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Author: Hui-Huang Hsu
Publisher: Morgan Kaufmann
ISBN: 012809625X
Category : Computers
Languages : en
Pages : 328
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Book Description
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
Author: Hui-Huang Hsu
Publisher: Morgan Kaufmann
ISBN: 012809625X
Category : Computers
Languages : en
Pages : 328
Get Book Here
Book Description
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
Author: Ching-Hsien Hsu
Publisher: Springer Nature
ISBN: 981992233X
Category : Computers
Languages : en
Pages : 570
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Book Description
This book constitutes the proceedings of the International Conference on Big Data Intelligence and Computing, DataCom 2022, which took place in Denarau Island, Fiji, in December 2022. The 30 full papers included in this volume were carefully reviewed and selected from 88 submissions. The papers detail big data analytics solutions, distributed computation paradigms, on-demand services, autonomic systems, and pervasive applications.
Author: Subhendu Kumar Pani
Publisher: CRC Press
ISBN: 1000793559
Category : Technology & Engineering
Languages : en
Pages : 346
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Book Description
Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.
Author: J. Dinesh Peter
Publisher: Springer Nature
ISBN: 9811552851
Category : Technology & Engineering
Languages : en
Pages : 625
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Book Description
This book is a compendium of the proceedings of the International Conference on Big-Data and Cloud Computing. The papers discuss the recent advances in the areas of big data analytics, data analytics in cloud, smart cities and grid, etc. This volume primarily focuses on the application of knowledge which promotes ideas for solving problems of the society through cutting-edge big-data technologies. The essays featured in this proceeding provide novel ideas that contribute for the growth of world class research and development. It will be useful to researchers in the area of advanced engineering sciences.
Author: Dhabaleswar K. Panda
Publisher: MIT Press
ISBN: 0262369427
Category : Computers
Languages : en
Pages : 275
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Book Description
An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.
Author: Sushruta Mishra
Publisher: Academic Press
ISBN: 0323851185
Category : Computers
Languages : en
Pages : 374
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Book Description
Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity. This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers metaheuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks. - Provides a unique opportunity to present the work on the state-of-the-art of metaheuristics approach in the area of big data processing developing automated and intelligent models - Explains different, feasible applications and case studies where cognitive computing can be successfully implemented in big data analytics using metaheuristics algorithms - Provides a snapshot of the latest advances in the contribution of metaheuristics frameworks in cognitive big data applications to solve optimization problems
Author: Kai Hwang
Publisher: John Wiley & Sons
ISBN: 1119247292
Category : Computers
Languages : en
Pages : 432
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Book Description
The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.
Author: Fernando Iafrate
Publisher: John Wiley & Sons
ISBN: 1786300834
Category : Computers
Languages : en
Pages : 162
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Book Description
With the idea of “deep learning” having now become the key to this new generation of solutions, major technological players in the business intelligence sector have taken an interest in the application of Big Data. In this book, the author explores the recent technological advances associated with digitized data flows, which have recently opened up new horizons for AI. The reader will gain insight into some of the areas of application of Big Data in AI, including robotics, home automation, health, security, image recognition and natural language processing.
Author: Siddhartha Bhattacharyya
Publisher: Springer Nature
ISBN: 981336176X
Category : Technology & Engineering
Languages : en
Pages : 301
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Book Description
This book is a collection of best selected research papers presented at International Conference on Intelligent and Smart Computing in Data Analytics (ISCDA 2020), held at K L University, Guntur, Andhra Pradesh, India. The primary focus is to address issues and developments in advanced computing, intelligent models and applications, smart technologies and applications. It includes topics such as artificial intelligence and machine learning, pattern recognition and analysis, computational intelligence, signal and image processing, bioinformatics, ubiquitous computing, genetic fuzzy systems, hybrid evolutionary algorithms, nature-inspired smart hybrid systems, Internet of things, industrial IoT, health informatics, human–computer interaction and social network analysis. The book presents innovative work by leading academics, researchers and experts from industry.
Author: Velayutham, Sathiyamoorthi
Publisher: IGI Global
ISBN: 1799831132
Category : Computers
Languages : en
Pages : 350
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Book Description
In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues.
