Intelligent power management device with middleware based living pattern learning for power reduction

Abstract

This paper presents design and implementation of intelligent power management devices using user location, user motion detection and user living patterns in home networks. Our design integrates the device to be controlled, the intelligent power management device (iPMD), and the adaptive light-weight middleware so that it can be used with minimal power consumption for a wide range of applications. iPMD which will be installed in every power outlet in a home, is made up of five blocks: the pyroelectric infrared (PIR) sensor circuit, the light sensor circuit, the microprocessor, the power meter with a LED display and the PLC module. iPMD detects if a human body enters the detection area or not. If there is no human body present, all controlled appliances are turned off and iPMDs help reduce standby power consumption. If there is, the iPMD detects the light intensity under the environment and maintains sufficient light by controlling the nearby lights. An iPMD transmits and receives the sensor data from nearby iPMDs so the IPG can control different lights and appliances in different regions. iPMDs also communicate with the lightweight middleware at an intelligent power gateway (IPG) that adaptively reason the optimal power control by analyzing user living pattern from the sensing data from devices. The experimental results obtained from the real apartments show that the total power consumption can be reduced up to 7.5 %.