Data Cleansing for Indoor Positioning Wi-Fi Fingerprinting Datasets

Darwin Quezada-Gaibor, Lucie Klus, Joaquín Torres-Sospedra, Elena Simona Lohan, Jari Nurmi, Carlos Granell, Joaquín Huerta

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

8 Downloads (Pure)


Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need to be pre-processed prior to being used in any indoor positioning system to ensure the data quality and provide a high Quality of Service (QoS) to the end-user. In this paper, we offer a novel and straightforward data cleansing algorithm for WLAN fingerprinting radio maps. This algorithm is based on the correlation among fingerprints using the Received Signal Strength (RSS) values and the Access Points (APs)'s identifier. We use those to compute the correlation among all samples in the dataset and remove fingerprints with low level of correlation from the dataset. We evaluated the proposed method on 14 independent publicly-available datasets. As a result, an average of 14% of fingerprints were removed from the datasets. The 2D positioning error was reduced by 2.7% and 3D positioning error by 5.3% with a slight increase in the floor hit rate by 1.2% on average. Consequently, the average speed of position prediction was also increased by 14%.

Original languageEnglish
Title of host publicationProceedings - 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022
Number of pages6
ISBN (Electronic)9781665451765
ISBN (Print)9781665451772
Publication statusPublished - 2022
Publication typeA4 Article in conference proceedings
EventIEEE International Conference on Mobile Data Management - Virtual, Paphos, Cyprus
Duration: 6 Jun 20229 Jun 2022

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
ISSN (Print)1551-6245
ISSN (Electronic)2375-0324


ConferenceIEEE International Conference on Mobile Data Management
CityVirtual, Paphos


  • Data cleansing
  • Data pre-processing
  • Indoor positioning
  • Localisation
  • Wi-Fi Fingerprinting

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Engineering(all)


Dive into the research topics of 'Data Cleansing for Indoor Positioning Wi-Fi Fingerprinting Datasets'. Together they form a unique fingerprint.

Cite this