable sensors are becoming increasingly important to capture the spatial and temporal distribution of environmental factors in the city. They also offer the unique opportunity to provide individualize
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Koch, Wolfgang. "Integration of Topographical Information." In Tracking and Sensor Data Fusion. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39271-9_9.

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Ogiela, Lidia, and Marek R. Ogiela. "Management Information Systems." In Ubiquitous Computing Application and Wireless Sensor. Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9618-7_44.

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Li, Jin, Chi Zhang, Wei Yi Liu, and Kun Yue. "No Regret Learning for Sensor Relocation in Mobile Sensor Networks." In Information Computing and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25255-6_28.

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Patel, Bhumika, and Devesh Jinwala. "Exploring Homomorphic Encryption in Wireless Sensor Networks." In Informatics Engineering and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25327-0_34.

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Park, Chang-Hong, Jungwon Cho, and Do-Hyeun Kim. "Sensor Web for Supporting Mobility in Sensor Networks." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35270-6_28.

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Huang, Xin, Yang Jiang, Xiong Gao, Rong Fu, and Tingting Zhang. "Sensor Aided Authentication." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13365-7_26.

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Mozos, Óscar Martínez. "Semantic Information in Sensor Data." In Semantic Labeling of Places with Mobile Robots. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11210-2_8.

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Conference papers on the topic "Sensor information"

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Ryan, Allison D., Hugh Durrant-Whyte, and J. Karl Hedrick. "Information-Theoretic Sensor Motion Control for Distributed Estimation." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-43791.

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Estimate uncertainty is a clear metric for sensing problems, but is not traditionally used for optimal control of mobile sensors because it is difficult to model how it is affected by sensor motion. This work develops a multiple-step receding horizon cost for sensor motion control based on minimization of expected entropy of the estimate distribution. The structure of the cost function is analyzed and used to upper bound the degree of coupling between sensors. The contribution is a multiple step prediction of the estimate entropy incorporating probabilistic sensor and target motion models and
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Flatau, Alison, Usha Varshney, and Peter Chang. "Future Trends in Sensed-Information Technology and Sensor Systems Research." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33177.

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Advances in MEMs, wireless, information technology and other enabling technologies are leading to new sensor system functionality and access to more accurate data and information than heretofore realizable. These advances are crucial for realizing the full potential of the on-going transition from data-poor to data-rich and information-poor to information-rich science and engineering practices. With decreases in size and cost of sensors resulting from advances in microsystem technologies, ubiquitous sensing is becoming both physically realizable and economically feasible. New developments in s
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Sohal, Shubhdildeep S., and Pinhas Ben-Tzvi. "Sensor Based Target Tracking With Application to Autonomous Docking and Self-Reconfigurability." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22181.

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Abstract This paper presents a target detection technique, which combines a supervised learning model with sensor data to eliminate false positives for a given input image frame. Such a technique aids with selective docking procedures where multiple robots are present in the environment. Hence the sensor data provides additional information for this decision making process. Senor accuracy plays a crucial role when the motion of the robot is defined by the use of data recorded by its sensors. The uncertainties in the sensory data can cause misalignments due to poor calibration of the sensor, wh
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Pourali, Masoud, and Ali Mosleh. "Application of Bayesian Sensor Placement Optimization for Real–Time Health Monitoring." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71143.

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Sensors are being increasingly used for real–time health monitoring of complex systems. The measured quantities are expected to provide real–time information about the state of the system, its subsystems, components, and internal and external physical parameters. A complex system normally requires many sensors to extract required information from the sensed environment. The increasing costs of aging systems and infrastructures have become a major concern and real–time health monitoring systems could ensure increased safety and reliability of these systems. Real–time system health monitoring, a
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Kumar, Manish, Devendra P. Garg, and Randy A. Zachery. "Intelligent Sensor Modeling and Data Fusion via Neural Network and Maximum Likelihood Estimation." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80972.

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The major thrust of this paper is to develop a sensor model based on a probabilistic approach that could accurately provide information about individual sensor’s uncertainties and limitations. The sensor model aims to provide a most informative likelihood function that can be used to obtain a statistical and probabilistic estimate of uncertainties and errors due to some environmental parameters or parameters of any feature extraction algorithm used in estimation based on sensor’s outputs. This paper makes use of a neural network that has been trained with the help of a novel technique that obt
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"Intelligent Sensors, Sensor Networks, and Information Processing." In 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2018. http://dx.doi.org/10.1109/etfa.2018.8502521.

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Muro, Keiro, Takehiro Urano, Toshiyuki Odaka, and Kei Suzuki. "AirSenseWare: Sensor-network Middleware for Information Sharing." In 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information. IEEE, 2007. http://dx.doi.org/10.1109/issnip.2007.4496893.

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Huang, Jiaxu, Rand Hidayah, Sunil Agrawal, Jorge A. Diez, and Nicolas García-Aracil. "Application of a Customized Optical Force Sensor to a Cable-Driven Leg Exoskeleton." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-69353.

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Abstract In this paper, a customized optical force sensor is developed for an application with a cable-driven leg exoskeleton. Sensors are vital components of cable-driven, exoskeletal robotic systems, which require real-time and accurate measurement of cable tensions. While these systems’ accuracy is a consideration, the added weight, volume, and complexity of the system must is an essential part of widespread adoption for wearable applications. These sensors can also be costly, which is undesirable. An optical force sensor has the advantages of being lightweight, lower in manufacturing cost,
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Hieu, Tran Trong, Paul C. P. Chao, Yu-Jen Wang, and Chun-Chieh Wang. "A New Method for Calibrating a Six-DOF Joint Force/Torque Sensor." In ASME 2014 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/isps2014-6969.

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One of the main senses that humans use to interact with their environment is the sense of touch and this is currently the major aim of many research projects of robots in varied forms. The measurement of the multi-dimension interactive force between the human hand and interaction device such as hand-controllers, joysticks, limb rehabilitation devices, etc., becomes important components. Encoders are installed in each joint for position-sensing feedbacks while tactile sensors are often installed at the fingertip of a hand to detect contacts [1][2][3][4]. There have been varied sensor structures
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"Publisher Information." In Implantable Body Sensor Networks Conference (BSN). IEEE, 2009. http://dx.doi.org/10.1109/bsn.2009.67.

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Reports on the topic "Sensor information"

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Bierman, A., D. Romascanu, and K. C. Norseth. Entity Sensor Management Information Base. RFC Editor, 2002. http://dx.doi.org/10.17487/rfc3433.

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Man, Hong, and Yafeng Yin. Information Assurance in Sensor Networks. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada523100.

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Pouchard, Line Catherine, Stephen W. Poole, and Josh Lothian. Open Standards for Sensor Information Processing. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/979218.

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Welborn, Matthew. Multi-Sensor Information Integration and Automatic Understanding. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada488781.

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SIGNAL INNOVATIONS GROUP INC DURHAM NC. Multi Sensor Information Integration and Automatic Understanding. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada455648.

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Thuraisingham, Bhavani. Secure Sensor Semantic Web and Information Fusion. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada610634.

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Welborn, Matthew, and Samantha Venters. Multi-Sensor Information Integration and Automatic Understanding. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada472949.

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Lee, Michael, and Tim Gregory. Sensor Information Recommender System Start-Up Guide. DEVCOM Army Research Laboratory, 2023. http://dx.doi.org/10.21236/ad1200257.

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Ding, Kung-Hau. Phenomenology-Based Inverse Scattering for Sensor Information Fusion. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada456574.

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Williams, Brian. Bayesian Optimal Sensor Augmentation Via Estimated Mutual Information. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1669078.

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