Mobile phones, location and indexing the real world
Mobile phones are rapidly becoming powerful data acquisition devices, as described e. g. in recent (and good) articles in The Economist and Nature. Many phones have cameras, GPS systems and net connections, and some of them sport accelerometers, which can be used to measure the amount of calories burnt by the user, or even to track earthquakes.
A number of enterprising researchers have started to mine the location data that can be obtained from mobile phones (through information from mobile towers routing the communication). Last year, the complex-networks guru Albert-László Barabási and co-workers published a paper, Understanding individual human mobility patterns, where they studied movement trajectories of 100.000 (anonymized) mobile phone users. The result reported by the authors – that human movement is not random but shows high spatial and temporal regularity – was perhaps not as impressive as the sheer size of the data set.
For those who would like to try their hand at analyzing mobile phone data, MIT’s Reality Mining project provides an interesting and freely accessible data set. In this project, students carried (Nokia) phones and their trajectories were tracked. The subjects also answered various questions about themselves and their habits. The data gathered for the Reality Mining project included location information (again, through mobile towers), communication data (call records) and proximity data (using Bluetooth).
The researchers behind the project developed algorithm for extracting routine everyday patterns from user’s lives and claim they can predict their subjects’ next actions to a fairly good approximation.
The Economist article linked above quotes one of the MIT researchers, Alex Pentland, as saying that “… some handsets can capture information about individuals, such as their activity levels or even their gait, using built-in motion sensors.” This suggested to me that it might be possible to detect changes in gross motor patterns in an individual, such as those that have been shown to sometimes occur in depressed patients. Thus, a smart phone could be an “early warning system” for depression.
The Reality Mining group has spawned off a company, Sense Networks, that aims to bring location-based data to the commercial sphere in a big way. Their slogan is “Indexing the real world using location data for predictive analytics.”
Indexing the real world! Now that would be something.
Currently, Sense Networks offers a service, CitySense, for finding out where the action is in a city. I quote from the web site:
Citysense passively “senses” the most popular places based on actual real-time activity and displays a live heat map. The application intelligently leverages the inherent wisdom of crowds without any change in existing user behavior, in order to navigate people to the hottest spots in a city. […]
The application learns about where each user likes to spend time – and it processes the movements of other users with similar patterns. In its next release, Citysense will not only answer “where is everyone right now” but “where is everyone like me right now.” Four friends at dinner discussing where to go next will see four different live maps of hotspots and unexpected activity. Even if they’re having dinner in a city they’ve never visited before.