As global attention to energy conservation and carbon reduction increases, the responsibility of companies in their energy use also grows, requiring them to implement energy-saving measures from various angles. Companies have found that office buildings account for 40% of their total energy consumption, with lighting and HVAC systems making up about 70% of this usage. To address this challenge, this study developed an energy consumption decision support system based on a microservices architecture. This system, leveraging the Internet of Things (IoT) and building automation and control systems, uses multiple sensors and data sources to analyze and identify key factors affecting energy consumption through Structural Equation Modeling (SEM). The decision support system provides users with energy-saving recommendations via a visual platform, aiming to reduce the energy consumption of lighting and HVAC systems in office environments.