Information Fusion And Analytics For Big Data And Iot

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Information Fusion and Analytics for Big Data and IoT

Author : Eloi Bosse,Basel Solaiman
Publisher : Artech House
Page : 280 pages
File Size : 42,5 Mb
Release : 2016-02-01
Category : Computers
ISBN : 9781630810887

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Information Fusion and Analytics for Big Data and IoT by Eloi Bosse,Basel Solaiman Pdf

The Internet of Things (IoT) and Big Data are hot topics in the world of intelligence operations and information gathering. This first-of-its-kind volume reveals the benefits of addressing these topics with the integration of Fusion of Information and Analytics Technologies (FIAT). The book explains how FIAT is materialized into decision support systems that are capable of supporting the prognosis, diagnosis, and prescriptive tasks within complex systems and organizations. This unique resource offers keen insight into how complex systems emerge from the interrelation of social and cognitive information, cyber and physical worlds, and the various models of decision-making and situational awareness. Practitioners also discover the central notions of analytics and information fusion. Moreover the book introduces propos such as integration through a FIAT computational model and applications at the systems level. This book concludes with a list of prospective research activities that can contribute towards the required FIAT integration for critical application domains such as: energy, health, transport and defense and security.

Possibility Theory for the Design of Information Fusion Systems

Author : Basel Solaiman,Éloi Bossé
Publisher : Springer Nature
Page : 294 pages
File Size : 45,7 Mb
Release : 2019-12-26
Category : Mathematics
ISBN : 9783030328535

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Possibility Theory for the Design of Information Fusion Systems by Basel Solaiman,Éloi Bossé Pdf

This practical guidebook describes the basic concepts, the mathematical developments, and the engineering methodologies for exploiting possibility theory for the computer-based design of an information fusion system where the goal is decision support for industries in smart ICT (information and communications technologies). This exploitation of possibility theory improves upon probability theory, complements Dempster-Shafer theory, and fills an important gap in this era of Big Data and Internet of Things. The book discusses fundamental possibilistic concepts: distribution, necessity measure, possibility measure, joint distribution, conditioning, distances, similarity measures, possibilistic decisions, fuzzy sets, fuzzy measures and integrals, and finally, the interrelated theories of uncertainty..uncertainty. These topics form an essential tour of the mathematical tools needed for the latter chapters of the book. These chapters present applications related to decision-making and pattern recognition schemes, and finally, a concluding chapter on the use of possibility theory in the overall challenging design of an information fusion system. This book will appeal to researchers and professionals in the field of information fusion and analytics, information and knowledge processing, smart ICT, and decision support systems.

Towards the definition of an information quality metric for information fusion models

Author : Horacio Paggi,Javier Soriano,Juan A. Lara,Ernesto Damiani
Publisher : Infinite Study
Page : 14 pages
File Size : 44,6 Mb
Release : 2024-06-02
Category : Education
ISBN : 8210379456XXX

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Towards the definition of an information quality metric for information fusion models by Horacio Paggi,Javier Soriano,Juan A. Lara,Ernesto Damiani Pdf

Managing information quality has become important in cyber-physical systems dealing with big data. In this regard, different models have been proposed, mainly in flat peer-to-peer networks, in which exchanging information efficiently is a key aspect due to scarce resources. However, little research has been conducted on information quality metrics for cyber-physical scenarios. In this paper, we propose an information quality metric and show its application to an information fusion model. It is a “model-oriented quality metric” since it allows non-predefined variants on its configuration depending on the application domain. The model was tested on several simulations using open datasets. The results obtained in the performance of the model confirm the validity of the information quality metric, proposed in this paper, on which the model is based. The model may have a wide variety of applications such as mobile recommendation or decision making in critical environments (emergencies, war, and so on).

Big Data, IoT, and Machine Learning

Author : Rashmi Agrawal,Marcin Paprzycki,Neha Gupta
Publisher : CRC Press
Page : 319 pages
File Size : 54,5 Mb
Release : 2020-09-01
Category : Computers
ISBN : 9781000098280

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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

Relational Calculus for Actionable Knowledge

Author : Michel Barès,Éloi Bossé
Publisher : Springer Nature
Page : 356 pages
File Size : 51,7 Mb
Release : 2022-01-21
Category : Computers
ISBN : 9783030924300

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Relational Calculus for Actionable Knowledge by Michel Barès,Éloi Bossé Pdf

This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, ‘Knowledge Discovery and Data Mining’ (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been ‘actionable’ for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge. Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authors provide an understanding of the concept of ‘relation’ and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering.

Big Data Analytics for Internet of Things

Author : Tausifa Jan Saleem,Mohammad Ahsan Chishti
Publisher : John Wiley & Sons
Page : 402 pages
File Size : 54,8 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.

Internet of Things and Big Data Analytics Toward Next-Generation Intelligence

Author : Nilanjan Dey,Aboul Ella Hassanien,Chintan Bhatt,Amira S. Ashour,Suresh Chandra Satapathy
Publisher : Springer
Page : 549 pages
File Size : 53,8 Mb
Release : 2017-08-14
Category : Technology & Engineering
ISBN : 9783319604350

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Internet of Things and Big Data Analytics Toward Next-Generation Intelligence by Nilanjan Dey,Aboul Ella Hassanien,Chintan Bhatt,Amira S. Ashour,Suresh Chandra Satapathy Pdf

This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

Handbook of IoT and Big Data

Author : Vijender Kumar Solanki,Vicente García Díaz,J. Paulo Davim
Publisher : CRC Press
Page : 268 pages
File Size : 50,6 Mb
Release : 2019-02-21
Category : Computers
ISBN : 9780429624490

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Handbook of IoT and Big Data by Vijender Kumar Solanki,Vicente García Díaz,J. Paulo Davim Pdf

This multi-contributed handbook focuses on the latest workings of IoT (internet of Things) and Big Data. As the resources are limited, it's the endeavor of the authors to support and bring the information into one resource. The book is divided into 4 sections that covers IoT and technologies, the future of Big Data, algorithms, and case studies showing IoT and Big Data in various fields such as health care, manufacturing and automation. Features Focuses on the latest workings of IoT and Big Data Discusses the emerging role of technologies and the fast-growing market of Big Data Covers the movement toward automation with hardware, software, and sensors, and trying to save on energy resources Offers the latest technology on IoT Presents the future horizons on Big Data

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Author : Kai Hwang,Min Chen
Publisher : John Wiley & Sons
Page : 428 pages
File Size : 44,6 Mb
Release : 2017-08-14
Category : Computers
ISBN : 9781119247029

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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.

Designing Wireless Sensor Network Solutions for Tactical ISR

Author : Timothy D. Cole
Publisher : Artech House
Page : 340 pages
File Size : 44,9 Mb
Release : 2020-09-30
Category : Technology & Engineering
ISBN : 9781630813383

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Designing Wireless Sensor Network Solutions for Tactical ISR by Timothy D. Cole Pdf

This comprehensive resource demonstrates how wireless sensor network (WSN) systems, a key element of the Internet of Things (IoT), are designed and evaluated to solve problems associated with autonomous sensing systems. Functional blocks that form WSN-based systems are described, chapter by chapter, providing the reader with a progressive learning path through all aspects of designing remote sensing capabilities using a WSN-based system. The development and a full description of fundamental performance equations and technological solutions required by these real-time systems are included. This book explores the objectives and goals associated with tactical intelligence, surveillance, and reconnaissance (T-ISR) missions. Readers gain insight into the correlation between fine-grained sensor resolution associated with WSN-based system complexities and the difficult requirements associated with T-ISR missions. The book demonstrates how to wield emergent technologies to arrive at reliable and robust wireless networking for T-ISR and associated tasks using low-cost, low-power persistent sensor nodes. WSN is broken down into constituent subsystems, key components, functional descriptions, and attendant mathematical descriptions. This resource explains how the design of each element can be approached and successfully integrated into a viable and responsive sensor system that is autonomous, adaptable to mission objectives and environments, and deployable worldwide. It also provides examples of what not to do based on lessons learned from past (and current) systems that failed to provide end users with the required information. Chapters are linked together, in order of system assembly (concepts to operation), to provide the reader with a full toolset that can help deliver versatility in design decisions, solutions, and understanding of such systems, end to end.

Innovations in Computational Intelligence, Big Data Analytics and Internet of Things

Author : Sam Goundar,J. Avanija,Gurram Sunitha,K. Reddy Madhavi
Publisher : IAP
Page : 385 pages
File Size : 48,8 Mb
Release : 2024-03-01
Category : Computers
ISBN : 9798887305615

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Innovations in Computational Intelligence, Big Data Analytics and Internet of Things by Sam Goundar,J. Avanija,Gurram Sunitha,K. Reddy Madhavi Pdf

As sensors spread across almost every industry, the internet of things is going to trigger a massive influx of big data. We delve into where IoT will have the biggest impact and what it means for the future of big data analytics. Internet of Things is changing the face of different sectors such as manufacturing, health-care, business, education etc. by completely redefining the way people, devices, and apps connect and interact with each other in the eco system. From personal fitness and wellness sensors, implantable devices to surgical robots – IoT is bringing in new tools and efficiencies in the ecosystem resulting in more integrated healthcare. Application of computational intelligence techniques is today considered as a key success factor to solve the growing scale and complexity of problems in the field of health care systems, agriculture, e-commerce etc. The convergence of Computational intelligence, Big Data and IoT provides new opportunities and revolutionize business in huge way. This book will support industry and governmental agencies to facilitate and make sense of myriad connected devices in coming decade. This book offers the recent advancements in Computational Intelligence, IoT and Big Data Analytics. • Development of models and algorithms for employing IoT based facilities in healthcare, industry, agriculture, e- commerce, manufacturing, business etc. • Methods for collection, management retrieval and processing of Big Data in various domains. • Provides taxonomy of challenges, issues and research directions in applications of computational intelligence techniques in different domains

Renewable Energies

Author : Fausto Pedro García Márquez,Alexander Karyotakis,Mayorkinos Papaelias
Publisher : Springer
Page : 159 pages
File Size : 52,6 Mb
Release : 2018-02-16
Category : Technology & Engineering
ISBN : 9783319453644

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Renewable Energies by Fausto Pedro García Márquez,Alexander Karyotakis,Mayorkinos Papaelias Pdf

This book provides a comprehensive overview of current renewable energy technologies and their basic principles. It also addresses the financial aspects of renewable energy projects and analyzes their profitability, covering the most relevant topics for engineers, economists, managers and scientists who are actively involved in renewable energy research and management. The authors are professionals and researchers who are active in the industry, and supplement the main content with revealing case studies and best-practice examples.

Applied Soft Computing

Author : Samarjeet Borah,Ranjit Panigrahi
Publisher : CRC Press
Page : 286 pages
File Size : 41,6 Mb
Release : 2022-02-03
Category : Computers
ISBN : 9781000406634

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Applied Soft Computing by Samarjeet Borah,Ranjit Panigrahi Pdf

This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence. This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.

Combating Security Challenges in the Age of Big Data

Author : Zubair Md. Fadlullah,Al-Sakib Khan Pathan
Publisher : Springer Nature
Page : 271 pages
File Size : 42,9 Mb
Release : 2020-05-26
Category : Computers
ISBN : 9783030356422

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Combating Security Challenges in the Age of Big Data by Zubair Md. Fadlullah,Al-Sakib Khan Pathan Pdf

This book addresses the key security challenges in the big data centric computing and network systems, and discusses how to tackle them using a mix of conventional and state-of-the-art techniques. The incentive for joining big data and advanced analytics is no longer in doubt for businesses and ordinary users alike. Technology giants like Google, Microsoft, Amazon, Facebook, Apple, and companies like Uber, Airbnb, NVIDIA, Expedia, and so forth are continuing to explore new ways to collect and analyze big data to provide their customers with interactive services and new experiences. With any discussion of big data, security is not, however, far behind. Large scale data breaches and privacy leaks at governmental and financial institutions, social platforms, power grids, and so forth, are on the rise that cost billions of dollars. The book explains how the security needs and implementations are inherently different at different stages of the big data centric system, namely at the point of big data sensing and collection, delivery over existing networks, and analytics at the data centers. Thus, the book sheds light on how conventional security provisioning techniques like authentication and encryption need to scale well with all the stages of the big data centric system to effectively combat security threats and vulnerabilities. The book also uncovers the state-of-the-art technologies like deep learning and blockchain which can dramatically change the security landscape in the big data era.

Big Data Analytics in Fog-Enabled IoT Networks

Author : Govind P. Gupta,Rakesh Tripathi,Brij B. Gupta,Kwok Tai Chui
Publisher : CRC Press
Page : 235 pages
File Size : 40,7 Mb
Release : 2023-04-19
Category : Computers
ISBN : 9781000861860

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Big Data Analytics in Fog-Enabled IoT Networks by Govind P. Gupta,Rakesh Tripathi,Brij B. Gupta,Kwok Tai Chui Pdf

The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.