Automatic switching window ventilation system based on STM32 microcontroller

Shuyue Lei; Haibing Yan; Ziyan Li; Yilin Zhou

doi:10.1117/12.2674867

2 May 2023 Automatic switching window ventilation system based on STM32 microcontroller

Shuyue Lei, Haibing Yan, Ziyan Li, Yilin Zhou

Author Affiliations +

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 126422V (2023) https://doi.org/10.1117/12.2674867
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

Scientific studies have shown that regular breathing of fresh air can speed up human metabolism and improve human immunity. In order to effectively realize the update of indoor air and ensure good indoor air quality, this paper uses sensor technology and infinite communication technology, through circuit design and program simulation, designs a sensor-motor-window hybrid system that is in line with the actual situation, and uses low-power MCU STM32 as the main control center. Assisted by a variety of sensors to monitor the indoor and outdoor environment in real time and send signals, according to the data of several dimensions, a set of algorithms for analyzing whether the current environmental factors should open/close the window are written, and finally the automatic switch control of the window is realized by controlling the stepper motor. In addition, this design provides a visual applet to realize the intelligence from air quality monitoring to switching Windows. The design of this paper can well adapt to the needs of the market for smart home in the ordinary people's homes, and has a wide range of market practice value.

Citation Download Citation

Shuyue Lei, Haibing Yan, Ziyan Li, and Yilin Zhou "Automatic switching window ventilation system based on STM32 microcontroller", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 126422V (2 May 2023); https://doi.org/10.1117/12.2674867

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