Internet of Things for Healthcare: An Intelligent and Energy Efficient Position Detection Algorithm
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F22%3A43905003" target="_blank" >RIV/60076658:12310/22:43905003 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore.ieee.org/document/9531553" target="_blank" >https://ieeexplore.ieee.org/document/9531553</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TII.2021.3110963" target="_blank" >10.1109/TII.2021.3110963</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Internet of Things for Healthcare: An Intelligent and Energy Efficient Position Detection Algorithm
Popis výsledku v původním jazyce
In this article, we develop a novel approach for detecting patients' position using the radial basis function of the neural network. This new approach aims to continuously monitor the patients' health statistics and real-time prediction, even when they are outside of cellular coverage. Our research is driven by an initiative to innovate a novel healthcare system of significant importance for intelligent and efficient medical services. For example, doctors need to remotely monitor any patient's health with the provided health statistics derived from data collected from battery-powered Internet of Things sensors. To this end, our proposed method has been quantified with a holistic mathematical analysis and extensive simulations considering realistic network situations. Our results have accredited the efficiency in the prediction of localization for the patients' position for the anticipated intelligent healthcare system.
Název v anglickém jazyce
Internet of Things for Healthcare: An Intelligent and Energy Efficient Position Detection Algorithm
Popis výsledku anglicky
In this article, we develop a novel approach for detecting patients' position using the radial basis function of the neural network. This new approach aims to continuously monitor the patients' health statistics and real-time prediction, even when they are outside of cellular coverage. Our research is driven by an initiative to innovate a novel healthcare system of significant importance for intelligent and efficient medical services. For example, doctors need to remotely monitor any patient's health with the provided health statistics derived from data collected from battery-powered Internet of Things sensors. To this end, our proposed method has been quantified with a holistic mathematical analysis and extensive simulations considering realistic network situations. Our results have accredited the efficiency in the prediction of localization for the patients' position for the anticipated intelligent healthcare system.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
IEEE Transactions on Industrial Informatics
ISSN
1551-3203
e-ISSN
1941-0050
Svazek periodika
18
Číslo periodika v rámci svazku
8
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
8
Strana od-do
5458-5465
Kód UT WoS článku
000793847600046
EID výsledku v databázi Scopus
2-s2.0-85114717090