Deep Learning For Internet Of Things Infrastructure

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Deep Learning for Internet of Things Infrastructure

Author : Uttam Ghosh
Publisher : CRC Press
ISBN 13 : 1000431959
Total Pages : 240 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Deep Learning for Internet of Things Infrastructure by : Uttam Ghosh

Download or read book Deep Learning for Internet of Things Infrastructure written by Uttam Ghosh and published by CRC Press. This book was released on 2021-09-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning for Internet of Things Infrastructure

Author : Uttam Ghosh
Publisher : CRC Press
ISBN 13 : 1000431894
Total Pages : 267 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Deep Learning for Internet of Things Infrastructure by : Uttam Ghosh

Download or read book Deep Learning for Internet of Things Infrastructure written by Uttam Ghosh and published by CRC Press. This book was released on 2021-09-30 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Analytics for Internet of Things Infrastructure

Author : Rohit Sharma
Publisher : Springer Nature
ISBN 13 : 3031338081
Total Pages : 330 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Data Analytics for Internet of Things Infrastructure by : Rohit Sharma

Download or read book Data Analytics for Internet of Things Infrastructure written by Rohit Sharma and published by Springer Nature. This book was released on 2023-09-19 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning in Internet of Things for Next Generation Healthcare

Author : Lavanya Sharma
Publisher : CRC Press
ISBN 13 : 1040030823
Total Pages : 311 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Deep Learning in Internet of Things for Next Generation Healthcare by : Lavanya Sharma

Download or read book Deep Learning in Internet of Things for Next Generation Healthcare written by Lavanya Sharma and published by CRC Press. This book was released on 2024-06-18 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning Techniques for IoT Security and Privacy

Author : Mohamed Abdel-Basset
Publisher : Springer Nature
ISBN 13 : 3030890252
Total Pages : 273 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Deep Learning Techniques for IoT Security and Privacy by : Mohamed Abdel-Basset

Download or read book Deep Learning Techniques for IoT Security and Privacy written by Mohamed Abdel-Basset and published by Springer Nature. This book was released on 2021-12-05 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

Author : Raut, Roshani
Publisher : IGI Global
ISBN 13 : 1799875172
Total Pages : 304 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by : Raut, Roshani

Download or read book Examining the Impact of Deep Learning and IoT on Multi-Industry Applications written by Raut, Roshani and published by IGI Global. This book was released on 2021-01-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Learning Techniques for the Internet of Things

Author : Praveen Kumar Donta
Publisher : Springer
ISBN 13 : 9783031505133
Total Pages : 0 pages
Book Rating : 4.5/5 (51 download)

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Book Synopsis Learning Techniques for the Internet of Things by : Praveen Kumar Donta

Download or read book Learning Techniques for the Internet of Things written by Praveen Kumar Donta and published by Springer. This book was released on 2024-03-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is structured into thirteen chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in various real-time applications such as healthcare, manufacturing, agriculture, and transportation. Chapter 2 motivates mathematical modeling for federated learning systems with respect to IoT and its applications. Further Chapter 3 extends the discussion of federated learning for IoT, which has emerged as a privacy-preserving distributed machine learning approach. Chapter 4 provides various machine learning techniques in Industrial IoT to deliver rapid and accurate data analysis, essential for enhancing production quality, sustainability, and safety. Chapter discusses the potential role of data-driven technologies, such as Artificial Intelligence, Machine Learning, and Deep Learning, focuses on their integration with IoT communication technologies. Chapter 6 presents the requirements and challenges to realize IoT deployments in smart cities, including sensing infrastructure, Artificial Intelligence, computing platforms, and enabling communications technologies such as 5G networks. To highlight these challenges in practice, the chapter also presents a real-world case study of a city-scale deployment of IoT air quality monitoring within Helsinki city. Chapter 7 uses digital twins within smart cities to enhance economic progress and facilitate prompt decision-making regarding situational awareness. Chapter 8 provides insights into using Multi-Objective reinforcement learning in future IoT networks, especially for an efficient decision-making system. Chapter 9 offers a comprehensive review of intelligent inference approaches, with a specific emphasis on reducing inference time and minimizing transmitted bandwidth between IoT devices and the cloud. Chapter 10 summarizes the applications of deep learning models in various IoT fields. This chapter also presents an in-depth study of these techniques to examine new horizons of applications of deep learning models in different areas of IoT. Chapter 11 explores the integration of Quantum Key Distribution (QKD) into IoT systems. It delves into the potential benefits, challenges, and practical considerations of incorporating QKD into IoT networks. In chapter 12, a comprehensive overview regarding the current state of quantum IoT in the context of smart healthcare is presented, along with its applications, benefits, challenges, and prospects for the future. Chapter 13 proposes a blockchain-based architecture for securing and managing IoT data in intelligent transport systems, offering advantages like immutability, decentralization, and enhanced security.

Advances in Deep Learning Applications for Smart Cities

Author : Kumar, Rajeev
Publisher : IGI Global
ISBN 13 : 1799897125
Total Pages : 335 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Advances in Deep Learning Applications for Smart Cities by : Kumar, Rajeev

Download or read book Advances in Deep Learning Applications for Smart Cities written by Kumar, Rajeev and published by IGI Global. This book was released on 2022-05-13 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence-based Internet of Things Systems

Author : Souvik Pal
Publisher : Springer Nature
ISBN 13 : 3030870596
Total Pages : 509 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Artificial Intelligence-based Internet of Things Systems by : Souvik Pal

Download or read book Artificial Intelligence-based Internet of Things Systems written by Souvik Pal and published by Springer Nature. This book was released on 2022-01-11 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Internet of Things

Author : John Davies
Publisher : John Wiley & Sons
ISBN 13 : 1119545269
Total Pages : 244 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis The Internet of Things by : John Davies

Download or read book The Internet of Things written by John Davies and published by John Wiley & Sons. This book was released on 2020-06-08 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems

Author : Pardeep Kumar
Publisher : Springer Nature
ISBN 13 : 3030766535
Total Pages : 462 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems by : Pardeep Kumar

Download or read book A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems written by Pardeep Kumar and published by Springer Nature. This book was released on 2021-08-23 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Convergence of Deep Learning and Internet of Things: Computing and Technology

Author : Kavitha, T.
Publisher : IGI Global
ISBN 13 : 166846277X
Total Pages : 371 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Convergence of Deep Learning and Internet of Things: Computing and Technology by : Kavitha, T.

Download or read book Convergence of Deep Learning and Internet of Things: Computing and Technology written by Kavitha, T. and published by IGI Global. This book was released on 2022-12-19 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Big Data, IoT, and Machine Learning

Author : Rashmi Agrawal
Publisher : CRC Press
ISBN 13 : 1000098281
Total Pages : 319 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Big Data, IoT, and Machine Learning by : Rashmi Agrawal

Download or read book Big Data, IoT, and Machine Learning written by Rashmi Agrawal and published by CRC Press. This book was released on 2020-09-01 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Handbook of Research on Cloud Computing and Big Data Applications in IoT

Author : Gupta, B. B.
Publisher : IGI Global
ISBN 13 : 1522584080
Total Pages : 609 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Cloud Computing and Big Data Applications in IoT by : Gupta, B. B.

Download or read book Handbook of Research on Cloud Computing and Big Data Applications in IoT written by Gupta, B. B. and published by IGI Global. This book was released on 2019-04-12 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, cloud computing, big data, and the internet of things (IoT) are becoming indubitable parts of modern information and communication systems. They cover not only information and communication technology but also all types of systems in society including within the realms of business, finance, industry, manufacturing, and management. Therefore, it is critical to remain up-to-date on the latest advancements and applications, as well as current issues and challenges. The Handbook of Research on Cloud Computing and Big Data Applications in IoT is a pivotal reference source that provides relevant theoretical frameworks and the latest empirical research findings on principles, challenges, and applications of cloud computing, big data, and IoT. While highlighting topics such as fog computing, language interaction, and scheduling algorithms, this publication is ideally designed for software developers, computer engineers, scientists, professionals, academicians, researchers, and students.

Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty
Publisher : John Wiley & Sons
ISBN 13 : 1119785804
Total Pages : 530 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning Approach for Cloud Data Analytics in IoT by : Sachi Nandan Mohanty

Download or read book Machine Learning Approach for Cloud Data Analytics in IoT written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-07-27 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Emerging Trends in Data Science Machine Learning, IoT and Artificial Intelligence

Author : Shaweta Narula
Publisher : Leilani Katie Publication
ISBN 13 : 8197147957
Total Pages : 236 pages
Book Rating : 4.1/5 (971 download)

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Book Synopsis Emerging Trends in Data Science Machine Learning, IoT and Artificial Intelligence by : Shaweta Narula

Download or read book Emerging Trends in Data Science Machine Learning, IoT and Artificial Intelligence written by Shaweta Narula and published by Leilani Katie Publication. This book was released on 2024-03-11 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Cognitive Internet of Things

Author : Pethuru Raj
Publisher : CRC Press
ISBN 13 : 1000547256
Total Pages : 326 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Cognitive Internet of Things by : Pethuru Raj

Download or read book Cognitive Internet of Things written by Pethuru Raj and published by CRC Press. This book was released on 2022-03-29 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet of Things (IoT) concept is defined as a flexible and futuristic network where all the different types of devices and smart objects can become seamlessly connected to each other and can actively participate in all types of processes which are happening around us. The grand objective of making physical, mechanical, electrical, and electronic devices to use the deeper and extreme connectivity and service-enablement techniques is to make them intelligent in their deeds, decisions, and deals. Cognitive IoT is the application of cognitive computing technologies to the data which is generated by the connected devices of the IoT ecosystem. Cognition means thinking; however, computers are not yet fully capable of mimicking human like thought. However, the present-day computer systems can perform some functions which are like the capability of human beings to think. Cognitive Internet of Things: Enabling Technologies, Platforms, and Use Cases explains the concepts surrounding Cognitive IoT. It also looks at the use cases and such supporting technologies as artificial intelligence and machine learning that act as key enablers of Cognitive IoT ecosystem. Different Cognitive IoT enabled platforms like IBM Watson and other product specific use cases like Amazon Alexa are covered in depth. Other highlights of the book include: Demystifying the cognitive computing paradigm Delineating the key capabilities of cognitive cloud environments Deep learning algorithms for cognitive IoT solutions Natural language processing (NLP) methods for cognitive IoT systems Designing a secure infrastructure for cognitive IoT platforms and applications