Washington, Sep 25 (ANI): The next time you go shopping, your smart phone will not only tell that you have entered the mall, but also know if you are in the jewellery store or the shoe store, thanks to a new system developed by Duke University computer engineers led by an Indian-origin professor.
Making use of standard cell phone features - accelerometers, cameras and microphones - students of Romit Roy Choudhury have successfully turned the unique properties of a particular space into a distinct fingerprint.
While standard global positioning systems (GPS) are only accurate to 10 meters (32 feet) and do not work indoors, the new application is designed to work indoors and can precisely tell whether a user is on one side of an interior wall or another.
Called SurroundSense, the system uses the phone's built-in camera and microphone to record sound, light and colours, while the accelerometer records movement patterns of the phone's user.
This information is sent to a server, which knits the disparate information together into a single fingerprint.
"You can't tell much from any of the measurements individually, but when combined, the optical, acoustic and motion information creates a unique fingerprint of the space," said Ionut Constandache, graduate student in computer science.
For example, in a bar, people spend little time moving and most time sitting, while the room is typically dark and noisy. On the other hand, a Target store will be brightly lit with vibrant colours - especially red - with movement up and down aisles.
SurroundSense can tell these differences.
Choudhury's students fanned out across Durham, N.C. with their cell phones, collecting data in different types of businesses.
The students "mirrored" the actions of selected customers so that they would not bias the measurements.
"We went to 51 different stores and found that SurroundSense achieved an average accuracy of about 87 percent when all of the sensing capabilities were used," said Constandache.
As more people use the application, it gets "smarter."
"As the system collects and analyzes more and more information about a particular site, the fingerprint becomes that much more precise. Not only is the ambience different at different locations, but also can be different at different times at the same location," said Choudhury.
SurroundSense collects data at different time points, which makes it possible to distinguish a Starbucks store at the morning rush when there are many customers from the slower period in mid-afternoon.
"We believe that SurroundSense is an early step toward a long-standing challenge of improving indoor localization," said Choudhury.
The details of SurroundSense will be presented at the 15th International Conference on Mobile Computing and Networking in Bejing. (ANI)