Dynamic Power Management for Mobile Platforms Using Sensor Activity Prediction
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Solution Overview
Problem
Mobile computing devices face limited battery life due to inefficient power management, as existing methods require manual switching between power modes, leading to reduced utility during low-power states like standby or hibernation, where the CPU is powerless and unable to execute instructions.
Innovation Solution
A user-activity-based dynamic power management system that monitors sensor values to predict user states and automatically adjusts power management policies, switching between power modes based on detected activities, such as mouse movement, keyboard activity, and application usage, to optimize power consumption and extend battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the device enters low-power states (Stand-by/Hibernate) to conserve battery power, then power consumption is reduced, but system utility is lost because the CPU cannot execute instructions
Solution Approach 1:
The patent implements dynamic power management that automatically adjusts power states based on detected user activity patterns. The system transitions between active and low-power states dynamically rather than requiring manual user intervention, optimizing the balance between power consumption and system utility based on real-time sensor data and usage patterns.
Solution Approach 2:
The system performs self-monitoring through sensors and self-adjustment of power states without requiring manual user input. The power management subsystem autonomously detects user presence and activity levels, then automatically transitions the device to appropriate power states, making the system self-regulating regarding power consumption and utility.
2Adaptability or versatility
If manual switching between power modes is required, then power management control is provided, but user convenience is reduced and system utility is compromised during transitions
Solution Approach 1:
The system autonomously monitors user activity through sensors and automatically selects appropriate power modes without requiring manual user switching. The power management subsystem serves itself by detecting usage patterns and making intelligent decisions about power state transitions, eliminating the need for manual user intervention while maintaining adaptability to different usage scenarios.
Solution Approach 2:
The system continuously monitors user activity through sensors and uses this feedback to dynamically adjust power management decisions. The feedback loop enables the system to adapt power modes based on real-time detection of user presence, device handling, and application usage, providing both adaptability and user convenience through automated responsive control.
Data Source
AI summary
A method and apparatus for user activity-based dynamic power management and policy creation for mobile platforms are described. In one embodiment, the method includes the monitoring of one or more sensor values of a mobile platform device to gather sensor activity data. Once the sensor activity data is gathered, the user state may be predicted according to the gathered user activity and an updated user state model. In one embodiment, the user state model is updated according to the sensor activity data. In one embodiment, a switch occurs from the present power management policy to a new power management policy if the new user state differs from a present user state by a predetermined amount. In one embodiment, at least one time-out parameter of a selected power management policy may be adjusted to comply with a predicted user state. Other embodiments are described and claimed.