Transportation mode detection based on mobile sensor data

Urbančič, Jasna (author), Pejović, Veljko (mentor), Mladenić, Dunja (co-mentor)

This thesis addresses transportation mode detection based primarily on mobile phone data using machine learning methods. Our approach uses short samples of accelerometer readings taken while traveling in a vehicle to distinguish between three modalities --- car, bus, and train. We use gravity estimation to pre-process the samples. We extract features from statistical, frequency-based, and peak-based domain. With statistical analysis of the features we gain an introspective into the data. To additionally analyze the features we construct several feature sets for classification. As a classifier we use random forest, support vector machine, and neural network. Our approach correctly classifies 65% cars, 63% buses, and 18% trains using neural network.

• Language: English
• Keywords: machine learning, mobile sensing, data mining, pattern recognition, intelligent transportation systems
• Work type: Master's thesis/paper
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2018
• PID: 20.500.12556/RUL-106015
• Publication date in RUL: 14.01.2019

Secondary language

• Language: Slovenian
• Title: Detekcija prevoznega sredstva z mobilnimi senzorji

Abstract

V delu obravnavamo detekcijo prevoznega sredstva z mobilnimi senzorji in metodami strojnega učenja. Pri tem uporabljamo kratke vzorce podatkov iz pospeškometra, ki jih zajamemo med uporabnikovim potovanjem v vozilu. Razločujemo med tremi prevoznimi sredstvi --- avtom, avtobusom in vlakom. Vzorce predobdelamo tako, da iz pospeškov izločimo gravitacijsko komponento. Iz vzorcev izločimo statistične in frekvenčne značilke ter značilke vrhov. S statistično analizo značilk dobimo vpogled v podatke. Dodatno analiziramo značilke preko različnih množic značilk, ki jih uporabljamo za klasifikacijo. Kot klasifikatorje uporabljamo naključne gozdove, metodo podpornih vektorjev in nevronske mreže. Z uporabo nevronskih mrež smo pravilno razpoznali 65% avtomobilov, 63% avtobusov in 18% vlakov.

• Keywords: strojno učenje, mobilno zaznavanje, podatkovno rudarjenje, razpoznava vzorcev, inteligentni transportni sistemi