A Taxonomy of Technologies for Fingerprint-Based Indoor Localization

  • Mário de Melo Neto UFRN
  • Gibeon de Aquino Júnior UFRN


In recent years, the need for indoor localization has increased. Earlier systems have been deployed in order to demonstrate that indoor localization can be done. Many researchers are referring to location estimation as a crucial component in numerous applications. The indoor localization techniques can be classified using the following classes: proximity, fingerprint, triangulation and vision analysis, with the fingerprint class being the most used. This paper presents the results of a literature systematic mapping on fingerprint-based indoor localization aiming to identify the technologies used for this purpose. The selected search strategy returned 1003 papers, which underwent a series of inclusion and exclusion criteria that resulted with 539 articles being accepted. This work identified that the main technology used for indoor localization is the WIFI, followed by ZigBee. As novelty, we propose a taxonomy of technologies used in the context of fingerprint-based indoor localization.


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DE MELO NETO, Mário; DE AQUINO JÚNIOR, Gibeon. A Taxonomy of Technologies for Fingerprint-Based Indoor Localization. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 7. , 2015, Recife. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2015 . p. 111-120. ISSN 2595-6183. DOI: https://doi.org/10.5753/sbcup.2015.10174.