Real-Time Data Analytics for Large Scale Sensor Data PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Real-Time Data Analytics for Large Scale Sensor Data PDF full book. Access full book title Real-Time Data Analytics for Large Scale Sensor Data by Himansu Das. Download full books in PDF and EPUB format.
Author: Himansu Das
Publisher: Academic Press
ISBN: 0128182423
Category : Science
Languages : en
Pages : 300
Get Book Here
Book Description
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
Author: Himansu Das
Publisher: Academic Press
ISBN: 0128182423
Category : Science
Languages : en
Pages : 300
Get Book Here
Book Description
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
Author: Byron Ellis
Publisher: John Wiley & Sons
ISBN: 1118838025
Category : Computers
Languages : en
Pages : 432
Get Book Here
Book Description
Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.
Author: Abdelkader Hameurlain
Publisher: Springer Nature
ISBN: 3662661462
Category : Computers
Languages : en
Pages : 157
Get Book Here
Book Description
The LNCS journal Transactions on Large-Scale Data and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 52nd issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains 6 fully revised selected regular papers.
Author: Sami Yangui
Publisher: Springer Nature
ISBN: 3030337022
Category : Computers
Languages : en
Pages : 593
Get Book Here
Book Description
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 at the Edge.
Author: Jitendra Kumar Rout
Publisher: Springer Nature
ISBN: 9811536899
Category : Technology & Engineering
Languages : en
Pages : 219
Get Book Here
Book Description
The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.
Author: K. Shankar
Publisher: CRC Press
ISBN: 1000374297
Category : Computers
Languages : en
Pages : 216
Get Book Here
Book Description
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 students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.
Author: José María Cavanillas
Publisher: Springer
ISBN: 3319215698
Category : Computers
Languages : en
Pages : 312
Get Book Here
Book Description
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
Author: Carlos Guedes Soares
Publisher: CRC Press
ISBN: 1498795935
Category : Technology & Engineering
Languages : en
Pages : 1226
Get Book Here
Book Description
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 Structures, Ship Design, Ship Machinery, Shipyard Technology, afety & Reliability, Fisheries, Oil & Gas, Marine Environment, Renewable Energy and Coastal Structures. This book will appeal to academics, engineers and professionals interested or involved in these fields.
Author: John A
Publisher: Springer Nature
ISBN: 9819996511
Category :
Languages : en
Pages : 253
Get Book Here
Book Description
Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 1498705480
Category : Computers
Languages : en
Pages : 544
Get Book Here
Book Description
Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.
