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      Dataset for multimodal transport analytics of smartphone users - Collecty

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          Abstract

          Urban mobility is facing many challenges, such as energy consumption, pollution, and safety. Therefore, it is necessary to analyze the mobility of users through the transportation network using data containing information regarding the used transport mode. This data article describes a dataset from mobile devices collected by users as they move through the transportation network. Each sample in this dataset is labelled with a corresponding transport mode. Eight transport modes are present in the dataset: Car, Bus, Walking, Bicycle, Train, Tram, Running and Electric Scooter. The basic breakdown of the raw data according to users, transport modes and multimodal routes is presented. During data collection, data from the accelerometer, magnetometer, and gyroscope sensors mounted within the mobile device were stored. The data were collected using a mobile application from mobile devices with an embedded Android operating system. The structure of the text files in which the data were stored and the structure of the application used to collect the data are presented in the paper. The collected data provides a highly relevant basis for mobility analysis and planning, analysis of road conditions, clustering of user behaviour, and comparison of transport mode classification methods.

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          The University of Sussex-Huawei Locomotion and Transportation Dataset for Multimodal Analytics With Mobile Devices

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            Author and article information

            Contributors
            Journal
            Data Brief
            Data Brief
            Data in Brief
            Elsevier
            2352-3409
            06 August 2023
            October 2023
            06 August 2023
            : 50
            : 109481
            Affiliations
            [0001]University of Zagreb, Faculty of Transport and Traffic Sciences, Department of Intelligent Transportation Systems, Vukelićeva 4, 10000 Zagreb Croatia
            Author notes
            [* ]Corresponding author. merdelic@ 123456fpz.unizg.hr
            Article
            S2352-3409(23)00581-4 109481
            10.1016/j.dib.2023.109481
            10425662
            a6db0255-a4f9-4620-9ba5-db61285f2c6e
            © 2023 The Author(s)

            This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

            History
            : 29 March 2023
            : 14 July 2023
            : 2 August 2023
            Categories
            Data Article

            transport dataset,user trajectories,urban mobility analysis,transport mode classification,smartphone sensor data,android application

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