Cloud Computing For Geospatial Big Data Analytics
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Cloud Computing For Geospatial Big Data Analytics
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Author : Himansu Das
language : en
Publisher: Springer
Release Date : 2018-12-11
Cloud Computing For Geospatial Big Data Analytics written by Himansu Das and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-11 with Technology & Engineering categories.
This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud computing and big data, such as scheduling, security issues using different techniques, which researchers from industry and academia have been attempting to solve in virtual environments. Some of these problems are of an intractable nature and so efficient technologies like fog, edge and mist computing play an important role in addressing these issues. By exploring emerging advances in cloud computing and big data analytics and their engineering applications, the book enables researchers to understand the mechanisms needed to implement cloud, edge, fog, and mist computing in their own endeavours, and motivates them to examine their own research findings and developments.
Data Science In Societal Applications
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Author : Siddharth Swarup Rautaray
language : en
Publisher: Springer Nature
Release Date : 2022-09-15
Data Science In Societal Applications written by Siddharth Swarup Rautaray and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-15 with Computers categories.
The book provides an insight into the practical applications and theoretical foundation of data science. The book discusses new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The book includes contributions from academia and industry experts detailing the shortfalls of current tools and techniques used and generating the blueprint of the new technologies. The topics covered in the book range from theoretical and foundational research, platforms, methods, applications, and tools in data science. The chapters in the book add a social, geographical, and temporal dimension to data science research. The papers included are application-oriented that prepare and use data in discovery research. This book will provide researchers and practitioners with a detailed snapshot of current progress in data science. Moreover, it will stimulate new study, research, and the development of new applications.
Big Data
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Author : Hassan A. Karimi
language : en
Publisher: CRC Press
Release Date : 2014-02-18
Big Data written by Hassan A. Karimi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-18 with Mathematics categories.
Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are acquired very fast, and geospatial databases are inherently very large. And while there have been advances in hardware and software for handling big data, they often fall short of handling geospatial big data ef
Progress In Computing Analytics And Networking
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Author : Prasant Kumar Pattnaik
language : en
Publisher: Springer
Release Date : 2018-04-10
Progress In Computing Analytics And Networking written by Prasant Kumar Pattnaik and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-10 with Technology & Engineering categories.
The book focuses to foster new and original research ideas and results in three broad areas: computing, analytics, and networking with its prospective applications in the various interdisciplinary domains of engineering. This is an exciting and emerging interdisciplinary area in which a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging real world problems. It also provides insights into the International Conference on Computing Analytics and Networking (ICCAN 2017) which is a premier international open forum for scientists, researchers and technocrats in academia as well as in industries from different parts of the world to present, interact, and exchange the state of art of concepts, prototypes, innovative research ideas in several diversified fields. The book includes invited keynote papers and paper presentations from both academia and industry to initiate and ignite our young minds in the meadow of momentous research and thereby enrich their existing knowledge. The book aims at postgraduate students and researchers working in the discipline of Computer Science & Engineering. It will be also useful for the researchers working in the domain of electronics as it contains some hardware technologies and forthcoming communication technologies.
Data Science And Big Data Analytics In Smart Environments
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Author : Marta Chinnici
language : en
Publisher: CRC Press
Release Date : 2021-07-28
Data Science And Big Data Analytics In Smart Environments written by Marta Chinnici and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Computers categories.
Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.
Intelligent Healthcare
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Author : Surbhi Bhatia
language : en
Publisher: Springer Nature
Release Date : 2021-07-02
Intelligent Healthcare written by Surbhi Bhatia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-02 with Technology & Engineering categories.
This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
Big Data In Healthcare
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Author : Pouria Amirian
language : en
Publisher: Springer
Release Date : 2017-09-18
Big Data In Healthcare written by Pouria Amirian and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-18 with Medical categories.
This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data? What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices? This book shows how it is feasible to store vast numbers of anonymous data and ask highly specific questions that can be performed in real-time to give precise and meaningful evidence to guide public health policy.
High Performance Computing For Geospatial Applications
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Author : Wenwu Tang
language : en
Publisher: Springer Nature
Release Date : 2020-07-20
High Performance Computing For Geospatial Applications written by Wenwu Tang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-20 with Technology & Engineering categories.
This volume fills a research gap between the rapid development of High Performance Computing (HPC) approaches and their geospatial applications. With a focus on geospatial applications, the book discusses in detail how researchers apply HPC to tackle their geospatial problems. Based on this focus, the book identifies the opportunities and challenges revolving around geospatial applications of HPC. Readers are introduced to the fundamentals of HPC, and will learn how HPC methods are applied in various specific areas of geospatial study. The book begins by discussing theoretical aspects and methodological uses of HPC within a geospatial context, including parallel algorithms, geospatial data handling, spatial analysis and modeling, and cartography and geovisualization. Then, specific domain applications of HPC are addressed in the contexts of earth science, land use and land cover change, urban studies, transportation studies, and social science. The book will be of interest to scientists and engineers who are interested in applying cutting-edge HPC technologies in their respective fields, as well as students and faculty engaged in geography, environmental science, social science, and computer science.
Big Data Computing For Geospatial Applications
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Author : Zhenlong Li
language : en
Publisher: MDPI
Release Date : 2020-11-23
Big Data Computing For Geospatial Applications written by Zhenlong Li and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Science categories.
The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.
Geospatial Data Analytics On Aws
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Author : Scott Bateman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-06-30
Geospatial Data Analytics On Aws written by Scott Bateman and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Computers categories.
Build an end-to-end geospatial data lake in AWS using popular AWS services such as RDS, Redshift, DynamoDB, and Athena to manage geodata Purchase of the print or Kindle book includes a free PDF eBook. Key Features Explore the architecture and different use cases to build and manage geospatial data lakes in AWS Discover how to leverage AWS purpose-built databases to store and analyze geospatial data Learn how to recognize which anti-patterns to avoid when managing geospatial data in the cloud Book DescriptionManaging geospatial data and building location-based applications in the cloud can be a daunting task. This comprehensive guide helps you overcome this challenge by presenting the concept of working with geospatial data in the cloud in an easy-to-understand way, along with teaching you how to design and build data lake architecture in AWS for geospatial data. You’ll begin by exploring the use of AWS databases like Redshift and Aurora PostgreSQL for storing and analyzing geospatial data. Next, you’ll leverage services such as DynamoDB and Athena, which offer powerful built-in geospatial functions for indexing and querying geospatial data. The book is filled with practical examples to illustrate the benefits of managing geospatial data in the cloud. As you advance, you’ll discover how to analyze and visualize data using Python and R, and utilize QuickSight to share derived insights. The concluding chapters explore the integration of commonly used platforms like Open Data on AWS, OpenStreetMap, and ArcGIS with AWS to enable you to optimize efficiency and provide a supportive community for continuous learning. By the end of this book, you’ll have the necessary tools and expertise to build and manage your own geospatial data lake on AWS, along with the knowledge needed to tackle geospatial data management challenges and make the most of AWS services.What you will learn Discover how to optimize the cloud to store your geospatial data Explore management strategies for your data repository using AWS Single Sign-On and IAM Create effective SQL queries against your geospatial data using Athena Validate postal addresses using Amazon Location services Process structured and unstructured geospatial data efficiently using R Use Amazon SageMaker to enable machine learning features in your application Explore the free and subscription satellite imagery data available for use in your GIS Who this book is forIf you understand the importance of accurate coordinates, but not necessarily the cloud, then this book is for you. This book is best suited for GIS developers, GIS analysts, data analysts, and data scientists looking to enhance their solutions with geospatial data for cloud-centric applications. A basic understanding of geographic concepts is suggested, but no experience with the cloud is necessary for understanding the concepts in this book.