Crowd-sensing Census

As increasingly more people seek to live in urban cities, governments and other organizations face the challenge of effectively identifying areas in most need of revitalization and intervention.

One way of designing such interventions is by using “poverty maps”.

Poverty maps are designed to simultaneously display the spatial distribution of welfare and different dimensions of poverty determinants. The plotting of such information on maps however heavily relies on data that is collected through infrequent national household surveys and censuses. However, due to the high cost associated with this type of data collection process, poverty maps are often inaccurate in capturing the current deprivation status.

In this project, we address this challenge by means of a methodology that relies on alternative data sources from which to derive up-to-date poverty indicators, at a very fine level of spatial granularity. We validate our methodology for the city of Milano. Based on our methodology and design requirements gathered from stakeholders we design and implement a poverty mapping tool for policy makers.