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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Viani, F. Polo, A. Robol, F. Oliveri, G. Rocca, P. Massa, A. |
| Copyright Year | 2014 |
| Description | Author affiliation: ELEDIA Res. Center@DISI, Univ. of Trento, Trento, Italy (Viani, F.; Polo, A.; Robol, F.; Oliveri, G.; Rocca, P.; Massa, A.) |
| Abstract | In this paper, the real-time estimation of indoor occupancy has been evaluated starting from the processing of environmental parameters. The proposed system is based on a low cost and non-invasive wireless sensor network infrastructure for the distributed acquisition of simple quantities like temperature and humidity. The proposed algorithm has been structured in three successive phases of detection, filtering, and classification in order to face with the high variability and instability of such quantities. The problem of occupancy estimation has been recast as an inverse problem solved by means of a customized learning-by-example strategy (i.e., the classification phase). A measurement campaign in a museum area has been carried out and preliminary experimental results have been obtained in order to assess the potentialities and limitations of the proposed strategy. |
| Starting Page | 2127 |
| Ending Page | 2130 |
| File Size | 859917 |
| Page Count | 4 |
| File Format | |
| ISBN | 9788890701849 |
| DOI | 10.1109/EuCAP.2014.6902229 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-04-06 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | European Association on Antennas and Propagation |
| Subject Keyword | Temperature sensors Temperature measurement Wireless sensor networks Buildings Estimation Humidity Indoor occupancy wireless sensor network learning-by-example crowd detection |
| Content Type | Text |
| Resource Type | Article |
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