TY  - GEN
N1  - This version is a pre-print of the final version available at IEEE.
AV  - public
ID  - elediasc12519
A1  - Viani, Federico
A1  - Oliveri, Giacomo
A1  - Massa, Andrea
N2  - The increasing demand in homeland security speeds up the development of innovative and non-invasive systems to localize and track moving objects in complex environments. In this paper the real-time localization of transceiver-free targets is addressed by means of learning by example methodology that exploits the received signal strength indicator available at the nodes of a wireless sensor network as input data. This approach uses neither dedicated sensors nor active devices put on the target to localize both idle and moving objects. The definition of a customized classifier during an offline training procedure enables the real-time generation of a probability map of presence by processing the output of the support vector machine. Some selected experimental results validate the effectiveness of the proposed methodology applied in real scenarios.
UR  - http://www.eledia.org/students-reports/519/
Y1  - 2011/01//
TI  - Real-Time Tracking of Transceiver-Free Objects for Homeland Security
ER  -