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master's thesis
Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:700554
Gulin, Ante
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Gulin, A. (2020). Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:700554

Gulin, Ante. "Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:700554

Gulin, Ante. "Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:700554

Gulin, A. (2020). 'Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:700554

Gulin A. Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 December 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:700554

A. Gulin, "Modeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:700554

Metadata
TitleModeliranje električne potrošnje korisnika pomoću IoT uređaja i neuronskih mreža
Title (english)Modelling of user power consumption by IoT controller with neural networks
AuthorAnte Gulin
MentorVinko Lešić (mentor)
Committee memberVinko Lešić (predsjednik povjerenstva)
Committee memberMario Vašak (član povjerenstva)
Committee memberBranimir Novoselnik (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Zgrade su jedan od najvećih potrošača energije na svijetu i također su prostor za značajne uštede energije. Učenje korisničkog ponašanja preduvjet je za prognoziranje i moguću optimizaciju cjelokupne energetske bilance prilagođene ponašanju korisnika. Da bi se to postiglo potrebno je pratiti ponašanje korisnika. IoT uređaj koristio se za otkrivanje prisutnosti korisnika i njihove potrošnje električne energije na razini od jedne godine, u različito doba dana, vremenske uvjete, godišnja doba i radne / neradne dane. Nakon prikupljanja podataka napravio se matematički model koji se temelji na informaciji te je naučen pomoću neuronskih mreža. Jednom naučeni model implementiran je kao Python skripta na mikroračunalo Rasberry Pi i pruža predviđeno ponašanje korisnicima 36 sati unaprijed.
Abstract (english)
Buildings are one of the largest energy consumers in the world and also a space for significant energy saving. Learning user behavior is a prerequisite for forecasting and possible optimization of the entire buldings energy balance adjusted to user behavior. In order to do so, it is necessary to monitor the behaviors of the users. IoT device was used for detecting the presence of users and their electricity consumption at the level of one year, at different times of the day, weather conditions, seasons and working/non-working days. After dana collection, mathematical model based on infomation and lusing neural networks were made. Once learned model was implemented as a Python script on Rasberry Pi microcomputer and it is delivering predicted user behavior 36 hours in advance.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:700554
Study programmeTitle: Electrical Engineering and Information Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije (magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2023-01-13 12:23:17