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Persistent Timekeeping Using Harvested Power Measurements

Published:15 November 2021Publication History

ABSTRACT

In this study, we propose SQUID, a software-based solution to predict the off-time of batteryless devices that operate in environments with short-term energy-harvesting stability. The key insight of SQUID is to sample the power in the environment when the device is on and use these samples to extrapolate the power availability when the device is off and charging its capacitor. Therefore, SQUID can predict the charging time of the batteryless sensors by using the predicted power availability. Our initial experiments showed that SQUID has a promising estimation accuracy by consuming up to 10 times less energy than existing timekeeping solutions.

References

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    • Published in

      cover image ACM Conferences
      SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems
      November 2021
      686 pages
      ISBN:9781450390972
      DOI:10.1145/3485730

      Copyright © 2021 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 15 November 2021

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      • short-paper
      • Research
      • Refereed limited

      Acceptance Rates

      SenSys '21 Paper Acceptance Rate25of139submissions,18%Overall Acceptance Rate174of867submissions,20%

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