Sense Networks, a company cofounded by Sandy Pentland, a professor of computer science at MIT, also tracks population density in cities. It offers this data to companies through an application called MacroSense. An application offered by the company, called CitySense, shows data similar to that offered by SpotRank, but only for the city of San Francisco. This summer, Sense Networks also plans to offer developers an API. Sense Networks says its offering will be even more detailed, and will combine demographic data with geospatial tracking data.
A few developers are beginning to explore the potential applications of the kind of location data provided by SpotRank. Utkarsh Shrivastava, a master’s student in information security at the Georgia Institute of Technology, has combined SpotRank data with Yahoo’s database of companies to create a search tool that ranks local businesses according to how busy they are at any time. “It could also expand to a route based model,” says Shrivastava. This would allow users to choose the least-crowded means of transport between two points–an application feature that has already been implemented on roadways by some GPS devices.
Joe Stump, cofounder of SimpleGEO, says developers are working on a wide array of ideas based on using SpotRank’s data. “There are lots of ideas around potential variable pricing for advertising,” he says. The data could also be used to make location-based social networks like FourSquare more interesting and useful, Stump says.
The next step, say developers working with SpotRank, is real-time data. This would let them check the “social weather” in a town to determine, say, if there’s a particularly popular event going on.
“You could see where activity is almost in real time and overlay geo-tagged images and tweets and watch as it happens,” says Skyhook’s Morgan. “We’re also building out a social compass, which looks like a regular compass, but it can direct you based on the volume of activity [in an area].”
However, even SpotRank’s existing offering, which is strictly historical data, is useful because people are predictable. “We see that in our data, which is 24 months worth of history, we can tell you with 90 percent confidence what will happen at 2:15 on a Tuesday,” says Morgan. “Ninety-nine percent of the time we know what will happen on any given spot. We can do that for almost every street corner in the world right now.”