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#movementdataanalysis

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MovingPandas

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

MDPIUtilizing IoT Sensors and Spatial Data Mining for Analysis of Urban Space Actors’ Behavior in University Campus Space DesignThis paper discusses the use of IoT sensor networks and spatial data mining methods to support the design process in the revitalization of the university campus of the Warsaw University of Technology (WUT) in the spirit of universal design. The aim of the research was to develop a methodology for the use of IoT and edge computing for the acquisition of spatial knowledge based on spatial big data, as well as for the development of an open (geo)information society that shares the responsibility for the process of shaping the spaces of smart cities. The purpose of the article is to verify the hypothesis on whether it is possible to obtain spatial–temporal quantitative data that are useful in the process of designing the space of a university campus using low-cost Internet of Things sensors, i.e., already existing networks of CCTV cameras supported by simple installed beam-crossing sensors. The methodological approach proposed in the article combines two main areas—the use of IT technologies (IoT, big data, spatial data mining) and data-driven design based on analysis of urban space actors’ behavior for participatory revitalization of a university campus. The research method applied involves placing a network of locally communicating heterogeneous IoT sensors in the space of a campus. These sensors collect data on the behavior of urban space actors: people and vehicles. The data collected and the knowledge gained from its analysis are used to discuss the shape of the campus space. The testbed of the developed methodology was the central campus of the WUT (Warsaw University of Technology), which made it possible to analyze the time-varying use of the selected campus spaces and to identify the premises for the revitalization project in accordance with contemporary trends in the design of the space of HEIs (higher education institutions), as well as the needs of the academic community and the residents of the capital. The results are used not only to optimize the process of redesigning the WUT campus, but also to support the process of discussion and activation of the community in the development of deliberative democracy and participatory shaping of space in general.
#MovementDataAnalysis#MobilityDataAnalytics#MobilityDataScience
MovingPandas

New #bicycle 🚲 research #preprint using yours truly:

Skåntorp et al. (2024). Data-driven bicycle driving cycles via mixed-integer programming

"we utilized the #KalmanFilter from the #MovingPandas library"

dx.doi.org/10.13140/RG.2.2.199

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

github.com/movingpandas/moving

#MixedIntegerProgramming#MovementDataAnalysis#MobilityDataAnalytics
MovingPandas

Cool to see more users from #MovementEcology 🐮 😎

Gu, C., Liu, L., Zhang, Y. et al. Understanding the spatial heterogeneity of #Grazing pressure in the Three-River-Source Region on the #TibetanPlateau. J. Geogr. Sci. 33, 1660–1680 (2023). doi.org/10.1007/s11442-023-214

"The #GPScollar’s velocity transducer collected the moving speed information, and we used #MovingPandas (...) a #Python package for #MovementDataAnalysis, to obtain the daily #MovingDistance and #HomeRange

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