Arvutiteaduse instituut

Selle valdkonna püsiv URIhttps://hdl.handle.net/10062/14970

Sirvi

Sirvi Arvutiteaduse instituut Autor "Aasa, Anto, juhendaja" järgi

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  • Pisipilt
    Kirje
    Mobility Pattern Analysis using CDR: A Case Study of Estonian Public Holidays in January & February
    (Tartu Ülikool, 2023) Koldekivi, Laura Liisa; Sharma, Rajesh, juhendaja; Aasa, Anto, juhendaja; Goel, Rahul, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
    With the rise of globalization and the growth of urban populations, mobility patterns have become a key factor in shaping our cities and communities. This study explores people’s mobility patterns during public holidays in Estonia using Call Data Records (CDR) data. Specifically, the study investigates mobility patterns at three different location levels: top locations, home municipality, and home county. The CDR dataset used in this study contains approximately 56M records and 499K distinct callers during January and February of 2018. The results indicate a correlation between public holidays and mobility patterns at all three location levels. People are less likely to stay in their top locations on both holidays, particularly in densely populated urban cities of Estonia, such as Tallinn, Tartu, and Pärnu. Additionally, people tend to spend their holidays in another municipality, with Hiiumaa island residents exhibiting the highest mobility and Ida-Viru County showing the most significant difference in mobility between the two holidays. The study also found that on a county level, people are more likely to deviate from their usual routines on New Year’s Day than on Independence Day. Overall, the results suggest that New Year’s Day alters mobility patterns more than Independence Day and the average mobility. These results are beneficial for urban planning and resource allocation during the holidays.
  • Pisipilt
    Kirje
    Understanding Mobility Patterns through GPS Data
    (Tartu Ülikool, 2023) Semilarski, Emma Belinda; Goel, Rahul, juhendaja; Aasa, Anto, juhendaja; Sharma, Rajesh, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
    The Global Positioning System (GPS) has enabled to collect locational data from humans. One way to use GPS data is for exploring mobility patterns. The aim of this bachelor thesis is to unravel the mobility patterns and identify points of interest to gain more insight of spatiotemporal patterns of humans in Tartumaa. To achieve this, we use exploratory analysis techniques such as data preprocessing, visualisation, and statistical tests. Outcomes of this thesis describe the temporal and spatial patterns of people moving in Tartu and the surrounding area, and identify the most visited places from the data. The findings have the potential to contribute to the field of human mobility analysis and can be useful for city officials and policy makers in developing efficient urban planning strategies.