Toward a Unified Architecture for Smart Home Energy Monitoring: Requirements, Design, and Use-Case Validation

The increasing deployment of smart devices in residential environments opens new opportunities for intelligent energy management. However, existing platforms often fall short in providing intuitive interfaces, zone-level control, and advanced predictive analytics accessible to non-expert users. This paper presents the design of a modular smart home energy management system that integrates real-time monitoring, consumption forecasting, and intelligent assistance via Large Language Models (LLMs). The system features an interactive floor plan interface, multi-user support, threshold-based alerting, and detailed historical analytics. Additionally, it introduces LLM-powered agents that guide users in configuring smart devices and adopting more efficient consumption behaviors. This architecture emphasizes accessibility, adaptability, and extensibility, aiming to empower users with actionable insights and seamless device management. The proposed solution addresses current gaps in existing platforms and lays the groundwork for intelligent, personalized, and proactive home energy systems.