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SenseWeb: Real Time Map of the World

Researchers at Microsoft are working on technology that they hope will someday enable people to browse online maps for up-to-the-minute information about local gas prices, traffic flows, restaurant wait times, and more.

By tracking real-life conditions, which are supplied directly by people or automated sensor equipment, and correlating that data with a searchable map, people could have a better idea of the activities going on in their local areas and make more informed decisions about, for instance, what driving route to take, says Suman Nath, a Microsoft researcher who works on the project, which is called SenseWeb.

“The value that you get out of [real-time data mapping] is huge,” he says, and the applications can range from finding a parking spot in a cavernous parking garage to checking the traffic flow in different parts of a city.

SenseWeb is composed of three basic parts:

  • sensors (or data-collecting units),
  • Microsoft’s database indexing scheme that sorts through the information,
  • and the online map that lets users interact with the data.

The sensors used in the project can vary in form and function, and can include thermometers, light sensors, cameras, and restaurant computers. SenseWeb puts baseline sensor information, such as location and function, into a database that’s searchable by location and type of sensor information. Then, if someone wants to check traffic conditions along a stretch of highway, for instance, the database will direct queries to cameras (“Web cams”) located along the route — and an image of traffic shows up on the map.

What makes Microsoft’s experimental project different from others that track information, Nath says, is that it would allow people to search for different types of real-time data within a user-specified area on a map, and progressively narrow that search. For instance, a person could highlight a region of a city and search for restaurants. SenseWeb would gather information provided by restaurants about their wait times and display it in various ways: the wait at specific establishments, the average wait for all restaurants in the region, or the minimum and maximum waits. If you needed to find a place to eat quickly, says Nath, but you learn that the minimum wait is 30 minutes in a certain part of town, you’d know to look in a different area. “You don’t have to take the time to look at each individual restaurant,” Nath says.

Additionally, a person could zoom into an area and see newly calculated information, such as maximum, minimum, and average wait times, according to the newly defined geography.

Searching for these types of real-time statistics within different areas on a map is a new take on displaying data on maps, says Phillip Levis, professor of computer science at Stanford University. “It’s very different to give the average wait time in the city than it is to scan around the city and see each restaurant’s wait time,” he says.