Optimizing of Q-learning day/night energy strategy for solar harvesting environmental wireless sensor networks nodes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248101" target="_blank" >RIV/61989100:27240/21:10248101 - isvavai.cz</a>

Result on the web

<a href="https://www.eejournal.ktu.lt/index.php/elt/article/view/28875" target="_blank" >https://www.eejournal.ktu.lt/index.php/elt/article/view/28875</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5755/j02.eie.28875" target="_blank" >10.5755/j02.eie.28875</a>

Result language

angličtina

Original language name

Optimizing of Q-learning day/night energy strategy for solar harvesting environmental wireless sensor networks nodes

Original language description

This research article presents the application of the Q-learning algorithm in the operational duty cycle control of solar-powered environmental wireless sensor network (EWSN) nodes. Those nodes are commonly implemented as embedded devices using low-power and low-cost microcontrollers. Therefore, there is a significant need for an effective and easy way to implement a machine learning (ML) algorithm in terms of computer performance. This approach uses a Q-learning-based policy implementing a sleep/run switching algorithm driven by the state of charge. The presented algorithm is based on two modes: daylight and nighttime, which is a suitable solution for solar-powered systems. The study includes the complete process of design EWSN node strategy with an optimal reward policy. The presented algorithm was tested and verified on an EWSN node model and a 5-year data set of solar irradiance values was used for the learning process and its validation. As part of the study, we are also presenting the validation in terms of Q-learning parameters, which include the learning rate and discount factor. The result section shows that the overall performance of the presented solution is more suitable for solar-powered EWSN then state-of-the-art studies. Both day/night experiments reached 828 203 measurement/transmission cycles, which is 12.7 % more than in the previous studies using the strategy defined by the state of energy storage. (C) 2021 Kauno Technologijos Universitetas. All rights reserved.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20205 - Automation and control systems

Project

<a href="/en/project/EF16_019%2F0000867" target="_blank" >EF16_019/0000867: Research Centre of Advanced Mechatronic Systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Elektronika ir elektrotechnika

ISSN

1392-1215

e-ISSN

—

Volume of the periodical

27

Issue of the periodical within the volume

3

Country of publishing house

LT - LITHUANIA

Number of pages

7

Pages from-to

50-56

UT code for WoS article

000668351900005

EID of the result in the Scopus database

2-s2.0-85108971347