Context-aware LLM-based AI Agents for Human-centered Energy Management Systems in Smart Buildings
In brief:
This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-aware energy management in smart…
This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-aware energy…
The proposed framework comprises three modules: perception (sensing), central control (brain), and action (actuation and user interaction), forming a closed feedback loop that captures, analyzes,…
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About this source
Source
arXiv cs.AI
Type
Research Preprint
Published
Credibility
Peer-submitted research paper on arXiv
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arXiv cs.AI·Research Preprint·Primary Source·
Context-aware LLM-based AI Agents for Human-centered Energy Management Systems in Smart Buildings
TL;DR
This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-aware energy management in smart…
Scan abstract → experiments → limitations. Also: verify benchmark methodology; note model size and inference requirements.
Full Analysis
Major industry investment.
This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-aware energy…
The proposed framework comprises three modules: perception (sensing), central control (brain), and action (actuation and user interaction), forming a closed feedback loop that captures, analyzes,…
