  Cell phone technology generates massive amounts of data. Although this data
has been gathered for billing and logging purposes, today it has a much higher
value, because its volume makes it very useful for big data analyses. In this
project, we analyze the viability of using cell phone records to lower the cost
of urban and transportation planning, in particular, to find out how people
travel in a specific city (in this case, Buenos Aires, in Argentina). We use
anonymized cell phone data to estimate the distribution of the population in
the city using different periods of time. We compare those results with
traditional methods (urban polling) using data from Buenos Aires
origin-destination surveys. Traditional polling methods have a much smaller
sample, in the order of tens of thousands (or even less for smaller cities), to
maintain reasonable costs. Furthermore, these studies are performed at most
once per decade, in the best cases, in Argentina and many other countries. Our
objective is to prove that new methods based on cell phone data are reliable,
and can be used indirectly to keep a real-time track of the flow of people
among different parts of a city. We also go further to explore new
possibilities opened by these methods.
