English

A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

Other Computer Science 2017-05-02 v1

Abstract

This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast 128x64128\mathrm{x}64 binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode (10μW10\mu W at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between 193μW193\mu W and 277μW277\mu W, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.

Keywords

Cite

@article{arxiv.1705.00221,
  title  = {A sub-mW IoT-endnode for always-on visual monitoring and smart triggering},
  author = {Manuele Rusci and Davide Rossi and Elisabetta Farella and Luca Benini},
  journal= {arXiv preprint arXiv:1705.00221},
  year   = {2017}
}

Comments

11 pages, 9 figures, submitteted to IEEE IoT Journal