Big Data Management In Sensing
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Big Data Management In Sensing
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Author : Renny Fernandez
language : en
Publisher: CRC Press
Release Date : 2022-09-01
Big Data Management In Sensing written by Renny Fernandez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Computers categories.
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.
Big Data Management In Sensing
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Author : Renny Fernandez
language : en
Publisher:
Release Date : 2021
Big Data Management In Sensing written by Renny Fernandez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Effective Big Data Management And Opportunities For Implementation
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Author : Singh, Manoj Kumar
language : en
Publisher: IGI Global
Release Date : 2016-06-20
Effective Big Data Management And Opportunities For Implementation written by Singh, Manoj Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-20 with Computers categories.
“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.
Big Data Analytics For Sensor Network Collected Intelligence
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Author : Hui-Huang Hsu
language : en
Publisher: Morgan Kaufmann
Release Date : 2017-02-02
Big Data Analytics For Sensor Network Collected Intelligence written by Hui-Huang Hsu and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-02 with Computers categories.
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
Applied Big Data Analytics In Operations Management
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Author : Kumar, Manish
language : en
Publisher: IGI Global
Release Date : 2016-09-30
Applied Big Data Analytics In Operations Management written by Kumar, Manish and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Business & Economics categories.
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.
Social Sensing And Big Data Computing For Disaster Management
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Author : Zhenlong Li
language : en
Publisher: Routledge
Release Date : 2020-12-17
Social Sensing And Big Data Computing For Disaster Management written by Zhenlong Li and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-17 with Social Science categories.
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.
Remote Sensing Big Data
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Author : Liping Di
language : en
Publisher: Springer Nature
Release Date : 2023-07-24
Remote Sensing Big Data written by Liping Di and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-24 with Technology & Engineering categories.
This monograph provides comprehensive coverage of the collection, management, and use of big data obtained from remote sensing. The book begins with an introduction to the basics of big data and remote sensing, laying the groundwork for the more specialized information to follow. The volume then goes on to address a wide variety of topics related to the use and management of remote sensing big data, including hot topics such as analysis through machine learning, cyberinfrastructure, and modeling. Examples on how to use the results of big data analysis of remotely sensed data for concrete decision-making are offered as well. The closing chapters discuss geospatial big data initiatives throughout the world and future challenges and opportunities for remote sensing big data applications. The audience for this book includes researchers at the intersection of geoscience and data science, senior undergraduate and graduate students, and anyone else interested in how large datasets obtained through remote sensing can be best utilized. The book presents a culmination of 30 years of research from renowned spatial scientists Drs. Liping Di and Eugene Yu.
Healthcare And Big Data Management
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Author : Bairong Shen
language : en
Publisher: Springer
Release Date : 2017-10-20
Healthcare And Big Data Management written by Bairong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-20 with Science categories.
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.
Big Data Analytics For Intelligent Healthcare Management
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2019-04-15
Big Data Analytics For Intelligent Healthcare Management written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-15 with Science categories.
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
Big Data Analytics For Satellite Image Processing And Remote Sensing
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Author : Swarnalatha, P.
language : en
Publisher: IGI Global
Release Date : 2018-03-09
Big Data Analytics For Satellite Image Processing And Remote Sensing written by Swarnalatha, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-09 with Technology & Engineering categories.
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.