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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Federated and Trustworthy AI for Climate-Resilient Cyber- Physical Systems: Foundations, Applications and Challenges

Federated and Trustworthy AI for Climate-Resilient Cyber- Physical Systems: Foundations, Applications and Challenges

Saini, Hemant Kumar
Ouaissa, Mariya
Sankaramoorthy, Balasubramaniam

Hardcover

Series: Studies in Systems, Decision and Control, Book 684

Technology & EngineeringGeneral Computers

PREORDER - Expected ship date October 28, 2026

ISBN10: 3032288460
ISBN13: 9783032288462
Publisher: Springer
Published: Oct 28 2026
Pages: 449
Language: English

This book provides a timely and much-needed examination of how Federated and Trustworthy Artificial Intelligence (AI) can address the real-time challenges posed by climate change on cyber-physical systems (CPS) and Internet of Things (IoT) infrastructures. With extreme weather events, energy shortages, agricultural disruptions, and urban vulnerabilities on the rise, there is an urgent demand for intelligent, distributed, and resilient solutions that can safeguard critical infrastructures while ensuring sustainability and trust.

The central premise of this book is that traditional centralized AI is no longer sufficient. Centralized models face serious limitations: they consume vast energy resources, expose sensitive environmental and operational data, and often collapse under communication bottlenecks during crises. In contrast, federated learning enables distributed IoT devices and CPS nodes to collaboratively train models without sharing raw data, reducing latency, preserving privacy, and improving system adaptability. Coupled with trustworthy AI principles--explainability, fairness, robustness, and transparency--this approach becomes indispensable for climate-resilient operations.

This book emphasizes real-time, high-impact applications where federated and trustworthy AI are urgently required:

-Smart energy grids that must dynamically balance renewable sources under fluctuating demand and unpredictable climate patterns.

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