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- W3089274832 abstract "The recent widespread deployment of smart meters on a global scale has created an immense amount of fine-grained smart meter data, which requires effective and real-time analysis. Although the cloud center has powerful data processing capabilities, it is insufficient for real-time analysis, especially in the case of huge and distributed data volumes. Correspondingly, intelligent edge computing is merged with smart meters in this work to create an Internet-of-Things-based architecture for an edge-intelligence-enabled smart meter (EI-smart meter) system. To achieve its potential, we also propose two (one offline and one online) ultra-low-latency cloud-edge collaboration schemes regarding real-time data analytics. Unlike the existing work, we integrate a deep neural network (DNN) into the cloud-edge collaboration scheme in a bid to reduce execution time and improve the adaptability. Finally, numerical results are presented to validate the performance of our proposed system." @default.
- W3089274832 created "2020-10-01" @default.
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- W3089274832 date "2020-09-01" @default.
- W3089274832 modified "2023-10-05" @default.
- W3089274832 title "Edge Intelligence for Real-Time Data Analytics in an IoT-Based Smart Metering System" @default.
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- W3089274832 doi "https://doi.org/10.1109/mnet.011.2000039" @default.
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