Industry 4 0 Convergence With Ai Iot Big Data And Cloud Computing Fundamentals Challenges And Applications
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Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications
Author: Parikshit N. Mahalle, Gitanjali R. Shinde, Prachi M. Joshi
language: en
Publisher: Bentham Science Publishers
Release Date: 2023-12-25
This volume showcases upcoming trends and applications that are set to redefine our technological landscape. Chapters comprise referenced reviews focused on the recent research that introduces new methods and techniques for using AI in Industry 4.0, and the integration of Internet of Things (IoT) to drive new industrial processes. The contributors have discussed challenges in industry 4.0 along with the applications and the way it is shaping different industries. Key themes: AI in Communication Media: Uncover the latest research, with insights into the challenges and adoption of AI in remote processes. New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing. IoT and AI for Smart Systems: Understand IoT with a special focus on enhancing smart systems, in different industries, including agriculture and transaction processing Explorable AI: Gain a quick understanding of Explainable AI (XAI) and its role in improving the predictability and transparency of IoT applications. Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, big data, and cloud computing.
Advances in Mathematics for Industry 4.0
Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision making, including mathematical and optimization techniques for dealing with large amount of data in short periods.