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Razvoj storitve za detekcijo prevoznega sredstva
ID ROBIČ, MATEVŽ (Author), ID Rupnik, Rok (Mentor) More about this mentor... This link opens in a new window

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Abstract
Današnje mobilne naprave z vgrajenimi senzorji in GPS sprejemniki nam omogočajo beleženje podatkov, s pomočjo katerih lahko izvemo veliko informacij o uporabniku. Cilj diplomske naloge je razviti mobilno aplikacijo oziroma storitev za detekcijo prevoznega sredstva uporabnika. Nabor izbranih prevoznih sredstev predstavljajo mestni avtobus, tramvaj in vlak. Za zajem podatkov smo uporabili merilnik pospeškov, giroskop in GPS sprejemnik mobilne naprave. S pomočjo zajetih podatkov, prosto dostopnih podatkov o geografski legi železniških objektov in različnih metod strojnega učenja smo razvili napovedni model. Metoda naključnih gozdov je s 97 % natančnostjo pokazala najboljši rezultat.

Language:Slovenian
Keywords:Android, aplikacija, detekcija, strojno učenje, prevozno sredstvo
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2023
PID:20.500.12556/RUL-144802 This link opens in a new window
COBISS.SI-ID:147555843 This link opens in a new window
Publication date in RUL:13.03.2023
Views:976
Downloads:119
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Secondary language

Language:English
Title:The Development for Transportation Mode Detection
Abstract:
Modern mobile devices with embedded sensors and GPS receivers allow us to collect all sorts of data, that we can use to gain information about users. The goal of this thesis is to develop a mobile app service for detecting user transportation mode. Our set of selected transportation modes consists of city bus, tram, and train. We used accelerometer, gyroscope, and GPS receiver for data collection. With the use of collected data, geographical railway data and different classification methods we developed a prediction model. Random forest performed best with 97 % accuracy.

Keywords:Android, application, detection, machine learning, transportation mode

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