Artificial intelligence electrical control system

By establishing a turbidity prediction model, and based on the pool data analysis and control module, the problem of untimely prediction of pool water turbidity was solved, ensuring the stability and safety of pool water quality.

CN122219265APending Publication Date: 2026-06-16BEIJING YANGQINGXIANG NETWORK TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202610385282.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-27
Publication Date
2026-06-16

AI Technical Summary

Technical Problem

Current technology cannot predict the trend of turbidity changes in pool water over a future period based on the pool's current water volume and turbidity, leading to untimely cleaning and disinfection and situations where pool water temporarily exceeds the standard value.

Method used

The data acquisition module collects data on pool water turbidity, pool water volume, and personnel in the pool. The data analysis module and turbidity prediction model generation module are used to establish a turbidity prediction model to predict future turbidity trends. The control module determines the timing of disinfectant administration to ensure stable pool water quality.

Benefits of technology

It enables timely prediction and disinfection of pool water turbidity, preventing the pool water turbidity from briefly exceeding the threshold and ensuring the stability and safety of the pool water quality.

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Abstract

The invention, which relates to the technical field of the electrical control system, discloses an artificial intelligence electrical control system comprising a data acquisition module, a data analysis module, a turbidity prediction model generation module, a determination module, a prediction module and a control module. The method solves the technical problem that the change trend of the turbidity of water in the swimming pool and the time when the turbidity reaches a threshold value in a period of time in the future cannot be predicted according to the existing water storage and the existing turbidity of the swimming pool. The method comprises the following steps of: establishing a swimming pool turbidity prediction model by analyzing the historical swimming pool water turbidity, pool water storage and in-pool personnel data of the swimming pool; the method comprises the following steps: predicting the turbidity change trend of swimming pool water in a future period of time and the duration when the turbidity reaches a threshold value through a swimming pool turbidity prediction model, marking the predicted duration as a threshold value exceeding predicted duration, and determining the putting time range of a disinfectant according to the threshold value exceeding predicted duration. And then the disinfectant is controlled to be put in the putting time range through the control module.
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