A method and system for predicting spoilage risk
By integrating multi-dimensional data collection and advanced algorithm models into the refrigerator, the problem of refrigerator food detection technology being unable to accurately predict the risk of spoilage has been solved. This enables accurate prediction and proactive intervention of food spoilage risk, extends the shelf life of food, and reduces the risk of users accidentally consuming spoiled food.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NINGBO FOTILE KITCHEN WARE CO LTD
- Filing Date
- 2026-01-07
- Publication Date
- 2026-06-05
AI Technical Summary
Existing refrigerator food testing technologies cannot fully reflect the actual condition of food during storage, lacking the ability to accurately predict and proactively intervene in the risk of food spoilage, leading to food waste and health risks.
Through multi-dimensional data collection and algorithms, including environmental parameter sensors and food information collection devices, models such as Support Vector Machine (SVM), Long Short-Term Memory Network (LSTM), and Convolutional Neural Network (CNN) are used to predict the risk level, probability, score, and degree of food spoilage, and then proactive intervention is carried out in conjunction with the intervention module.
It enables accurate prediction and proactive intervention of the risk of food spoilage inside the refrigerator, extends the shelf life of food, reduces the risk of users accidentally eating spoiled food, and improves the intelligence level of the refrigerator and the user experience.
Smart Images

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