Embedded artificial intelligence : devices, embedded systems, and industrial applications / editors, Ovidiu Vermesan, SINTEF, Norway, Mario Diaz Nava, STMicroelectronics, France, Björn Debaillie, imec, Belgium.

Format:

Book

Contributor:

Vermesan, Ovidiu, editor.

Nava, Mario Diaz, editor.

Debaillie, Björn, editor.

Series:

River Publishers series in communications and networking.

River Publishers Series in Communications and Networking

Language:

English

Subjects (All):

Embedded computer systems.

Artificial intelligence.

Artificial intelligence--Industrial applications.

Edge computing.

Physical Description:

1 online resource (143 pages)

Place of Publication:

Gistrup, Denmark : River Publishers, [2023]

Summary:

"Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge.Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources.Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations.This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO.The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries."--Provided by publisher.

Contents:

1: Power Optimized Wafermap Classification for Semiconductor Process Monitoring / Ana Pinzari,Thomas Baumela,Liliana Andrade,Marcello Coppola,and Frédéric Pétrot

2: Low-power Analog In-memory Computing Neuromorphic Circuits / Roland Müller, Bijoy Kundu, Elmar Herzer, Claudia Schuhmann, and Loreto Mateu

3: Tools and Methodologies for Edge-AI Mixed-Signal Inference Accelerators / Loreto Mateu, Johannes Leugering, Roland Müller, Yogesh Patil, Maen Mallah, Marco Breiling, and Ferdinand Pscheidl

4: Low-Power Vertically Stacked One Time Programmable Multi-bit IGZO-Based BEOL Compatible Ferroelectric TFT Memory Devices with Lifelong Retention for Monolithic 3D-Inference Engine Applications / Sourav De, Sunanda Thunder, David Lehninger, Michael P.M. Jank, Maximilian Lederer, Yannick Raffel, Konrad Seidel, and Thomas Kämpfe

5: Generating Trust in Hardware through Physical Inspection / Bernhard Lippmann, Matthias Ludwig, and Horst Gieser

6: Meeting the Latency and Energy Constraints on Timing-critical Edge-AI Systems / Ivan Miro-Panades, Inna Kucher, Vincent Lorrain, and Alexandre Valentian

7: Sub-mW Neuromorphic SNN Audio Processing Applications with Rockpool and Xylo / Hannah Bos and Dylan Muir

8: An Embedding Workflow for Tiny Neural Networks on Arm Cortex-M0(+) Cores / Jianyu Zhao, Cecilia Carbonelli, and Wolfgang Furtner

9: Edge AI Platforms for Predictive Maintenance in Industrial Applications / Ovidiu Vermesan and Marcello Coppola

10: Food Ingredients Recognition Through Multi-label Learning / Rameez Ismail and Zhaorui Yuan.

Notes:

Includes bibliographical references and index.

Description based on online resource (viewed 20 October 2023), publisher-supplied metadata and other sources.

ISBN:

1-5231-5637-6

1-00-339444-2

1-000-88191-1

1-000-88203-9

1-003-39444-2

87-7022-820-5

9781003394440

OCLC:

1396874682