Razvoj večmodalnega zaznavnega omrežja za zajemanje občutkov in ocene kakovosti življenja : magistrsko delo

Šafran, Valentino

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Title:	Razvoj večmodalnega zaznavnega omrežja za zajemanje občutkov in ocene kakovosti življenja : magistrsko delo
Authors:	ID Šafran, Valentino (Author) ID Rojc, Matej (Mentor) More about this mentor... ID Mlakar, Izidor (Comentor)
Files:	MAG_Safran_Valentino_2021.pdf (2,59 MB) MD5: 8A8A4ED125DA0BA7CBEBE0C2E8DD96B1 PID: 20.500.12556/dkum/932abf2f-93d2-46dd-98a3-187cae845767
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	V magistrskem delu predstavljamo razvoj večmodalnega zaznavnega omrežja za namene evropskega projekta H2020 PERSIST, ki zajema podatke oziroma občutke, z namenom ocenjevanja kakovosti življenja pacientov. Pred razvojem sistema, smo preučili in podali pregled procesa zajema podatkov že obstoječih sistemov, ter pregled izbranih gradnikov za naš sistem. Predstavljamo tudi uporabljene standarde in protokole, ki se uporabljajo znotraj predlaganega sistema. Za arhitekturo večmodalnega zaznavnega omrežja smo izbrali tri temeljne gradnike za katere smo ocenili, da lahko tvorijo zmogljivo omrežje za prenos in obdelavo podatkov, ter ponujajo možnost nadgrajevanja v primeru zvišanja zahtev projekta. Ti trije gradniki so Apache Camel, Apache ActiveMQ Artemis in Apache Kafka. Vse gradnike smo postavili na fizičnem strežniku PERSIST_CAMEL, in sicer vsakega na svojem virtualnem stroju. Mikroservisi strojnega učenja, razen vprašalnikov, ki jih izvaja Rasa Chatbot, ki so v procesu razvoja, pa predstavljajo odjemalce tega sistema. Večmodalno zaznavno omrežje je ustrezno zavarovano z varnimi protokoli in z uporabo drugih varnostnih elementov. Na koncu podamo tudi rezultate testiranja obremenjenosti in odzivnosti sistema pri odgovarjanju na vprašalnike. Iz rezultatov je razvidno, da zastavljen sistem uspešno izvaja pretakanje podatkov za podano število 200 pacientov v projektu PERSIST, in lahko podpre tudi večje število uporabnikov.
Keywords:	večmodalno zaznavno omrežje, kakovost življenja, skrb za zdravje, zbiranje podatkov pacientov, Apache Camel, Apache ActiveMQ Artemis, Apache Kafka
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[V. Šafran]
Year of publishing:	2021
Number of pages:	XI, 72 str.
PID:	20.500.12556/DKUM-79850
UDC:	004.415.5:004.657(043.2)
COBISS.SI-ID:	86205187
Publication date in DKUM:	18.10.2021
Views:	1121
Downloads:	121
Metadata:
Categories:	KTFMB - FERI
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	19.08.2021

Secondary language

Language:	English
Title:	Development of a multimodal sensing network to capture feelings and assessment of quality of life
Abstract:	In the master's thesis, we present the development of a multimodal sensing network for the european project H2020 PERSIST, that captures data or human condition, in order to assess the quality of life of patients. Prior to development, we reviewed and provide an overview of the data acquisition process, already used systems and an overview of several building blocks selected for the proposed system. We also describe standards and protocols selected for the system. For the architecture of the multimodal sensing network, we decided to use three basic building blocks, since we believe that they can form a powerful network for data transmission and processing, and also has the possibility to be upgraded in case of more demanded project requirements. These three building blocks are: Apache Camel, Apache ActiveMQ Artemis, and Apache Kafka. Machine learning microservices, with the exception of questionnaires conducted by Rasa Chatbot, are still under development. The multimodal sensing network is adequately secured with several secure protocols and uses also other security features. Finally, we present the results of testing the load and responsiveness of the system, when users are answering the questionnaires. From these results we concluded that the proposed system can perform data streaming for 200 patients, as needed in the PERSIST project, and can handle even more users.
Keywords:	mutimodal sensing network, quality of life, healthcare, patient gathered health data, Apache Camel, Apache ActiveMQ Artemis, Apache Kafka

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