Data Mining Techniques In Sensor Networks

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Data Mining Techniques in Sensor Networks

Author : Annalisa Appice
Publisher : Springer Science & Business Media
ISBN 13 : 1447154541
Total Pages : 115 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Data Mining Techniques in Sensor Networks by : Annalisa Appice

Download or read book Data Mining Techniques in Sensor Networks written by Annalisa Appice and published by Springer Science & Business Media. This book was released on 2013-09-12 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data. This work introduces a recently defined spatio-temporal pattern, called trend cluster, to summarize, interpolate and identify anomalies in a sensor network. As an example, the application of trend cluster discovery to monitor the efficiency of photovoltaic power plants is discussed. The work closes with remarks on new possibilities for surveillance enabled by recent developments in sensing technology.

Managing and Mining Sensor Data

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
ISBN 13 : 1461463092
Total Pages : 547 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Managing and Mining Sensor Data by : Charu C. Aggarwal

Download or read book Managing and Mining Sensor Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2013-01-15 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

Intelligent Techniques for Warehousing and Mining Sensor Network Data

Author : Cuzzocrea, Alfredo
Publisher : IGI Global
ISBN 13 : 1605663298
Total Pages : 424 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Intelligent Techniques for Warehousing and Mining Sensor Network Data by : Cuzzocrea, Alfredo

Download or read book Intelligent Techniques for Warehousing and Mining Sensor Network Data written by Cuzzocrea, Alfredo and published by IGI Global. This book was released on 2009-12-31 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the relevant research theme of warehousing and mining sensor network data, specifically for the database, data warehousing and data mining research communities"--Provided by publisher.

Sensor Technology: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799824551
Total Pages : 1618 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Sensor Technology: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Sensor Technology: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-02-07 with total page 1618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collecting and processing data is a necessary aspect of living in a technologically advanced society. Whether it’s monitoring events, controlling different variables, or using decision-making applications, it is important to have a system that is both inexpensive and capable of coping with high amounts of data. As the application of these networks becomes more common, it becomes imperative to evaluate their effectiveness as well as other opportunities for possible implementation in the future. Sensor Technology: Concepts, Methodologies, Tools, and Applications is a vital reference source that brings together new ways to process and monitor data and to put it to work in everything from intelligent transportation systems to healthcare to multimedia applications. It also provides inclusive coverage on the processing and applications of wireless communication, sensor networks, and mobile computing. Highlighting a range of topics such as internet of things, signal processing hardware, and wireless sensor technologies, this multi-volume book is ideally designed for research and development engineers, IT specialists, developers, graduate students, academics, and researchers.

Learning from Data Streams

Author : João Gama
Publisher : Springer Science & Business Media
ISBN 13 : 3540736786
Total Pages : 486 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Learning from Data Streams by : João Gama

Download or read book Learning from Data Streams written by João Gama and published by Springer Science & Business Media. This book was released on 2007-10-11 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Knowledge Discovery from Data Streams

Author : Joao Gama
Publisher : CRC Press
ISBN 13 : 1439826129
Total Pages : 256 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Knowledge Discovery from Data Streams by : Joao Gama

Download or read book Knowledge Discovery from Data Streams written by Joao Gama and published by CRC Press. This book was released on 2010-05-25 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents

Big Data Analytics for Sensor-Network Collected Intelligence

Author : Hui-Huang Hsu
Publisher : Morgan Kaufmann
ISBN 13 : 012809625X
Total Pages : 328 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Big Data Analytics for Sensor-Network Collected Intelligence by : Hui-Huang Hsu

Download or read book Big Data Analytics for Sensor-Network Collected Intelligence written by Hui-Huang Hsu and published by Morgan Kaufmann. This book was released on 2017-02-02 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Contains contributions from noted scholars in computer science and electrical engineering from around the globe - Provides a broad overview of recent developments in sensor collected intelligence - Edited by a team comprised of leading thinkers in big data analytics

Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's

Author : Pradeep Kumar Singh
Publisher : Springer Nature
ISBN 13 : 303040305X
Total Pages : 722 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's by : Pradeep Kumar Singh

Download or read book Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's written by Pradeep Kumar Singh and published by Springer Nature. This book was released on 2020-02-08 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various challenging problems and applications areas of wireless sensor networks (WSNs), and identifies the current issues and future research challenges. Discussing the latest developments and advances, it covers all aspects of in WSNs, from architecture to protocols design, and from algorithm development to synchronization issues. As such the book is an essential reference resource for undergraduate and postgraduate students as well as scholars and academics working in the field.

Knowledge Discovery from Sensor Data

Author : Mohamed Medhat Gaber
Publisher : Springer Science & Business Media
ISBN 13 : 3642125182
Total Pages : 235 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Knowledge Discovery from Sensor Data by : Mohamed Medhat Gaber

Download or read book Knowledge Discovery from Sensor Data written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2010-04-14 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.

Advanced Data Mining and Applications

Author : Reda Alhajj
Publisher : Springer
ISBN 13 : 3540738711
Total Pages : 651 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Advanced Data Mining and Applications by : Reda Alhajj

Download or read book Advanced Data Mining and Applications written by Reda Alhajj and published by Springer. This book was released on 2007-08-14 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Advanced Data Mining and Applications, ADMA 2007, held in Harbin, China in August 2007. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining.

IoT and Analytics for Sensor Networks

Author : Padmalaya Nayak
Publisher : Springer
ISBN 13 : 9789811629181
Total Pages : 508 pages
Book Rating : 4.6/5 (291 download)

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Book Synopsis IoT and Analytics for Sensor Networks by : Padmalaya Nayak

Download or read book IoT and Analytics for Sensor Networks written by Padmalaya Nayak and published by Springer. This book was released on 2021-09-12 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality research papers presented at the 1st International Conference on Wireless Sensor Networks, Ubiquitous Computing and Applications (ICWSNUCA, 2021), which is held at Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India, during 26–27 February, 2021. This volume focuses on the applications, use-cases, architectures, deployments, and recent advances of wireless sensor networks as well as ubiquious computing. Different research topics are illustrated in this book, like wireless sensor networks for the Internet of Things; IoT applications for eHealth; smart cities; architectures for WSNs and IoT, WSNs hardware and new devices; low-power wireless technologies; wireless ad hoc sensor networks; routing and data transfer in WSNs; multicast communication in WSNs; security management in WSNs and in IoT systems; and power consumption optimization in WSNs.

Advanced Methods for Knowledge Discovery from Complex Data

Author : Ujjwal Maulik
Publisher : Springer Science & Business Media
ISBN 13 : 1846282845
Total Pages : 375 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Advanced Methods for Knowledge Discovery from Complex Data by : Ujjwal Maulik

Download or read book Advanced Methods for Knowledge Discovery from Complex Data written by Ujjwal Maulik and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.

Machine Learning for Data Streams

Author : Albert Bifet
Publisher : MIT Press
ISBN 13 : 0262346052
Total Pages : 262 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Machine Learning for Data Streams by : Albert Bifet

Download or read book Machine Learning for Data Streams written by Albert Bifet and published by MIT Press. This book was released on 2018-03-16 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Advances in Intelligent Data Analysis and Applications

Author : Jeng-Shyang Pan
Publisher : Springer Nature
ISBN 13 : 9811650365
Total Pages : 379 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Advances in Intelligent Data Analysis and Applications by : Jeng-Shyang Pan

Download or read book Advances in Intelligent Data Analysis and Applications written by Jeng-Shyang Pan and published by Springer Nature. This book was released on 2021-11-25 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the Proceeding of the Sixth International Conference on Intelligent Data Analysis and Applications, October 15–18, 2019, Arad, Romania. This edition is technically co-sponsored by “Aurel Vlaicu” University of Arad, Romania, Southwest Jiaotong University, Fujian University of Technology, Chang’an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology), China, Romanian Academy, and General Association of Engineers in Romania - Arad Section. The book covers a range of topics: Machine Learning, Intelligent Control, Pattern Recognition, Computational Intelligence, Signal Analysis, Modeling and Visualization, Multimedia Sensing and Sensory Systems, Signal control, Imaging and Processing, Information System Security, Cryptography and Cryptanalysis, Databases and Data Mining, Information Hiding, Cloud Computing, Information Retrieval and Integration, Robotics, Control, Agents, Command, Control, Communication and Computers (C4), Swarming Technology, Sensor Technology, Smart cities. The book offers a timely, board snapshot of new development including trends and challenges that are yielding recent research directions in different areas of intelligent data analysis and applications. The book provides useful information to professors, researchers, and graduated students in area of intelligent data analysis and applications.

Mining Complex Networks

Author : Bogumil Kaminski
Publisher : CRC Press
ISBN 13 : 1000515907
Total Pages : 228 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Mining Complex Networks by : Bogumil Kaminski

Download or read book Mining Complex Networks written by Bogumil Kaminski and published by CRC Press. This book was released on 2021-12-14 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision-making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks aim to understand the principles governing the organization and the behavior of such networks is crucial for a broad range of fields of study. Here are a few selected typical applications of mining networks: Community detection (which users on some social media platforms are close friends). Link prediction (who is likely to connect to whom on such platforms). Node attribute prediction (what advertisement should be shown to a given user of a particular platform to match their interests). Influential node detection (which social media users would be the best ambassadors of a specific product). This textbook is suitable for an upper-year undergraduate course or a graduate course in programs such as data science, mathematics, computer science, business, engineering, physics, statistics, and social science. This book can be successfully used by all enthusiasts of data science at various levels of sophistication to expand their knowledge or consider changing their career path. Jupiter notebooks (in Python and Julia) accompany the book and can be accessed on https://www.ryerson.ca/mining-complex-networks/. These not only contain all the experiments presented in the book, but also include additional material. Bogumił Kamiński is the Chairman of the Scientific Council for the Discipline of Economics and Finance at SGH Warsaw School of Economics. He is also an Adjunct Professor at the Data Science Laboratory at Ryerson University. Bogumił is an expert in applications of mathematical modeling to solving complex real-life problems. He is also a substantial open-source contributor to the development of the Julia language and its package ecosystem. Paweł Prałat is a Professor of Mathematics in Ryerson University, whose main research interests are in random graph theory, especially in modeling and mining complex networks. He is the Director of Fields-CQAM Lab on Computational Methods in Industrial Mathematics in The Fields Institute for Research in Mathematical Sciences and has pursued collaborations with various industry partners as well as the Government of Canada. He has written over 170 papers and three books with 130 plus collaborators. François Théberge holds a B.Sc. degree in applied mathematics from the University of Ottawa, a M.Sc. in telecommunications from INRS and a PhD in electrical engineering from McGill University. He has been employed by the Government of Canada since 1996 where he was involved in the creation of the data science team as well as the research group now known as the Tutte Institute for Mathematics and Computing. He also holds an adjunct professorial position in the Department of Mathematics and Statistics at the University of Ottawa. His current interests include relational-data mining and deep learning.

Urban Informatics

Author : Wenzhong Shi
Publisher : Springer Nature
ISBN 13 : 9811589836
Total Pages : 941 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Urban Informatics by : Wenzhong Shi

Download or read book Urban Informatics written by Wenzhong Shi and published by Springer Nature. This book was released on 2021-04-06 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Data Mining and Machine Learning Applications

Author : Rohit Raja
Publisher : John Wiley & Sons
ISBN 13 : 1119791782
Total Pages : 500 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Mining and Machine Learning Applications by : Rohit Raja

Download or read book Data Mining and Machine Learning Applications written by Rohit Raja and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.