This paper presents a fully programmable Internet of Things visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode at 10 frames/s), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power field-programmable gate array, wakes up an ultralow-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 193 and, depending on context activity. The digital subsystem is extremely flexible, thanks to a fully programmable digital signal processing engine, but still achieves lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.

Rusci, M., Rossi, D., Farella, E., Benini, L. (2017). A Sub-mW IoT-Endnode for Always-On Visual Monitoring and Smart Triggering. IEEE INTERNET OF THINGS JOURNAL, 4(5), 1284-1295 [10.1109/JIOT.2017.2731301].

A Sub-mW IoT-Endnode for Always-On Visual Monitoring and Smart Triggering

Rusci, Manuele;Rossi, Davide;Farella, Elisabetta;Benini, Luca
2017

Abstract

This paper presents a fully programmable Internet of Things visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode at 10 frames/s), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power field-programmable gate array, wakes up an ultralow-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 193 and, depending on context activity. The digital subsystem is extremely flexible, thanks to a fully programmable digital signal processing engine, but still achieves lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.
2017
Rusci, M., Rossi, D., Farella, E., Benini, L. (2017). A Sub-mW IoT-Endnode for Always-On Visual Monitoring and Smart Triggering. IEEE INTERNET OF THINGS JOURNAL, 4(5), 1284-1295 [10.1109/JIOT.2017.2731301].
Rusci, Manuele; Rossi, Davide; Farella, Elisabetta; Benini, Luca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/614082
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