Intelligent Device Control via Predictive Environment Adjustment
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Solution Overview
Problem
Users face inconvenience due to the complex manual process of controlling intelligent devices, which requires attention to time and environment state adjustments.
Innovation Solution
A method and device that acquire current time and environment state, determine the required running time to adjust the environment to a target state, and control the device based on this information, using historical data to calculate weighted values for environment states and times to simplify the control process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual control process is used for intelligent devices, then user can control the device operation, but the control process becomes complicated and brings inconvenience to users
Solution Approach 1:
The system automatically monitors environment states, calculates running times, and triggers device control without user intervention. The control device performs self-service by autonomously determining when and how to adjust environmental parameters based on pre-set rules and real-time sensor data.
Solution Approach 2:
The system pre-calculates the running time required to transition between environment states before actual control action is needed. By determining the required duration in advance based on historical data and current conditions, the system prepares control parameters ahead of time, simplifying the actual control execution.
2Measurement precision
If the system calculates running time based on historical environment states with weighted values, then the control accuracy is improved, but the calculation process becomes more complex
Solution Approach 1:
The system incorporates feedback mechanisms by continuously monitoring current environment states, comparing them with historical data, and adjusting weighted values based on prediction accuracy. This feedback loop refines the calculation model over time, improving precision while managing complexity through iterative optimization.
Solution Approach 2:
The system dynamically adjusts weighted values for different historical environment states based on their relevance and recency. By changing these parameters adaptively rather than using fixed weights, the system achieves higher prediction accuracy while maintaining a manageable calculation framework through focused parameter optimization.
Data Source
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AI summary
The present disclosure relates to a method and device for controlling an intelligent device and belongs to the field of intelligent household appliances. The method may include: acquiring (101) a current time and a current environment state; determining (102) a running time required to adjust the current environment state to a first target environment state, the first target environment state being an environment state at a target time, the target time being a time for controlling the intelligent device; and controlling (103) the intelligent device based on the current time, the running time and the target time. In the present disclosure, an intelligent device may be controlled automatically. The control process is simple, and the operation overhead for a user is decreased. [FIG. 1]