Embedded AI : Intelligence at the Deep Edge
Language: English
Published by Random House LLC US Okt 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 77.06
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Add to basketItem description from seller
Neuware - A project-driven guide to designing, training, and deploying artificial intelligence directly on embedded hardware, showing how to build intelligent, autonomous systems under real-world constraints.You already know how to build embedded systems. Now it’s time to make them intelligent.Adding AI to an embedded device takes more than training a model. You have to choose the right hardware, collect and prepare data, deploy models to resource-constrained devices, and integrate everything into a system that performs reliably.Drawing on more than 30 years of embedded engineering experience, David Such takes you through the complete engineering process. You’ll work through more than 25 hands-on projects (complete with downloadable source code, schematics, PCB designs, and datasets); no machine learning experience required.You’ll build:- A wake-word detector that responds to your voice- A real-time AI noise suppressor- An AI-powered MIDI synthesizer that composes music- A battery monitor that collects its own training data- A person detector that runs a neural network on a camera board Whether you’re an embedded developer adding AI to your products, a machine learning practitioner moving onto embedded hardware, or a maker ready to move beyond beginner projects, Embedded AI teaches you the engineering decisions behind every design. When the breadboard is flaky, the sensor data is noisy, or the tensor arena is too small, you’ll know how to fix it—and why.Prerequisites Most projects require an Arduino UNO or Raspberry Pi Pico; a few use specialized boards. You’ll also need to download some free software, including Python with TensorFlow, Arduino IDE, and Raspberry Pi Pico SDK.…
Seller Inventory # 9781718504905
- Title
- Embedded AI : Intelligence at the Deep Edge
- Author
- David Such
- Publisher
- Random House LLC US Okt 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 171850490X
- ISBN 13
- 9781718504905
- Item weight
- 368 grams
- Dimensions
- 235x178x29 mm
Embedded AI is a hands-on, hardware-first guide to building intelligent systems that run locally, in real time, on microcontrollers and single-board computers. Rather than focusing on theory or isolated case studies, the book emphasizes practical design decisions and the trade-offs engineers face when deploying AI on constrained devices.
Readers begin with the foundations of embedded systems and machine learning, then learn how to collect, explore, and preprocess sensor data. The book places particular emphasis on exploratory data analysis, feature engineering, and data quality—areas that are critical to embedded machine learning but often overlooked.
Using popular platforms such as Arduino, Raspberry Pi, STM32, and Seeed Studio boards, readers work through concrete projects including battery monitoring, hot-word detection, gesture recognition, noise classification, occupancy detection, and intelligent control systems. Industry-standard tools such as scikit-learn, TensorFlow Lite, and Edge Impulse are introduced only to the extent needed to support real projects.
Advanced chapters address sensor fusion, power management, model compression, security, and privacy, helping readers understand how to build systems that are not just intelligent, but robust and deployable. The book concludes with a biologically inspired approach to embedded intelligence using the open-source Primal Layers framework, culminating in an embedded AI robot project.
"Synopsis" may belong to another edition of this title.
About the Author
He mentors aspiring entrepreneurs at the University of Sydney through the Business Industry Mentoring Program and the Lean Startup course in the Faculty of Business. He also holds a Remote Pilot Licence (RePL) and an Aeronautical Radio Operator Certificate, reflecting his interest in autonomous systems and UAV technologies. Earlier in his career, he held senior leadership roles including Managing Director of Serco Australia, executive directorships across multiple Serco subsidiaries, and senior management positions at ADT and Honeywell. His qualifications include an MBA (Strategy), a B.E. in Electrical Engineering, a B.Sc. in Computer Science, and a B.App.Sc. in Wine Making.
"About the title" may belong to another edition of this title.
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