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Conformal Prediction for Indoor Localisation with Fingerprinting Method

Abstract : 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.
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Khuong Nguyen, Zhiyuan Luo. Conformal Prediction for Indoor Localisation with Fingerprinting Method. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.214-223, ⟨10.1007/978-3-642-33412-2_22⟩. ⟨hal-01523074⟩

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