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master's thesis
Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje
Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2021. urn:nbn:hr:179:265842
Topić, Karlo
University of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Department of Electronics and Computing

Cite this document

Topić, K. (2021). Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje (Master's thesis). Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:179:265842

Topić, Karlo. "Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje." Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2021. https://urn.nsk.hr/urn:nbn:hr:179:265842

Topić, Karlo. "Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje." Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2021. https://urn.nsk.hr/urn:nbn:hr:179:265842

Topić, K. (2021). 'Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje', Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, accessed 23 April 2024, https://urn.nsk.hr/urn:nbn:hr:179:265842

Topić K. Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje [Master's thesis]. Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture; 2021 [cited 2024 April 23] Available at: https://urn.nsk.hr/urn:nbn:hr:179:265842

K. Topić, "Komponenta za podršku odlučivanju u sustavu za potragu i spašavanje", Master's thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:179:265842

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Metadata
TitleKomponenta za podršku odlučivanju u sustavu za potragu i spašavanje
Title (english)Search and rescue decision support component
AuthorKarlo Topić
MentorLjiljana Šerić (mentor)
GranterUniversity of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
(Department of Electronics and Computing)
Split
Defense date and country2021-09-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema ovog diplomskog rada je izrada aplikacije koja asistira pripadnike Gorske službe spašavanja prilikom potrage za nestalom osobom. U trenutku dojave nestanka osobe, spasitelj preko grafičkog sučelja odabire točku nestanka, a kao rezultat aplikacije jest vjerojatnost pronalaska osobe na pojedinom području. Aplikacija za predviđanje koristi model temljen na strojnom učenju, a koji je treniran na podacima prikupljenim od strane Gorske službe spašavanja. Korišteni podaci prikupljeni su prilikom akcija spašavanja nestalih osoba te ih je naknadno trebalo filtrirati i obraditi. Nakon uspješne obrade podataka, sljedeći korak je bio treniranje modela u Python programskom jeziku pomoću scikit-learn paketa koji temeljem parametara predviđa brzinu kretanja na segmentu terena te procjenjuje najveću daljenost koju osoba može preći u unaprijed zadano vrijeme. Kompletan model implementiran je kao dodatak u programskom okruženju QGIS jednostavan za korištenje.
Abstract (english)
The topic of this work is the development of an application that assists members of the Mountain Rescue Service in the search for a missing person. At the moment of reporting the disappearance of a person, rescuer selects the point of disappearance via the graphical interface, and the result of the application is the probability of finding the person in a particular area. The application for prediction uses a machine learning based model which is trained on data collected by the Mountain Rescue Service. Data was collected during the rescue operations of missing persons and had to be subsequently filtered and processed. After successful data processing, the next step was to train the model in the Python programming language using the scikit-learn package, which predicts the movement speed on a segment of the terrain based on the parameters and estimates the maximum distance a person can cover in a predetermined time. The model is implemented as an add-in in the easy-to-use QGIS programming environment.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:179:265842
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to authenticated users
Terms of useLicence In copyright icon
RepositoryRepository of the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Created on2021-12-01 11:53:50