Semantic 3D City Agents—An intelligent automation for dynamic geospatial knowledge graphs
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Authors
Chadzynski, A
Li, S
Grisiute, A
Farazi, F
Lindberg, C
Mosbach, S
Herthogs, P
Publication Date
2022-05Journal Title
Energy and AI
ISSN
2666-5468
Publisher
Elsevier BV
Volume
8
Number
100137
Pages
100137-100137
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Chadzynski, A., Li, S., Grisiute, A., Farazi, F., Lindberg, C., Mosbach, S., Herthogs, P., & et al. (2022). Semantic 3D City Agents—An intelligent automation for dynamic geospatial knowledge graphs. Energy and AI, 8 (100137), 100137-100137. https://doi.org/10.1016/j.egyai.2022.100137
Abstract
This paper presents a system of autonomous intelligent software agents, based on a cognitive architecture, capable of automated instantiation, visualisation and analysis of multifaceted City Information Models in dynamic geospatial knowledge graphs. Design of JPS Agent Framework and Routed Knowledge Graph Access components was required in order to provide backbone infrastructure for an intelligent agent system as well as technology agnostic knowledge graph access enabling automation of multi-domain data interoperability. Development of CityImportAgent, CityExportAgent and DistanceAgent showcased intelligent automation capabilities of the Cities Knowledge Graph. The agents successfully created a semantic model of Berlin in LOD 2, compliant with CityGML 2.0 standard and consisting of 419 909 661 triples described using OntoCityGML. The system of agents also visualised and analysed the model by autonomously tracking interactions with a web interface as well as enriched the model by adding new information to the knowledge graph. This way it was possible to design a geospatial information system able to meet demands imposed by the Industry 4.0 and link it with the other multi-domain knowledge representations of The World Avatar.
Sponsorship
National Research Foundation Singapore (via Cambridge Centre for Advanced Research and Education in Singapore (CARES)) (unknown)
Identifiers
External DOI: https://doi.org/10.1016/j.egyai.2022.100137
This record's URL: https://www.repository.cam.ac.uk/handle/1810/334464
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