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Fever status detection using artificial neuron network

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dc.title Fever status detection using artificial neuron network en
dc.contributor.author Nchena, Linos Mabvuto
dc.contributor.author Janáčová, Dagmar
dc.relation.ispartof Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021), Vol 1
dc.identifier.issn 2184-4992 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-989-758-509-8
dc.date.issued 2021
utb.relation.volume 1
dc.citation.spage 776
dc.citation.epage 781
dc.event.title 23rd International Conference on Enterprise Information Systems (ICEIS)
dc.event.location online
dc.event.sdate 2021-04-26
dc.event.edate 2021-04-28
dc.type conferenceObject
dc.language.iso en
dc.publisher Scitepress
dc.identifier.doi 10.5220/0010485407760781
dc.relation.uri https://www.scitepress.org/Link.aspx?doi=10.5220/0010485407760781
dc.subject Assistive Technologies en
dc.subject Senior Citizen Assistance en
dc.subject Incident Detection System en
dc.subject Health Status Monitor en
dc.subject Artificial Intelligence en
dc.subject Artificial Neural Networks en
dc.subject Machine Learning en
dc.description.abstract This research paper proposes a monitoring system and a prototype that has been developed for detecting if a when fever is present in senior citizens or any other specific groups of people requiring continuous care. With various issues affecting the health of senior citizens, it is imperative to continuously monitor their health status. The monitoring system is beneficial as it will make it feasible to enable the real time detection of fever and thus allowing for the early treatment. Delaying treatment can lead to the underlining health issue going beyond the remediable condition. Thus, quick detection is vital. There are various issues that might causes illness in people. Some of the issues include virus outbreak, seasonal infections, disease, and old age. In this paper our focus is mainly on old age. This group of people is much more at risk of getting ill or frequently need more attention. In this project, the presence of fever or illness has been detected by using artificial intelligence (AI). The AI technique that is utilized in this project is artificial neural networks. The computation is done by first training the system and then secondly validating the trained system. After the training, the system is supplied with a new set of data, with a known state, to validate that the training was successful. To validate the system, it is provided with sample data to test its efficiency. If the system is well trained the validation data would label that data correctly. That label is known before the validation test, as the sample data had known labels. These known labels were not given to training but not validation system. The system is function properly if its label matched the sample data label. The conducted experiment demonstrated a successful detection with an efficiency rate of 82 percent. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010959
utb.identifier.rivid RIV/70883521:28140/21:63528698!RIV22-MSM-28140___
utb.identifier.obdid 43882497
utb.identifier.scopus 2-s2.0-85137948778
utb.identifier.wok 000783390600085
utb.source C-wok
dc.date.accessioned 2022-05-05T12:14:41Z
dc.date.available 2022-05-05T12:14:41Z
dc.description.sponsorship Faculty of Applied Informatics, Tomas Bata University in Zlin [IGA/CebiaTech/2021/001]
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.access openAccess
utb.ou Department of Automation and Control Engineering
utb.contributor.internalauthor Nchena, Linos Mabvuto
utb.contributor.internalauthor Janáčová, Dagmar
utb.fulltext.affiliation Linos Nchena and Dagmar Janacova Department of Automation and Control Engineering, Tomas Bata University in Zlín, Czech Republic
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by IGA/CebiaTech/2021/001, a research project of the Faculty of Applied Informatics, Tomas Bata University in Zlin.
utb.wos.affiliation [Nchena, Linos; Janacova, Dagmar] Tomas Bata Univ Zlin, Dept Automat & Control Engn, Zlin, Czech Republic
utb.scopus.affiliation Department of Automation and Control Engineering, Tomas Bata University, Zlín, Czech Republic
utb.fulltext.projects IGA/CebiaTech/2021/001
utb.fulltext.faculty -
utb.fulltext.ou Department of Automation and Control Engineering
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