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#mobilitydataanalytics — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #mobilitydataanalytics, aggregated by home.social.

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  1. If you are at on Thursday and fancy some , come and join our final @emeraldseu event.

    I'll be talking about for and a similarly awesome @carto collaboration

  2. If you are at #EBDVF on Thursday and fancy some #MobilityDataAnalytics, come and join our final @emeraldseu event.

    I'll be talking about #Trajectools for #QGIS and a similarly awesome @carto collaboration

  3. Even more human research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

  4. Even more human #MovementBehavior research:

    Elkin-Frankston et al. (2025). Beyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts. Cogn. Research 10, 10 (2025).
    doi.org/10.1186/s41235-025-006

    "We first segmented time periods when the group was in motion by identifying break periods using the stop detection feature from the MovingPandas Python package"

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience #HumanMobility

  5. New research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

  6. New #IOT research using yours truely:

    Koszewski et al. (2025). Utilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space Design.
    doi.org/10.3390/s25051393

    "Trajectories were processed by the MovingPandas Python library, which offers several valuable processing algorithms"

    For the full list of publications we're aware of, check out:

    github.com/movingpandas/moving

    #MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience

  7. Today, we've had our first successful mini workshop with colleagues from the EMERALDS project, working on

    If everything goes to plan, Trajectools will be at
    @mdm

    There are still a few days left to submit your own work and join us: mdm2024.github.io/calls.html