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Towards Always-on Event-based Cameras for Long-lasting Battery-operated Smart Sensor Nodes
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2021 (Engelska)Ingår i: Conference Record - IEEE Instrumentation and Measurement Technology Conference, Institute of Electrical and Electronics Engineers Inc. , 2021Konferensbidrag (Refereegranskat)
Abstract [en]

A recent and promising approach to minimize the power consumption of always-on battery-operated sensors is to perform 'smart' detection of events to trigger processing. This approach effectively reduces the data bandwidth and power consumption at the system-level and increases the lifetime of sensor nodes. This paper presents an always-on, event-driven ultra-low-power camera platform for motion detection applications. The platform exploits an event-driven VGA imager that features a motion detection mode based on a tunable scene background subtraction algorithm and a grayscale imaging mode. To reduce the power consumption in the motion detection mode, the platform implements a configurable refresh rate which allows for adaption to sensing requirements by trading off between power consumption and detection sensitivity. With accurate experimental evaluation the paper demonstrates that the proposed approach reduces the system-level power consumption for always-on motion sensing applications by switching between an active 15 FPS imaging mode, consuming 5.5 mW and a low-power motion detection mode consuming 1.8 mW. We further estimate the power consumption for a single-chip solution and show that the system-level power budget can be reduced to 2.4 mW in imaging, and 400W in detection mode. © 2021 IEEE.

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Institute of Electrical and Electronics Engineers Inc. , 2021.
Nyckelord [en]
Embedded Processing, Event-based Sensing, Event-driven Processing, Low-power Vision, Budget control, Cameras, Electric batteries, Motion analysis, Sensor nodes, Background subtraction algorithms, Camera platform, Detection sensitivity, Experimental evaluation, Motion detection, Single chip solution, Trigger processing, Ultra low power, Electric power utilization
Identifikatorer
URN: urn:nbn:se:miun:diva-43090DOI: 10.1109/I2MTC50364.2021.9460037Scopus ID: 2-s2.0-85113713668ISBN: 9781728195391 (tryckt)OAI: oai:DiVA.org:miun-43090DiVA, id: diva2:1595716
Anmärkning

Export Date: 20 September 2021; Conference Paper; CODEN: CRIIE

Tillgänglig från: 2021-09-20 Skapad: 2021-09-20 Senast uppdaterad: 2021-09-20Bibliografiskt granskad

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Magno, M.

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Totalt: 8 träffar
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