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Big data architecture and data mining analysis for market segment applications of differential global navigation satellite system (GNSS) services: case study of the analysis of the demand for navigation and agriculture

Published online by Cambridge University Press:  07 February 2022

Angel Martín ,
Raquel Maria Capilla  and
Ana Belén Anquela
Angel Martín
Affiliation:
Cartographic Engineering Department, Universitat Politècnica de València, Valencia, Spain
Raquel Maria Capilla*
Affiliation:
Geodesy, Cartographic Institute of Valencia, Valencia, Spain
Ana Belén Anquela
Affiliation:
Cartographic Engineering Department, Universitat Politècnica de València, Valencia, Spain
*
*Corresponding author. E-mail: racaro@upv.es
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Abstract

Location and navigation services based on global navigation satellite systems (GNSS) are needed for real-time high-precision positioning applications in relevant economic sectors, such as precision agriculture, transport, civil engineering or mapping. Real-time navigation users of GNSS networks have significantly increased all around the world, since the 1990s, and usage has exceeded initial expectations. Therefore, if the evolution of GNSS network users is monitored, the dynamics of market segments can be studied. The implementation of this hypothesis requires the treatment of big volumes of navigation data over several years and the continuous monitoring of customers. This paper is focused on the management of massive connection of GNSS users in an efficient way, in order to obtain analysis and statistics. Big data architecture and data analyses based on data mining algorithms have been implemented as the best way to approach the hypothesis. Results demonstrate the dynamic of users of different market segments, the increasing demand over the years and, specifically, conclusions are obtained about the trends, year-on-year correlation and business volume recovering after economic crisis periods.

Keywords

GNSSdifferential positioningnetwork RTKnational marine electronics association (NMEA)navigationprecisionbig data
Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 2 , March 2022 , pp. 421 - 436
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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