Water purifier filter element service life prediction method based on artificial intelligence

By using an AI-based method to predict the lifespan of water purifier filters, a prediction model is built using filter images and basic information. This solves the problem of low prediction accuracy in traditional methods and achieves accurate prediction of filter lifespan.

WO2026123752A1 Publication Date: 2026-06-18SHANGHAI PURE DEAU ENVIRONMENT PROTECTION TECH CO LTD
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
SHANGHAI PURE DEAU ENVIRONMENT PROTECTION TECH CO LTD
Filing Date
2025-08-13
Publication Date
2026-06-18

AI Technical Summary

⚠Technical Problem

Traditional methods for predicting the lifespan of water purifier filters fail to fully utilize multi-dimensional information such as user behavior data, water quality differences, and usage frequency, resulting in low prediction accuracy and a lack of precision and personalization.

⚗Method used

Using an artificial intelligence-based approach, the filter cartridge's usage status and color information are determined by acquiring filter cartridge image information and basic water purifier information. A predictive model is then built, and combined with differences in filter cartridge performance, the filter cartridge's lifespan is accurately predicted.

🎯Benefits of technology

It improves the accuracy of filter life prediction, avoids the risk of misjudgment caused by a single indicator, and achieves more accurate judgment on when to replace the filter.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present application relates to the technical field of water purifiers, and discloses a water purifier filter element service life prediction method based on artificial intelligence. The method comprises: acquiring filter element image information, and on the basis of the filter element image information, determining a filter element usage state and filter element color information; acquiring basic information of a water purifier, and determining feature vectors on the basis of the filter element usage state and the basic information of the water purifier; constructing a prediction model on the basis of the feature vectors; determining a filter element performance difference on the basis of the filter element color information; and determining a filter element service life by means of the prediction model and on the basis of the filter element performance difference. The present application can improve the accuracy of filter element service life prediction.
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