Large Scale Multimodal Data Processing Middleware for Intelligent Transport Systems
Modern Intelligent Transport Systems are comprehensive applications that have to cope with a multitude of challenges while meeting strict service and security standards. A novel data-centric middleware that provides the foundation of such systems is presented in this paper. This middleware is design...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
FRUCT
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/0a3a7f7e01f6434d97c5001d46d149ce |
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| Sumario: | Modern Intelligent Transport Systems are comprehensive applications that have to cope with a multitude of challenges while meeting strict service and security standards. A novel data-centric middleware that provides the foundation of such systems is presented in this paper. This middleware is designed for high scalability, fast data processing and multimodality. To achieve these goals, an innovative spatial annotation (SpatialJSON) is utilised. SpatialJSON allows the representation of geometry, topology and traffic information in one dataset. Data processing is designed in such a manner that any schema or ontology can be used to express information. Further, common concerns of ITS are addressed, such as authenticity of messages. The core task, however, is to ensure a quick exchange of evaluated information between the individual traffic participants. |
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