Publication Date:
2013
abstract:
In this paper, we present a WiSARD-based system facing the problem of Indoor Positioning (IP) by taking advantage of pervasively available infrastructures (WiFi Access Points - AP). The goal is to develop a system to be used to position users in indoor environments, such as: museums, malls, factories, offshore platforms etc. Based on the fingerprint approach, we show how the proposed weightless neural system provides very good results in terms of performance and positioning resolution. Both the approach to the problem and the system will be presented through two correlated experiments.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Indoor positioning; weightless neural systems
List of contributors:
DE GREGORIO, Massimo; Giordano, Maurizio
Book title:
21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning