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#humanmobility

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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"

SpringerOpenBeyond boundaries: a location-based toolkit for quantifying group dynamics in diverse contexts - Cognitive Research: Principles and ImplicationsExisting toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group dynamics in large-scale, unbounded, or semi-constrained environments. Examples of such contexts include tourist groups, cycling teams, search and rescue teams, and military units. To address this issue, we survey existing methods and metrics for characterizing individual and collective movement in humans and animals. Using a rich GPS dataset from groups of military personnel engaged in a foot march, we develop a comprehensive, general-purpose toolkit for quantifying group dynamics using location-based metrics during goal-directed movement in open environments. This toolkit includes a repository of Python functions for extracting and analyzing movement data, integrating cognitive factors such as decision-making, situational awareness, and group coordination. By extending location-based analytics to non-traditional domains, this toolkit enhances the understanding of collective movement, group behavior, and emergent properties shaped by cognitive processes. To demonstrate its practical utility, we present a use case utilizing metrics derived from the foot march data to predict group performance during a subsequent strategic and tactical exercise, highlighting the influence of cognitive and decision-making behaviors on team effectiveness.

Our Call for Demo Track Papers is out now.

Topics of Interest include, but not limited to:
- #MachineLearning / #AI for Mobile Data
- Synthetic Mobility Data generation
- #HumanMobility Prediction
- Impact of AI on Human Mobility
- #IoT and Mobile Smartphone-based and Wearable Sensor Systems
- Data Management for Mobile #AR, #VR and #MixedReality Systems, #ConnectedCars, #AutonomousVehicles, #IntelligentTransportationSystems, and #SmartSpaces
...

mdm2024.github.io/callsDemo.ht

mdm2024.github.ioThe 25th IEEE International Conference on Mobile Data Management, IEEE MDM 2024, June 24 - June 27, 2024 (Brussels)

Interested in movement analysis? Join us at the Disruptive Movement Analysis (DMA’23) GIScience conference
workshop in Leeds, UK, on 12 Sept. Featuring short research & vision papers, student competition, data challenge and a special issue of @ijgis

More info:

Workshop CfP: somayehdodge.info/amd-giscienc

GIScience conference:
giscience2023.github.io/

#MovementAnalysis
#HumanMobility #MovementEcology
#GIScience #GPS #SpatialDataScience
#SpatialBehaviour
#GISchat

Somayeh DodgeDMA 2023By Somayeh Dodge