Neha Singhal – författare

This book details cutting-edge technologies, versatile tools, adaptive processes, integrated platforms, and best practices of digitized systems. With the faster maturity and stability of digitization and digitalization technologies, all kinds of physical, mechanical, and electrical systems in our everyday environments (homes, hotels, hospitals, manufacturing floors, etc.) have become digitized systems. Such technology has empowered systems to gain the power to join and contribute to fulfilling the goals of modern computing. Such digitized entities assist in producing and deploying hugely complicated yet sophisticated context-aware services and applications. The other principal contribution is capturing environmental data in real time and enabling local data processing to bring forth actionable insights. This facilitates insight-driven decisions and deeds. Precisely speaking, the aspects of real-time knowledge discovery and dissemination enable the creation and delivery of real-time and real-world features and functionalities.All industrial artifacts are being digitized, connected and empowered to be cognitive in their operations, offerings and outputs. By smartly leveraging a dazzling array of digital technologies and tools, the interaction and collaboration with human experts becomes hugely simplified and speeded up considerably. Such cognition-enabled industrial machineries, equipment, appliances, assembly lines, robots, vehicles, drones, and other assets collectively provide an intelligent environment to envisage and realize state-of-the-art industry 4.0 and 5.0 applications. Every industrial process gets optimized and automated to produce next-generation products to ensure customer delight, to explore fresh avenues to enhance revenues and to embark on higher productivity.In addition, there are chapters illustrating industrial use cases, infrastructure optimization, technology assimilation, and AI-powered data analytics towards industry automation.

This book details cutting-edge technologies, versatile tools, adaptive processes, integrated platforms, and best practices of digitized systems. With the faster maturity and stability of digitization and digitalization technologies, all kinds of physical, mechanical, and electrical systems in our everyday environments (homes, hotels, hospitals, manufacturing floors, etc.) have become digitized systems. Such technology has empowered systems to gain the power to join and contribute to fulfilling the goals of modern computing. Such digitized entities assist in producing and deploying hugely complicated yet sophisticated context-aware services and applications. The other principal contribution is capturing environmental data in real time and enabling local data processing to bring forth actionable insights. This facilitates insight-driven decisions and deeds. Precisely speaking, the aspects of real-time knowledge discovery and dissemination enable the creation and delivery of real-time and real-world features and functionalities.All industrial artifacts are being digitized, connected and empowered to be cognitive in their operations, offerings and outputs. By smartly leveraging a dazzling array of digital technologies and tools, the interaction and collaboration with human experts becomes hugely simplified and speeded up considerably. Such cognition-enabled industrial machineries, equipment, appliances, assembly lines, robots, vehicles, drones, and other assets collectively provide an intelligent environment to envisage and realize state-of-the-art industry 4.0 and 5.0 applications. Every industrial process gets optimized and automated to produce next-generation products to ensure customer delight, to explore fresh avenues to enhance revenues and to embark on higher productivity.In addition, there are chapters illustrating industrial use cases, infrastructure optimization, technology assimilation, and AI-powered data analytics towards industry automation.

This book deeply explores the evolving landscape of AI and elucidates the cutting-edge technologies and state-of-the-art infrastructures for engineering and running next-generation intelligent systems. It covers how to produce and sustain predictive, generative, agentic, and physical AI systems. It delves into multi-agent systems, expert systems, autonomous agents, and development toolkits. Ideal for researchers and advanced students, it offers a deep dive into the frameworks and AI model/agent engineering methods driving the future of artificial intelligence.