Applied Edge AI: Concepts, Platforms, and Industry Use Cases

Description

The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI.　 With the faster... Read more

The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI.　 With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance　processors, etc.　　The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations.

Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases.

FEATURES

The opportunities and benefits of intelligent edge computing

Edge architecture and infrastructure

AI-enhanced analytics in an edge environment

Encryption for securing information

An Edge AI system programmed with Tiny Machine learning algorithms for decision making

An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge

Ambient intelligence in healthcare services and in development of consumer electronic systems

Smart manufacturing of unmanned aerial vehicles (UAVs)

AI, edge computing, and blockchain in systems for environmental protection

Case studies presenting the potential of leveraging AI in 5G wireless communication

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Editor(s)

Biography

Dr. Pethuru Raj Chelliah is the chief architect in the Site Reliability Engineering (SRE) division of Reliance Jio Infocomm Ltd. (RJIL), Bangalore, India.

Dr. G. Nagarajan is a professor at the Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science and Technology, Chennai, India.

Dr. R. I. Minu is an associate professor at the Department of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India.

Applied Edge AI Concepts, Platforms, and Industry Use Cases

Description

Table of Contents

Editor(s)

Biography

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