One of the simplest, most useful, and well executed applications on the iPhone is UrbanSpoon’s free restaurant finder. Open the application, it geolocates you, give the iPhone and shake and three Slot machine style selectors spin around and randomly choose a restaurant nearby. You can then even lock in specifics such as location, cuisine, or price range and shake to give more suggestions.
However, what’s particularly neat about the application is that UrbanSpoon has been recording these “shakes” by location (inherent in the API call obviously) and created a great visualization showing the locations around the US over a day of “shaking”.
The heatmap essentially shows the evolving enquiry of people looking for a place to eat. There isn’t an actual time display or timeline slider to investigate – but I imagine there are interesting trends during meals, and particularly after normal eating times when people don’t have a plans on where to eat. In addition, a timezone lag that would show shaking progressing east to west.
Context mining of mobile devices, combined with geographic location – and especially via inferred geographic information instead of directly volunteered information can yield interesting trends on ambient behaviors. Imagine if UrbanSpoon could also collect the number of people in the group by detecting other repeatedly seen nearby bluetooth/wifi devices, previous meals of the day, and the ultimate destination and distance to the chosen restaurant.