Edge AI on Embedded Devices Running Machine Learning on Microcontrollers and Low-Power Hardware

Name: Edge AI on Embedded Devices Running Machine Learning on Microcontrollers and Low-Power Hardware
Brand: Independently Published
SKU: 9798241712158
Price: 2980.0 INR
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ISBN13: 9798241712158
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: December 29, 2025
Pages: 472
Original Price: GBP 25.92
Language: English
Edition: N/A
Item Weight: 744 grams
BISAC Subject(s): Embedded Computer Systems

About The Book

What if your AI model has to run on a device with less RAM than a single smartphone photo? Edge AI on Embedded Devices answers that question with engineering discipline, not theory.
Why this matters now: Billions of microcontrollers power our world-pacemakers, industrial sensors, smart infrastructure. Cloud AI can't reach them. This book shows how to build machine learning systems that thrive under constraints where standard ML practices break down.
What makes this different:

Concrete trade-offs between accuracy, latency, memory, and power consumption on real hardware
Model optimization techniques that preserve performance when kilobytes matter
Deployment pipelines designed for resource-limited targets, not GPU clusters
Security and maintenance strategies for devices in the field for decades
Hardware selection frameworks that match model complexity to silicon capabilities

Systems-level thinking: Connects model architecture to power management, real-time OS behavior, and long-term reliability. No abstraction comes without cost analysis.
For practitioners: Written for engineers building production systems, not running benchmarks. Embedded developers learn ML constraints. ML engineers learn embedded realities. Both learn to design AI that survives deployment.
Build AI that runs where cloud computing ends. Start designing systems engineered for silicon, not slides.

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