Automatic Settings Negotiation for Multi-User Devices
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Solution Overview
Problem
Existing home appliances lack the ability to automatically adjust settings based on individual user preferences and external stimuli, such as ambient lighting and time of day, especially when multiple users are present, requiring manual intervention or not accommodating simultaneous users effectively.
Innovation Solution
A method and apparatus that automatically adjusts device settings by determining the presence of users, negotiating settings based on their profiles, and modifying settings according to external stimuli like ambient lighting, time, and activity, using sensors and cameras to detect physical characteristics and activities, and applying rules to compromise on settings for optimal user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual intervention is used to adjust device settings, then individual user preferences can be accommodated, but user convenience and time efficiency deteriorate
Solution Approach 1:
The system automatically detects user presence through sensors and cameras, retrieves stored profile information, and adjusts device settings without requiring manual user input. The appliance serves itself by autonomously negotiating settings based on detected users and their preferences, eliminating the need for manual intervention while maintaining personalized settings.
Solution Approach 2:
User profiles and preferences are pre-stored in the system memory before users arrive. When users enter the room, the system immediately retrieves these pre-stored preferences and applies them without requiring users to manually configure settings each time, thus saving time while maintaining ease of operation.
2Adaptability or versatility
If vehicle systems change settings automatically when keys are used, then individual driver preferences are accommodated, but interaction requirements and applicability to multiple simultaneous users worsen
Solution Approach 1:
The system automatically detects which users are present through sensors and cameras, retrieves their profile information from storage, and negotiates settings autonomously without requiring any user interaction such as button presses or key insertions. The appliance independently determines and applies settings based on user preferences stored in their profiles.
Solution Approach 2:
The system is designed to handle multiple simultaneous users by detecting all present individuals, retrieving their respective profiles, and negotiating a compromise setting that accommodates all users. This multi-functional capability extends beyond single-user systems like traditional key-based vehicle settings.
3Adaptability or versatility
If device settings are manually adjusted for each user, then individual preferences are satisfied, but system complexity and time consumption increase
Solution Approach 1:
User profiles containing preferences are pre-stored in the system before users arrive. When users enter, the system retrieves these pre-configured preferences and uses them as the basis for automatic negotiation, eliminating the need for real-time manual configuration and reducing the computational complexity of on-the-spot decision-making.
Solution Approach 2:
The system introduces an intermediary negotiation mechanism that automatically mediates between multiple users' preferences by retrieving their profiles, comparing preferences, and determining compromise settings according to predefined rules. This intermediary process handles the complexity internally without requiring users to directly manage the complexity themselves.
4Extent of automation
If automatic detection of users is implemented, then seamless settings adjustment is achieved, but device complexity and processing requirements increase
Solution Approach 1:
The system segments the automation process into distinct functional modules: user detection through sensors and cameras, profile retrieval from stored data, preference comparison logic, and settings application. This segmentation allows each module to handle a specific task independently, managing overall system complexity through modular design while achieving seamless automatic adjustment.
Solution Approach 2:
User profiles and preferences are pre-stored and organized in the system before users arrive. This preliminary preparation of data structures and preference information reduces the processing burden during actual user detection and negotiation, allowing the system to achieve high automation with manageable processing requirements by working with pre-organized data.
Data Source
AI summary
A method and apparatus for a first device to determine profile information are described including receiving input from a second device, wherein at least one of the first device or the second device detects physical characteristics of people present in an area and the physical characteristics are used by the device to determine who is present in the area, retrieving profile information of the people present in the area, determining a relationship between profiles of the people in the area, applying rules to negotiate a compromise regarding device settings responsive to the relationship between profiles of the people present in the area and adjusting settings of a first device or a third device responsive to the compromise.