Washing machine and cloud server setting function based on object sensing using artificial intelligence, and method for setting function
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Solution Overview
Problem
Washing machines lack the ability to accurately identify the properties of laundry, leading to inappropriate function settings and potential damage or inefficiency during the washing process.
Innovation Solution
A washing machine and cloud server system that uses object sensing and artificial intelligence to analyze images, physical information, and electrical data to determine the properties of laundry, automatically setting optimal wash courses and controlling operations to prevent issues like water splash and unbalanced loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high-resolution camera is used to capture images inside the washing machine, then the image quality improves, but the device complexity and cost increase
Solution Approach 1:
The patent introduces an image processing unit that acts as an intermediary between the simple camera and the control unit. This unit processes images to extract meaningful information about laundry properties, making the system effective without requiring a complex high-resolution camera. The intermediary layer transforms simple visual data into actionable washing parameters.
Solution Approach 2:
The patent replaces the need for complex mechanical sensing systems with an optical-based image recognition system. Instead of using multiple sensors to detect laundry properties, a single camera captures images that are then analyzed computationally to determine fabric type, color, and other characteristics.
2Device complexity
If the washing machine uses limited functions to operate, then the device complexity is reduced, but the ability to identify laundry properties and set appropriate functions deteriorates
Solution Approach 1:
The washing machine performs self-diagnosis and self-adjustment by automatically analyzing images of the laundry and setting appropriate washing functions without user intervention. The control unit processes image data to identify fabric types and automatically selects suitable wash cycles, making the system adaptable despite having limited physical functions.
Solution Approach 2:
The system changes operational parameters (water temperature, cycle time, agitation intensity) based on image analysis results. By dynamically adjusting these parameters according to detected laundry properties, the washing machine achieves versatility without requiring multiple dedicated functions for different fabric types.
3Adaptability or versatility
If the washing machine manually sets functions based on user input, then the adaptability to different laundry types improves, but the ease of operation and user convenience deteriorates
Solution Approach 1:
The washing machine automatically performs the function of identifying laundry properties and setting appropriate wash cycles without requiring user input. The system captures images, analyzes them to determine fabric type and color, and automatically configures washing parameters, eliminating the need for manual selection while maintaining accuracy.
Solution Approach 2:
The system uses image feedback to continuously monitor and adjust washing functions. By capturing images during the washing process and analyzing changes in laundry state, the control unit can dynamically adjust parameters to optimize performance for the specific load detected.
Data Source
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AI summary
Washing machine (100) and cloud server (200) that set functions based on object sensing using artificial intelligence, and a setting method thereof, whereby the washing machine (100), based on said object sensing produces information on setting of a wash course adequate for the laundry on the basis of the height, image, weight of the laundry, physical information or electrical information generated during a wash or receives the information from the cloud server (200) and operates.