An intelligent lifestyle has become a hotspot for researchers and industries nowadays. The smart home monitoring and controlling system with the Arduino as the main controller is designed in this paper, combined with sensors, Wi-Fi, and cloud technologies. Various sensors collect household environmental information, such as indoor temperature and humidity, soil moisture, combustible gas concentration, and light intensity. The main controller processes the collected signals and automatically operates the devices, including a refrigeration equipment, water pump, buzzer, fan, stepping motor. The data can also be transmitted to the cloud platform through Wi-Fi for processing, and the home environment information and device can be remotely monitored and controlled by the cloud platform or smartphone APP.

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The rapid development of 5G communication provides a huge opportunity for the research on the Internet of vehicles. With the increasing shortage of low-frequency spectrum resources and the demand for high transmission rates for the architecture of the internet of vehicles, the highly qualified millimeter wave has been combined into the research on the internet of vehicles. However, due to the various characteristics of millimeter wave and the limitation of the complex communication environment of the internet of vehicles, how to achieve stable beam tracking is a big problem that needs to be solved urgently. This paper mainly introduces an extended Kalman filter algorithm with updated threshold to solve the problem of continuous stable beam tracking of millimeter waveInternet of vehicles. Simulation shows that this method has lower tracking error than the original algorithm, and better overcomes the problem of continuous accumulation of tracking error of the original algorithm.