Intelligent indoor air conditioning system and conditioning method based on environment parameters

Abstract

The invention discloses an intelligent indoor air conditioning system and a conditioning method based on environment parameters. The intelligent indoor air conditioning system comprises a window control terminal, an air conditioning system and an air purification system, and further comprises a distributed Wi-Fi network, a data acquisition module and a processing module. The window control terminal, the air conditioning system, the air purification system and the data acquisition module are connected with the processing module through the distributed Wi-Fi network. According to the conditioning system of the invention, an indoor temperature and humidity sensor, a CO2 concentration sensor and an indoor PM2.5 sensor collect environment parameters and upload data to the local server processing module through the distributed Wi-Fi network, an electric meter uploads data to the local server processing module, and the local server processing module makes analysis and performs calculation through a method based on reinforcement learning according to the data obtained and the set values of temperature and humidity to give actions which should be done by the window control terminal, the air conditioning system and the air purification equipment, in order to change the indoor air in such a way that the quality of indoor air is improved under lowest energy consumption.

Description

technical field [0001] The invention relates to the technical field of air conditioning, in particular to an intelligent indoor air conditioning system and an adjusting method based on environmental parameters. Background technique [0002] As awareness of the hazards of environmental pollution increases, people begin to pay more attention to indoor air quality. Studies have shown that modern people spend an average of 90% of their time indoors, so the quality of indoor air quality will directly affect the health of modern people, so it has become a better research to use various control methods to adjust air quality. direction. [0003] At present, most families only have air conditioners and air purifiers that can work smartly, and they only work independently. Even though some air-conditioning systems for households can interconnect devices, they lack the function of machine self-learning, require a lot of manual intervention and adjustment, cannot adapt to seasonal cha...

AI Technical Summary

Problems solved by technology

Even though some household air-conditioning systems allow devices to be interconnected, they lack the function of machine self-learning, require a lot of manual intervention and adjustment, cannot adapt to seasonal changes, and cannot well adapt to the needs of various market conditions.

In addition, manual intervention and adjustment cannot guarantee better results. For example, when people want to open windows to ventilate and reduce indoor CO 2 When the concentration is high, the outdoor temperature may be low at this time, which will affect the indoor temperature, or there may be smog outside, which will greatly affect the indoor air quality. How to deal with these problems more efficiently can also ensure energy saving. The machine can only solve the problem through continuous trial and error learning.

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