Machine-Learning Indoor Localization with Access Point Selection and Signal Strength Reconstruction

Indoor localization technique is a key enabling technology for the future Internet of things (IoT) paradigm. Improving the precision of indoor localization will expand the horizon of indoor IoT applications. In this paper, we propose an enhanced machine-learning indoor localization scheme which incorporates access point (AP) selection and the proposed signal strength reconstruction to enhance robustness in noisy environments. The proposed signal...