An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics in Location-aware Games
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 phenome...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/671588 |
| Acceso en línea: | http://hdl.handle.net/10803/671588 http://dx.doi.org/10.6035/14101.2021.357562 |
| Access Level: | acceso abierto |
| Palabra clave: | Geogames Context-aware applications Data model Metrics processing Tecnologies de la informació i les comunicacions (TIC) 004 |
| Sumario: | 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 scenario |
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