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Understanding Urban Dynamics with Community Behaviour Modelling ! - - PowerPoint PPT Presentation
Understanding Urban Dynamics with Community Behaviour Modelling ! - - PowerPoint PPT Presentation
Understanding Urban Dynamics with Community Behaviour Modelling ! Future Communities Future Communities ! Afra Mashhadi ! Network Applications and Devices ! Understanding Urban Dynamics with Community Behaviour Modelling ! Infrastructural sensors
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Challenge! Results!
Can we leverage Transportation Data to understand the urban dynamics better, e.g., who, when, (and how often) go to a particular area and why?!
Citizen Behaviour Modelling with Transportation Data!
Impact!
Better Crowd Management, Improved Infrastructure Planning, Adaptive Transport Scheduling. ! Location Profiling Models with Different Ranking Algorithms for! "- Spatio-Temporal Travel Trajectory with Activity Inference.! "- Significant Place Detection (Home, Work, Favourite Dining etc.)! "- Citizen Behaviour Analysis : Diversity, Introversion, etc.! ! Given ONLY transportation data, our model can infer the profile of the location and the purpose of the travel.!
Dataset!
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Challenge! Dataset! Results!
Can we rely on the quality of the crowd-sourcing to deal with accuracy and coverage issues? !
Understanding Urban Crowd-sourcing!
Impact!
Enabling crowd-sourcing for practical and important problems with massive social impact. ! A model model that can predict the growth and accuracy of crowd-sourced information.! "- Accuracy is high and sometimes higher than proprietary data.! "- Coverage is low and non-uniformly distributed. ! "- Participation is highly affected by the cultural factors. " " " "! Given a set of users and profile of an area (e.g., population) we can predict the future crowd-sourcing participation in that area.!
Census!
6 6 YEARS OF CROWDSOURCING CONTRIBUTIONS! 35 35 COUNT OUNTRIES
OpenStreetMap!
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Challenge! Dataset! Results!
Can we leverage mobile communication meta data to understand a community better? Can we model their level of socio-economic?!
Understanding Socio-Economic Structure through Communication Patterns !
Impact!
Radical minimization of the cost and complexity of traditional methods (household surveys, Census)! A set of models that can infer the socio-economic level of areas in fine granularity ! "-Based on models from physics (gravity) and economy (diversity, introversion). " " " "! With meta communication data we can infer the state and change of socio-economic level
- f a community in fine granularity that was not possible before. !
Global-Pulse!
1 1 YEAR aggregated CDR data ! Ivor
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