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English(EN) A Real-Time Tsetlin Machine-based Non-intrusive Load Monitoring System on MCUs

Tsetlin机在MCU上实现实时、低内存的NILM

研究人员开发了一种新颖的非侵入式负荷监测(NILM)系统,该系统利用Tsetlin机(TM)框架,专为资源受限的微控制器单元(MCU)上的实时运行而设计。该方法将能耗估算问题重新构建为分类任务,通过在本地处理敏感的家庭数据,实现隐私保护的边缘部署。基于TM的系统表现出强大的性能,在REDD数据集上,对两种电器进行分类时达到90%的精确率和96%的召回率,对四种电器进行分类时达到77%的精确率和80%的召回率。值得注意的是,训练好的模型仅需18 KB的闪存,并在ESP32上表现出0.43毫秒的推理延迟,使其非常适合嵌入式NILM应用。 AI

影响 支持在低功耗边缘设备上实现隐私保护的实时能源监测。

排序理由 学术论文,详细介绍了一种针对特定应用的新机器学习方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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Tsetlin机在MCU上实现实时、低内存的NILM

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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Tianhang Tan, Han Wu, Tousif Rahman, Shengyu Duan, Alex Yakovlev, Rishad Shafik ·

    基于Tsetlin机器的实时非侵入式负载监测系统在MCU上的应用

    arXiv:2608.18780v1 Announce Type: new Abstract: Non-Intrusive Load Monitoring (NILM) systems estimate individual appliance energy consumption from a single aggregate meter, without requiring separate sensors for each device. By installing a single meter that measures a building's…