Adaptive Autonomy Selection for User-Aware Building Alarms
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Solution Overview
Problem
Existing home security and automation systems lack the ability to adapt their level of autonomy to the preferences and conditions of individual users, leading to suboptimal interaction and decision-making.
Innovation Solution
A method and system for determining a user's likely condition and selecting an appropriate autonomy level based on that condition, allowing users to make some or all decisions, or for the system to make decisions on their behalf, through modules that analyze historical behavior, user input, and system interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system uses rule-based decision processes with fixed autonomy levels, then the system operation is simple and reliable, but the system cannot adapt to individual user preferences and conditions
Solution Approach 1:
The system dynamically adjusts the autonomy level based on user conditions and preferences rather than using fixed rule-based decisions. The autonomy level is selected from multiple levels (0-3) depending on the user's likely condition, allowing the system to adapt its decision-making behavior to individual users while maintaining a manageable structure through predefined autonomy levels.
2Productivity
If the system makes all decisions autonomously, then decision-making efficiency is high, but user satisfaction decreases due to lack of control
Solution Approach 1:
The system dynamically selects the autonomy level (ranging from fully autonomous level 0 to fully manual level 3) based on the user's likely condition and preferences. This allows the system to optimize decision-making efficiency by making decisions autonomously when appropriate while maintaining user satisfaction by allowing user control when preferred, creating a flexible balance between automation and user involvement.
3Ease of operation
If the system asks users to select autonomy levels manually, then user control is maximized, but time is lost in the selection process
Solution Approach 1:
The system performs preliminary analysis to determine the user's likely condition and automatically selects an appropriate autonomy level before the user needs to make a decision. By pre-determining the autonomy level based on user conditions and preferences, the system eliminates the need for manual selection at the moment of decision-making, thus saving time while maintaining user control through the accuracy of the pre-selection.
Solution Approach 2:
The system uses feedback from user conditions, historical data, and satisfaction ratings to continuously improve its determination of the appropriate autonomy level. This feedback mechanism allows the system to learn from user responses and adjustments, refining its ability to automatically select the correct autonomy level without requiring manual input from the user.
Data Source
AI summary
Methods and systems are described for selecting a level of autonomy. According to at least one embodiment, a method for detecting a behavior of a first user, selecting a first autonomy level comprising a first decision, determining that an alarm condition is triggered, updating the first autonomy level without receiving additional input from the first user to an updated first decision, executing the updated first decision.