An analytics platform for integrating and computing spatio-temporal metrics in location-aware games
- Autores: Luis Enrique Rodriguez Pupo
- Directores de la Tesis: Sven Casteleyn (dir. tes.)
, Carlos Granell Canut (dir. tes.) - Lectura: En la Universitat Jaume I ( España ) en 2021
- Idioma: español
- Tribunal Calificador de la Tesis: Christoph Schlieder (presid.) , Michael Gould (secret.) , Alain Tamayo Fong (voc.)
- Enlaces
- Tesis en acceso abierto en: TDX
- Resumen
This thesis presents an analytics platform for calculating spatio-temporal metrics in the context of geogames and context-based applications. It is based on an underlying conceptual model for spatio-temporal metrics, which consists of dimensions and variables to describe spatial and temporal phenomena, metrics functions to calculate application-relevant information and conditions using these data models, and actions to be triggered when certain conditions are met. The analytics platform is implemented as a cloud-based, distributed application that allows developers to define data requirements, collect required (client-generated) data, and define and execute spatio-temporal metrics. It is designed to handle large amounts of (streaming) data and to scale well under increasing amounts of data and metrics computations. The platform is validated in two experiments: a location-aware game for collecting noise data in a city and a mobile application for location-based mental health treatments, which shows its usability, versatility, and feasibility in real-world scenarios.
