AI – Driven Computational Engineering for Sustainable Development | 15.53 MB
Title: AI-Driven Computational Engineering for Sustainable Development
Author: Subir Gupta, Indrajit Ghosal, Keshav Kaushik & Monika Dandotiya
Category: Nonfiction, Computers, Advanced Computing, Artificial Intelligence
Language: English | 292 Pages | ISBN: 9815324055
Description:
AI-Driven Computational Engineering for Sustainable Development explores the convergence of Artificial Intelligence (AI), Natural Language Processing (NLP), and computational engineering in shaping the transition toward Industry 5.0. The book focuses on human-centric, sustainable, and data-driven approaches that enhance collaboration between humans and machines while improving productivity and environmental outcomes.
It begins by outlining the evolution from Industry 4.0 to Industry 5.0, followed by core concepts in AI, NLP, and computational engineering. The chapters then examine real-world applications in smart manufacturing, intelligent automation, and sustainable industrial systems. The book also addresses key challenges such as data management, ethics, system integration, and the need for resilient technological frameworks, offering insights into future research and innovation directions.
Key Features:
-Covers AI, NLP, and computational engineering applications in Industry 5.0
-Focuses on sustainable, human-centric, and data-driven industrial systems
-Real-world applications and cases in smart manufacturing and intelligent automation
-Discusses emerging research trends and future technological directions
-Insights into challenges such as data governance, ethics, and system integration
AI-Driven Computational Engineering for Sustainable Development explores the convergence of Artificial Intelligence (AI), Natural Language Processing (NLP), and computational engineering in shaping the transition toward Industry 5.0. The book focuses on human-centric, sustainable, and data-driven approaches that enhance collaboration between humans and machines while improving productivity and environmental outcomes.
It begins by outlining the evolution from Industry 4.0 to Industry 5.0, followed by core concepts in AI, NLP, and computational engineering. The chapters then examine real-world applications in smart manufacturing, intelligent automation, and sustainable industrial systems. The book also addresses key challenges such as data management, ethics, system integration, and the need for resilient technological frameworks, offering insights into future research and innovation directions.
Key Features:
-Covers AI, NLP, and computational engineering applications in Industry 5.0
-Focuses on sustainable, human-centric, and data-driven industrial systems
-Real-world applications and cases in smart manufacturing and intelligent automation
-Discusses emerging research trends and future technological directions
-Insights into challenges such as data governance, ethics, and system integration
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