@inproceedings{f447b2d6c0d54e55b60934df2cefb799,
title = "Lessons learnt from designing indoor positioning system using 868 MHz radios and neural networks",
abstract = "This paper summarizes our approach and experimental evaluation of infrastructure-based Indoor Positioning System (IPS) designed to be used by First Responders. We are using 868 MHz single channel, power-efficient radio markers and RSSI (Receiver Signal Strength Indicator) fingerprinting. Artificial Neural Network translates vectors of RSSI constructed using mobile units into position. Special preprocessing needs to be applied to on-line signal to construct a vector for classification.",
author = "Micha{\l} Meina and Bartosz Celmer and Krzysztof Rykaczewski",
note = "Publisher Copyright: {\textcopyright} 2015, IEEE.; Federated Conference on Computer Science and Information Systems, FedCSIS 2015 ; Conference date: 13-09-2015 Through 16-09-2015",
year = "2015",
doi = "10.15439/2015F283",
language = "English",
series = "Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, FedCSIS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "101--107",
editor = "Marcin Paprzycki and Leszek Maciaszek and Maria Ganzha and Leszek Maciaszek",
booktitle = "Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, FedCSIS 2015",
}