S5-HES代理：面向社会5.0的代理框架，以民主化智能家庭环境模拟
S5-HES Agent: Society 5.0-driven Agentic Framework to Democratize Smart Home Environment Simulation
AI总结：
S5-HES代理通过自主AI编排，实现无需编程的智能家庭模拟，满足社会5.0的多样化研究需求。
摘要：
智能家庭是社会5.0愿景中人本社会的关键领域。智能家庭技术迅速发展，研究应多样化但仍需与社会5.0目标保持一致。民主化智能家庭研究将吸引更广泛的创新者群体，而不仅仅是传统有限专家。这种转变需要包容性的模拟框架，以支持工业和学术界各领域的研究。然而，现有的智能家庭模拟器需要显著的技术专业知识，适应性有限，缺乏自动进化，因此无法满足社会5.0的全面需求。这些限制阻碍了研究人员高效地进行安全、能源、健康、气候和社会经济研究的模拟和实验。为了解决这些挑战，本文提出了社会5.0驱动的智能家庭环境模拟代理（S5-HES代理），一种代理模拟框架，通过自主AI编排将传统智能家庭模拟转变为自动化。该框架通过可互换的大型语言模型（LLMs）协调专门的代理，使自然语言驱动的端到端智能家庭模拟配置无需编程专业知识。一个检索增强生成（RAG）管道通过语义、关键词和混合搜索检索智能家庭知识。对S5-HES代理的全面评估显示，RAG管道实现了接近最优的检索保真度，模拟设备行为和威胁场景与真实世界物联网数据集一致，且模拟引擎在家庭配置中可预测地扩展，为社会5.0智能家庭研究建立了稳定的基础。源代码可在MIT许可证下获取，网址为https://github.com/AsiriweLab/S5-HES-Agent。
英文摘要：
The smart home is a key domain within the Society 5.0 vision for a human-centered society. Smart home technologies rapidly evolve, and research should diversify while remaining aligned with Society 5.0 objectives. Democratizing smart home research would engage a broader community of innovators beyond traditional limited experts. This shift necessitates inclusive simulation frameworks that support research across diverse fields in industry and academia. However, existing smart home simulators require significant technical expertise, offer limited adaptability, and lack automated evolution, thereby failing to meet the holistic needs of Society 5.0. These constraints impede researchers from efficiently conducting simulations and experiments for security, energy, health, climate, and socio-economic research. To address these challenges, this paper presents the Society 5.0-driven Smart Home Environment Simulator Agent (S5-HES Agent), an agentic simulation framework that transforms traditional smart home simulation through autonomous AI orchestration. The framework coordinates specialized agents through interchangeable large language models (LLMs), enabling natural-language-driven end-to-end smart home simulation configuration without programming expertise. A retrieval-augmented generation (RAG) pipeline with semantic, keyword, and hybrid search retrieves smart home knowledge. Comprehensive evaluation on S5-HES Agent demonstrates that the RAG pipeline achieves near-optimal retrieval fidelity, simulated device behaviour and threat scenarios align with real-world IoT datasets, and simulation engine scales predictably across home configurations, establishing a stable foundation for Society 5.0 smart home research. Source code is available under the MIT License at https://github.com/AsiriweLab/S5-HES-Agent.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
