Talking buildings: Interactive human-building smart-bot for smart buildings

Devmane, Suhas, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646, Lannon, Simon ORCID: https://orcid.org/0000-0003-4677-7184 and Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346 2025. Talking buildings: Interactive human-building smart-bot for smart buildings. Presented at: WISE 2024: 25th International Web Information Systems Engineering conference, Doha, Qatar, 2-5 December 2024. Published in: Barhamgi, Mahmoud, Wang, Hua and Wang, Xin eds. Web Information Systems Engineering – WISE 2024: 25th International Conference, Doha, Qatar, December 2–5, 2024, Proceedings, Part I. Lecture Notes in Computer Science , vol.15436 (1) Springer, pp. 399-415. 10.1007/978-981-96-0579-8_28

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Abstract

Conventional conversational agents have a limited ability to respond to different user intents when interacting with smart buildings. The uniqueness of each building, coupled with the heterogeneity of built environments, makes it challenging to adapt communication methods universally. A possible solution is to develop a conversational agent capable of understanding physical, logical, and virtual assets in the built environment, with the aim of establishing a standardised method of human-building communication. Current smart building ontologies and metadata description schemas aim to give smart buildings a common language for the rapidly growing number of devices in smart buildings. This research paper focuses on developing a comprehensive smart building framework that integrates chatbot-driven natural language interactions into smart buildings using the SPARQL query language to query the smart building Knowledge Base (KB) and interact with buildings using a chatbot. An environmental sensor network testbed was set up using an ontology representing a smart building to evaluate the answer to the question. We have used transformer-based machine learning (ML) models to translate the natural language (NL) queries into SPARQL queries and summarise combined SPARQL and natural language queries, which produced promising performance. By integrating chatbots into smart building systems on the edge, users can interact in natural language, provide real-time information, and detect potential threats without the need for specialised knowledge. Our future work will be to extend this model to support heterogeneous building types represented by smart building ontologies. The source code and data sets are publicly available. https://github.com/suhasdevmane/abacws-chatbot

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Architecture Schools > Computer Science & Informatics
Subjects:	Q Science > Q Science (General) T Technology > T Technology (General)
Publisher:	Springer
ISBN:	9789819605781
Date of First Compliant Deposit:	23 January 2025
Date of Acceptance:	2 December 2024
Last Modified:	26 Feb 2025 10:45
URI:	https://orca.cardiff.ac.uk/id/eprint/175543

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