Edge Ai Merging Iot And Machine Learning For Real Time Analytics

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Edge Ai Merging Iot And Machine Learning For Real Time Analytics

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Author : Dr. D. Srinivasa Rao
language : en
Publisher: Xoffencer International Book Publication house
Release Date : 2024-10-10

Edge Ai Merging Iot And Machine Learning For Real Time Analytics written by Dr. D. Srinivasa Rao and has been published by Xoffencer International Book Publication house this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-10 with Computers categories.

In order to provide real-time analytics directly at the edge of the network, edge artificial intelligence (AI) is a disruptive technique that combines the capabilities of Internet of Things (IoT) devices with the power of machine learning (ML). As a result of this paradigm shift away from conventional cloud-centric approaches, latency is reduced, privacy is improved, and operational efficiency is increased. Information is processed locally on devices. The Internet of Things (IoT) is experiencing exponential expansion, which presents a problem for centralized cloud processing due to the sheer amount of data created by sensors, cameras, and linked equipment of all kinds. By putting artificial intelligence closer to the source of the data, Edge AI makes it possible to make decisions more quickly and reduces the need for continual data transmission to the cloud, which in turn reduces the expenses associated with bandwidth and cloud storage. Innovation is fostered across a variety of sectors, including healthcare, smart cities, autonomous cars, and industrial automation, via the integration of the Internet of Things (IoT) and machine learning at the edge. Real-time analytics makes it possible to identify trends and irregularities, which in turn leads to improvements in accessibility and efficiency in areas such as tailored services, increased security, and predictive maintenance. Utilizing on-device machine learning models enables quick insights, which is essential in applications that are time-sensitive. This is also true as Internet of Things devices grow more sophisticated. Furthermore, the infrastructure for edge computing is capable of supporting dispersed systems, which not only ensures increased system resilience but also reduces the likelihood of downtime. Nevertheless, putting Edge AI into practice is not without its difficulties. The management of the computational needs of machine learning models on devices with limited resources, the maintenance of scalability, and the guarantee of security across dispersed nodes are all key concerns that need to be addressed. The development of lightweight machine learning models, hardware that has been optimized, and security mechanisms that have been improved are all essential components in promoting the widespread use of this technology. Furthermore, the continuing developments in 5G networks and edge computing frameworks promise to push the frontiers of edge artificial intelligence, which will offer up new opportunities for real-time, decentralized intelligence. In conclusion, Edge AI is able to bridge the gap between the increasing needs of Internet of Things ecosystems and the requirement for real-time insights that can be put into action. With the ability to facilitate decision-making processes that are quicker, more intelligent, and more secure, it has the potential to completely transform whole sectors. Artificial intelligence at the edge of the network will play a crucial part in determining the future of intelligent systems as technology continues to advance

Merging Artificial Intelligence With The Internet Of Things

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Author : Tariq, Muhammad Usman
language : en
Publisher: IGI Global
Release Date : 2025-05-08

Merging Artificial Intelligence With The Internet Of Things written by Tariq, Muhammad Usman and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-08 with Computers categories.

Artificial intelligence (AI) and the Internet of Things (IoT) converge to create smart, interconnected systems. This intelligent connectivity enhances the efficiency and innovation of the systems with greater automation, improved decision-making capabilities, and faster reaction times. By amplifying each other, they can transform engineering, security, and management in numerous settings. As a result, their blending is shaping the future of technology in smart cities, healthcare, agriculture, and other sectors. Merging Artificial Intelligence With the Internet of Things stimulates further research into AIoT applications and provides a robust framework for teaching the next generation of tech innovators. By presenting a blend of theoretical knowledge and practical case studies, it bridges the gap between academia and industry, encouraging interdisciplinary research and collaboration. Covering topics such as bio-inspired algorithms, clinical care, and food security, this book is an excellent resource for technology professionals, technology developers, industry leaders, policymakers, professionals, researchers, scholars, academicians, and more.

The Intersection Of 6g Ai Machine Learning And Embedded Systems

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Author : Shruti Sharma
language : en
Publisher: CRC Press
Release Date : 2025-03-24

The Intersection Of 6g Ai Machine Learning And Embedded Systems written by Shruti 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 2025-03-24 with Technology & Engineering categories.

This comprehensive guide to the emerging areas and synergistic relationships among the domains of 6G, machine learning, and embedded systems offers readers a detailed analysis of their converging paths and contributions to the development of intelligent wireless systems. Readers will gain a solid understanding of the principles and technologies behind 6G, machine learning, and embedded systems. They will learn how these three areas intertwine and why this intersection is pivotal for the next generation of wireless technologies. The contributors to this volume present a thorough and detailed analysis of this technology, highlighting its promising features, underlying technologies, and potential applications. The book first explores various applications of machine learning algorithms in areas such as network optimization, resource allocation, interference management, and intelligent data processing and analysis. Design considerations and challenges are presented, and case studies of innovative applications, such as smart cities, autonomous vehicles, healthcare, and industrial automation, are examined. The book concludes with a discussion of future trends and opportunities in this rapidly evolving field. Readers will benefit from the theoretical foundations and practical insights presented within and will be prepared to address future challenges and opportunities in these three fields. This book is a valuable resource for academic researchers and industry professionals working in the fields of wireless communication, machine learning, embedded systems, and artificial intelligence.

Building Scalable Edge Ai Solutions For The Internet Of Things

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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :

Building Scalable Edge Ai Solutions For The Internet Of Things written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

Building Scalable Edge AI Solutions for the Internet of Things" explores the convergence of IoT, edge computing, and AI, providing a practical guide to developing and deploying intelligent edge solutions. The book begins by establishing foundational concepts, explaining the limitations of cloud-centric IoT architectures and introducing the benefits of edge computing and Edge AI, such as reduced latency, bandwidth efficiency, and enhanced privacy. It then delves into the building blocks of Edge AI solutions, covering data acquisition and preprocessing techniques optimized for resource-constrained devices, model selection and compression strategies, and an overview of relevant frameworks and hardware platforms like MCUs, MPUs, GPUs, and FPGAs. The book further provides a practical development approach, detailing the steps from problem definition and data preparation to model training, evaluation, and deployment on edge devices. It emphasizes the importance of robust deployment strategies, including OTA updates, device management tools, and crucial security considerations. Finally, the book examines advanced topics like real-time Edge AI applications in industrial automation, robotics, and autonomous systems, along with scalability and orchestration strategies for large deployments. It concludes by exploring future trends, including emerging hardware and software, the role of 5G, and the ethical implications of Edge AI, advocating for responsible AI development.

Applied Edge Ai

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Author : Pethuru Raj
language : en
Publisher: CRC Press
Release Date : 2022-04-05

Applied Edge Ai written by Pethuru Raj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-05 with Computers categories.

The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI, edge computing, and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication

Transforming Cloud Service Models The Impact Of Edge Computing On Real Time Data Processing And Decision Making

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Author : Rama Chandra Rao Nampalli
language : en
Publisher: SADGURU PUBLICATIONS
Release Date :

Transforming Cloud Service Models The Impact Of Edge Computing On Real Time Data Processing And Decision Making written by Rama Chandra Rao Nampalli and has been published by SADGURU PUBLICATIONS this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

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Essential Guide To Llmops

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Author : RYAN. DOAN
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-31

Essential Guide To Llmops written by RYAN. DOAN and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Computers categories.

Unlock the secrets to mastering LLMOps with innovative approaches to streamline AI workflows, improve model efficiency, and ensure robust scalability, revolutionizing your language model operations from start to finish Key Features Gain a comprehensive understanding of LLMOps, from data handling to model governance Leverage tools for efficient LLM lifecycle management, from development to maintenance Discover real-world examples of industry cutting-edge trends in generative AI operation Purchase of the print or Kindle book includes a free PDF eBook Book Description The rapid advancements in large language models (LLMs) bring significant challenges in deployment, maintenance, and scalability. This Essential Guide to LLMOps provides practical solutions and strategies to overcome these challenges, ensuring seamless integration and the optimization of LLMs in real-world applications. This book takes you through the historical background, core concepts, and essential tools for data analysis, model development, deployment, maintenance, and governance. You’ll learn how to streamline workflows, enhance efficiency in LLMOps processes, employ LLMOps tools for precise model fine-tuning, and address the critical aspects of model review and governance. You’ll also get to grips with the practices and performance considerations that are necessary for the responsible development and deployment of LLMs. The book equips you with insights into model inference, scalability, and continuous improvement, and shows you how to implement these in real-world applications. By the end of this book, you’ll have learned the nuances of LLMOps, including effective deployment strategies, scalability solutions, and continuous improvement techniques, equipping you to stay ahead in the dynamic world of AI. What you will learn Understand the evolution and impact of LLMs in AI Differentiate between LLMOps and traditional MLOps Utilize LLMOps tools for data analysis, preparation, and fine-tuning Master strategies for model development, deployment, and improvement Implement techniques for model inference, serving, and scalability Integrate human-in-the-loop strategies for refining LLM outputs Grasp the forefront of emerging technologies and practices in LLMOps Who this book is for This book is for machine learning professionals, data scientists, ML engineers, and AI leaders interested in LLMOps. It is particularly valuable for those developing, deploying, and managing LLMs, as well as academics and students looking to deepen their understanding of the latest AI and machine learning trends. Professionals in tech companies and research institutions, as well as anyone with foundational knowledge of machine learning will find this resource invaluable for advancing their skills in LLMOps.

Challenges And Opportunities For The Convergence Of Iot Big Data And Cloud Computing

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Author : Velayutham, Sathiyamoorthi
language : en
Publisher: IGI Global
Release Date : 2021-01-29

Challenges And Opportunities For The Convergence Of Iot Big Data And Cloud Computing written by Velayutham, Sathiyamoorthi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-29 with Computers categories.

In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues.

Hands On Artificial Intelligence For Iot

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Author : Dr. Amita Kapoor
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-16

Hands On Artificial Intelligence For Iot written by Dr. Amita Kapoor and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-16 with Computers categories.

Master AI and IoT integration, from fundamentals to advanced techniques, and revolutionize your approach to building intelligent, data-driven solutions across industries Key Features Leverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT data Enhance your IoT solutions with advanced AI techniques, including deep learning, optimization, and generative adversarial networks Gain practical insights through industry-specific IoT case studies in manufacturing, smart cities, and automation Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTransform IoT devices into intelligent systems with this comprehensive guide by Amita Kapoor, Chief AI Officer at Tipz AI. Drawing on 25 years of expertise in developing intelligent systems across industries, she demonstrates how to harness the combined power of artificial intelligence and IoT technology. A pioneer in making AI and neuroscience education accessible worldwide, Amita guides you through creating smart, efficient systems that leverage the latest advances in both fields. This new edition is updated with various optimization techniques in IoT used for enhancing efficiency and performance. It introduces you to cloud platforms such as Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) for analyzing data generated using IoT devices. You’ll learn about machine learning algorithms, deep learning techniques, and practical applications in real-world IoT scenarios and advance to creating AI models that work with diverse data types, including time series, images, and audio. You’ll also harness the power of widely used Python libraries, TensorFlow and Keras, to build a variety of smart AI models. By the end of the book, you’ll emerge as a master of AI-driven IoT, armed with invaluable experience in optimizing IoT devices, boosting their performance, and integrating AI algorithms to make intelligent decisions.What you will learn Integrate AI and IoT for enhanced device intelligence Understand how to build scalable and efficient IoT systems Master both supervised and unsupervised machine learning techniques for processing IoT data Explore the full potential of deep learning in IoT applications Discover AI-driven strategies to optimize IoT system efficiency Implement real-world IoT projects that leverage AI capabilities Improve device performance and decision-making using AI algorithms Who this book is for This book is for IoT developers, engineers, and tech enthusiasts, particularly those with a background in Python, looking to integrate artificial intelligence and machine learning into IoT systems. Python developers eager to apply their knowledge in new, innovative ways will find it useful. It’s also an invaluable guide for anyone with a foundational understanding of IoT concepts ready to take their skills to the next level and shape the future of intelligent devices.

Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing

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Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2024-10-23

Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-23 with Computers categories.

Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.