Design and implementation of intelligent building energy management system integrating Internet of Things and edge computing
Abstract
Traditional centralized energy management system (EMS) has some problems, such as delayed response, low reliability and difficult data sharing. This paper proposes a distributed EMS architecture that integrates the Internet of Things (IoT) and edge computing. The system adopts a three-layer architecture of perception layer, edge layer and cloud layer. In the edge layer, lightweight energy consumption prediction and anomaly detection algorithms are deployed to achieve millisecond-level device response and control, and local optimization strategies are implemented when the network is interrupted. Cloud layer is responsible for long-term data storage, analysis and global optimization strategy formulation. Design and implement master-slave backup and service discovery mechanism. The experimental results show that the system can reduce the response delay and improve the energy-saving effect, and has good robustness.