Monday, October 18, 2010


Interesting use of context/presence data

MIT has done some interesting research that uses context data from mobile phones — location and usage patterns — to predict broader situations (in this case, illness):

Epidemiologists know that disease outbreaks change mobility patterns, but until now have been unable to track these patterns in any detail. So Madan and colleagues gave cellphones to 70 students in an undergraduate dormitory. The phones came with software that supplied the team with anonymous data on the students’ movements, phone calls and text messages. The students also completed daily surveys on their mental and physical health.

A characteristic signature of illness emerged from the data, which was gathered over a 10-week period in early 2009. Students who came down with a fever or full-blown flu tended to move around less and make fewer calls late at night and early in the morning. When Madan trained software to hunt for this signature in the cellphone data, a daily check correctly identified flu victims 90 per cent of the time.

The technique could be used to monitor the health status of individuals who live alone. Madan is developing a smartphone app that will alert a named contact, perhaps a relative or doctor, when a person’s communication and movement patterns suggest that they are ill.

Public health officials could also use the technique to spot emerging outbreaks of illness ahead of conventional detection systems, which today rely on reports from doctors and virus-testing labs. Similar experiments in larger groups and in different communities will have to be done first though.

This is very much related to work I’d been doing with context data several years ago, and which still interests me a lot. If we can get around the privacy concerns (which is a large part of what I’d been working on), we can synthesize a lot of useful meta-information from the devices that people use. That information can then be used to perform services on the user’s behalf, or do other helpful things.

Alas, the paper is behind a paywall, and I can’t find a loose copy around.

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