Shulph Ink
Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices
Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices
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- More about Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices
The book explores the concepts and challenges in developing novel approaches using IoT, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors. It highlights case studies and solutions, covers applications in smart agriculture, healthcare, and manufacturing, and provides the latest methodologies in machine intelligence systems.
Format: Hardback
Length: 348 pages
Publication date: 21 December 2022
Publisher: Taylor & Francis Ltd
The book delves into the realm of innovative approaches utilizing the Internet of Things, intelligent systems, machine intelligence systems, and data analytics across diverse industrial sectors, including manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market, and healthcare. Furthermore, it explores the latest advancements in these sectors through the application of machine intelligence learning and intelligent systems techniques, particularly in the realm of robotics.
Key Features:
• Presents case studies and solutions to industrial challenges employing machine learning and intelligent systems.
• Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing.
• Offers the latest methodologies using machine intelligence systems in the early forecasting of weather.
• Examines the research challenges and identifies gaps in data collection and data analysis, particularly in imagery, signal, and speech.
• Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing.
• Discusses a comprehensive and exhaustive analysis of intelligent software effort estimation models.
This book will serve as an invaluable reference text for graduate students, post-graduate students, IT professionals, and academic researchers in the domains of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Weight: 830g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032261447
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