Design and Implementation of Intelligent Window based on Embedded System

Abstract

With the advance of science and technology, individuals have a want for convenient and cozy living. Making comfortable and healthy indoor environments may be a major thought for coming up with sensible homes. As hand-held devices become more and more powerful and ubiquitous, this paper proposes an innovative use of smart handheld devices (SHD), exploitation Massachusetts Institute of Technology App creator and fuzzy management, to perform the time period observance and smart control of the designed intelligent window system (IWS) in a smart home. A compact meteorological observation post that consists of setting sensors was created within the IWS for indoor luminance, temperature-humidity, dioxide (CO2) concentration and outside rain and wind direction. Per the measured environment information, the planned system will mechanically send a command to a fuzzy microcontroller performed by Arduino UNO to totally or partially open the electrical curtain and electric window for adapting to climate changes in the indoor and outdoor environment. Moreover, the IWS can automatically shut windows for rain splashing on the window. The conferred novel management methodology for the sill not solely expands the SHD applications, however greatly enhances convenience to users. To validate the feasibleness and effectiveness of the IWS, a laboratory paradigm was designed and confirmed experimentally. An intelligent window supported the embedded system is introduced during this paper, the system of which may mechanically shut or open the window per the alteration of weather and wind speed. In addition, network communication and network management operates may be realized during this intelligent system. We tend to establish a fuzzy logical thinking modeling with 2 inputs of temperature and wind speed. The network communication function extraordinarily expedited our remote monitoring. Moreover, we use the Hall sensing element for indicating the various positions of the window. Typically we use the fuzzy inference control and network control to comprehend the motor vehicle and remote moving of the window.