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Scalable architecture for availability prediction of BicikeLj stations

Klemen Koželj (2017) Scalable architecture for availability prediction of BicikeLj stations. EngD thesis.

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    Recently, we are witnessing a true digital revolution in every sector of the industry, which is involved in mobility and transportation. As an example, we can expose American start-up Uber, which has drastically digitalized mobility in the recent years. Their business strategy is data driven; with the data mining methodologies they are trying to answer a question "From and where people will travel?", and for that they use their services. The better they can predict the movement of people through the area, the more successful and optimised their actions on the market are. In this bachelor thesis, first we will collect the data of movement of people through the city of Ljubljana, then we will form horizontally scalable system, which will enable us persistent storage and processing of the collected data. The most suitable system for this kind of project is bike sharing system located in Ljubljana, which operates under the brand BicikeLj. The question, on which we will try to answer, is how empty or full BicikeLj stations will be in a certain time in the future, and how precisely we can predict that based on the previous data.

    Item Type: Thesis (EngD thesis)
    Keywords: apache hadoop, apache spark, data mining
    Number of Pages: 90
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    viš. pred. dr. Aleksander Sadikov934Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537391811)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 3828
    Date Deposited: 16 Mar 2017 14:56
    Last Modified: 27 Mar 2017 09:29
    URI: http://eprints.fri.uni-lj.si/id/eprint/3828

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