Washing machine
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Solution Overview
Problem
Conventional washing machines provide laundry courses that do not consider individual user preferences and situations, leading to suboptimal washing experiences as users have diverse needs based on their activities and preferences.
Innovation Solution
A washing machine equipped with a reinforcement learning model that collects user data on laundry patterns and context information to recommend personalized laundry courses, using feedback to adjust and optimize the recommended courses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If laundry courses are provided by manufacturer according to type of laundry and washing time, then the washing machine can perform basic washing functions, but it cannot satisfy the diverse requirements of various users based on their individual preferences and situations
Solution Approach 1:
The washing machine performs self-learning by automatically collecting user feedback on laundry courses and using reinforcement learning to autonomously generate personalized laundry patterns for different users, eliminating the need for manual programming or complex configuration interfaces
Solution Approach 2:
The system collects feedback information from users about their satisfaction with recommended laundry courses and uses this feedback to continuously optimize and update the reinforcement learning model, enabling the system to adapt to individual user preferences over time
2Adaptability or versatility
If the same laundry course is recommended to all users, then the system operation is simple, but it does not consider individual user preferences and situations leading to suboptimal washing experiences
Solution Approach 1:
The washing machine proactively recommends laundry courses to users based on preliminary analysis of their past feedback and usage patterns, rather than waiting for users to manually configure settings or for the system to learn through extensive trial-and-error periods
Solution Approach 2:
The system automatically generates personalized laundry patterns for each user by self-learning from collected feedback data, eliminating the need for users to spend time configuring preferences manually
3Ease of operation
If reinforcement learning model is used to recommend personalized laundry courses, then user satisfaction is improved, but device complexity increases
Solution Approach 1:
The washing machine autonomously performs data collection, feedback analysis, and model training operations without requiring user intervention or external computational resources, managing the complexity internally while maintaining simplicity for the user
Solution Approach 2:
The reinforcement learning model serves multiple functions including collecting user feedback, analyzing usage patterns, generating personalized laundry patterns, and recommending optimal laundry courses, consolidating multiple complex functions into a single integrated system
Data Source
AI summary
Disclosed herein is a washing machine including a first data acquirer configured to collect data related to a laundry pattern of a user, a second data acquirer configured to collect data related to context information, and a processor configured to provide the laundry pattern of the user and the context information to a reinforcement learning model as an environment and to train the reinforcement learning model using feedback of the user on a recommended laundry course when the reinforcement learning model recommends the laundry course.