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Artificial Intelligence Applications on Edge

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Edge AI

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Abstract

In general, AI services are currently deployed in cloud data centers (the cloud) for handling requests, due to the fact that most AI models are complex and hard to compute their inference results on the side of resource-limited devices. However, such kind of “end–cloud” architecture cannot meet the needs of real-time AI services such as real-time analytics, smart manufacturing, etc. Thus, deploying AI applications on the edge can broaden the application scenarios of AI especially with respect to the low-latency characteristic. In the following, we present edge AI applications and highlight their advantages over the comparing architectures without edge computing.

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Authors and Affiliations

  1. College of Intelligence and Computing, Tian** University Tian**, Tian**, China

    **aofei Wang & Yiwen Han

  2. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, China

    Victor C. M. Leung

  3. School of Computer and Engineering, Nanyang Technological University, Singapore, Singapore

    Dusit Niyato

  4. 2012 Lab, Huawei Technologies (China), Shenzhen, China

    Xueqiang Yan

  5. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, Guangdong, China

    Xu Chen

Authors
  1. **aofei Wang
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  2. Yiwen Han
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  3. Victor C. M. Leung
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  4. Dusit Niyato
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  5. Xueqiang Yan
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  6. Xu Chen
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Wang, X., Han, Y., Leung, V.C.M., Niyato, D., Yan, X., Chen, X. (2020). Artificial Intelligence Applications on Edge. In: Edge AI. Springer, Singapore. https://doi.org/10.1007/978-981-15-6186-3_4

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  • DOI: https://doi.org/10.1007/978-981-15-6186-3_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6185-6

  • Online ISBN: 978-981-15-6186-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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