Build scalable, secure, and intelligent systems by utilizing IoT architectures, AWS, Azure, AI, and real-world solutions to become a skilled IIoT architect Key Features: - Leverage IoT, AI/ML, and cloud technologies to unlock industrial potential and drive business innovation - Work with labs on real-world edge computing scenarios, integrating AWS, Azure, and open source tools - Use diagnostic and predictive analytics to develop digital twins, improve industrial processes, and manage assets - Purchase of the print or Kindle book includes a free PDF eBook Book Description: In today's automation-driven era, precision is crucial, and the Industrial Internet of Things (IIoT) has made a remarkable impact. This updated second edition explores the technologies fueling the IIoT revolution and shares essential knowledge to enable you to establish remote-access networks. Written by IIoT and AI experts, as well as renowned authors, this book helps you enhance your skills in emerging technologies by introducing new techniques from Azure and AWS and keeping you up to date with the latest advancements. You'll find out how Artificial Intelligence of Things (AIoT) and MLOps apply to IIoT and learn how to handle complex projects confidently. The book covers identifying and connecting industrial data sources from various sensors, advancing from foundational concepts to professional skills. You'll discover how to connect these sensors to cloud networks such as AWS IoT, Azure IoT, and open source IoT platforms, and extract data from the cloud to your devices. Through hands-on experience with tools such as Node-RED, OPC UA, MQTT, NoSQL, defense in depth, and Python, you'll develop streaming and batch-based AI algorithms. By the end of this book, you'll have achieved a professional level of expertise in the cloud, IoT, and AI, and be able to build more robust, efficient, and reliable IoT infrastructure for your industry. What You Will Learn: - Get a solid understanding of industrial processes, devices, and protocols - Harness IoT technology to effectively manage industrial use cases - Design and implement an IIoT network flow to continuously monitor the performance of your critical assets - Get to grips with popular cloud-based platforms such as AWS and Azure - Explore Edge devices and learn about Edge and fog computing to gather field data - Apply diagnostic analytics to real-world data to answer critical workforce questions - Develop AIoT technology for predictive maintenance