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2022 | OriginalPaper | Chapter

Embedded Intelligence for Safety and Security Machine Vision Applications

Authors : Panagiotis Lioupis, Aris Dadoukis, Evangelos Maltezos, Lazaros Karagiannidis, Angelos Amditis, Maite Gonzalez, Jon Martin, David Cantero, Mikel Larrañaga

Published in: Image Analysis and Processing. ICIAP 2022 Workshops

Publisher: Springer International Publishing

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Abstract

Artificial intelligence (AI) has experienced a recent increase in use across a wide variety of domains, such as image processing for security applications. Deep learning, a subset of AI, is particularly useful for those image processing applications. Deep learning methods can achieve state-of-the-art results on computer vision for image classification, object detection, and face recognition applications. This allows to automate video surveillance reducing human intervention.

At the same time, although deep learning is a very intensive task in terms of computing resources, hardware and software improvements have emerged, allowing embedded systems to implement sophisticated machine learning algorithms at the edge. Hardware manufacturers have developed powerful co-processors specifically designed to execute deep learning algorithms. But also, new lightweight open-source middleware for constrained resources devices such as EdgeX foundry have emerged to facilitate the collection and processing of data at sensor level, with communication capabilities to cloud enterprise applications.

The aim of this work is to show and describe the development of Smart Camera Systems within S4AllCities H2020 project, following the edge approach.

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previous chapter Decision-Support System for Safety and Security Assessment and Management in Smart Cities

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Title: Embedded Intelligence for Safety and Security Machine Vision Applications
Authors: Panagiotis Lioupis
Aris Dadoukis
Evangelos Maltezos
Lazaros Karagiannidis
Angelos Amditis
Maite Gonzalez
Jon Martin
David Cantero
Mikel Larrañaga
Publisher: Springer International Publishing
Book: Image Analysis and Processing. ICIAP 2022 Workshops
Print ISBN: 978-3-031-13323-7

Electronic ISBN: 978-3-031-13324-4

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-3-031-13324-4_4

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