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Title:Sistem za naročanje prehrane s pomočjo platforme Raspberry Pi : diplomsko delo
Authors:Bencik, Matevž (Author)
Korže, Danilo (Mentor) More about this mentor... New window
Borovič, Mladen (Co-mentor)
Files:.pdf UN_Bencik_Matevz_2019.pdf (2,17 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu opisujemo izvedbo sistema za naročanje prehrane, ki deluje na računalniku Raspberry Pi 3B+. Spoznamo družino računalnikov Raspberry Pi, programski jezik Python, tehnologijo NFC, grafne podatkovne baze in priporočilne sisteme. Razvijemo sistem, ki omogoča identifikacijo uporabnika z uporabo kartice NFC, izbiro malice za naslednjih 5 dni in priporočanje izbire malice. Priporočilni sistem deluje po principu vsebinskega priporočanja. Naša rešitev deluje v programskem jeziku Python, uporabniški vmesnik pa je narejen s pomočjo ogrodja Flask. Vsi podatki so shranjeni v grafni podatkovni bazi Neo4j. Identifikacija uporabnika s kartico NFC je izdelana s pomočjo razširitvene plošče EXPLORE-NFC.
Keywords:Raspberry Pi, priporočilni sistem, grafna podatkovna baza, NFC
Year of publishing:2019
Place of performance:Maribor
Publisher:[M. Bencik]
Number of pages:VII, 35 f.
Source:Maribor
UDC:004.777:004.775(043.2)
COBISS_ID:22577942 Link is opened in a new window
NUK URN:URN:SI:UM:DK:CBGUD0FJ
License:CC BY-NC-ND 4.0
This work is available under this license: Creative Commons Attribution Non-Commercial No Derivatives 4.0 International
Views:144
Downloads:46
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:Food ordering system using the Raspberry Pi platform
Abstract:The diploma thesis deals with food ordering system using Raspberry Pi 3B+. In this thesis we get to know Raspberry Pi computer series, programming language Python, NFC technology, graph databases and recommender systems. We developed system that allows users to be identified with the NFC card and select their next 5 food menus. System also recommends them what menu to choose. Recommender system is using content-based filtering. Our solution is written in Python programming language and the user interface is built, using the Flask framework. Data is stored in Neo4j graph database. User identification is built, using the EXPLORE-NFC expansion board.
Keywords:Raspberry Pi, recommender system, graph database, NFC


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