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Applied Edge AI

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Age Group_Uncategorized
algorithms
AmI
AmI System
artificial intelligence
automatic-update
B01=G. Nagarajan
B01=Pethuru Raj
B01=R.I. Minu
Balanced Approach Model
Big Data Analytics
Blockchain Technology
business
Category1=Non-Fiction
Category=UN
chips
Cloud Computing
COP=United Kingdom
cybersecurity in IoT
Deep Neural Network
Delivery_Delivery within 10-20 working days
Edge Computing
Edge Devices
Edge Nodes
Edge Server
enterprises
environmental monitoring solutions
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Fog Computing
industrial automation
IoT Device
IoT Network
Language_English
MEC
Mobile Cloud Computing
Network Slicing
Object Detection
PA=Available
PdM
Pervasive Computing
predictive analytics
Price_€50 to €100
PS=Active
real-time edge AI deployment
RGB Camera
SDN Controller
Self-driving Car
Smart City Environment
softlaunch
unmanned aerial systems
Vehicular Network
wireless sensor networks

Product details

  • ISBN 9781032217284
  • Weight: 500g
  • Dimensions: 156 x 234mm
  • Publication Date: 07 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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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 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
About

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.