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master's thesis
Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:363505
Marijanović, Ivana
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Marijanović, I. (2022). Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:363505

Marijanović, Ivana. "Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:363505

Marijanović, Ivana. "Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:363505

Marijanović, I. (2022). 'Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 22 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:363505

Marijanović I. Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 November 22] Available at: https://urn.nsk.hr/urn:nbn:hr:168:363505

I. Marijanović, "Upravljanje sustavima automatiziranog staklenika pomoću IoT uređaja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:363505

Metadata
TitleUpravljanje sustavima automatiziranog staklenika pomoću IoT uređaja
Title (english)Control of automated glasshouse systems by IoT Controller
AuthorIvana Marijanović
MentorNedjeljko Perić (mentor)
Committee memberNedjeljko Perić (član povjerenstva)
Committee memberVinko Lešić (član povjerenstva)
Committee memberMario Vašak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
U sklopu ovog rada objašnjena je predikcija temperature automatiziranog staklenika koristeći neuronsku mrežu. Korišten je LSTM model neuronske mreže. Učenje modela je provedeno na unaprijed dobivenom skupu podataka koji je sadržavao vanjske i unutarnje uvjete („AGROSparc_measurements“). Točnost predviđanja modela procjenjuje se srednjom apsolutnom pogreškom. Testiranjem mreže različitim vrijednostima hiperparametara dobiven je konačni model koji je, kao Python skripta, učitan na Raspberry Pi. To je udaljeno mikroračunalo koje putem senzora i aktuatora komunicira sa bazom podataka. Na kraju je prikazana sinteza upravljačkog algoritma sa estimiranom vrijednošću koju daje LSTM mreža, a validacija predloženog modela na stvarnom računalu je ostavljena za buduća istraživanja.
Abstract (english)
Within this paper, it's briefly explained how to predict the temperature of an automated greenhouse using a neural network. An LSTM neural network model was used. Model learning was performed on a pre obtained set of data that maintains external and internal conditions („AGROSparc_measurements“). The accuracy of model prediction is estimated by the mean absolute error. By testing a network of different hyperparameter values, a final model was obtained, which was loaded on the Raspberry Pi. It's a remote microcomputer that communicates with databases via sensors and actuators. Finally, the synthesis of the control algorithm with the estimated value given by the LSTM network is presented, and the validation model on a real computer is set for future research.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:363505
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 on2023-01-14 09:25:39