WiFiNet: WiFi-based indoor localisation using CNNs

作者：

Highlights：

• Custom Convolutional Neural Networks improve WiFi localisation performance.

• Reduction of the localisation error compared to traditional methods.

• Great generalisation ability and adaptation to motion conditions.

• Highly scalable, able to achieve real-time localisation in bigger environments.

摘要

•Custom Convolutional Neural Networks improve WiFi localisation performance.•Reduction of the localisation error compared to traditional methods.•Great generalisation ability and adaptation to motion conditions.•Highly scalable, able to achieve real-time localisation in bigger environments.

论文关键词：Indoor localisation,WiFi,Fingerprinting,Deep learning

论文评审过程：Received 7 October 2019, Revised 10 February 2021, Accepted 8 March 2021, Available online 16 March 2021, Version of Record 12 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114906