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Big Data Analytics for Sensor-Network Collected Intelligence

Big Data Analytics for Sensor-Network Collected Intelligence
Author: Hui-Huang Hsu
Publisher: Morgan Kaufmann
Total Pages: 328
Release: 2017-02-02
Genre: Computers
ISBN: 012809625X
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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

Big data management in Sensing

Big data management in Sensing
Author: Renny Fernandez
Publisher: CRC Press
Total Pages: 286
Release: 2022-09-01
Genre: Computers
ISBN: 100079427X
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The book is centrally focused on human computer Interaction and how sensors within small and wide groups of Nano-robots employ Deep Learning for applications in industry. It covers a wide array of topics that are useful for researchers and students to gain knowledge about AI and sensors in nanobots. Furthermore, the book explores Deep Learning approaches to enhance the accuracy of AI systems applied in medical robotics for surgical techniques. Secondly, we plan to explore bio-nano-robotics, which is a field in nano-robotics, that deals with automatic intelligence handling, self-assembly and replication, information processing and programmability.

Social Sensing and Big Data Computing for Disaster Management

Social Sensing and Big Data Computing for Disaster Management
Author: Zhenlong Li
Publisher: Routledge
Total Pages: 233
Release: 2020-12-17
Genre: Social Science
ISBN: 1000261530
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Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management. Specifically, analysed within this book are some of the promises and pitfalls of social sensing data for disaster relevant information extraction, impact area assessment, population mapping, occurrence patterns, geographical disparities in social media use, and inclusion in larger decision support systems. Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive, heterogeneous, noisy, and unreliable in some aspects. It comes in continuous streams, and often lacks geospatial reference information. Together, these issues represent a grand challenge toward fully leveraging social sensing for emergency management decision making under extreme duress. Meanwhile, big data computing methods and technologies such as high-performance computing, deep learning, and multi-source data fusion become critical components of using social sensing to understand the impact of and response to the disaster events in a timely fashion. This book was originally published as a special issue of the International Journal of Digital Earth.

Big Data Analytics for Satellite Image Processing and Remote Sensing

Big Data Analytics for Satellite Image Processing and Remote Sensing
Author: Swarnalatha, P.
Publisher: IGI Global
Total Pages: 272
Release: 2018-03-09
Genre: Technology & Engineering
ISBN: 1522536442
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The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.

Big Data Analytics for Intelligent Healthcare Management

Big Data Analytics for Intelligent Healthcare Management
Author: Nilanjan Dey
Publisher: Academic Press
Total Pages: 312
Release: 2019-04-15
Genre: Science
ISBN: 0128181478
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Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more

Applied Big Data Analytics in Operations Management

Applied Big Data Analytics in Operations Management
Author: Kumar, Manish
Publisher: IGI Global
Total Pages: 270
Release: 2016-09-30
Genre: Business & Economics
ISBN: 1522508872
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Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Management in the Era of Big Data

Management in the Era of Big Data
Author: Joanna Paliszkiewicz
Publisher: CRC Press
Total Pages: 246
Release: 2020-06-18
Genre: Business & Economics
ISBN: 1000093670
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This book is a wonderful collection of chapters that posits how managers need to cope in the Big Data era. It highlights many of the emerging developments in technologies, applications, and trends related to management’s needs in this Big Data era. —Dr. Jay Liebowitz, Harrisburg University of Science and Technology This book presents some meaningful work on Big Data analytics and its applications. Each chapter generates helpful guidance to the readers on Big Data analytics and its applications, challenges, and prospects that is necessary for organizational strategic direction. —Dr. Alex Koohang, Middle Georgia State University Big Data is a concept that has caught the attention of practitioners, academicians, and researchers. Big Data offers organizations the possibility of gaining a competitive advantage by managing, collecting, and analyzing massive amounts of data. As the promises and challenges posed by Big Data have increased over the past decade, significant issues have developed regarding how data can be used for improving management. Big Data can be understood as large amounts of data generated by the Internet and a variety of connected smart devices and sensors. This book discusses the main challenges posed by Big Data in a manner relevant to both practitioners and scholars. It examines how companies can leverage Big Data analytics to act and optimize the business. This book brings together the theory and practice of management in the era of Big Data. It offers a look at the current state of Big Data, including a comprehensive overview of both research and practical applications. By bringing together conceptual thinking and empirical research on the nature, meaning, and development of Big Data in management, this book unifies research on Big Data in management to stimulate new directions for academic investigation as well as practice.

Managerial Perspectives on Intelligent Big Data Analytics

Managerial Perspectives on Intelligent Big Data Analytics
Author: Sun, Zhaohao
Publisher: IGI Global
Total Pages: 335
Release: 2019-02-22
Genre: Computers
ISBN: 1522572783
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Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

Effective Big Data Management and Opportunities for Implementation

Effective Big Data Management and Opportunities for Implementation
Author: Singh, Manoj Kumar
Publisher: IGI Global
Total Pages: 345
Release: 2016-06-20
Genre: Computers
ISBN: 1522501835
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“Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.

Healthcare and Big Data Management

Healthcare and Big Data Management
Author: Bairong Shen
Publisher: Springer
Total Pages: 165
Release: 2017-10-20
Genre: Science
ISBN: 981106041X
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The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare; physiological and gut microbiota – data collection and analysis; big data standardization and ontology; and personal data privacy and systems level modeling in the healthcare context. The book offers a valuable resource for biomedical informaticians, clinicians, health practitioners and researchers alike.