RT Journal Article
T1 Solar Energy Harvesting to Improve Capabilities of Wearable Devices
A1 Páez Montoro, Alba
A1 García Valderas, Mario
A1 Olías Ruiz, Emilio
A1 López Ongil, Celia
AB The market of wearable devices has been growing over the past decades. Smart wearablesare usually part of IoT (Internet of things) systems and include many functionalities such asphysiological sensors, processing units and wireless communications, that are useful in fields likehealthcare, activity tracking and sports, among others. The number of functions that wearableshave are increasing all the time. This result in an increase in power consumption and more frequentrecharges of the battery. A good option to solve this problem is using energy harvesting so that theenergy available in the environment is used as a backup power source. In this paper, an energyharvesting system for solar energy with a flexible battery, a semi-flexible solar harvester module anda BLE (Bluetooth® Low Energy) microprocessor module is presented as a proof-of-concept for thefuture integration of solar energy harvesting in a real wearable smart device. The designed devicewas tested under different circumstances to estimate the increase in battery lifetime during commondaily routines. For this purpose, a procedure for testing energy harvesting solutions, based on solarenergy, in wearable devices has been proposed. The main result obtained is that the device couldpermanently work if the solar cells received a significant amount of direct sunlight for 6 h every day.Moreover, in real-life scenarios, the device was able to generate a minimum and a maximum powerof 27.8 mW and 159.1 mW, respectively. For the wearable system selected, Bindi, the dynamic testsemulating daily routines has provided increases in the state of charge from 19% (winter cloudy days,4 solar cells) to 53% (spring sunny days, 2 solar cells).Keywords: energy harvesting; internet of things; physiological
PB MDPI AG
SN 1424-3210
YR 2022
FD 2022-05
LK https://hdl.handle.net/10016/34999
UL https://hdl.handle.net/10016/34999
LA eng
NO This research was funded by the Department of Research and Innovation of MadridRegional Authority, in the EMPATIA-CM research project (reference Y2018/TCS-5046). This work hasbeen partially supported by the European Union—NextGenerationEU, with the SAPIENTIAE4BINDIproject “Proof of Concept” 2021. (Ref: PDC2021-121071-I00/AEI/10.13039/501100011033). Thiswork has been supported by the Madrid Government (Comunidad de Madrid-Spain) under theMultiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M26),and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).
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RD 27 jul. 2024