IoT Router Apparatus Recognition via Priority-Based Parameter Sequencing
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Solution Overview
Problem
Current IoT router systems are inefficient in recognizing apparatuses due to the need to try multiple communication parameters sequentially, leading to time-consuming connections.
Innovation Solution
A method and device that utilize a combined sequence table to prioritize communication parameters based on historical occurrence numbers, allowing for sequential message sending according to priority levels to improve recognition efficiency and reduce recognition time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the router tries all communication parameters sequentially to establish connection, then the connection can be established, but the recognition time is long and efficiency is low
Solution Approach 1:
The system pre-collects and stores historical occurrence numbers of communication parameters in a combined sequence table before actual connection attempts. This preliminary data preparation allows the router to prioritize parameters with higher historical success rates, avoiding random or sequential trial-and-error approaches during actual device recognition.
Solution Approach 2:
The system changes the order of communication parameter attempts based on historical occurrence numbers. Instead of using a fixed sequential order or random selection, the parameters are dynamically reordered according to their historical performance data, optimizing the probability of successful connection while reducing recognition time.
2Reliability
If the router tries multiple communication parameter combinations, then the correct combination can be found, but the recognition process is inefficient and time consuming
Solution Approach 1:
Historical occurrence numbers are pre-calculated and stored in the combined sequence table, providing a ready-to-use prioritization guide for communication parameter attempts. This eliminates the need for real-time analysis during device recognition, improving processing speed while maintaining detection accuracy.
Solution Approach 2:
The system uses historical feedback data (occurrence numbers from previous successful connections) to guide future connection attempts. By analyzing past connection outcomes and storing this feedback in the combined sequence table, the system continuously improves its parameter selection strategy, achieving both high reliability and efficiency.
Data Source
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AI summary
Method and device for recognizing an apparatuses and computer readable storage medium and program are provided, the method includes reading a combined sequence table including candidate device information, candidate communication parameters and historical occurrence numbers of combinations of the candidate device information and the candidate communication parameters for each candidate device information; determining priority levels of the combinations according to the historical occurrence numbers; and determining a current combination according to the priority levels, sending a message to the apparatus to be recognized by using a candidate communication parameter in the current combination, and determining whether the current combination is the correct combination capable of establishing a communication with the apparatus to be recognized according to a feedback from the apparatus to be recognized. The recognition efficiency may be improved effectively and the recognition time may be shortened significantly through the method.