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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: 50487966
Price: 754 CZK
Availability: InStock
Author: Byte Weaver
ISBN: 9798241712158

Byte Weaver

Jazyk

Angličtina

Kniha Brožovaná

Libristo kód: 50487966

Nakladatelství Independently published, prosinec 2025

What if your AI model has to run on a device with less RAM than a single smartphone photo? Edge AI o... Celý popis

Libristo kód: 50487966

75 b

754 Kč

Skladem u dodavatele Odesíláme za 14-21 dnů

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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.