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Fog and Edge Computing for Automotive Applications Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Edge Analytics and Deep Learning for Sustainable Development

Authors : Santosh Kumar Singh, Supernova Chakraborty, Vishal Soodan

Published in: Challenges and Solutions for Sustainable Smart City Development

Publisher: Springer International Publishing

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Abstract

Edge computing is the only sustainable method to meet ever-increasing computing needs bearing in mind the amount of data edge devices produce and process every day to provide better analytical reports to simplify human lives. The core of this analysis is based on artificial intelligence and machine learning. Yet, as of now this current Cloud Service Architecture model doesn’t prove to be accurate in “providing artificial intelligence for every one, at everyplace", and this motivated authors to shift the focus from cloud computing to edge computing and analytics. Recently this solution has gained much attention because it uses edge devices in a substantial manner to accumulate information without any extensive use of resources. Hence, this is the reason that it has emerged as a desirable solution and can be used as a representative technique to harness and improve artificial intelligence for a better and sustainable solution; this chapter discusses the concept of edge intelligence and deep learning and analytics.

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Metadata
Title
Edge Analytics and Deep Learning for Sustainable Development
Authors
Santosh Kumar Singh
Supernova Chakraborty
Vishal Soodan
Copyright Year
2021
Book
Challenges and Solutions for Sustainable Smart City Development

Print ISBN: 978-3-030-70182-6

Electronic ISBN: 978-3-030-70183-3

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-70183-3_10

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