Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics.
Features:
• Highlights case studies and solutions to industrial problems using machine learning and intelligent systems.
• Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing.
• Provides the latest methodologies using machine intelligence systems in the early forecasting of weather.
• Examines the research challenges and identifies the gaps in data collection and data analysis, especially 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 systematic and exhaustive analysis of intelligent software effort estimation models.
It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.