AI-Based Hardware Parameter Control for Application Busyness
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Solution Overview
Problem
Computers often operate with suboptimal hardware efficiency and power consumption due to uniform hardware settings regardless of the applications being executed and their operating status.
Innovation Solution
An electronic device employs AI technology to detect the operating status of applications and dynamically adjust hardware parameters such as processor frequency, memory allocation, and frame refresh rate based on the detected status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the computer adopts the same hardware setting regardless of the applications being executed and the operating status, then the hardware setting remains stable and simple to manage, but the computer will not produce best hardware efficiency and best power saving effect
Solution Approach 1:
The patent implements dynamic hardware parameter adjustment based on application operating status. The system continuously monitors application behavior and dynamically changes hardware parameters (such as CPU frequency, memory allocation) to match the current workload requirements, transitioning from static to adaptive hardware configuration.
Solution Approach 2:
The patent employs a feedback mechanism where the system monitors application execution status and uses this information to adjust hardware parameters. The identification model analyzes application behavior patterns and provides feedback signals that trigger hardware parameter changes, creating a closed-loop control system for optimal performance.
2Loss of energy
If the computer adopts the same hardware setting regardless of the applications being executed and the operating status, then the system remains stable and easy to control, but the computer will not produce best power saving effect
Solution Approach 1:
The patent enables the system to automatically monitor and adjust its own hardware parameters based on application execution status. The identification model and control system work autonomously to detect application behavior patterns and trigger appropriate hardware parameter changes without requiring manual user intervention.
Solution Approach 2:
The patent changes hardware parameters dynamically based on application operating status. The system adjusts parameters such as processor frequency, memory allocation, and power states according to the detected application behavior, transitioning from fixed parameter settings to adaptive parameter changes.
3Productivity
If AI technology is used to detect application operating status and dynamically adjust hardware parameters, then hardware efficiency and power saving are optimized, but the system complexity and detection requirements increase
Solution Approach 1:
The patent introduces an identification model as an intermediary between application execution and hardware parameter adjustment. This intermediary component analyzes application behavior patterns and translates them into meaningful operating status indicators that trigger appropriate hardware parameter changes, simplifying the detection process.
Solution Approach 2:
The patent implements continuous interception of input signals during a detection period to preliminarily analyze application behavior patterns before making hardware parameter adjustments. This preliminary detection phase allows the system to build a understanding of application characteristics and predict optimal hardware configurations in advance.
Data Source
AI summary
An electronic device and a smart control method thereof are provided. The electronic device includes an application management unit, an interception unit, an identification model, and a control unit. The application management unit is used to detect an application being executed by the electronic device. The interception unit is used to continuously intercept at least one input unit during a detection period to obtain a plurality of input signals and a plurality of time information corresponding to the input signals. The identification model is used to receive the application, the input signals, and the time information corresponding to the input signals to output an operating status of the application. The operating status includes a busyness level. The control unit is used to control at least one hardware parameter of the electronic device according to the application and the operating status thereof.