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.
|Title of host publication||IFIP Advances in Information and Communication Technology|
|Publication status||Published - 2012|
|Name||IFIP Advances in Information and Communication Technology|
Nguyen, K. A., & Luo, Z. (2012). Conformal Prediction for indoor localisation with fingerprinting method. In IFIP Advances in Information and Communication Technology (pp. 214-223). (IFIP Advances in Information and Communication Technology; Vol. 382). Springer. https://doi.org/10.1007/978-3-642-33412-2_22