Battery Optimization Using Priority-Based Rule Engine
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Solution Overview
Problem
Consumer electronic devices face battery power limitations, especially when performing critical tasks over extended periods, leading to battery drain and potential loss of crucial information, due to inadequate optimization of battery usage based on energy levels, processing power, and communication network bandwidth.
Innovation Solution
A method and system that determine the criticality of the environment and process sensor data locally using a priority-based rule engine, optimizing battery usage by adjusting parameters such as image resolution, compression, and transmission rate based on energy levels, processing power, and communication bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If computation is reduced at the electronic device to conserve battery power, then battery consumption decreases, but the amount of data to be transmitted increases, causing data transmission to consume more battery power
Solution Approach 1:
The patent segments data processing into two parts: critical data is processed locally at the electronic device, while non-critical data is transmitted for remote processing. This segmentation allows the device to reduce overall computation while maintaining essential local processing capabilities, thereby reducing battery consumption without significantly increasing transmission volume.
Solution Approach 2:
The patent dynamically changes processing parameters based on battery energy levels. When energy is sufficient, more data is processed locally; when energy is low, more data is transmitted for remote processing. This parameter adjustment optimizes the balance between local computation and data transmission to minimize overall battery consumption.
2Use of energy by moving object
If processing power of the electronic device is reduced to conserve battery power, then battery consumption decreases, but the time required to perform computations increases, consuming more battery power
Solution Approach 1:
The patent implements dynamic processing power adjustment based on real-time battery energy levels and task criticality. The processing power is not fixed but adapts continuously, increasing when energy is abundant and decreasing when energy is low. This dynamic approach optimizes the balance between processing speed and energy consumption.
Solution Approach 2:
The patent introduces a cloud-based processing intermediary that handles non-critical computations. This intermediary allows the electronic device to offload time-consuming tasks without requiring high local processing power, thereby reducing battery consumption while maintaining acceptable computation times through distributed processing.
3Reliability
If the electronic device processes all sensor data locally to ensure critical task completion, then task reliability is improved, but battery power is drained rapidly
Solution Approach 1:
The patent applies local quality by processing different types of data with different quality levels locally. Critical data requiring high reliability is processed locally with high computational effort, while non-critical data is processed with lower effort or transmitted for remote processing. This differentiated approach maintains task reliability for critical functions while reducing overall battery consumption.
Data Source
AI summary
A method and a system are provided for optimizing battery usage of an electronic device. The method comprises determining, by a battery optimization unit, a degree of criticality of environment in which one or more sensors are operating based on one or more pre-defined conditions. The method further comprises determining, by the battery optimization unit, a plurality of parameters comprising an energy level of the electronic device, an available processing power, and an available communication network bandwidth associated with the electronic device. The method further comprises processing, by the battery optimization unit, a first portion of sensor data locally based on the degree of criticality of environment and a priority based rule engine, wherein the priority based rule engine is configured to optimize battery usage of the electronic device based on the plurality of parameters.