Utjecaj strojnog učenja u aplikaciji pesticida

Zorko, Luka

undergraduate thesis

Utjecaj strojnog učenja u aplikaciji pesticida

Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, 2023. urn:nbn:hr:151:849135

Zorko, Luka

Josip Juraj Strossmayer University of Osijek
Faculty of Agrobiotechnical Sciences Osijek
Department of Agricultural Engineering and Renewable Energy Resources

Institutional repository: Repository of the Faculty of Agrobiotechnical Sciences Osijek

Cite this document

APA 6th Edition

Zorko, L. (2023). Utjecaj strojnog učenja u aplikaciji pesticida (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:151:849135

MLA 8th Edition

Zorko, Luka. "Utjecaj strojnog učenja u aplikaciji pesticida." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:151:849135

Chicago 17th Edition

Harvard

Zorko, L. (2023). 'Utjecaj strojnog učenja u aplikaciji pesticida', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, accessed 12 January 2025, https://urn.nsk.hr/urn:nbn:hr:151:849135

Vancouver

Zorko L. Utjecaj strojnog učenja u aplikaciji pesticida [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek; 2023 [cited 2025 January 12] Available at: https://urn.nsk.hr/urn:nbn:hr:151:849135

IEEE

L. Zorko, "Utjecaj strojnog učenja u aplikaciji pesticida", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:151:849135

Cite this item: https://urn.nsk.hr/urn:nbn:hr:151:849135

Metadata

Title	Utjecaj strojnog učenja u aplikaciji pesticida
Title (english)	Impact of machine learning in pesticide application
Author	Luka Zorko
Mentor	Domagoj Zimmer (mentor)
Committee member	Luka Šumanovac (predsjednik povjerenstva)
Committee member	Tomislav Jurić (član povjerenstva)
Granter	Josip Juraj Strossmayer University of Osijek Faculty of Agrobiotechnical Sciences Osijek (Department of Agricultural Engineering and Renewable Energy Resources) Osijek
Defense date and country	2023-11-24, Croatia
Scientific / art field, discipline and subdiscipline	BIOTECHNICAL SCIENCES Agronomy Agricultural Engineering and Technology
Abstract	Umjetna inteligencija područje je koje se danas primjenjuje u različitim sektorima među kojima je upravo i poljoprivreda. Tumači se kako umjetna inteligencija, odnosno strojno učenje, mogu revolucionirati poljoprivredu koja utječe na gospodarstvo zemlje, izravno ili neizravno zapošljavajući više od 30 % svjetskog stanovništva. Automatizacijom se na taj način mogu zadovoljiti potrebe sve većeg svjetskog stanovništva. Gledajući tradicionalne prakse na području poljoprivrede kao što su primjerice kultivacija, prskanje pesticidima, praćenje statusa hranjivih tvari i drugo, navedene se mogu značajno brže izvesti putem korištenja umjetne inteligencije i strojnog učenja. Zahvaljujući navedenom dolazi do osiguranja smanjenja rasipanja vode, prekomjerne uporabe pesticida, pomoći u smanjenju rada, ali ujedno dolazi do povećanja plodnosti tla, a samim time i usjeva. Primjena umjetne inteligencije i strojnog učenja u poljoprivredi je još u razvoju zbog nedostatnosti stručnosti i zahtjeva za točnost velikih podataka. Ono što je za očekivati je kako će područje strojnog učenja i uporabe umjetne inteligencije u poljoprivredi u budućnosti i dalje rasti. Cilj ovog rada je konkretno usmjeren na utjecaj strojnog učenja pri aplikaciji pesticida.
Abstract (english)	Artificial intelligence is a field that is applied today in various sectors, one of which is agriculture. It is interpreted as how artificial intelligence, or machine learning, can revolutionize agriculture, which affects the country's economy, directly or indirectly employing more than 30 % of the world's population. Automation can thus meet the needs of the ever-increasing world population. Looking at traditional practices in the field of agriculture such as weeding, spraying with pesticides, monitoring the status of nutrients and others, the above can be performed significantly faster through the use of artificial intelligence and machine learning. Thanks to the above, there is a reduction in water wastage, excessive use of pesticides, help in reducing work, but at the same time there is an increase in the fertility of the soil, and thus the crops. The application of artificial intelligence and machine learning in agriculture is still in development due to the lack of expertise and requirements for the accuracy of big data. What can be expected is that the field of machine learning and the use of artificial intelligence in agriculture will continue to grow in the future. The goal of this paper is specifically focused on the influence of machine learning in the application of pesticides.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:151:849135
Study programme	Title: Agriculture; specializations in: Agroeconomics, Plant production, Mechanization, Zootechnique, Horticulture Course: Mechanization Study programme type: university Study level: undergraduate Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka agronomije (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka agronomije)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Public note	završni rad
Created on	2024-03-12 07:52:14

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