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Smartphone Applications Developed to Collect Mobility Data: A Review and SWOT Analysis

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Intelligent Systems and Applications (IntelliSys 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1251))

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Abstract

Travel surveys and other traditional methods have been used for collecting mobility data since 1930s. Those surveys have been so far the most reliable approaches to understand people mobility patterns, but their high costs do not allow a high frequency collection to obtain continuously updated data. To overcome these limitations, digitalization opens the gate for renewed travel data collection and analysis methods. To this extent, this paper aims to present a review of the various smartphone applications, classifying them according to three different purposes: 1) Travel Data Collection and Analysis; 2) Travel Surveys; and 3) Promotion of Sustainable Mobility. 81 apps were retrieved and analysed in detail and evaluated according to their features and the methods used for data collection. A subsequent SWOT analysis has then been performed to understand the strengths, weaknesses, opportunities and threats of using the smartphone applications to understand mobility patterns. Finally, recommendations for future research are put forward.

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Authors and Affiliations

  1. Politecnico di Torino, DIST, Turin, Italy

    Cristina Pronello & Pinky Kumawat

  2. Sorbonne Universités – UTC. AVENUES, Compiègne, France

    Cristina Pronello

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  1. Cristina Pronello
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  2. Pinky Kumawat
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Correspondence to Cristina Pronello .

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Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Pronello, C., Kumawat, P. (2021). Smartphone Applications Developed to Collect Mobility Data: A Review and SWOT Analysis. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1251. Springer, Cham. https://doi.org/10.1007/978-3-030-55187-2_35

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