Metadata only
Date
2020-11Type
- Conference Paper
Abstract
This paper presents a battery-free smart camera that combines tiny machine learning, long-range communication, power management, and energy harvesting. The smart sensor node has been implemented and evaluated in the field, showing both battery-less capabilities with a small-size photovoltaic panel and the energy efficiency of the proposed solution. We evaluated two different ARM Cortex-M4F microcontrollers, the Ambiq Apollo 3 that is an energy-efficient microcontroller, and a Microchip SAMD51 able to work in high radiation environments but with a higher power in active mode. Finally, a low power LoRa module provides the long-range wireless transmission capability. The tiny machine learning algorithm for face recognition has been optimized in terms of accuracy versus energy, achieving up to 97% accuracy recognizing five different faces. Experimental results demonstrated the capability of the developed sensor node to start from the cold start after 1 minute at a very low luminosity of 350 lux using a cm size flexible photovoltaic panels and work perpetually after the cold start. © 2020 Association for Computing Machinery. Show more
Publication status
publishedExternal links
Book title
ENSsys '20: Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing SystemsPages / Article No.
Publisher
ACMEvent
Subject
Battery-Free; Smart Sensors; Smart Camera; Energy Harvesting; Power Management; Low Power Design; Tiny Machine LearningOrganisational unit
01225 - D-ITET Zentr. f. projektbasiertes Lernen / D-ITET Center for Project-Based Learning03996 - Benini, Luca / Benini, Luca
01225 - D-ITET Zentr. f. projektbasiertes Lernen / D-ITET Center for Project-Based Learning
Notes
Due to the Coronavirus (COVID-19) the conference was conducted virtually.More
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