用于边缘推理的自供电物联网系统

Dileep Kurian, T. Karnik, Saksham Soni, Saransh Chhabra, Suhwan Kim, Jaykant Timbadiya, Ankit Gupta, K. Ravichandran, Mukesh Bhartiya, Angela Nicoara
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引用次数: 0

摘要

我们提出了一个端到端物联网系统,可以从多个来源收集能量。它包括x86的计算、安全和边缘图像推理。该mote由能量收集电源管理IC (EHPMIC)自供电。该系统通过无线方式连接到一个连接到云的网关。可持续的能源中性操作是通过太阳能和风能收集来实现的。实现了14000行软件堆栈,系统被证明仅消耗0.2mW的空闲功率和24mW的峰值功率。在运行Dhrystone基准测试时,在0.5V /100MHz下测量到的最小能量点为6.2pJ/cycle。EHPMIC输出功率高达120mW,峰值效率为81.7%,控制功率开销仅为120美元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-Powered IOT System for Edge Inference
We present an end to end IoT system that works off harvested energy from multiple sources. It includes X86s compute, security and image inference at the edge. The mote is self-powered by an energy harvesting power management IC (EHPMIC). The system connects wirelessly to a gateway that connects to the cloud. Sustainable energy-neutral operation is achieved by solar and wind energy harvesting. 14000 lines of software stack was implemented, and the system was demonstrated to consume only 0.2mW idle and 24mW peak power. Measured minimum energy point was 6.2pJ/cycle at 0.5V /100MHz running Dhrystone benchmarks. EHPMIC delivers up to 120mW with a peak efficiency of 81.7% and only $120\mu \mathrm{W}$ control power overhead.
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