#mobilitydatascience — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #mobilitydatascience, aggregated by home.social.
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Do I have any followers here who used scikit-mobility's human mobility metrics?
Since #skmob isn't maintained anymore, we're considering porting the essential functionality to @movingpandas and would love to have more feedback, especially if it's first-hand experience with the functionality:
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Do I have any followers here who used scikit-mobility's human mobility metrics?
Since #skmob isn't maintained anymore, we're considering porting the essential functionality to @movingpandas and would love to have more feedback, especially if it's first-hand experience with the functionality:
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Do I have any followers here who used scikit-mobility's human mobility metrics?
Since #skmob isn't maintained anymore, we're considering porting the essential functionality to @movingpandas and would love to have more feedback, especially if it's first-hand experience with the functionality:
-
Do I have any followers here who used scikit-mobility's human mobility metrics?
Since #skmob isn't maintained anymore, we're considering porting the essential functionality to @movingpandas and would love to have more feedback, especially if it's first-hand experience with the functionality:
-
Do I have any followers here who used scikit-mobility's human mobility metrics?
Since #skmob isn't maintained anymore, we're considering porting the essential functionality to @movingpandas and would love to have more feedback, especially if it's first-hand experience with the functionality:
-
RE: https://mastodon.social/@xlth/116144192667591833
Not the ideal conditions for geospatial applications of VLMs 😅
#GIScience #VLM #spatiotemporal #MobilityDataScience #SpatialDataScience
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RE: https://mastodon.social/@xlth/116144192667591833
Not the ideal conditions for geospatial applications of VLMs 😅
#GIScience #VLM #spatiotemporal #MobilityDataScience #SpatialDataScience
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RE: https://mastodon.social/@xlth/116144192667591833
Not the ideal conditions for geospatial applications of VLMs 😅
#GIScience #VLM #spatiotemporal #MobilityDataScience #SpatialDataScience
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RE: https://mastodon.social/@xlth/116144192667591833
Not the ideal conditions for geospatial applications of VLMs 😅
#GIScience #VLM #spatiotemporal #MobilityDataScience #SpatialDataScience
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RE: https://mastodon.social/@xlth/116144192667591833
Not the ideal conditions for geospatial applications of VLMs 😅
#GIScience #VLM #spatiotemporal #MobilityDataScience #SpatialDataScience
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The #MobilityDB team just announced v1.3.0-alpha featuring
New temporal types:
🆕 tgeometry & tgeography that can represent the temporal evolution of any geometry type (polygon, multipoint, etc.)
🆕 temporal circular buffer (tcbuffer)
🆕 temporal pose (tpose) type, storing the evolution of a pose
(point position + orientation)and more ...
https://github.com/MobilityDB/MobilityDB/releases/tag/v1.3.0-alpha
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The #MobilityDB team just announced v1.3.0-alpha featuring
New temporal types:
🆕 tgeometry & tgeography that can represent the temporal evolution of any geometry type (polygon, multipoint, etc.)
🆕 temporal circular buffer (tcbuffer)
🆕 temporal pose (tpose) type, storing the evolution of a pose
(point position + orientation)and more ...
https://github.com/MobilityDB/MobilityDB/releases/tag/v1.3.0-alpha
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The #MobilityDB team just announced v1.3.0-alpha featuring
New temporal types:
🆕 tgeometry & tgeography that can represent the temporal evolution of any geometry type (polygon, multipoint, etc.)
🆕 temporal circular buffer (tcbuffer)
🆕 temporal pose (tpose) type, storing the evolution of a pose
(point position + orientation)and more ...
https://github.com/MobilityDB/MobilityDB/releases/tag/v1.3.0-alpha
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The #MobilityDB team just announced v1.3.0-alpha featuring
New temporal types:
🆕 tgeometry & tgeography that can represent the temporal evolution of any geometry type (polygon, multipoint, etc.)
🆕 temporal circular buffer (tcbuffer)
🆕 temporal pose (tpose) type, storing the evolution of a pose
(point position + orientation)and more ...
https://github.com/MobilityDB/MobilityDB/releases/tag/v1.3.0-alpha
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The #MobilityDB team just announced v1.3.0-alpha featuring
New temporal types:
🆕 tgeometry & tgeography that can represent the temporal evolution of any geometry type (polygon, multipoint, etc.)
🆕 temporal circular buffer (tcbuffer)
🆕 temporal pose (tpose) type, storing the evolution of a pose
(point position + orientation)and more ...
https://github.com/MobilityDB/MobilityDB/releases/tag/v1.3.0-alpha
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If you're at #AGIT2025, I'd love to see you at our #MobilityDataScience workshop focused on #PublicTransport tomorrow morning 🌄
09:00-10:15 Session 1A: WS: Mobility Data Science & KI – Potenziale für den öffentlichen Verkehr
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If you're at #AGIT2025, I'd love to see you at our #MobilityDataScience workshop focused on #PublicTransport tomorrow morning 🌄
09:00-10:15 Session 1A: WS: Mobility Data Science & KI – Potenziale für den öffentlichen Verkehr
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If you're at #AGIT2025, I'd love to see you at our #MobilityDataScience workshop focused on #PublicTransport tomorrow morning 🌄
09:00-10:15 Session 1A: WS: Mobility Data Science & KI – Potenziale für den öffentlichen Verkehr
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If you're at #AGIT2025, I'd love to see you at our #MobilityDataScience workshop focused on #PublicTransport tomorrow morning 🌄
09:00-10:15 Session 1A: WS: Mobility Data Science & KI – Potenziale für den öffentlichen Verkehr
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If you're at #AGIT2025, I'd love to see you at our #MobilityDataScience workshop focused on #PublicTransport tomorrow morning 🌄
09:00-10:15 Session 1A: WS: Mobility Data Science & KI – Potenziale für den öffentlichen Verkehr
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🤩 #MobilityDataAnalytics & #GIScience all around:
Attending the @emeraldseu GA today. Presented progress on #Trajectools and our #explainableAI & #activeLearning for #MobilityDataScience. While simultaneously traveling to #AGIT2025 🚄
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🤩 #MobilityDataAnalytics & #GIScience all around:
Attending the @emeraldseu GA today. Presented progress on #Trajectools and our #explainableAI & #activeLearning for #MobilityDataScience. While simultaneously traveling to #AGIT2025 🚄
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🤩 #MobilityDataAnalytics & #GIScience all around:
Attending the @emeraldseu GA today. Presented progress on #Trajectools and our #explainableAI & #activeLearning for #MobilityDataScience. While simultaneously traveling to #AGIT2025 🚄
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🤩 #MobilityDataAnalytics & #GIScience all around:
Attending the @emeraldseu GA today. Presented progress on #Trajectools and our #explainableAI & #activeLearning for #MobilityDataScience. While simultaneously traveling to #AGIT2025 🚄
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🤩 #MobilityDataAnalytics & #GIScience all around:
Attending the @emeraldseu GA today. Presented progress on #Trajectools and our #explainableAI & #activeLearning for #MobilityDataScience. While simultaneously traveling to #AGIT2025 🚄
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🎉 New @movingpandas 0.22 and #Trajectools 2.6 just landed
Over 50% runtime reduction for many #MovementDataAnalytics tasks 📉
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And here's @martinfleis et al.'s new street network generalization tool:
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Another interesting new paper on street network analysis, HT @gboeing
💯 it's surprisingly hard to count intersections
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Direct links for convenience ...
📄 Paper: https://www.mdpi.com/2071-1050/17/8/3634
:github: Code: https://github.com/plus-mobilitylab/netascore/tree/v0.9.0
#Walkability #HumanMobility #MobilityDataScience #GIScience #GISchat #OSM
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🥳 New versions of @movingpandas and #Trajectools have just landed:
🚢🚚🚲🦅 #MovingPandas 0.21.3 https://github.com/movingpandas/movingpandas/releases/tag/v0.21.3
:qgis: Trajectools 2.5 https://codeberg.org/movingpandas/trajectools/releases/tag/v2.5
🙏 Please update your MovingPandas install to get all the improvements in #QGIS Trajectools https://plugins.qgis.org/plugins/processing_trajectory/#plugin-versions
#GISChat #MovementDataAnalytics #MobilityDataScience #Python
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The quest for a fair TimeGPT benchmark
At the end of yesterday's #TimeGPT for mobility post, we concluded that TimeGPT's trainingset probably included a copy of the popular BikeNYC timeseries dataset and that, therefore, we were not looking at a fair comparison ...
http://anitagraser.com/2025/03/29/the-quest-for-a-fair-timegpt-benchmark/
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#TimeGPT for #mobility: Can foundation models outperform classic machine learning models for flow predictions?
tldr; Maybe. Preliminary results certainly are impressive.
#MobilityDataScience #gischat #urbanmobility #geoai #foundationmodels
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Only one more week to submit to ACM TSAS special issue on Urban Mobility https://dl.acm.org/pb-assets/static_journal_pages/tsas/pdf/TSAS_Special_Issue_Urban_Mobility-1737749682787.pdf
HT https://mastodon.social/@luis_de_sousa/113946946892555809
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Today I'm at #edbticdt2025 to present MobiML, our latest contribution to facilitate #MachineLearning from movement data, building on @movingpandas, #pymeos, and others
More details:
https://github.com/movingpandas/mobiml -
Today I'm at #edbticdt2025 to present MobiML, our latest contribution to facilitate #MachineLearning from movement data, building on @movingpandas, #pymeos, and others
More details:
https://github.com/movingpandas/mobiml -
Today I'm at #edbticdt2025 to present MobiML, our latest contribution to facilitate #MachineLearning from movement data, building on @movingpandas, #pymeos, and others
More details:
https://github.com/movingpandas/mobiml -
Today I'm at #edbticdt2025 to present MobiML, our latest contribution to facilitate #MachineLearning from movement data, building on @movingpandas, #pymeos, and others
More details:
https://github.com/movingpandas/mobiml -
Today I'm at #edbticdt2025 to present MobiML, our latest contribution to facilitate #MachineLearning from movement data, building on @movingpandas, #pymeos, and others
More details:
https://github.com/movingpandas/mobiml -
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).
https://doi.org/10.1186/s41235-025-00617-6"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
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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).
https://doi.org/10.1186/s41235-025-00617-6"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
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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).
https://doi.org/10.1186/s41235-025-00617-6"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
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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).
https://doi.org/10.1186/s41235-025-00617-6"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
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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).
https://doi.org/10.1186/s41235-025-00617-6"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
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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.
https://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:
#MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience
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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.
https://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:
#MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience
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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.
https://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:
#MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience
-
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.
https://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:
#MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience
-
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.
https://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:
#MovementDataAnalysis #MobilityDataAnalytics #MobilityDataScience
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The EMERALDS project @emeraldseu is hosting an MLOps webinar "EMERALDS Data Infrastructure and Development Frameworks” on 21 February, at 11:30 CET, see https://emeralds-horizon.eu/events/emeralds-webinar-data-infrastructure-and-development-frameworks
The talks explore the design and implementation of a dedicated #MLOps platform built with specialised #mobility libraries and tools. This platform is tailored to support ML engineers in the development and deployment of machine learning models for real-world applications
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#Moveapps is looking for a Technical Assistant (m/f/d) proficient in #RStats and/or #Python to improve their #MovementDataAnalytics plattform