*A clever sonic localization app for smartphones. Yet another potential AR registration hack. None of these schemes have even worked very well, which is why augments are still "floaties" instead of being nailed to reality with centimeter-scale Vernor Vingean accuracy.
*On the other hand, if you just keep piling up sensor data and then averaging out the differences... yeah, it's all about the post-production; "fix it in the cloud."
http://www.mccormick.northwestern.edu/news/articles/article_935.html
(...)
"The Batphone app records 10 seconds of noises that humans often ignore: vents, computers, lights, and appliances. The program then looks at how the sound energy is distributed over various frequencies, and after filtering out transient, short-lived sounds (like someone talking), it creates a sound fingerprint for the room. ((("Sound fingerprint"? weirdly synesthesic piece of jargon there.)))
"Tarzia has tagged rooms in his home and around McCormick’s Technological Institute and is currently refining the app so it works in hallways.
“It was an interesting research question because I thought it was going to fail,” he said. “I’m surprised by how accurate it is.” (((Oh really.)))
"Right now the app is just a proof-of-concept for the technique; in the future, it could help provide indoor navigation or help determine indoor locations for users of social applications..." (((yadda yadda. Okay, what happens in the sonic environments that your "BatPhone" knows best? Does it keep records and get better with time?)))
via @timoreilly, always the hearing-trumpet for the alpha geeks
http://slashdot.org/story/11/07/02/0539240/Researchers-Track-Cell-Phones-Indoors-By-Listening-In
(((More: "SurroundSense," or, syesthetically jamming together all the local sensor data your mobile can grab.)))
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.151.1620
(...)
"his paper argues that the increasing number of sensors on mobile phones presents new opportunities for logical localization. We postulate that ambient sound, light, and color in a place convey a photo-acoustic signature that can be sensed by the phone’s camera and microphone. In-built accelerometers in some phones may also be useful in inferring broad classes of user-motion, often dictated by the nature of the place. By combining these optical, acoustic, and motion attributes, it may be feasible to construct an identifiable fingerprint for logical localization. Hence, users in adjacent stores can be separated logically, even when their physical positions are extremely close. We propose SurroundSense, a mobile phone based system that explores logical localization via ambience fingerprinting. Evaluation results from 51 different stores show that SurroundSense can achieve an average accuracy of 87 % when all sensing modalities are employed. We believe this is an encouraging result..."
