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Title:Pametna vremenska postaja za napoved temperature s pomočjo strojnega učenja : diplomsko delo
Authors:ID Jeušnik, Nejc (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
ID Kranjec, Jernej (Co-mentor)
Files:.pdf UN_Jeusnik_Nejc_2021.pdf (1,67 MB)
MD5: 08DFEF0B7F110D7900B987C34D8CD73C
PID: 20.500.12556/dkum/438d2d97-0c52-414e-8f6f-9b3061ce09ff
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Namen diplomskega dela je bil razviti pametno vremensko postajo s spletno aplikacijo, ki bi omogočala napoved temperature do pet dni vnaprej. Želeli smo tudi preizkusiti kako natančne so napovedi z različnimi modeli in metodami. V diplomskem delu predstavimo zasnovo in implementacijo rešitve. Na koncu podamo rezultate napovedi. Celoten sistem je sestavljen iz razvojne plošče platforme Arduino, senzorja temperature in vlage, oblačne podatkovne baze in računalniškega strežnika z integracijo napovednih metod, ki omogoča uporabniku dostop do spletne aplikacije z vsemi rezultati v domačem omrežju.
Keywords:napoved temperature, Arduino, LSTM, SARIMA
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[N. Jeušnik]
Year of publishing:2021
Number of pages:X, 36 str.
PID:20.500.12556/DKUM-80000 New window
UDC:551.507-027.43(043.2)
COBISS.SI-ID:90501379 New window
Publication date in DKUM:18.10.2021
Views:745
Downloads:73
Metadata:XML RDF-CHPDL DC-XML DC-RDF
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:25.08.2021

Secondary language

Language:English
Title:Smart weather station for temperature forecast using machine learning
Abstract:The goal of this thesis was to develop a smart weather station with included web application, which would be able to forecast the temperature up to five days in advance. The secondary goal was to test the accuracy of predicitions with different models and methods. In this thesis we present the design and implementation of the solution to this problem. At the end we describe the results of our forecasts. The complete system consists of Arduino development board, temperature and humidity sensor, cloud database and computer server with integrated forecast methods, which provide end user with results of forecasts from web application in their home network.
Keywords:temperature forecast, Arduino, LSTM, SARIMA


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