Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs
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...
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sg-ntu-dr.10356-1640332023-12-29T06:47:24Z Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs Chadzynski, Arkadiusz Li, Shiying Grisiute, Ayda Farazi, Feroz Lindberg, Casper Mosbach, Sebastian Herthogs, Pieter Kraft, Markus School of Chemical and Biomedical Engineering Cambridge Centre for Advanced Research and Education in Singapore (CARES) Engineering::Computer science and engineering Cognitive Architecture Artificial Intelligence 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. National Research Foundation (NRF) Published version This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. Markus Kraft gratefully acknowledges the support of the Alexander von Humboldt foundation, Germany. The research was conducted as part of an Intra-CREATE collaborative project involving CARES (Cambridge Centre for Advanced Research and Education in Singapore), which is University of Cambridge’s presence in Singapore, and Future Cities Laboratory at the Singapore-ETH Centre, which was established collaboratively between ETH Zurich and the National Research Foundation Singapore. 2023-01-03T05:15:40Z 2023-01-03T05:15:40Z 2022 Journal Article Chadzynski, A., Li, S., Grisiute, A., Farazi, F., Lindberg, C., Mosbach, S., Herthogs, P. & Kraft, M. (2022). Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs. Energy and AI, 8, 100137-. https://dx.doi.org/10.1016/j.egyai.2022.100137 2666-5468 https://hdl.handle.net/10356/164033 10.1016/j.egyai.2022.100137 2-s2.0-85124321434 8 100137 en Energy and AI © 2022 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). application/pdf |
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Engineering::Computer science and engineering Cognitive Architecture Artificial Intelligence Chadzynski, Arkadiusz Li, Shiying Grisiute, Ayda Farazi, Feroz Lindberg, Casper Mosbach, Sebastian Herthogs, Pieter Kraft, Markus Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs |
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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. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Chadzynski, Arkadiusz Li, Shiying Grisiute, Ayda Farazi, Feroz Lindberg, Casper Mosbach, Sebastian Herthogs, Pieter Kraft, Markus |
format |
Article |
author |
Chadzynski, Arkadiusz Li, Shiying Grisiute, Ayda Farazi, Feroz Lindberg, Casper Mosbach, Sebastian Herthogs, Pieter Kraft, Markus |
author_sort |
Chadzynski, Arkadiusz |
title |
Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs |
title_short |
Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs |
title_full |
Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs |
title_fullStr |
Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs |
title_full_unstemmed |
Semantic 3D city agents—an intelligent automation for dynamic geospatial knowledge graphs |
title_sort |
semantic 3d city agents—an intelligent automation for dynamic geospatial knowledge graphs |
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2023 |
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https://hdl.handle.net/10356/164033 |
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1787136504888295424 |