1st Edition

Applied Edge AI Concepts, Platforms, and Industry Use Cases

Edited By Pethuru Raj, G. Nagarajan, R.I. Minu Copyright 2022
    328 Pages 117 B/W Illustrations
    by Auerbach Publications

    328 Pages 117 B/W Illustrations
    by Auerbach Publications

    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.


    • 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

    1. Edge Computing: Opportunities and Challenges
    Ashwini S, R. I. Minu, and G Nagarajan

    2. Demystifying the Edge AI Paradigm
    P Beaulah Soundarabai, Peter Augustine, and Smitha Vinod

    3. Big Data Driven Edge-Cloud Collaboration for Cloud Manufacturing with SDN Technologies
    M. Vijayalakshmi and R. I. Minu

    4. Artificial Intelligence in 5G and Beyond Networks
    Dimitris Tsolkas, Harilaos Koumaras, Anastasios-Stavros Charismiadis, and Andreas Foteas

    5. An Application Oriented Study of Security Threats and Countermeasures in Edge Computing-Assisted Internet of Things
    G Nagarajan, Serin V. Simpson, and T. Sasikala

    6. Edge AI for Industrial IoT Applications
    Sivabalan S and R. I. Minu

    7. Edge AI: From the Perspective of Predictive Maintenance
    S. Sharanya, Revathi Venkataraman, and G. Murali

    8. Unlocking the Potential of AI-Powered Block Chain Technology in Environment Sustainability and Social Good
    R. Sivarethinamohan, Parthiban Jovin, and S. Sujatha

    9. UAV-Based Smart Wing Inspection System
    S. Karthikeyan, Ahmed Dulvi, R. Raghavi, and S. Sai Suresh

    10. Edge AI-Based Ariel Monitoring
    S. Karthikeyan, A. Sharun, G. Bharath Ajay, and N. Raakin Ahamed

    11. Object Detection in Edge Environment: A Comparative Study of Algorithms and Use-Cases
    Aishwarya D, Sony Priya S, and R. I. Minu

    12. Ambient Intelligence: An Emerging Innovation of Sensing and Service Systems
    V. J. K. Kishor Sonti and G. Sundari


    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.