Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.12140 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of 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.