Terminal AI Operation Management via Charging State Detection
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Solution Overview
Problem
Intelligent terminal devices face power consumption issues when performing large-scale artificial intelligence operations, leading to potential power loss and reduced battery life, which can disrupt continuous operation and user experience.
Innovation Solution
A method and terminal configuration that adaptively manage power usage by determining a predetermined charging state, allowing AI operations only when the terminal is in a suitable charging condition, and controlling parameters such as learning rate for machine learning models based on charging parameters to optimize power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a larger-capacity battery is installed to meet power demands for large-scale AI operations, then power supply capacity is improved, but device weight increases and cost increases
Solution Approach 1:
The patent implements dynamic power management by adjusting AI operation parameters (such as model complexity, computation precision, and processing frequency) based on real-time battery status. When battery charge is sufficient, the system performs more intensive AI computations; when battery charge is low, the system reduces computation intensity or switches to lighter models, thereby adapting power consumption to available energy reserves without requiring a larger battery
Solution Approach 2:
The system changes operational parameters of AI tasks based on battery charge levels. Specifically, it adjusts parameters such as the scale of data processing, the complexity of neural network models, and the frequency of inference operations. This allows the device to perform adequate AI functions across different battery states without needing a consistently large power supply capacity
2Productivity
If AI operations are performed during charging to utilize available power, then power consumption efficiency is improved, but battery stability may be compromised
Solution Approach 1:
The system continuously monitors battery charge levels, charging status, and power consumption rates during AI operations. Based on this feedback, it dynamically adjusts the intensity and type of AI computations being performed. If battery charge drops below a threshold during charging, the system automatically reduces computation load to prevent instability, thus maintaining reliability while maximizing productivity during favorable conditions
Solution Approach 2:
The patent implements periodic assessment of battery status during charging phases, interspersing intensive AI operations with monitoring intervals. The system periodically checks whether charging power is sufficient to support current AI tasks and adjusts accordingly, creating a rhythm of computation and monitoring that balances productivity gains with battery stability
Data Source
AI summary
A terminal and a method for managing the terminal are provided. The method includes: obtaining usage data of a user; determining whether the terminal is in a predetermined charging state; and performing an operation related to an artificial intelligence based on the usage data of the user, in response to the terminal being in the predetermined charging state. According to the terminal and the method for managing a terminal, the timing for performing the operation related to artificial intelligence can be adaptively selected to achieve a technical effect of improving the stability of the intelligent operation and reducing the power consumption of the terminal.