Home Appliance Error Prediction Using Local Weather Matching
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Solution Overview
Problem
Existing methods for predicting operational errors in home appliances, such as freezing and bursting of washing machines and dryers, are inaccurate due to the use of atmospheric temperature data for large administrative divisions, which does not account for specific residential space conditions, leading to ineffective prevention of failures.
Innovation Solution
A method that obtains future weather information for a specific administrative division and compares it with past environmental data from home appliances to predict operational errors, using a server to register home appliances with location-specific information and provide guidance for preventing errors, ensuring accurate predictions and prevention of failures like freezing and bursting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If atmospheric temperature data for large administrative divisions is used, then data availability is improved, but prediction accuracy deteriorates
Solution Approach 1:
The patent segments the administrative division data into hierarchical levels (large administrative division and specific administrative division). The system first obtains weather data for the large administrative division to ensure data availability, then further segments it to the specific administrative division level (e.g., district or county level) where the home appliance is installed to improve prediction accuracy. This segmentation allows the system to balance between data availability and precision by using appropriate granularity levels.
Solution Approach 2:
The patent applies local quality by obtaining weather information specifically tailored to the local area where the home appliance is installed. Instead of using uniform weather data for the entire large administrative division, the system retrieves weather data for the specific administrative division (local level) matching the appliance's installation location. This ensures that the prediction reflects local environmental conditions, thereby improving accuracy while maintaining data availability through the hierarchical structure.
2Device complexity
If generic weather data is used, then system complexity is reduced, but prediction reliability deteriorates
Solution Approach 1:
The patent segments the weather data acquisition process into multiple hierarchical levels. The system first queries weather data for the large administrative division, then segments it down to the specific administrative division level. This segmentation approach maintains manageable system complexity by using a structured, multi-level query process while improving reliability through progressively more specific local data.
Solution Approach 2:
The patent applies preliminary action by obtaining and storing weather information for different administrative division levels in advance. The system pre-acquires weather data for both large and specific administrative divisions, allowing it to quickly retrieve appropriate data during operation without complex real-time processing. This preliminary data preparation maintains low system complexity while ensuring high prediction reliability when needed.
3Measurement precision
If location-specific weather information is obtained, then prediction accuracy is improved, but information processing complexity increases
Solution Approach 1:
The patent segments the information processing into hierarchical levels corresponding to administrative divisions. The system processes weather data in stages: first for the large administrative division, then for the specific administrative division. This segmentation of information processing reduces overall complexity by breaking down a complex single-step process into manageable hierarchical stages, while still achieving high prediction accuracy through location-specific data.
Solution Approach 2:
The patent applies universality by creating a multi-functional weather data acquisition system that can retrieve information at multiple administrative division levels. The same system infrastructure handles both large administrative division data and specific administrative division data, making the system universally applicable to different precision requirements without proportionally increasing complexity. This multi-functionality allows the system to adapt to different accuracy needs while maintaining efficient information processing.
Data Source
AI summary
A server for managing a home appliance and a method for controlling the same are disclosed. The disclosed server and control method therefor can obtain current information on a specific administrative division regarding a residential space, and compare the acquired current weather information on the specific administrative division with environmental information detected in a home appliance so as to predict in advance an operational error of the home appliance. Accordingly, it is possible to accurately predict an operational error of the home appliance that may occur in the further, and to prevent an operational error in advance.