Published:
In this project, we developed novel measures of social and spatial entropy using large-scale pseudonymized CDRs in Sri Lanka by extending prior work. Currently exploring the results to derive possible migration and mobility behaviour related insights of an ego user.
Published:
Generated fictional privacy-preserving CDRs that maintain population-level behavioral characteristics of the original data set for sharing purposes.
Published:
Usage patterns in calling behaviour as well as movement patterns have been shown to correlate with socio-economic levels. In this project, we use Call Detail Records (CDRs) to derive proxy indicators on mobility, consumption and social behaviours of mobile phone subscribers at a large scale to investigate which indicators correlate most in a Sri Lankan regional context.
Published:
In this project, we use mobile network big data to model human movement patterns. Then using these human mobility models, we make use of other related data sources as well to develop machine learning models to predict dengue outbreaks for a spatial administrative district of Sri Lanka, 2 weeks ahead of time.