Smart-home users increasingly want to control their homes in natural language rather than assemble rules, dashboards, and API integrations by hand. At the same time, real deployments are brittle: devices fail, integrations break, and recoveries often require manual intervention. Existing agent toolkits are effective for session-scoped delegation, but smart-home control operates under a different scenario: it is persistent, event-driven, failure-prone, and tied to physical devices with no shared context window. We present HearthNet, an edge multi-agent orchestration system for smart homes. HearthNet deploys a small set of persistent, role-specialized LLM agents at the home hub, where they coordinate through MQTT, Git-backed shared state, and root-issued actuation leases to govern heterogeneous devices through thin adapters. This design externalizes context, preserves execution history, and separates planning, verification, authorization, and actuation across explicit boundaries. Our current prototype runs on commodity edge hardware and Android devices; it keeps orchestration, state management, and device control on-premise while using hosted LLM APIs for inference. We demonstrate the system through three live scenarios: intent-driven multi-agent coordination from ambiguous natural language, conflict resolution with timeline-based tracing, and rejection of stale or unauthorized commands before device actuation.

翻译：智能家居用户越来越倾向于使用自然语言控制家庭设备，而非手动编写规则、配置仪表盘或集成API接口。然而，实际部署的系统存在脆弱性问题：设备故障、集成中断，且恢复过程往往需要人工干预。现有智能体工具包在会话级委托任务中表现有效，但智能家居控制面临不同的应用场景——它具有持久性、事件驱动性、易故障性，且与物理设备绑定，缺乏共享上下文窗口。本文提出HearthNet，一个面向智能家居的边端多智能体编排系统。HearthNet在家庭网关部署一组持久化、角色专业化的大语言模型（LLM）智能体，通过MQTT协议、基于Git的共享状态以及根节点颁发的执行权限租赁机制进行协同，借助轻量适配器管理异构设备。该设计将上下文外化、保留执行历史，并沿显式边界分离了规划、验证、授权和执行功能。当前原型系统可在商用边缘硬件与安卓设备上运行，将编排、状态管理与设备控制保留在本地，同时利用托管式LLM API进行推理。我们通过三个实景案例展示系统能力：基于模糊自然语言的意图驱动多智能体协同、基于时间线追踪的冲突消解，以及在设备执行前对过期或未授权指令的拦截。