---
title: "A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data"
authors:
  - "Sebastian Thrun"
  - "Geoffrey J. Gordon"
  - "Frank Pfenning"
  - "Mary Berna"
  - "Brennan Sellner"
  - "Brad Lisien"
doi: ""
url: "https://ijcai.org/proceedings/2003/224"
pdf: "https://ijcai.org/proceedings/2003/0224.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "1427-1427"
track: ""
keywords:
---

# A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data

Sebastian Thrun, Geoffrey J. Gordon, Frank Pfenning, Mary Berna, Brennan Sellner, Brad Lisien

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 1427-1427.

## Abstract

This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11 b network. Our approach uses data labeled by ground truth position to learn a probabi listic mapping from locations to wireless signals, represented by piecewise linear Gaussians. It then uses sequences of wireless signal data (without position labels) to acquire motion models of individual people, which further improves the localization accuracy. The approach has been implemented and evaluated in an office environment.