Learn Internet Of Things Iot

DOWNLOAD

Download Learn Internet Of Things Iot PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Learn Internet Of Things Iot book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Internet Of Things

DOWNLOAD
Author : Revathi Venkataraman
language : en
Publisher: Springer Nature
Release Date : 2023-03-29

Internet Of Things written by Revathi Venkataraman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-29 with Computers categories.

This book constitutes the refereed and selected papers presented during the Third International Conference on Internet of Things, ICIoT 2022, held in Chennai, India, in April 2022. The 10 papers were thoroughly reviewed and selected from the 100 qualified submissions. They focus on application of IoT in the field of Computer Science and Information Technology as well as on Industrial IoT.

Learning Techniques For The Internet Of Things

DOWNLOAD
Author : Praveen Kumar Donta
language : en
Publisher: Springer Nature
Release Date : 2024-02-19

Learning Techniques For The Internet Of Things written by Praveen Kumar Donta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Computers categories.

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.

Deep Learning In Internet Of Things For Next Generation Healthcare

DOWNLOAD
Author : Lavanya Sharma
language : en
Publisher: CRC Press
Release Date : 2024-06-18

Deep Learning In Internet Of Things For Next Generation Healthcare written by Lavanya Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-18 with Computers categories.

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.

2024 25 O M4 R5 Level Introduction To Internet Of Things Study Material

DOWNLOAD
Author : YCT Expert Team
language : en
Publisher: YOUTH COMPETITION TIMES
Release Date :

2024 25 O M4 R5 Level Introduction To Internet Of Things Study Material written by YCT Expert Team and has been published by YOUTH COMPETITION TIMES this book supported file pdf, txt, epub, kindle and other format this book has been release on with Antiques & Collectibles categories.

2024-25 ‘O’ [M4-R5]Level Introduction to Internet of Things Study Material

The Internet Of Educational Things

DOWNLOAD
Author : Muralidhar Kurni
language : en
Publisher: Springer Nature
Release Date : 2024-09-19

The Internet Of Educational Things written by Muralidhar Kurni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-19 with Computers categories.

The Internet of Educational Things - Enhancing Students’ Engagement and Learning Performance delves into the transformative potential of the Internet of Things (IoT) within education. This comprehensive guide explores how IoT technology can revolutionize traditional teaching methods and learning environments, fostering more interactive, adaptive, and data-driven experiences. The book covers a wide range of topics, including the development of IoT-enabled classrooms, intelligent tutoring systems, and online labs. By leveraging real-time data and advanced analytics, educators can personalize learning paths, enhance student engagement, and optimize resource allocation. Practical applications, real-world examples, and case studies illustrate the benefits and challenges of incorporating IoT in educational settings, making it a valuable resource for students, teachers, researchers, and policymakers. The book provides practical implementation strategies and addresses critical issues such as data privacy, cybersecurity, and ethical considerations. It thoroughly examines the latest technologies, including AI, AR, VR, and digital twins, and their integration with IoT to create futuristic learning environments. The book’s unique contribution lies in its emphasis on securing IoT systems and its recommendations for overcoming infrastructure readiness and staff training obstacles. By presenting a forward-looking perspective on the role of IoT in education, this book aims to equip stakeholders with the knowledge and tools necessary to create innovative, inclusive, and secure learning ecosystems that prepare students for the future.

The Internet Of Things Breakthroughs In Research And Practice

DOWNLOAD
Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2017-02-14

The Internet Of Things Breakthroughs In Research And Practice written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-14 with Computers categories.

The ubiquity of modern technologies has allowed for increased connectivity between people and devices across the globe. This connected infrastructure of networks creates numerous opportunities for applications and uses. The Internet of Things: Breakthroughs in Research and Practice is an authoritative reference source for the latest academic material on the interconnectivity of networks and devices in the digital era and examines best practices for integrating this advanced connectivity across multiple fields. Featuring extensive coverage on innovative perspectives, such as secure computing, regulatory standards, and trust management, this book is ideally designed for engineers, researchers, professionals, graduate students, and practitioners seeking scholarly insights on the Internet of Things.

Internet Of Things And Machine Learning In Agriculture

DOWNLOAD
Author : Jyotir Moy Chatterjee
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-02-08

Internet Of Things And Machine Learning In Agriculture written by Jyotir Moy Chatterjee and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-08 with Computers categories.

Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.

Green Internet Of Things And Machine Learning

DOWNLOAD
Author : Roshani Raut
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-10

Green Internet Of Things And Machine Learning written by Roshani Raut and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-10 with Computers categories.

Health Economics and Financing Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment. The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. Audience The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.

Machine Learning Paradigm For Internet Of Things Applications

DOWNLOAD
Author : Shalli Rani
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-02

Machine Learning Paradigm For Internet Of Things Applications written by Shalli Rani and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-02 with Computers categories.

MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

Deep Learning For Internet Of Things Infrastructure

DOWNLOAD
Author : Uttam Ghosh
language : en
Publisher: CRC Press
Release Date : 2021-09-30

Deep Learning For Internet Of Things Infrastructure written by Uttam Ghosh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-30 with Computers categories.

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.