• home
• current students
• graduate
• events

Presenter: Minh Tu Hoang
Supervisor:

Date: Thu, August 29, 2019
Time: 11:00:00 - 12:00:00
Place: EOW 430

ABSTRACT

This seminar presents recurrent neuron networks (RNNs) for a fingerprinting indoor localization using WiFi. Instead of locating user's position one at a time as in the cases of conventional algorithms, our RNN solution aims at trajectory positioning and takes into account the relation among the received signal strength indicator (RSSI) measurements in a trajectory. The results using different types of RNN including vanilla RNN, long short-term memory (LSTM), gated recurrent unit (GRU) and bidirectional LSTM (BiLSTM) are presented. On-site experiments demonstrate that the proposed structure achieves an average localization error of 0.75 m with 80% of the errors under 1 m, which outperforms the conventional KNN algorithms and probabilistic algorithms by approximately 30% under the same test environment.