Artificial intelligence washing machine providing automatic washing course based on vision
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Solution Overview
Problem
Conventional home appliances, such as laundry washing machines, require users to manually select and input treatment information, which is inefficient and labor-intensive, and do not utilize true artificial intelligence for optimizing treatment processes.
Innovation Solution
A home appliance system that uses artificial intelligence to automatically set optimal treatment information through learning, utilizing a camera to capture images of the objects and process this information to determine the best treatment course, allowing for user-customized settings and reducing the need for manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection and input of treatment information is used, then the appliance can treat objects according to user-specified parameters, but the operation becomes labor-intensive and inefficient
Solution Approach 1:
The appliance automatically captures images of objects using an integrated camera, processes these images through AI algorithms to identify object types and characteristics, and autonomously determines optimal treatment parameters without requiring manual user input. The system serves itself by performing the information gathering and decision-making functions that would otherwise require user intervention.
Solution Approach 2:
The manual mechanical process of selecting and inputting treatment parameters through physical interfaces (buttons, dials, touchscreens) is replaced by an automated optical and computational system. The camera captures visual information, which is then processed by AI algorithms to automatically set treatment parameters, substituting the mechanical interaction with an intelligent automated system.
2Adaptability or versatility
If conventional data processing is used, then accumulated data can be utilized, but true artificial intelligence learning and adaptation cannot be achieved
Solution Approach 1:
The system continuously captures images of objects during operation, processes these images through AI learning algorithms, and uses the learned information to automatically adjust and improve treatment parameters over time. User interactions and treatment outcomes provide feedback that is fed back into the learning system, enabling the appliance to adapt and evolve its performance based on accumulated experience.
Solution Approach 2:
The AI system performs preliminary learning and analysis by processing object images and determining optimal treatment parameters before the actual treatment process begins. This preliminary intelligent processing enables the system to be fully prepared and configured automatically, eliminating the need for manual parameter setting during operation.
3Adaptability or versatility
If multiple treatment courses are provided, then optimal treatment for different object types can be achieved, but the complexity of operation increases
Solution Approach 1:
The system extracts only the essential visual features and characteristics of objects from captured images that are necessary for determining appropriate treatment parameters. Rather than requiring users to navigate through multiple treatment course options, the AI algorithm extracts key identifying features and automatically matches them with the most suitable treatment protocol, simplifying the user interface to essentially just object placement and automatic processing.
Solution Approach 2:
The AI-based automatic recognition system serves multiple functions simultaneously: it identifies object types, determines material composition, assesses object condition, and selects appropriate treatment parameters across all treatment courses. This universal intelligent system replaces multiple specialized controls and selection mechanisms, providing adaptability for various object types while maintaining operational simplicity.
Data Source
AI summary
The present invention relates to home appliances treating the laundry or object received therein using artificial intelligence. Specifically, the home appliance may include an artificial intelligence-based laundry washing machine that recognizes a load based on vision and automatically provides a specific course. The home appliance include a processor configured to: obtain a learning result from a learning operation using image information previously acquired using the camera and treatment information previously acquired from user interface; and process image information currently acquired using the camera with respect to the learning result, thereby to generate and set current treatment information; and control the home appliance to treat the object based on the set current treatment information.