Publication Type
Journal Article
Version
acceptedVersion
Publication Date
3-2020
Abstract
We propose the use of the conventional energy storage component, i.e., capacitor, in the kinetic-powered wearable IoTs as the sensor to detect human activities. Since activities accumulate energy in the capacitor at different rates, the charging rate of the capacitor can be used to detect the activities. The key advantage of the proposed capacitor-based activity sensing mechanism, called CapSense, is that it obviates the need for sampling the motion signal at a high rate, and thus, significantly reduces power consumption of the wearable device. The challenge we face is that capacitors are inherently non-linear energy accumulators, which leads to significant variations in the charging rates. We solve this problem by jointly configuring the parameters of the capacitor and the associated energy harvesting circuits, which allows us to operate in the charging cycles that are approximately linear. We design and implement a kinetic-powered shoe and conduct experiments with 10 subjects. Our results show that CapSense can classify five different daily activities with 95% accuracy while consuming 57% less system power compared to conventional motion-sensor-based approaches.
Keywords
Kinetic energy harvesting, Capacitor, Activity recognition, Wearable IoTs
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
ACM Transactions on Internet of Things
Volume
1
Issue
1
First Page
1
Last Page
26
ISSN
2577-6207
Identifier
10.1145/3362124
Publisher
ACM
Citation
LAN, Guohao; MA, Dong; XU, Weitao; HASSAN, Mahbub; and HU, Wen.
Capacitor-based activity sensing for kinetic-powered wearable IoTs. (2020). ACM Transactions on Internet of Things. 1, (1), 1-26.
Available at: https://ink.library.smu.edu.sg/sis_research/6839
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3362124