Real Time Data Analytics for Large Scale Sensor Data

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  • Author : Himansu Das
  • Publisher : Academic Press
  • Pages : 298 pages
  • ISBN : 0128182423
  • Rating : /5 from reviews
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Download or Read online Real Time Data Analytics for Large Scale Sensor Data full in PDF, ePub and kindle. this book written by Himansu Das and published by Academic Press which was released on 31 August 2019 with total page 298 pages. We cannot guarantee that Real Time Data Analytics for Large Scale Sensor Data book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more. Examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data Discusses intelligent management systems for applications such as healthcare, robotics and environment modeling Provides a focused approach towards the design and implementation of real-time intelligent systems for the management of sensor data in large-scale environments

Real Time Data Analytics for Large Scale Sensor Data

Real Time Data Analytics for Large Scale Sensor Data
  • Author : Himansu Das,Nilanjan Dey,Valentina Emilia Balas
  • Publisher : Academic Press
  • Release : 31 August 2019
GET THIS BOOK Real Time Data Analytics for Large Scale Sensor Data

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods

Demand based Data Stream Gathering Processing and Transmission

Demand based Data Stream Gathering  Processing  and Transmission
  • Author : Jonas Traub
  • Publisher : BoD – Books on Demand
  • Release : 09 April 2021
GET THIS BOOK Demand based Data Stream Gathering Processing and Transmission

This book presents an end-to-end architecture for demand-based data stream gathering, processing, and transmission. The Internet of Things (IoT) consists of billions of devices which form a cloud of network connected sensor nodes. These sensor nodes supply a vast number of data streams with massive amounts of sensor data. Real-time sensor data enables diverse applications including traffic-aware navigation, machine monitoring, and home automation. Current stream processing pipelines are demand-oblivious, which means that they gather, transmit, and process as much data

Handbook of Large Scale Distributed Computing in Smart Healthcare

Handbook of Large Scale Distributed Computing in Smart Healthcare
  • Author : Samee U. Khan,Albert Y. Zomaya,Assad Abbas
  • Publisher : Springer
  • Release : 07 August 2017
GET THIS BOOK Handbook of Large Scale Distributed Computing in Smart Healthcare

This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working

Artificial Intelligence for the Internet of Health Things

Artificial Intelligence for the Internet of Health Things
  • Author : K. Shankar,Eswaran Perumal,Deepak Gupta
  • Publisher : CRC Press
  • Release : 10 May 2021
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This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and

Smart Grid Using Big Data Analytics

Smart Grid Using Big Data Analytics
  • Author : Robert C. Qiu,Paul Antonik
  • Publisher : John Wiley & Sons
  • Release : 17 April 2017
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This book is aimed at students in communications and signal processing who want to extend their skills in the energy area. It describes power systems and why these backgrounds are so useful to smart grid, wireless communications being very different to traditional wireline communications.

Service Oriented Computing

Service Oriented Computing
  • Author : Sami Yangui,Ismael Bouassida Rodriguez,Khalil Drira,Zahir Tari
  • Publisher : Springer Nature
  • Release : 25 October 2019
GET THIS BOOK Service Oriented Computing

This book constitutes the proceedings of the 17th International Conference on Service-Oriented Computing, ICSOC 2019, held in Toulouse, France, in October 2019. The 28 full and 12 short papers presented together with 7 poster and 2 invited papers in this volume were carefully reviewed and selected from 181 submissions. The papers have been organized in the following topical sections: Service Engineering; Run-time Service Operations and Management; Services and Data; Services in the Cloud; Services on the Internet of Things; Services in Organizations, Business and Society; and Services

Big Data Management and Processing

Big Data Management and Processing
  • Author : Kuan-Ching Li,Hai Jiang,Albert Y. Zomaya
  • Publisher : CRC Press
  • Release : 19 May 2017
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From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore

Computational Intelligence Applications in Business Intelligence and Big Data Analytics

Computational Intelligence Applications in Business Intelligence and Big Data Analytics
  • Author : Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu
  • Publisher : CRC Press
  • Release : 26 June 2017
GET THIS BOOK Computational Intelligence Applications in Business Intelligence and Big Data Analytics

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned

Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry
  • Author : Patrick Bangert
  • Publisher : Gulf Professional Publishing
  • Release : 04 March 2021
GET THIS BOOK Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often

Online Engineering and Society 4 0

Online Engineering and Society 4 0
  • Author : Michael E. Auer,Kalyan Ram Bhimavaram,Xiao-Guang Yue
  • Publisher : Springer Nature
  • Release : 21 October 2021
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This book presents the general objective of the REV2021 conference which is to contribute and discuss fundamentals, applications, and experiences in the field of Online and Remote Engineering, Virtual Instrumentation, and other related new technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber Security, and M2M & Smart Objects. Nowadays, online technologies are the core of most fields of engineering and the whole society and are inseparably connected, for example, with Internet

Next Generation Information Processing System

Next Generation Information Processing System
  • Author : Prachi Deshpande,Ajith Abraham,Brijesh Iyer,Kun Ma
  • Publisher : Springer Nature
  • Release : 13 June 2020
GET THIS BOOK Next Generation Information Processing System

This book gathers high-quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2020) [formerly ICCASP], a flagship event in the area of engineering and emerging next-generation technologies jointly organized by the Dr. Babasaheb Ambedkar Technological University and MGM’s College of Engineering in Nanded, India, on 9-11 January 2020. Focusing on next-generation information processing systems, this second volume of the proceedings includes papers on cloud computing and information systems, artificial intelligence and the Internet of Things,

Maritime Technology and Engineering III

Maritime Technology and Engineering III
  • Author : Carlos Guedes Soares,T.A. Santos
  • Publisher : CRC Press
  • Release : 01 December 2016
GET THIS BOOK Maritime Technology and Engineering III

Maritime Technology and Engineering 3 is a collection of papers presented at the 3rd International Conference on Maritime Technology and Engineering (MARTECH 2016, Lisbon, Portugal, 4-6 July 2016). The MARTECH Conferences series evolved from biannual national conferences in Portugal, thus reflecting the internationalization of the maritime sector. The keynote lectures and the papers, making up nearly 150 contributions, came from an international group of authors focused on different subjects in a variety of fields: Maritime Transportation, Energy Efficiency, Ships in Ports, Ship Hydrodynamics, Ship

Data Analytics for Smart Cities

Data Analytics for Smart Cities
  • Author : Amir Alavi,William G. Buttlar
  • Publisher : CRC Press
  • Release : 26 October 2018
GET THIS BOOK Data Analytics for Smart Cities

The development of smart cities is one of the most important challenges over the next few decades. Governments and companies are leveraging billions of dollars in public and private funds for smart cities. Next generation smart cities are heavily dependent on distributed smart sensing systems and devices to monitor the urban infrastructure. The smart sensor networks serve as autonomous intelligent nodes to measure a variety of physical or environmental parameters. They should react in time, establish automated control, and collect

Managing and Mining Sensor Data

Managing and Mining Sensor Data
  • Author : Charu C. Aggarwal
  • Publisher : Springer Science & Business Media
  • Release : 15 January 2013
GET THIS BOOK Managing and Mining Sensor Data

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