EHAAS: Energy harvesters as a sensor for place recognition on wearables

Yoshinori Umetsu, Yugo Nakamura, Yutaka Arakawa, Manato Fujimoto, Hirohiko Suwa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

A wearable based long-term lifelogging system is desirable for the purpose of reviewing and improving users lifestyle habits. Energy harvesting (EH) is a promising means for realizing sustainable lifelogging. However, present EH technologies suffer from instability of the generated electricity caused by changes of environment, e.g., the output of a solar cell varies based on its material, light intensity, and light wavelength. In this paper, we leverage this instability of EH technologies for other purposes, in addition to its use as an energy source. Specifically, we propose to determine the variation of generated electricity as a sensor for recognizing "places" where the user visits, which is important information in the lifelogging system. First, we investigate the amount of generated electricity of selected energy harvesting elements in various environments. Second, we design a system called EHAAS (Energy Harvesters As A Sensor) where energy harvesting elements are used as a sensor. With EHAAS, we propose a place recognition method based on machine-learning and implement a prototype wearable system. Our prototype evaluation confirms that EHAAS achieves a place recognition accuracy of 88.5% F-value for nine different indoor and outdoor places. This result is better than the results of existing sensors (3-axis accelerometer and brightness). We also clarify that only two types of solar cells are required for recognizing a place with 86.2% accuracy.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538691489
DOIs
Publication statusPublished - Mar 1 2019
Event2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019 - Kyoto, Japan
Duration: Mar 12 2019Mar 14 2019

Publication series

Name2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019

Conference

Conference2019 IEEE International Conference on Pervasive Computing and Communications, PerCom 2019
CountryJapan
CityKyoto
Period3/12/193/14/19

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

Fingerprint Dive into the research topics of 'EHAAS: Energy harvesters as a sensor for place recognition on wearables'. Together they form a unique fingerprint.

Cite this