Towards an LLM-Powered Smart Home for Efficient and Safe Living Environment

The rapid advancements in Generative AI (GenAI), particularly the Large Language Models (LLMs) present transformative opportunities for enhancing smart home environments. This research investigates the integration of LLM agents as reasoning entities into smart homes, with a focus on optimizing energy efficiency, improving indoor living conditions, and addressing safety and security challenges. By leveraging their natural language processing and reasoning capabilities, LLM agents are used to analyze the data from sensors deployed across the smart home to identify usage patterns, detect anomalies, and generate actionable recommendations. The proposed framework demonstrates how LLM agents can optimize appliance settings, enable predictive maintenance, and mitigate vendor lock-in by providing a versatile and non-proprietary solution for intelligent home management. Key contributions of this research include the development of a platform for monitoring and maintaining energy efficiency and living comfort, as well as issuing structured recommendations aligned with standard living guidelines. The findings highlight the potential of LLMs in transforming smart home ecosystems, paving the way for more sustainable, efficient, and user-centric living environments.