As physical space is increasingly suffused with digital technologies, data from communication networks allow us to better understand human behavior. New meaning can be revealed within these datasets, outlining characteristic usages and dynamic patterns at both the individual and collective scale.

The SENSEable City Lab and Ericsson have embarked on an unprecedented journey inside the telecommunications network – a dataset that traces across the planet. Our leading project aims at exploring the calls, SMS, data requests (initiated either by the users or background applications), and data traffic within major cities.

The project investigates questions such as:

• Can we find repeating dynamical patterns?
• How are these patterns affected by specific events?
• Can we differentiate specific spatial areas with their activity patterns?
• Which are the similarities and difference between major cities in different parts of the world?

As the partnership between Ericsson and MIT continues, our research will delve further into these questions, promoting a deeper understanding of how the pulses of cities around the world interact to shape a single signal: the signature of humanity.

Learn more in the press release.

ManyCities is an intuitive and robust tool for exploring mobile phone traffic and patterns, mapped onto urban space. The application can be implemented by a wide spectrum of users – from specialized to general. Many Cities allows mobile operators to easily check the completeness of their records, to detect repeating patterns or special events and to define new development strategies. For a more general audience, the tool’s visualization output can inform collective behaviors and offer the possibility to participate and influence global trends.

The application currently browses mobile phone traffic patterns in London, New York, Hong Kong and Los Angeles during a 10 month period going from April 2013 to January 2014. More specifically, the records consist in network level counter data that includes the numbers of calls, SMS and data requests, as well as the amount of data uploaded and downloaded by subscribers (measured in Bytes and denoted in the app by "UL Data" and "DL Data"). To simplify and streamline the user experience, all data has been aggregated on the administrative areas of the target cities, which are easily identifiable spatial units.

Help the community to discover patterns and unusual gaps or outliers in the graphs! The application allows you to annotate any selected subset of the data and share your thoughts, insights or hypothesis with all users. You can also share your experience on Twitter by publishing direct link to specific map configurations. Sign in with your favorite social network account to engage in the community!

S Grauwin, S Sobolevski, I Gódor , S Moritz, C Ratti (2014), Towards a Comparative Science of Cities: Mobile Traffic Records in New York, London and Hong Kong, in Computational Approaches for Urban Environments (Ed. Springer) [Download]

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