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DESCRIPTIONThis book teaches theory and coding examples to help readers design AI-powered cloud robotics applications. AI and robotics engineers will learn to build scalable systems, apply various methods for monitoring and prediction, and optimize systems to reduce costs and increase performance using the architectural techniques described.This book offers a detailed look into cloud robotics, starting with cloud computing basics and moving into its applications in robotics. It highlights the role of AI, ML, and computer vision in advancing robotic capabilities. This book also covers cloud robotics infrastructure, focusing on communication protocols and the ROS2 framework. Further, you will learn about building cloud-enabled robots and using AWS for AI and robotics. It addresses data privacy and security, concluding with real-world applications across various industries and insights into the future of cloud robotics.This book equips you with the foundational knowledge and practical skills to leverage the power of cloud computing to enhance the capabilities of robotic systems. You will gain the ability to design, develop, deploy, and manage cloud-enabled robots, pushing the boundaries of automation and innovation across various industries.WHAT YOU WILL LEARN¿ Understand cloud computing concepts, including service models, deployment models, and security.¿ Explore cloud robotics history, benefits, and AI integration in robotic systems.¿ Learn AI algorithms, ML, and deep learning for robotics applications.¿ Gain skills in computer vision, object detection, and enhancing robot perception using AI.¿ Master Robot Operating System 2 (ROS2) architecture and build cloud-enabled robots with hands-on experience.WHO THIS BOOK IS FORThe primary audience of this book is robotics engineers, AI engineers, and software developers with a basic understanding of robotics and cloud computing or no prior experience of the subject. This book contains practical code samples in Python and assumes that the reader has a fundamental understanding of Python programming.
Leverage Phoenix as an ANSI SQL engine built on top of the highly distributed and scalable NoSQL framework HBase. Learn the basics and best practices that are being adopted in Phoenix to enable a high write and read throughput in a big data space. This book includes real-world cases such as Internet of Things devices that send continuous streams to Phoenix, and the book explains how key features such as joins, indexes, transactions, and functions help you understand the simple, flexible, and powerful API that Phoenix provides. Examples are provided using real-time data and data-driven businesses that show you how to collect, analyze, and act in seconds. Pro Apache Phoenix covers the nuances of setting up a distributed HBase cluster with Phoenix libraries, running performance benchmarks, configuring parameters for production scenarios, and viewing the results. The book also shows how Phoenix plays well with other key frameworks in the Hadoop ecosystem such as Apache Spark, Pig, Flume, and Sqoop.You will learn how to:Handle a petabyte data store by applying familiar SQL techniquesStore, analyze, and manipulate data in a NoSQL Hadoop echo system with HBaseApply best practices while working with a scalable data store on Hadoop and HBaseIntegrate popular frameworks (Apache Spark, Pig, Flume) to simplify big data analysisDemonstrate real-time use cases and big data modeling techniquesWho This Book Is ForData engineers, Big Data administrators, and architects.
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