With the growth in power demand, energy management is an important issue in the 21st century. This article proposes a smart power management framework system, which comprises three parts. Part 1: a smart plug. Controlling the switching power supply, different sensors can be mounted for different application environments. The power supply can be switched on/off automatically according to environmental changes. Added to this, it can measure voltage and current for analysis. Part 2: a smart gateway. This can act as the mediation module for communication and implement the concept of fog computing. The local inference model is built and deployed by deep learning, and the model is learned, updated, and improved continuously to increase the intelligent control efficiency. Part 3: a management platform and mobile app. This allows for data visualization and a remote control for a user interface medium for scheduling. The smart plug and smart gateway are integrated into the overall distributed sensor network, analyzing and improving the power consumption effectively. Finally, the feasibility and practicability of the overall power management framework system are described experimentally.
|Journal||International Journal of Distributed Sensor Networks|
|Publication status||Published - 2017 Jul 1|
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications