Self-learning for Day-night Mode Energy Strategy for Solar Powered Environmental WSN Nodes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246783" target="_blank" >RIV/61989100:27240/20:10246783 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9255790" target="_blank" >https://ieeexplore.ieee.org/document/9255790</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CCECE47787.2020.9255790" target="_blank" >10.1109/CCECE47787.2020.9255790</a>
Alternative languages
Result language
angličtina
Original language name
Self-learning for Day-night Mode Energy Strategy for Solar Powered Environmental WSN Nodes
Original language description
Environmental data is in many cases acquired in remote locations that are difficult to access for sensor maintenance. Therefore, efficient use of available energy is crucial, particularly in systems that use energy harvesting devices, such as solar panels. This study presents a hybrid energy management strategy implemented in an environmental wireless sensor network (EWSN) controller. The control unit employs a model-free Q-learning algorithm during the day and linear energy discharging at night. A three-component Q-learning reward signal along with 7 actions and 11 energy states are designed for the system to achieve optimal performance in terms of data sensing and transmission operation and to minimize the amount of failures due energy storage depletion. (C) 2020 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
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
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Canadian Conference on Electrical and Computer Engineering 2020
ISBN
978-1-72815-443-5
ISSN
0840-7789
e-ISSN
2576-7046
Number of pages
5
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
London
Event date
Aug 30, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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