Throughout the world, mobile phones are ubiquitous; there are now more mobile phones than people on the earth. These phones generate huge volumes of user-generated data in the form of Call Duration or Detail Records (CDRs). CDRs record the date, time and nearest mobile tower every time the phone communicates with the network. Using these CDRs we can build an understanding of an individual user's mobility pattern (travel motif) and certain 'stay regions' for the user can also be identified. By combining travel motifs for many individual users and including their stay regions, temporal patterns in a population’s mobility and distribution on an urban scale can be identified. To account for sparsity in the CDR data, the mobility patterns can be combined with high-resolution data sources such as building footprint data. In this way, this research will aim to create models that are accurate from the urban scale down to the block level.
Accurate modeling of mobility at this scale can be of huge benefit to creating a more intelligent lighting infrastructure, and can also identify areas for targeted introduction innovative lighting strategies to improve urban living standards and energy efficiency. The Grand Challenge project will incorporate CDRs from the Greater Boston region, though the analysis techniques will be applicable to other contexts as well. This 5-month research effort will result in an understanding of spatio-temporal population distribution by use (home, work, other), identification of lighting demand “hot” and “cold” spots, and smart lighting suggestions based on building occupancies.
This project is funded by Philips Lighting.