A Spatio-Semantic Model for Agricultural Environments and Machines
| Autor: | Joachim Hertzberg, Thomas Wiemann, Henning Deeken |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
Computer science Process (engineering) Core ontology 02 engineering and technology Semantic data model 01 natural sciences Data science Domain (software engineering) Semantic mapping 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Spatial analysis Digitization 010606 plant biology & botany |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319920573 IEA/AIE |
| Popis: | Digitization of agricultural processes is advancing fast as telemetry data from the involved machines becomes more and more available. Current approaches commonly have a machine-centric view that does not account for machine-machine or machine-environment relations. In this paper we demonstrate how to model such relations in the generic semantic mapping framework SEMAP. We describe how SEMAP’s core ontology is extended to represent knowledge about the involved machines and facilities in a typical agricultural domain. In the framework we combine different information layers – semantically annotated spatial data, semantic background knowledge and incoming sensor data – to derive qualitative spatial facts about the involved actors and objects within a harvesting campaign, which add to an increased process understanding. |
| Databáze: | OpenAIRE |
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