Fuzzy Controlled Wavelet-Based Edge Computing Method for Energy-Harvesting IoT Sensors
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253434" target="_blank" >RIV/61989100:27240/23:10253434 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore.ieee.org/document/10174646" target="_blank" >https://ieeexplore.ieee.org/document/10174646</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/JIOT.2023.3292915" target="_blank" >10.1109/JIOT.2023.3292915</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Fuzzy Controlled Wavelet-Based Edge Computing Method for Energy-Harvesting IoT Sensors
Popis výsledku v původním jazyce
The study presents a novel edge computing (EC) method based on a discrete wavelet transform (DWT) and fuzzy logic controller suitable for application with energy harvesting IoT sensors. The authors propose a new solution to address information latency in an IoT device when compressed data with high information density are transmitted to the cloud with high priority or detailed information is added to the cloud when the energy state in the IoT device is sufficient. The solution potentially delivers a completely lossless scenario for low-power sensors, a significant benefit that state-of-the-art methods do not provide. The article describes the hardware model for an IoT device, input and predicted energy data, and a methodology for designing the parameters of DWT and fuzzy logic controllers. The results of the study indicate that the proposed EC method achieved full data transmission in contrast to the reference solution which had the worst case parameters of maximum outage and penalties caused by delayed data. The average delay in uploading approximate data was 0.51 days with the proposed fuzzy controller EC method compared to reference methods, which have an average delay of at least 0.91 days. The results also highlighted the importance of the trade-off between information latency and reliable functionality. The results are discussed in terms of an innovative approach which features an IoT sensor that maximizes its own energy consumption according to the data measured ...
Název v anglickém jazyce
Fuzzy Controlled Wavelet-Based Edge Computing Method for Energy-Harvesting IoT Sensors
Popis výsledku anglicky
The study presents a novel edge computing (EC) method based on a discrete wavelet transform (DWT) and fuzzy logic controller suitable for application with energy harvesting IoT sensors. The authors propose a new solution to address information latency in an IoT device when compressed data with high information density are transmitted to the cloud with high priority or detailed information is added to the cloud when the energy state in the IoT device is sufficient. The solution potentially delivers a completely lossless scenario for low-power sensors, a significant benefit that state-of-the-art methods do not provide. The article describes the hardware model for an IoT device, input and predicted energy data, and a methodology for designing the parameters of DWT and fuzzy logic controllers. The results of the study indicate that the proposed EC method achieved full data transmission in contrast to the reference solution which had the worst case parameters of maximum outage and penalties caused by delayed data. The average delay in uploading approximate data was 0.51 days with the proposed fuzzy controller EC method compared to reference methods, which have an average delay of at least 0.91 days. The results also highlighted the importance of the trade-off between information latency and reliable functionality. The results are discussed in terms of an innovative approach which features an IoT sensor that maximizes its own energy consumption according to the data measured ...
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20202 - Communication engineering and systems
Návaznosti výsledku
Projekt
<a href="/cs/project/FW03010194" target="_blank" >FW03010194: Vývoj systému pro monitoring a vyhodnocení vybraných rizikových faktorů fyzické zátěže pracovních operací v kontextu Průmyslu 4.0.</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
IEEE Internet of Things Journal
ISSN
2327-4662
e-ISSN
—
Svazek periodika
10
Číslo periodika v rámci svazku
23
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
9
Strana od-do
18909-18918
Kód UT WoS článku
001098109800045
EID výsledku v databázi Scopus
2-s2.0-85164439483