Demo abstract: Histogram distance-based radio tomographic localization | Zendy

Yang Zhao | Zendy; Neal Patwari | Zendy

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Demo abstract: Histogram distance-based radio tomographic localization

Author(s) -

Yang Zhao,

Neal Patwari

Publication year - 2012

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1109/ipsn.2012.6920930

Subject(s) - histogram , computer science , tomographic reconstruction , computer vision , artificial intelligence , iterative reconstruction , image (mathematics)

We present an interactive demonstration of histogram distance-based radio tomographic imaging (HD-RTI), a device-free localization (DFL) system that uses measurements of received signal strength (RSS) on static links in a wireless network to estimate the locations of people who do not participate in the system by wearing any radio device in the deployment area. Compared to prior methods of RSS-based DFL, using a histogram difference metric is a very accurate method to quantify the change in RSS on the link compared to historical metrics. The new method is remarkably accurate, and works with lower node densities than prior methods.

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