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

[EN] 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...

Descripción completa

Detalles Bibliográficos
Autores: Martín Furones, Ángel Esteban|||0000-0001-9379-0694, Anquela Julián, Ana Belén|||0000-0001-6024-3790, Capilla, Raquel Maria
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/197783
Acceso en línea:https://riunet.upv.es/handle/10251/197783
Access Level:acceso abierto
Palabra clave:GNSS
Differential positioning
Network RTK
National marine electronics association (NMEA)
Navigation
Precision
Big data
INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA
Descripción
Sumario:[EN] 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.