A Convolutional Neural Network Architecture for Multi-Floor Indoor Localization Based on Wi-Fi Fingerprinting

Xin Chen, Wan Chi Siu, Yuk Hee Chan, Chuen Yu Chan, Chun Pong Chau

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Nowadays Location Based Services applications are increasingly useful. However, problems like floor identification for multi-buildings and adverse effects of devices diversity are needed to be resolved. In this paper we propose a new approach using cosine similarity computed by Wi-Fi fingerprints and radio map and using Convolutional Neural Network (CNN) model to achieve multi-floor classification. We propose in this paper to use locations-based similarity as the feature vector instead of using conventional Access Point sets. We also use a timesaving walk-survey method to collect Wi-Fi fingerprint. Experimental results show that our proposed CNN floor classifier has 98.37% training accuracy and 99.51% test accuracy. Compared with recent deep neural networks, our proposed approach achieves state-of-the-art floor classification accuracy but only needs a training data set almost 5 times smaller than that of other approaches.

Original languageEnglish
Title of host publication2023 24th International Conference on Digital Signal Processing, DSP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350339598
ISBN (Print)9798350339598
DOIs
Publication statusPublished - 2023
Event24th International Conference on Digital Signal Processing, DSP 2023 - Rhodes, Greece
Duration: 11 Jun 202313 Jun 2023

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2023-June

Conference

Conference24th International Conference on Digital Signal Processing, DSP 2023
Country/TerritoryGreece
CityRhodes
Period11/06/2313/06/23

Keywords

  • CNN
  • Cosine similarity
  • floor classification
  • small data set

Fingerprint

Dive into the research topics of 'A Convolutional Neural Network Architecture for Multi-Floor Indoor Localization Based on Wi-Fi Fingerprinting'. Together they form a unique fingerprint.

Cite this