Intelligent Power Equipment Management Based on Distributed Context-Aware Inference in Smart Cities

Smart cities are systematically promoting the transition to sustainable and effective energy systems by promoting policies for energy efficiency, regionalized/distributed renewable energy generation, and intelligent energy management. In particular, this transition toward a more integrated and intelligent energy supply has created a plethora of energy meta-information made available through the IoT smart grid, thereby allowing big data analytical services to forecast energy consumption and to manage usage patterns. In this article, we propose a context-aware framework for intelligent power equipment management. Our contribution is to present a design of the proposed framework based on context awareness, the definition of a context ontology for power equipment management, a specification of the inference rules for the context ontology, and a context-aware inference service for power equipment management. The proposed system has broad applications to handle system monitoring and express system controls, so as to be easily and effectively applied to various application domains.