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PUBLICATIONS

Kinetic-Based Micro Energy-Harvesting for Wearable Sensors

Published

Author(s)

Kamran Sayrafian, Dora Budic, Dina Simunic

Abstract

Wearable sensors are considered to be a key component of cognitive infocommunications systems. These sensors, which are basically enabler of inter-cognitive communication, will provide physical interfaces between humans and future information and communication technology (ICT) devices. Due to their small size, such sensors are often powered by small batteries which might necessitate frequent recharge or even sensor replacement. Energy harvesting can reduce the charging frequency of these sensors. Longer operational lifetime can simplify the everyday use of wearable sensors in many of their applications. In this paper, our objective is to estimate the average amount of kinetic energy that can be harvested to power a wearable device. To obtain this estimate, we have measured typical acceleration of the human body through the use of a triaxial accelerometer placed at various locations on the body surface. These locations are assumed to be associated with the typical placement of a wearable sensor. Using a mathematical model of a micro energy-harvester, instantaneous harvested power can be generated, and target statistics such as average can be calculated. Our results show that kinetic-based micro harvesters could be a promising technology for prolonging the operational lifetime of wearable sensors.
Conference Dates
October 19-21, 2015
Conference Location
Gyor
Conference Title
6th IEEE International Conference on Cognitive Infocommunications (IEEE CogInfoCom 2015)
Pub Type
Conferences

Download Paper

https://doi.org/10.1109/CogInfoCom.2015.7390645
Local Download

Keywords

Micro energy-harvester, wearable sensors, triaxial accelerometer
Wireless (RF), Information technology and Health IT

Citation

Sayrafian, K. , Budic, D. and Simunic, D. (2016), Kinetic-Based Micro Energy-Harvesting for Wearable Sensors, 6th IEEE International Conference on Cognitive Infocommunications (IEEE CogInfoCom 2015), Gyor, -1, [online], https://doi.org/10.1109/CogInfoCom.2015.7390645 (Accessed April 26, 2024)

Created January 28, 2016, Updated May 13, 2020