Collaborative Filtering for Gas Leakage Prediction in Refrigerators
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies lack effective methods to predict gas leakage using collaborative filtering, which is crucial for reducing the risks associated with gas leaks in households.
Innovation Solution
A method utilizing collaborative filtering to analyze historical user scenario information, calculate similarities, and apply linear regression equations to predict gas leakage, sending warnings and activating safety measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If collaborative filtering algorithm is applied to predict gas leakage, then prediction accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the prediction task into distinct modules: user behavior data collection, collaborative filtering calculation engine, gas leakage prediction model, and warning notification system. Each module handles a specific aspect of the prediction process, making the overall complex system manageable and maintainable while achieving accurate predictions through coordinated operation of these segmented components
Solution Approach 2:
The patent introduces a server as an intermediary that hosts the collaborative filtering algorithm and prediction model, mediating between the refrigerator's gas detection sensors and the user notification system. This intermediary handles the complex computational tasks centrally, allowing the refrigerator units themselves to remain relatively simple while still benefiting from advanced prediction capabilities
2Reliability
If gas concentration monitoring is continuously performed, then safety reliability is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic gas concentration monitoring through the gas sensor, continuously sampling the environment at set intervals rather than maintaining constant high-power detection. The collaborative filtering prediction model processes this periodic data to identify leakage trends, enabling reliable safety monitoring while allowing the sensor and processing unit to enter low-power states between measurement cycles
Solution Approach 2:
The collaborative filtering algorithm performs preliminary analysis on historical user behavior data and gas concentration readings to predict potential leakage scenarios before they become critical. By detecting early signs of gas leakage through pattern recognition in the collected data, the system can trigger warnings and preventive measures before significant gas accumulation occurs, thereby maintaining high safety reliability without requiring continuous high-intensity monitoring
Data Source
Figure 1
AI summary
The present invention discloses a method and device for predicting a gas concentration based on collaborative filtering, and a refrigerator. The method comprises: acquiring gas-related scenario information of a plurality of historical users having a gas leakage; acquiring scenario information of a current user, and calculating a similarity in the scenario information between the plurality of historical users and the current user via a collaborative filtering algorithm; and acquiring a first user set by selecting the historical users whose similarity exceeds a threshold, and acquiring a gas leakage predicting equation for the current user based on gas leakage data of the historical users in the first user set. Compared with the prior art, the method for predicting the gas concentration according to the present invention performs linear fitting on the gas leakage data of the historical users to acquire the linear regression equations, and predicts the gas leakage data of the current user via the linear regression equations.