Apparatus and method for operating a personal grooming appliance or household cleaning appliance
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Solution Overview
Problem
There is a need for personal grooming and household appliances to leverage internal sensor data and image data to enhance user experience, as existing technologies lack the ability to effectively utilize these data sources for improved operation and user feedback.
Innovation Solution
A system and method that incorporates a personal grooming or household appliance with a combination of physical sensors (orientation, acceleration, global positioning, pressure, etc.) and a camera, using trained machine learning classifiers to derive an augmented classification from sensor and image data, which modifies the appliance's operation based on this classification, providing user feedback and customizing treatment plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple sensors and a camera are integrated into the appliance, then the user experience and personalization capability are improved, but the device complexity increases
Solution Approach 1:
The system segments the complex data processing task by using separate machine learning classifiers for sensor data and image data, which then feed into an augmented classification module. This modular approach allows the system to handle multiple data sources without creating a monolithic complex structure, resolving the contradiction between personalization capability and device complexity.
Solution Approach 2:
The appliance is designed with multi-functionality by integrating various sensors (orientation, acceleration, pressure, etc.) and a camera into a single device that can perform both traditional grooming functions and advanced monitoring/personalization functions. This universal design allows one device to serve multiple purposes, improving adaptability while managing complexity through integrated architecture.
2Measurement precision
If machine learning classifiers are used to process sensor and image data, then the measurement precision and classification accuracy are improved, but the computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary classification by using separate machine learning classifiers to process sensor data and image data independently before combining them into augmented classification. This preliminary action allows each classifier to specialize in its data type, improving overall accuracy while enabling parallel processing that reduces total computation time.
Solution Approach 2:
The system applies partial action by using multiple specialized classifiers for different data types rather than one comprehensive classifier. This approach processes each data type to the necessary degree of accuracy without over-processing, balancing measurement precision with computational efficiency and processing time.
3Productivity
If real-time data analysis and operation modification are implemented, then the effectiveness of grooming tasks is improved, but the energy consumption increases
Solution Approach 1:
The system implements feedback by continuously analyzing sensor and image data in real-time, deriving augmented classification, and modifying appliance operation based on this classification. This closed-loop feedback mechanism improves grooming effectiveness by adapting to real-time conditions while optimizing energy consumption through intelligent control rather than continuous full-power operation.
Solution Approach 2:
The appliance operation is made dynamic through real-time modification based on data analysis. The system adjusts operational parameters dynamically according to the augmented classification derived from sensor and image data, improving effectiveness by adapting to current conditions while managing energy consumption through variable operation rather than constant high-power mode.
Data Source
AI summary
A system and method for operating a personal grooming/household appliance, including: providing a personal grooming/household appliance including at least one physical sensor taken from a group consisting of: an orientation sensor, an acceleration sensor, an inertial sensor, a global positioning sensor, a pressure sensor, and a load sensor, audio sensor, humidity sensor, and a temperature sensor; providing a camera associated with the personal grooming/household appliance; classifying data received from the physical sensor and from the camera using at least one trained machine learning classifier to generate an augmented classification; and providing user feedback information based upon the augmented classification or modifying operation of the grooming/household appliance based upon the augmented classification.