In my latest article for TheFeature, I interview Nathan Eagle, a researcher at MIT's Media Lab who has collected approximately 40 years of continuous data on human behavior by capturing communication, proximity, location and activity information from 100 cell phone-wielding subjects at his school. Now he's building applications that take advantage of "reality mining."
TheFeature: How does your application Serendipity leverage Reality Mining data?
Eagle: We're uncovering affiliations between people. I have a similarity metric based on distance in behavior states. The end idea is that the software would notice, say, that you typically hang out at the B-Side Lounge on Friday nights. So do I and perhaps you also do other behaviors similar to me. Those things in common may mean that we would want to be introduced. That's one method of matchmaking. Another is based on proximity. The Bluetooth addresses of those people running our client get pushed to our server. Then we do a comparison based on their profiles.
TheFeature: It sounds like Friendster for the physical world?
Eagle: That's the general idea. But Serendipity is based not just on explicit user profiles (that you enter) but also implicit behavioral information.