diplomsko delo
David Slatinek (Author), Aleš Holobar (Mentor)

Abstract

V diplomskem delu predstavimo uporabo računalnika Raspberry Pi in interneta stvari za zdravstvene namene, s čimer omogočimo merjenje srčnega utripa, nivoja kisika v krvi, elektrokardiograma, telesne temperature skupaj s temperaturo okolice in vlažnostjo. Najprej predstavimo področje dela, med kar spadajo vgrajeni sistemi, operacijski sistem Linux, zaledni sistemi s spletnimi vmesniki in podatkovnimi bazami ter čelni sistemi skupaj s Flutterjem. Nato opišemo zasnovo rešitve, predstavimo uporabljene senzorje ter prikažemo razvoj podatkovne baze in razvoj spletnega vmesnika. Pokažemo izdelavo modula za nalaganje podatkov in mehanizem za opozarjanje na napake, zatem pa opišemo razvoj mobilne aplikacije. Na koncu analiziramo rešitev.

Keywords

zdravje;internet stvari;platforma Raspberry Pi;sistem GraphQL;sistem Flutter;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: [D. Slatinek]
UDC: 004.777(043.2)
COBISS: 115624451 Link will open in a new window
Views: 379
Downloads: 132
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: English
Secondary title: Using Raspberry Pi and the Internet of Things for healthcare
Secondary abstract: In this thesis, we present the use of Raspberry Pi and the Internet of Things in healthcare applications, which enables the measurement of heart rate, blood oxygen level, electrocardiogram, and body temperature alongside ambient temperature and humidity. First, we introduce the scope of work and used technology, including embedded systems, the Linux operating system, back-end systems with application programming interfaces and databases, and front-end systems along with Flutter. We then describe the design of the solution, present the sensors used, and show database and web interface development. Next, we display the development of the data loading module and the error alerting mechanism. Afterward, we describe the development of the mobile application. In the end, we analyze the solution.
Secondary keywords: health;internet of things;Raspberry Pi;GraphQL;Flutter;
Type (COBISS): Bachelor thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages: 1 spletni vir (1 datoteka PDF (XIII, 70 f.))
ID: 15755964