Recent Advances in Embedded Computing, Intelligence and Applications

ISBN 10: 3036542469 / ISBN 13: 9783036542461

Published by MDPI AG, 2022

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems.

Seller Inventory # 9783036542461

Bibliographic Details

• Title: Recent Advances in Embedded Computing, Intelligence and Applications
• Publisher: MDPI AG
• Publication Date: 2022
• Language: English
• ISBN 10: 3036542469
• ISBN 13: 9783036542461
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 17D millimeters 250 millimeters width by 175 millimeters height by 17 millimeters depth
• Weight: 670 grams

About this title

Synopsis

The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems.