KeepEdge: A Knowledge Distillation Empowered Edge Intelligence Framework for Visual Assisted Positioning in UAV Delivery Article Swipe
Haoyu Luo
,
Tianxiang Chen
,
Xuejun Li
,
Shuangyin Li
,
Chong Zhang
,
Gansen Zhao
,
Xiao Liu
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/tmc.2022.3157957
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/tmc.2022.3157957
The Unmanned Aerial Vehicles (UAVs) delivery service is being increasingly used in logistics. However, it is challenging for a UAV to precisely identify the position for parcel delivering if it is only aided by the GPS, especially in some complex environments with weak signals and high interference. For this issue, we present a knowledge distillation empowered edge intelligence architecture, KeepEdge, to achieve visual information-assisted positioning for the UAV delivery services. Specifically, we integrate deep neural networks (DNN) into an edge computing framework to enable edge intelligence which empowers the UAVs to autonomously identify the expected delivery position. Deploying the DNN model and conducting model inference on UAVs however, requires high computing performance. To manage the trade-off between the limited resources onboard the UAVs and high-performance requirements, we employ knowledge distillation to produce a lightweight model with high accuracy based on the full model trained in the cloud. The lightweight model with significantly lower complexity and less inference latency is used onboard of the UAVs for accurate positioning. Comprehensive experiments show that the proposed architecture achieves satisfactory performance for assisted positioning. A real-world case study is presented to demonstrate the effectiveness of the proposed edge intelligence solution for UAV delivery services.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tmc.2022.3157957
- https://ieeexplore.ieee.org/ielx7/7755/4358975/09732222.pdf
- OA Status
- hybrid
- Cited By
- 26
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4226145436
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- OpenAlex ID
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https://openalex.org/W4226145436Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tmc.2022.3157957Digital Object Identifier
- Title
-
KeepEdge: A Knowledge Distillation Empowered Edge Intelligence Framework for Visual Assisted Positioning in UAV DeliveryWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-03-09Full publication date if available
- Authors
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Haoyu Luo, Tianxiang Chen, Xuejun Li, Shuangyin Li, Chong Zhang, Gansen Zhao, Xiao LiuList of authors in order
- Landing page
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https://doi.org/10.1109/tmc.2022.3157957Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/7755/4358975/09732222.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/7755/4358975/09732222.pdfDirect OA link when available
- Concepts
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Computer science, Global Positioning System, Enhanced Data Rates for GSM Evolution, Edge computing, Cloud computing, Inference, Artificial intelligence, Real-time computing, Artificial neural network, Deep learning, Distributed computing, Telecommunications, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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26Total citation count in OpenAlex
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2025: 9, 2024: 10, 2023: 6, 2022: 1Per-year citation counts (last 5 years)
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40Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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