Big Data Iot And Machine Learning

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Big Data, IoT, and Machine Learning

Author : Rashmi Agrawal,Marcin Paprzycki,Neha Gupta
Publisher : CRC Press
Page : 237 pages
File Size : 43,8 Mb
Release : 2020-07-29
Category : Computers
ISBN : 9781000098303

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Big Data, IoT, and Machine Learning by Rashmi Agrawal,Marcin Paprzycki,Neha Gupta Pdf

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases

Machine Learning, Big Data, and IoT for Medical Informatics

Author : Pardeep Kumar,Yugal Kumar,Mohamed A. Tawhid
Publisher : Academic Press
Page : 458 pages
File Size : 51,9 Mb
Release : 2021-06-13
Category : Computers
ISBN : 9780128217818

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Machine Learning, Big Data, and IoT for Medical Informatics by Pardeep Kumar,Yugal Kumar,Mohamed A. Tawhid Pdf

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT. Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems. Includes several privacy preservation techniques for medical data. Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis. Offers case studies and applications relating to machine learning, big data, and health care analysis.

Proceedings of the International Conference on Big Data, IoT, and Machine Learning

Author : Mohammad Shamsul Arefin,M. Shamim Kaiser,Anirban Bandyopadhyay,Md. Atiqur Rahman Ahad,Kanad Ray
Publisher : Springer Nature
Page : 784 pages
File Size : 45,7 Mb
Release : 2021-12-03
Category : Technology & Engineering
ISBN : 9789811666360

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Proceedings of the International Conference on Big Data, IoT, and Machine Learning by Mohammad Shamsul Arefin,M. Shamim Kaiser,Anirban Bandyopadhyay,Md. Atiqur Rahman Ahad,Kanad Ray Pdf

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty,Jyotir Moy Chatterjee,Monika Mangla,Suneeta Satpathy,Sirisha Potluri
Publisher : John Wiley & Sons
Page : 528 pages
File Size : 43,5 Mb
Release : 2021-07-14
Category : Computers
ISBN : 9781119785859

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Machine Learning Approach for Cloud Data Analytics in IoT by Sachi Nandan Mohanty,Jyotir Moy Chatterjee,Monika Mangla,Suneeta Satpathy,Sirisha Potluri Pdf

Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre,Jinghua Zhao,Xiaomeng Ma
Publisher : Springer Nature
Page : 887 pages
File Size : 45,9 Mb
Release : 2020-11-04
Category : Computers
ISBN : 9783030627461

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by John MacIntyre,Jinghua Zhao,Xiaomeng Ma Pdf

This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Advanced Deep Learning Applications in Big Data Analytics

Author : Bouarara, Hadj Ahmed
Publisher : IGI Global
Page : 351 pages
File Size : 42,5 Mb
Release : 2020-10-16
Category : Computers
ISBN : 9781799827931

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Advanced Deep Learning Applications in Big Data Analytics by Bouarara, Hadj Ahmed Pdf

Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre,Jinghua Zhao,Xiaomeng Ma
Publisher : Springer Nature
Page : 907 pages
File Size : 51,8 Mb
Release : 2020-11-03
Category : Computers
ISBN : 9783030627430

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by John MacIntyre,Jinghua Zhao,Xiaomeng Ma Pdf

This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John Macintyre,Jinghua Zhao,Xiaomeng Ma
Publisher : Springer Nature
Page : 999 pages
File Size : 40,5 Mb
Release : 2021-11-02
Category : Computers
ISBN : 9783030895112

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The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by John Macintyre,Jinghua Zhao,Xiaomeng Ma Pdf

This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John Macintyre,Jinghua Zhao,Xiaomeng Ma
Publisher : Springer Nature
Page : 1169 pages
File Size : 41,7 Mb
Release : 2021-10-27
Category : Computers
ISBN : 9783030895082

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The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by John Macintyre,Jinghua Zhao,Xiaomeng Ma Pdf

This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Big Data Analytics for Internet of Things

Author : Tausifa Jan Saleem,Mohammad Ahsan Chishti
Publisher : John Wiley & Sons
Page : 402 pages
File Size : 49,7 Mb
Release : 2021-04-20
Category : Mathematics
ISBN : 9781119740759

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Big Data Analytics for Internet of Things by Tausifa Jan Saleem,Mohammad Ahsan Chishti Pdf

BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Author : Kai Hwang,Min Chen
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 48,9 Mb
Release : 2017-03-17
Category : Computers
ISBN : 9781119247296

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Big-Data Analytics for Cloud, IoT and Cognitive Computing by Kai Hwang,Min Chen Pdf

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.

Machine Intelligence, Big Data Analytics, and IoT in Image Processing

Author : Ashok Kumar,Megha Bhushan,Jose A. Galindo,Lalit Garg,Yu-Chen Hu
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 42,5 Mb
Release : 2023-02-14
Category : Technology & Engineering
ISBN : 9781119865490

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Machine Intelligence, Big Data Analytics, and IoT in Image Processing by Ashok Kumar,Megha Bhushan,Jose A. Galindo,Lalit Garg,Yu-Chen Hu Pdf

MACHINE INTELLIGENCE, BIG DATA ANALYTICS, AND IoT IN IMAGE PROCESSING Discusses both theoretical and practical aspects of how to harness advanced technologies to develop practical applications such as drone-based surveillance, smart transportation, healthcare, farming solutions, and robotics used in automation. The concepts of machine intelligence, big data analytics, and the Internet of Things (IoT) continue to improve our lives through various cutting-edge applications such as disease detection in real-time, crop yield prediction, smart parking, and so forth. The transformative effects of these technologies are life-changing because they play an important role in demystifying smart healthcare, plant pathology, and smart city/village planning, design and development. This book presents a cross-disciplinary perspective on the practical applications of machine intelligence, big data analytics, and IoT by compiling cutting-edge research and insights from researchers, academicians, and practitioners worldwide. It identifies and discusses various advanced technologies, such as artificial intelligence, machine learning, IoT, image processing, network security, cloud computing, and sensors, to provide effective solutions to the lifestyle challenges faced by humankind. Machine Intelligence, Big Data Analytics, and IoT in Image Processing is a significant addition to the body of knowledge on practical applications emerging from machine intelligence, big data analytics, and IoT. The chapters deal with specific areas of applications of these technologies. This deliberate choice of covering a diversity of fields was to emphasize the applications of these technologies in almost every contemporary aspect of real life to assist working in different sectors by understanding and exploiting the strategic opportunities offered by these technologies. Audience The book will be of interest to a range of researchers and scientists in artificial intelligence who work on practical applications using machine learning, big data analytics, natural language processing, pattern recognition, and IoT by analyzing images. Software developers, industry specialists, and policymakers in medicine, agriculture, smart cities development, transportation, etc. will find this book exceedingly useful.

Applications of Machine Learning in Big-Data Analytics and Cloud Computing

Author : Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt
Publisher : CRC Press
Page : 346 pages
File Size : 53,5 Mb
Release : 2022-09-01
Category : Technology & Engineering
ISBN : 9781000793550

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Applications of Machine Learning in Big-Data Analytics and Cloud Computing by Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt Pdf

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.

New Trends and Applications in Internet of Things (IoT) and Big Data Analytics

Author : Rohit Sharma,Dilip Sharma
Publisher : Springer Nature
Page : 278 pages
File Size : 47,8 Mb
Release : 2022-05-16
Category : Technology & Engineering
ISBN : 9783030993290

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New Trends and Applications in Internet of Things (IoT) and Big Data Analytics by Rohit Sharma,Dilip Sharma Pdf

This book focuses on the use of The Internet of Things (IoT) and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. IoT and big data emerged from the early 2000s data boom, driven forward by many of the early internet and technology companies. The Internet of Things (IoT) is an interconnection of several devices, networks, technologies, and human resources to achieve a common goal. There are a variety of IoT-based applications being used in different sectors and have succeeded in providing huge benefits to the users. The generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends to adopt the data analytics to strengthen solutions. The success of IoT depends upon the influential association of big data analytics. New technologies like search engines, mobile devices, and industrial machines provided as much data as companies could handle—and the scale continues to grow. In a study conducted by IDC, the market intelligence firm estimated that the global production of data would grow 10x between 2015 and 2020. So, the proposed book covers up all the aspects in the field discuss above.

Big Data Analytics for Internet of Things

Author : Tausifa Jan Saleem,Mohammad Ahsan Chishti
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 48,9 Mb
Release : 2021-03-23
Category : Mathematics
ISBN : 9781119740766

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Big Data Analytics for Internet of Things by Tausifa Jan Saleem,Mohammad Ahsan Chishti Pdf

BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.