Dynamic Polling Schedule for Remote Control Battery Life
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Solution Overview
Problem
Conventional remote control devices face challenges in conserving battery life due to the need for continuous power to maintain connections with multimedia devices, leading to finite battery energy consumption.
Innovation Solution
Implementing a system that generates a polling schedule based on the predicted active or idle mode of the multimedia device using a Bayesian network, allowing the remote control to alternate between low-power standby and high-power awake modes, adjusting polling intervals based on usage probability and battery level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the remote control continuously polls the multimedia device to maintain connection, then the connection reliability is improved, but the battery consumption increases
Solution Approach 1:
The polling interval is made dynamic rather than fixed. The system adjusts the polling frequency based on the predicted usage state of the multimedia device, transitioning between different polling strategies to balance connection reliability and power consumption in real-time
Solution Approach 2:
The system uses usage data and Bayesian prediction to create feedback loops that continuously refine polling decisions. The polling strategy is adjusted based on feedback from predicted usage patterns, allowing the system to maintain reliability when needed while conserving power when the device is likely idle
2Duration of action of moving object
If the remote control reduces polling frequency to conserve battery, then the battery life is extended, but the connection responsiveness deteriorates
Solution Approach 1:
The polling interval dynamically adapts based on predicted usage. When the multimedia device is predicted to be in active mode, the polling frequency increases to maintain responsiveness. When idle mode is predicted, the frequency decreases to extend battery life, creating a dynamic balance between these competing requirements
Solution Approach 2:
The system performs preliminary prediction of usage patterns using Bayesian networks before adjusting polling frequency. This allows the system to proactively optimize polling intervals based on anticipated device activity, preventing both unnecessary power consumption and potential responsiveness delays
3Device complexity
If the remote control uses fixed polling intervals, then the system simplicity is maintained, but the energy efficiency is reduced
Solution Approach 1:
The polling interval parameter is changed from a fixed value to a dynamically adjusted value based on usage predictions. The system modifies this key parameter in response to changing conditions, allowing energy-efficient operation without requiring complete system redesign
Solution Approach 2:
The remote control system autonomously adjusts its own polling behavior based on usage data and predictions. The device self-optimizes its operation without requiring external intervention or complex user configuration, balancing simplicity with energy efficiency
Data Source
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AI summary
System, method and computer program product for determining a polling schedule for a remote control, are described. A multimedia device collects usage data that identifies when the multimedia device is in use. The probability that the multimedia device is in use for a particular time is determined based on the usage data. A polling schedule is generated based on the usage probability such that the periods in the polling schedule vary according to the usage probability to minimize energy consumption. The polling schedule is then transmitted to the remote control where the remote control polls the multimedia device according to the polling schedule.