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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2512.12140 |
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| _version_ | 1866914200234754048 |
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| author | Ge, Hangli Mori, Hiroaki Chiba, Yasuhira Koshizuka, Noboru |
| author_facet | Ge, Hangli Mori, Hiroaki Chiba, Yasuhira Koshizuka, Noboru |
| contents | This paper presents a novel framework for implementing space-oriented control systems in smart buildings. In contrast to conventional device-oriented approaches, which often suffer from issues related to development efficiency and portability, our framework adopts a space-oriented paradigm that leverages natural language processing and word embedding techniques. The proposed framework features a chat-based graphical user interface (GUI) that converts natural language inputs into actionable OpenAI API calls, thereby enabling intuitive space level (e.g., room) control within smart environments. To support efficient embedding-based search and metadata retrieval, the framework integrates a vector database powered by Elasticsearch. This ensures the accurate identification and invocation of appropriate smart building APIs. A prototype implementation has been tested in a smart building environment at the University of Tokyo, demonstrating the feasibility of the approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_12140 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Realizing Space-oriented Control in Smart Buildings via Word Embeddings Ge, Hangli Mori, Hiroaki Chiba, Yasuhira Koshizuka, Noboru Systems and Control This paper presents a novel framework for implementing space-oriented control systems in smart buildings. In contrast to conventional device-oriented approaches, which often suffer from issues related to development efficiency and portability, our framework adopts a space-oriented paradigm that leverages natural language processing and word embedding techniques. The proposed framework features a chat-based graphical user interface (GUI) that converts natural language inputs into actionable OpenAI API calls, thereby enabling intuitive space level (e.g., room) control within smart environments. To support efficient embedding-based search and metadata retrieval, the framework integrates a vector database powered by Elasticsearch. This ensures the accurate identification and invocation of appropriate smart building APIs. A prototype implementation has been tested in a smart building environment at the University of Tokyo, demonstrating the feasibility of the approach. |
| title | Realizing Space-oriented Control in Smart Buildings via Word Embeddings |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2512.12140 |