Attention-Aware Virtual Assistant Session Control for Battery Conservation
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Solution Overview
Problem
Intelligent automated assistants consume significant electric power, which is a limited resource on handheld or portable devices, necessitating energy-efficient operation.
Innovation Solution
Implementing a virtual assistant session management system that determines user engagement or disinterest through sensors, allowing for timely deactivation to conserve battery and processing power when the user is disengaged, and maintaining the session when the user is engaged.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the virtual assistant session is kept active continuously, then the user experience and responsiveness are improved, but the energy consumption increases
Solution Approach 1:
The patent implements dynamic session management where the virtual assistant session state transitions between active and deactivated states based on real-time sensor data analysis. The system adjusts session continuity dynamically by evaluating user engagement metrics (eye tracking, gesture detection, speech patterns) to determine whether to maintain or terminate the session, resolving the contradiction between continuous responsiveness and energy conservation
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring sensor data (eye tracking cameras, motion sensors, microphones) during the virtual assistant session and using this feedback to automatically determine session termination. The feedback loop analyzes user engagement in real-time and triggers session deactivation when disengagement is detected, or extends the session when engagement continues, thereby optimizing energy usage while maintaining service availability
2Use of energy by moving object
If the virtual assistant session is deactivated early to save energy, then battery life is extended, but the user experience may be interrupted
Solution Approach 1:
The patent applies preliminary action by detecting user disengagement indicators before complete session termination is necessary. The system monitors for early signs of user disengagement (lack of eye contact, absence of gestures, silence) and proactively manages session transition, allowing for graceful deactivation that conserves energy while minimizing user experience interruption. The system prepares for session end by analyzing sensor data trends before the session actually terminates
Solution Approach 2:
The virtual assistant system performs self-service by autonomously determining when to deactivate sessions based on sensor data analysis without requiring explicit user commands. The system independently evaluates engagement metrics, makes termination decisions, and executes session deactivation, thereby extending battery life through intelligent autonomous management while maintaining service continuity when users remain engaged
Data Source
AI summary
Systems and processes for operating an intelligent automated assistant are provided. An example process includes initiating a virtual assistant session responsive to receiving user input. In accordance with initiating the virtual assistant session, the process includes determining, based on data obtained using one or more sensors of the electronic device, whether one or more criteria representing expressed user disinterest are satisfied. In accordance with determining that the one or more criteria representing expressed user disinterest are satisfied prior to a first time, the process includes automatically deactivating the virtual assistant session prior to the first time. The first time is defined by a setting of the electronic device. In accordance with determining that the one or more criteria representing expressed user disinterest are not satisfied prior to the first time, the process includes automatically deactivating the virtual assistant session at the first time.