Conformal Prediction for Indoor Localisation with Fingerprinting Method

Khuong Nguyen, Zhiyuan Luo

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Indoor localisation is the state-of-the-art to identify and observe a moving human or object inside a building. Location Fingerprinting is a cost-effective software-based solution utilising the built-in wireless signal of the building to estimate the most probable position of a real-time signal data. In this paper, we apply the Conformal Prediction (CP) algorithm to further enhance the Fingerprinting method. We design a new nonconformity measure with the Weighted K-nearest neighbours (W-KNN) as the underlying algorithm. Empirical results show good performance of the CP algorithm.
Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations
Subtitle of host publicationFirst Conformal Prediction and Its Applications Workshop (COPA 2012)
Place of PublicationHalkidiki, Greece
Number of pages10
ISBN (Print)978-3-642-33411-5
Publication statusPublished - Sept 2012


  • indoor localisation
  • fingerprinting
  • Conformal Prediction

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