Predictive Processor Startup for Power-Constrained Embedded Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Embedded devices, such as smartwatches and smartphones, face challenges in efficiently presenting relevant information on limited screens while conserving battery power, especially when handling rich media interfaces for calendar events and natural light-related activities like sunrise and sunset times.
Innovation Solution
An apparatus with multiple processor cores is used to predict the need for a rich media interface based on calendar events, triggering the startup of a higher capability processing device at optimal times, allowing for power-saving hibernation states and efficient information presentation on a limited-size screen by integrating sunset and sunrise times into a timeline interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a higher capability processing device is continuously active to handle rich media interfaces and calendar applications, then information presentation capability is improved, but battery power consumption increases
Solution Approach 1:
The system predicts future user needs for rich media interfaces based on calendar events and proactively activates the higher capability processing device before it is actually needed. This allows the device to be ready when the user needs it, while still allowing the lower power mode to operate for extended periods between predictions, thus reducing overall power consumption.
Solution Approach 2:
The system dynamically transitions between two operational modes: a low power mode using a basic processing device, and a high performance mode using a higher capability processing device. The transition is triggered by predictions based on calendar events, allowing the system to adapt its resource usage to actual user needs rather than maintaining constant high performance.
2Loss of information
If a larger screen is used to present more information for calendar applications, then information quantity is improved, but device size and power consumption increase
Solution Approach 1:
The system predicts when the user will need access to rich calendar information and activates the higher capability processing device in advance. This allows the full information presentation capability to be available when needed, while the device can operate in a lower power state with reduced information display capabilities during periods when calendar access is not predicted to be needed.
3Loss of time
If the higher capability processing device is activated earlier to ensure readiness for rich media interface, then response time is improved, but battery power consumption increases
Solution Approach 1:
The system uses calendar event data to predict when the user will need rich media interface capabilities and activates the higher capability processing device at an optimally calculated time before the predicted need. This balances the trade-off between having the device ready when needed and minimizing the duration of high power consumption.
Solution Approach 2:
The system continuously monitors calendar applications and user behavior patterns to refine its predictions about when rich media interface capabilities will be needed. This feedback mechanism allows the system to progressively improve its timing for activating the higher capability processing device, optimizing the balance between response time and power consumption.
Data Source
AI summary
According to an example aspect of the present invention, there is provided apparatus comprising at least one processing core, at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processing core, cause the apparatus at least to cause the apparatus to predict, based at least in part on a calendar application, a need for a rich media interface and to trigger startup of a higher capability processing device from among a low capability processing device and the higher capability processing device in the apparatus at a time that is selected based on the prediction.