Towards people indoor localization combining wifi and human motion recognition

Alonso, José María; Alvarez, A.; Trivino, G.; Hernández, Noelia; Herranz, Fernando; Ocaña, Manuel
Year: 2010
Type of Publication: In Proceedings
Book title: XV Spanish conference for Fuzzy Logic and Technology (ESTYLF)
Pages: 7-12
Address: Huelva
ISBN: 978-84-92944-02-6
This work presents a general framework for people indoor localization. Firstly, a WiFi localization system implemented as a fuzzy rule-based classifier (FRBC) is used to deal with the intrinsic uncertainty of such envi- ronments. It consists of a set of linguistic variables and rules automatically generated from experimental data. As a result, it yields an approximate position at the level of discrete zones (room, corridor, toilet, etc). Secondly, a Fuzzy Finite State Machine (FFSM) mainly based on expert knowledge is used for human motion (activity, body posture and step length) recognition. The goal is find- ing out whether people is (or not) moving, in which direction, at which pace, etc. Finally, another FFSM combines bothWiFi localiza- tion and human motion recognition with the aim of obtaining a robust, reliable, and eas- ily understandable human-oriented localiza- tion system.
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