Babu T. Jose (ed.); Dipak Kumar Sahoo (ed.); Eun Chul Shin (ed.); Deepankar Choudhury (ed.); Anil Joseph (ed.); Rahul Pai Springer (2024) Kovakantinen kirja
Babu T. Jose (ed.); Dipak Kumar Sahoo (ed.); Eun Chul Shin (ed.); Deepankar Choudhury (ed.); Anil Joseph (ed.); Rahul Pai Springer (2024) Kovakantinen kirja
Monica L. Chavez Gonzalez; Jose Juan Buenrostro Figueroa; Cristobal Noe Aguilar; Deepak K. Verma Elsevier Science & Technology (2024) Pehmeäkantinen kirja
Gerhard-Wilhelm Weber (ed.); Jose Francisco Martinez Trinidad (ed.); Michael Sheng (ed.); Raghavendra Ramachand (ed.); Kharb Springer (2024) Pehmeäkantinen kirja
Taylor & Francis Ltd Sivumäärä: 402 sivua Asu: Kovakantinen kirja Julkaisuvuosi: 2024, 07.11.2024 (lisätietoa) Kieli: Englanti
The purpose of this book is to discuss the trends and key drivers of Internet of Things (IoT) and artificial intelligence (AI) for automation in Industry 4.0. IoT and AI are transforming the industry thus accelerating efficiency and forging a more reliable automated enterprise. AI-driven IoT systems for Industry 4.0 explore current research to be carried out in the cutting-edge areas of AI for advanced analytics, integration of industrial IoT (IIoT) solutions and Edge components, automation in cyber-physical systems, world leading Industry 4.0 frameworks and adaptive supply chains, etc.
A thorough exploration of Industry 4.0 is provided, focusing on the challenges of digital transformation and automation. It covers digital connectivity, sensors, and the integration of intelligent thinking and data science. Emphasizing the significance of AI, the chapter delves into optimal decision-making in Industry 4.0. It extensively examines automation and hybrid edge computing architecture, highlighting their applications. The narrative then shifts to IIoT and edge AI, exploring their convergence and the use of edge AI for visual insights in smart factories. The book concludes by discussing the role of AI in constructing digital twins, speeding up product development lifecycles, and offering insights for decision-making in smart factories. Throughout, the emphasis remains on the transformative impact of deep learning and AI in automating and accelerating manufacturing processes within the context of Industry 4.0.
This book is intended for undergraduates, postgraduates, academicians, researchers, and industry professionals in industrial and computer engineering.
