Deep Learning For Internet Of Things Infrastructure

Author : Uttam Ghosh,Mamoun Alazab,Ali Kashif Bashir,Al-Sakib Khan Pathan
Publisher : CRC Press
Page : 266 pages
File Size : 45,9 Mb
Release : 2021-09-30
Category : Computers
ISBN : 9781000431896

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Deep Learning for Internet of Things Infrastructure by Uttam Ghosh,Mamoun Alazab,Ali Kashif Bashir,Al-Sakib Khan Pathan Pdf

This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.

Author : Uttam Ghosh,Mamoun Alazab,Ali Kashif Bashir,Al-Sakib Khan Pathan
Publisher : Unknown
Page : 128 pages
File Size : 54,5 Mb
Release : 2022
Category : Electronic
ISBN : 1032064706

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Deep Learning for Internet of Things Infrastructure by Uttam Ghosh,Mamoun Alazab,Ali Kashif Bashir,Al-Sakib Khan Pathan Pdf

USA.Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia.Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom.Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.

Author : Praveen Kumar Donta
Publisher : Springer Nature
Page : 334 pages
File Size : 45,6 Mb
Release : 2024-07-01
Category : Electronic
ISBN : 9783031505140

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Learning Techniques for the Internet of Things by Praveen Kumar Donta Pdf

Author : Lavanya Sharma,Pradeep Kumar Garg
Publisher : CRC Press
Page : 311 pages
File Size : 54,6 Mb
Release : 2024-06-18
Category : Computers
ISBN : 9781040030820

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Deep Learning in Internet of Things for Next Generation Healthcare by Lavanya Sharma,Pradeep Kumar Garg Pdf

This book presents the latest developments in deep learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with deep learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of deep learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with deep learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, Alzheimer's disease, and genomes. Presents practical approaches of using the IoT with deep learning vision and how it deals with human dynamics Offers novel solution for medical imaging including skin lesion detection, cancer detection, enhancement techniques for MRI images, automated disease prediction, fraud detection, genomes, and many more Includes the latest technological advances in the IoT and deep learning with their implementations in healthcare Combines deep learning and analysis in the unified framework to understand both IoT and deep learning applications Covers the challenging issues related to data collection by sensors, detection and tracking of moving objects and solutions to handle relevant challenges Postgraduate students and researchers in the departments of computer science, working in the areas of the IoT, deep learning, machine learning, image processing, big data, cloud computing, and remote sensing will find this book useful.

Author : Rohit Sharma,Gwanggil Jeon,Yan Zhang
Publisher : Springer Nature
Page : 330 pages
File Size : 54,9 Mb
Release : 2023-09-19
Category : Technology & Engineering
ISBN : 9783031338083

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Data Analytics for Internet of Things Infrastructure by Rohit Sharma,Gwanggil Jeon,Yan Zhang Pdf

This book provides techniques for the deployment of semantic technologies in data analysis along with the latest applications across the field such as Internet of Things (IoT). The authors focus on the use of the IoT and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. They discuss how the generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends the adoption of data analytics to strengthen solutions. The book addresses the challenges in designing the web based IoT system, provides a comparative analysis of different advanced approaches in industries, and contains an analysis of databases to provide expert systems. The book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of IoT and big data analytics.

Author : Kumar, Rajeev,Dwivedi, Rakesh Kumar
Publisher : IGI Global
Page : 335 pages
File Size : 53,9 Mb
Release : 2022-05-13
Category : Political Science
ISBN : 9781799897125

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Advances in Deep Learning Applications for Smart Cities by Kumar, Rajeev,Dwivedi, Rakesh Kumar Pdf

Within the past decade, technology has grown exponentially, and governments have promoted smart cities. Emerging smart cities have become both crucibles and showrooms for the practical application of the internet of things (IoT), cloud computing, and the integration of big data into everyday life. This complex concoction requires new thinking of the synergistic utilization of deep learning and blockchain methods and data-driven decision making with automation infrastructure, autonomous transportation, and more. Advances in Deep Learning Applications for Smart Cities provides a global perspective on current and future trends concerning the integration of deep learning and blockchain for smart cities. It provides valuable insights on the best practices and success factors for smart cities. Covering topics such as digital healthcare, object detection methods, and power consumption, this book is an excellent reference for researchers, scientists, libraries, industry experts, government organizations, students and educators of higher education, business professionals, communication and marketing agencies, entrepreneurs, and academicians.

Author : Souvik Pal,Debashis De,Rajkumar Buyya
Publisher : Springer Nature
Page : 509 pages
File Size : 46,5 Mb
Release : 2022-01-11
Category : Technology & Engineering
ISBN : 9783030870591

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Artificial Intelligence-based Internet of Things Systems by Souvik Pal,Debashis De,Rajkumar Buyya Pdf

The book discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers, academicians, and industry people can easily understand the AI algorithms, machine learning algorithms, and learning analytics in IoT-enabled technologies. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable AI-enabled IoT ecosystem and to implement cyber-physical pervasive infrastructure solutions. This book brings together some of the top IoT-enabled AI experts throughout the world who contribute their knowledge regarding different IoT-based technology aspects.

Author : John Davies,Carolina Fortuna
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 52,5 Mb
Release : 2020-06-08
Category : Technology & Engineering
ISBN : 9781119545262

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The Internet of Things by John Davies,Carolina Fortuna Pdf

Provides comprehensive coverage of the current state of IoT, focusing on data processing infrastructure and techniques Written by experts in the field, this book addresses the IoT technology stack, from connectivity through data platforms to end-user case studies, and considers the tradeoffs between business needs and data security and privacy throughout. There is a particular emphasis on data processing technologies that enable the extraction of actionable insights from data to inform improved decision making. These include artificial intelligence techniques such as stream processing, deep learning and knowledge graphs, as well as data interoperability and the key aspects of privacy, security and trust. Additional aspects covered include: creating and supporting IoT ecosystems; edge computing; data mining of sensor datasets; and crowd-sourcing, amongst others. The book also presents several sections featuring use cases across a range of application areas such as smart energy, transportation, smart factories, and more. The book concludes with a chapter on key considerations when deploying IoT technologies in the enterprise, followed by a brief review of future research directions and challenges. The Internet of Things: From Data to Insight Provides a comprehensive overview of the Internet of Things technology stack with focus on data driven aspects from data modelling and processing to presentation for decision making Explains how IoT technology is applied in practice and the benefits being delivered. Acquaints readers that are new to the area with concepts, components, technologies, and verticals related to and enabled by IoT Gives IoT specialists a deeper insight into data and decision-making aspects as well as novel technologies and application areas Analyzes and presents important emerging technologies for the IoT arena Shows how different objects and devices can be connected to decision making processes at various levels of abstraction The Internet of Things: From Data to Insight will appeal to a wide audience, including IT and network specialists seeking a broad and complete understanding of IoT, CIOs and CIO teams, researchers in IoT and related fields, final year undergraduates, graduate students, post-graduates, and IT and science media professionals.

Author : Sachi Nandan Mohanty,Jyotir Moy Chatterjee,Monika Mangla,Suneeta Satpathy,Sirisha Potluri
Publisher : John Wiley & Sons
Page : 528 pages
File Size : 48,9 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.

Author : Pardeep Kumar,Ahmed Jabbar Obaid,Korhan Cengiz,Ashish Khanna,Valentina Emilia Balas
Publisher : Springer Nature
Page : 462 pages
File Size : 49,9 Mb
Release : 2021-08-23
Category : Technology & Engineering
ISBN : 9783030766535

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A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems by Pardeep Kumar,Ahmed Jabbar Obaid,Korhan Cengiz,Ashish Khanna,Valentina Emilia Balas Pdf

This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community. In the era when the world is grappling with many unforeseen challenges, scientists and researchers are envisioning smart cyber systems that guarantee sustainable development for a better human life. The main contributors that destined to play a huge role in developing such systems, among others, are AI and IoT. While AI provides intelligence to machines and data by identifying patterns, developing predictions, and detecting anomalies, IoT performs as a nerve system by connecting a huge number of machines and capturing an enormous amount of data. AI-enabled IoT, therefore, redefines the way industries, businesses, and economies function with increased automation and efficiency and reduced human interaction and costs. This book is an attempt to publish innovative ideas, emerging trends, implementation experience, and use-cases pertaining to the merger of AI and IoT. The primary market of this book is centered around students, researchers, academicians, industrialists, entrepreneurs, and professionals working in electrical/computer engineering, IT, telecom/electronic engineering, and related fields. The secondary market of this book is related to individuals working in the fields such as finance, management, mathematics, physics, environment, mechatronics, and the automation industry.

Author : Kavitha, T.,Senbagavalli, G.,Koundal, Deepika,Guo, Yanhui,Jain, Deepak
Publisher : IGI Global
Page : 371 pages
File Size : 43,6 Mb
Release : 2022-12-19
Category : Computers
ISBN : 9781668462775

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Convergence of Deep Learning and Internet of Things: Computing and Technology by Kavitha, T.,Senbagavalli, G.,Koundal, Deepika,Guo, Yanhui,Jain, Deepak Pdf

Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Author : Rashmi Agrawal,Marcin Paprzycki,Neha Gupta
Publisher : CRC Press
Page : 237 pages
File Size : 41,7 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

Author : Shaweta Narula, Vivek Narula
Publisher : Leilani Katie Publication
Page : 236 pages
File Size : 40,5 Mb
Release : 2024-03-11
Category : Computers
ISBN : 9788197147951

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Emerging Trends in Data Science Machine Learning, IoT and Artificial Intelligence by Shaweta Narula, Vivek Narula Pdf

Shaweta Narula, Assistant Professor, Department of Electronics and Communication, Nutan College of Engineering and Research, Talegaon Dabhade, Pune Maharashtra,India. Vivek Narula, Quality Manager, Multinational Company, Automotive Industry, Pune, Maharashtra, India.

Author : Shalli Rani,Vyasa Sai,R. Maheswar
Publisher : Springer Nature
Page : 288 pages
File Size : 50,7 Mb
Release : 2022-05-30
Category : Technology & Engineering
ISBN : 9783030841829

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IoT and WSN based Smart Cities: A Machine Learning Perspective by Shalli Rani,Vyasa Sai,R. Maheswar Pdf

This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. The authors cover important areas and issues around implementation roadblocks, ideas, and opportunities in smart city development. The authors also include new algorithms, architectures and platforms that can accelerate the growth of smart city concepts and applications. Moreover, this book provides details on specific applications and case studies related to smart city infrastructures, big data management, and prediction techniques using machine learning.

Author : Bharat Bhushan,Arun Kumar Sangaiah,Tu N. Nguyen
Publisher : Springer Nature
Page : 396 pages
File Size : 53,7 Mb
Release : 2023-06-08
Category : Computers
ISBN : 9783031319525

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AI Models for Blockchain-Based Intelligent Networks in IoT Systems by Bharat Bhushan,Arun Kumar Sangaiah,Tu N. Nguyen Pdf

The goal of this book is to explore various security paradigms such as Machine Learning, Big data, Cyber Physical Systems, and Blockchain to address both intelligence and reconfigurability in various IoT devices. The book further aims to address and analyze the state of the art of blockchain-based intelligent networks in IoT systems and related technologies including healthcare sector. AI can ease, optimize, and automate the blockchain-based decision-making process for better governance and higher performance in IoT systems. Considering the incredible progress made by AI models, a blockchain system powered by intelligent AI algorithms can detect the existence of any kind of attack and automatically invoke the required defense mechanisms. In case of unavoidable damage, AI models can help to isolate the compromised component from the blockchain platform and safeguard the overall system from crashing. Furthermore, AI models can also contribute toward the robustness and scalability of blockchain-based intelligent IoT networks. The book is designed to be the first-choice reference at university libraries, academic institutions, research and development centers, information technology centers, and any institutions interested in integration of AI and IoT. The intended audience of this book include UG/PG students, Ph.D. scholars of this fields, industry technologists, young entrepreneurs, professionals, network designers, data scientists, technology specialists, practitioners, and people who are interested in exploring the role of AI and blockchain technology in IoT systems.