AI-Based Laundry Recognition to Replace Manual Washing Tag Reading
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Solution Overview
Problem
Conventional laundry treatment apparatuses require users to manually recognize and input washing tags for each laundry item, which is inconvenient and prone to errors, especially when tags are removed or difficult to read.
Innovation Solution
An AI-based laundry treatment apparatus equipped with a camera and machine learning algorithms that analyzes images of laundry to automatically identify materials and their ratios, determining optimal washing courses without the need for tags, and provides personalized washing instructions through a washing course learning model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If washing tags are used to identify laundry information, then laundry information can be recognized, but users must manually find and read tags which is inconvenient and time-consuming
Solution Approach 1:
The laundry treatment apparatus automatically captures images of laundry items using an integrated camera and processes them through AI algorithms to extract washing information, eliminating the need for users to manually search for and read washing tags. The system serves itself by autonomously identifying laundry materials and determining appropriate washing parameters.
Solution Approach 2:
The patent replaces the mechanical process of manually finding and reading physical washing tags with an automated optical recognition system. The camera captures images and AI algorithms process them to extract laundry information, substituting human manual operations with automated image processing and pattern recognition.
2Ease of operation
If washing tags are removed or text is erased, then laundry becomes easier to handle, but washing tag recognition fails
Solution Approach 1:
Instead of relying on physical washing tags that may be removed or damaged, the system creates a digital copy of the laundry item through image capture. The AI algorithm processes this digital copy to extract washing information directly from the laundry item's visual characteristics, such as fabric texture and color, making the system independent of physical tags.
Solution Approach 2:
The patent introduces an intermediary AI recognition system that bridges the gap between the laundry item and the washing machine control. This intermediary processes visual information from the laundry and translates it into washing parameters, eliminating the need for physical washing tags as intermediaries.
3Productivity
If multiple laundry items are washed simultaneously, then washing efficiency increases, but incompatible materials may be damaged
Solution Approach 1:
The AI recognition system segments the laundry load by identifying and classifying different fabric materials and their proportions. By analyzing the composition of each laundry item and determining compatibility between materials, the system divides the washing process into appropriate groups, allowing simultaneous washing of compatible items while protecting delicate materials from damage.
Solution Approach 2:
The system dynamically adjusts washing parameters such as water temperature, washing intensity, and cycle duration based on the detected laundry composition. When incompatible materials are detected, the AI modifies the washing parameters to accommodate the most delicate items, thereby maintaining high productivity while ensuring the safety of all laundry materials.
Data Source
AI summary
Disclosed is an artificial intelligence (AI)-based laundry treatment apparatus comprising: a washing module; a camera to acquire an image of laundry; a memory for storing therein a laundry recognition model, wherein the model is trained using a machine learning or deep learning algorithm, wherein the model is configured to recognize laundry information about the laundry; and a processor configured to apply image data from the acquired image to the laundry recognition model to acquire the laundry information.