Multi-terminal data interaction method and system based on Bluetooth communication

Abstract

The invention belongs to the technical field of data interaction, and discloses a multi-terminal data interaction method and system based on Bluetooth communication, and the method comprises the steps: carrying out the analysis of the data interaction proportion of each terminal in a historical period, screening out high-interaction terminals, carrying out the interaction stability analysis of the interaction data size of each high-interaction terminal in different historical periods, and carrying out the analysis of the interaction stability. Therefore, in a multi-terminal data interaction scene based on Bluetooth communication, tasks and resources are reasonably arranged according to the stability of the interaction data volume of each high-interaction terminal in different historical periods, data interaction problems caused by unstable terminal processing capability are avoided, stable interaction terminals are screened out, and the data interaction efficiency is improved. And the stable interaction terminal can be conveniently and emphatically concerned and managed, and the data interaction efficiency and quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data interaction, and particularly to a multi-terminal data interaction method and system based on Bluetooth communication. Background Art

[0002] With the rapid development and wide popularization of Bluetooth technology, multi-terminal data interaction scenarios based on Bluetooth communication have emerged in large numbers in many fields such as smart home, industrial Internet of Things, and mobile office. However, there are many thorny problems in current multi-terminal data interaction.

[0003] In the prior art, there are differences in the data interaction ratio and processing capabilities of different terminals. Some terminals may have abnormal situations that affect the overall interaction efficiency. At the same time, the periodicity of data interaction of each terminal is inconsistent, resulting in problems such as chaos and packet loss during the interaction process, and it is difficult to achieve efficient and stable data interaction; Therefore, on the one hand, it is necessary to analyze the data interaction ratio of each terminal in the historical period, screen out high-interaction terminals, and then perform stability analysis on the interaction data volume of each high-interaction terminal in different historical periods, so as to avoid problems in data interaction caused by unstable terminal processing capabilities in the multi-terminal data interaction scenario based on Bluetooth communication; On the other hand, it is necessary to evaluate whether there is a periodicity when stable interaction terminals perform data interaction, be able to quantify the similarity degree between the interaction period analysis model and the fitting period function model, and perform arbitrary combination of multiple periodic key terminals and perform periodic similarity analysis to obtain a periodic similarity group, and set a polling period, which not only enables the terminals within the periodic similarity group to perform data interaction within a reasonable period, avoids resource waste, improves the overall data interaction efficiency, but also helps the terminals within the group to have better synchronization during data interaction, enhancing the stability of multi-terminal data interaction based on Bluetooth communication. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for integrally and efficiently removing hypophosphite in electroless plating wastewater, so as to solve at least one of the above-mentioned prior art problems.

[0005] In a first aspect, the present invention provides a multi-terminal data interaction method based on Bluetooth communication, including: Performing ratio analysis on the data interaction volume of each terminal in the historical period to obtain high-interaction terminals, and constructing a high-interaction terminal sequence; Performing interaction stability analysis on each high-interaction terminal in the high-interaction terminal sequence, screening out stable interaction terminals, and integrating them into a stable interaction terminal sequence; Performing interaction period analysis on each stable interaction terminal in the stable interaction terminal sequence to evaluate whether there is a periodicity when the stable interaction terminal performs data interaction in the historical period; If there is periodicity, mark the stable interaction terminal as the periodic key terminal, and arbitrarily combine multiple periodic key terminals for combined diagnosis to obtain a periodic similarity group, and further set a polling period for the periodic similarity group.

[0006] A further solution of the present invention is as follows: The process of obtaining the high-interaction terminal sequence is as follows: Divide the historical period into several historical time periods with equal time intervals; Obtain the ratio of the interaction data volume of the terminal in the historical time period to the data processing volume in the corresponding historical time period, and perform averaging processing on the ratios in all historical time periods, output the interaction ratio, and sort the terminals in descending order to obtain the high-interaction terminal sequence.

[0007] A further solution of the present invention is as follows: Analyze the interaction stability of the high-interaction terminal, and the analysis process is as follows: Any high-interaction terminal within the high-interaction terminal sequence; Combine the data interaction volumes in adjacent historical time periods to obtain multiple interaction analysis groups, and input them into the Euclidean distance model respectively, and output the interaction stability value.

[0008] A further solution of the present invention is as follows: The process of obtaining the stable interaction terminal sequence is: If the interaction stability value is less than the interaction stability threshold, mark it as a stable interaction terminal, and sort the corresponding interaction stability values from small to large to obtain the stable interaction terminal sequence.

[0009] A further solution of the present invention is as follows: Analyze the interaction period of the stable interaction terminal, and the process is as follows: Based on the interaction data volume of the stable interaction terminal in all historical time periods, construct an interaction period analysis model, and perform fitting through the least squares method to obtain a fitting period function model; Input the interaction period analysis model and the fitting period function model into the period determination formula, and output the period determination value.

[0010] A further solution of the present invention is as follows: Evaluate whether there is periodicity when the stable interaction terminal performs data interaction, and the process is as follows: If the period determination value is less than or equal to the period determination threshold, generate a terminal period signal and mark it as a periodic key terminal.

[0011] A further solution of the present invention is as follows: Arbitrarily combine multiple periodic key terminals, and the specific process is as follows: Based on the magnitude of the period determination value, sort the periodic key terminals from small to large to obtain the periodic key sequence; Within the periodic key sequence, any two periodic key terminals are arbitrarily combined to obtain a periodic key group.

[0012] A further solution of the present invention is: perform periodic deviation diagnosis on the periodic key terminals within the periodic key group to obtain a periodic similarity group. The process is as follows: From the interaction period analysis model corresponding to the periodic key terminal, respectively extract the distance between adjacent wave peaks and the distance between adjacent wave valleys; Perform averaging processing on all the distances between adjacent wave peaks, output to obtain the adjacent wave peak change period, and respectively input the adjacent wave peak change period corresponding to each periodic key terminal into the Euclidean distance formula, and output to obtain the adjacent wave peak period deviation; Perform averaging processing on all the distances between adjacent wave valleys, output to obtain the adjacent wave valley change period, and respectively input the adjacent wave valley change period corresponding to each periodic key terminal into the Euclidean distance formula, and output to obtain the adjacent wave valley period deviation; Sum the adjacent wave peak period deviation and the adjacent wave valley period deviation, output to obtain the periodic similarity value. If it is less than or equal to the periodic similarity threshold, it is recorded as a periodic similarity group.

[0013] A further solution of the present invention is: set a polling period for the periodic similarity group. The process is as follows: Within the periodic similarity group, perform summation averaging calculation on the periods of the interaction period analysis models corresponding to the periodic key terminals to obtain the polling period.

[0014] In a second aspect, the present invention provides a multi-terminal data interaction system based on Bluetooth communication, including the following modules: Terminal high-traffic analysis module: perform proportion analysis on the data interaction volume of each terminal within the historical period to obtain high-interaction terminals, and construct a high-interaction terminal sequence; High-traffic stability screening module: perform interaction stability analysis on each high-interaction terminal within the high-interaction terminal sequence, screen out stable interaction terminals, and integrate them into a stable interaction terminal sequence; Stable period evaluation module: perform interaction period analysis on each stable interaction terminal within the stable interaction terminal sequence to evaluate whether there is periodicity when the stable interaction terminal performs data interaction within the historical period; Similarity diagnosis setting module: If there is periodicity, record the stable interaction terminal as a periodic key terminal, and arbitrarily combine and diagnose multiple periodic key terminals to obtain a periodic similarity group, and further set a polling period for the periodic similarity group.

[0015] The beneficial effects of the present invention: 1. The present invention analyzes the data interaction proportion of each terminal within a historical period, selects high-interaction terminals, and then conducts interaction stability analysis on the interaction data volume of each high-interaction terminal in different historical time periods. Thus, in the multi-terminal data interaction scenario based on Bluetooth communication, according to the stability of the interaction data volume of each high-interaction terminal in different historical time periods, tasks and resources are reasonably arranged to avoid problems in data interaction caused by unstable terminal processing capabilities. Moreover, screening out stable interaction terminals also facilitates focusing on and managing stable interaction terminals, improving the efficiency and quality of data interaction. 2. The present invention evaluates whether there is a periodicity when stable interaction terminals conduct data interaction, can quantify the similarity degree between the interaction period analysis model and the fitting periodic function model, accurately capture the periodic change law of data interaction, and thus distinguish periodic key terminals and non-periodic key terminals, providing strong data support for the targeted optimization and management of stable interaction terminals. Arbitrarily combining multiple periodic key terminals and conducting periodic similarity analysis to obtain a periodic similarity group and setting a polling period not only enables the terminals within the periodic similarity group to conduct data interaction within a reasonable period, avoiding resource waste and improving the overall data interaction efficiency, but also helps the terminals within the group to have better synchronization during data interaction, enhancing the stability of multi-terminal data interaction based on Bluetooth communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for description in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 is a flowchart of the multi-terminal data interaction method based on Bluetooth communication of the present invention; Figure 2 is a module diagram of the multi-terminal data interaction system based on Bluetooth communication of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] Embodiment 1 As Figure 1As shown in the figure, the multi-terminal data interaction method based on Bluetooth communication provided by the embodiment of the present invention specifically includes the following steps: Step 1: Based on the historical data processing reports of multiple terminals, perform a proportion analysis on the data interaction volume of each terminal within the historical period to obtain a high-interaction terminal sequence; In some embodiments, the terminal historical data processing report can be obtained by SQL (Structured Query Language), and the specific obtaining process is as follows: By writing an SQL query statement, use the SELECT statement to select the required columns, such as terminal ID, processing time, processed data volume, etc., use the WHERE clause to filter Bluetooth communication-related data, group by terminal using GROUP BY, sort using ORDER BY, and finally export the query result to the required format of the report, such as CSV or Excel, to generate the terminal historical data processing report; Among them, the terminal historical data processing report includes data processing volume, data interaction volume, etc.; Divide the historical period into several historical time periods with equal time intervals; Arbitrarily select a terminal; According to the terminal historical data processing report, obtain the proportion of the interaction data volume of the terminal in each historical time period to the data processing volume, and perform an averaging calculation to output the interaction proportion; Compare the interaction proportions corresponding to the terminals and sort them in descending order to obtain a high-interaction terminal sequence; Step 2: Perform an interaction stability analysis on each terminal in the high-interaction terminal sequence, screen out the stable interaction terminals, and integrate them into a stable interaction terminal sequence; Within the high-interaction terminal sequence, obtain the interaction data volume of the terminal in each historical time period, and combine the interaction data volumes in adjacent historical time periods to obtain multiple interaction analysis groups; Input the multiple interaction analysis groups into the Euclidean distance model respectively, and output the interaction stability value ; Specifically, the Euclidean distance model is: , where represents the total number of interaction analysis groups, represents the interaction data volume in the th historical time period, represents the interaction data volume in the Specifically, the purpose of the Euclidean distance model outputting the interaction stability value is: The Euclidean distance model is used to quantify the distance between two data points. When processing the historical data of the terminal, the amount of interaction data within adjacent historical time periods is combined as a data point, and the distance (degree of difference) between the amounts of interaction data within adjacent historical time periods is calculated through the Euclidean distance formula, so as to be able to reflect the difference in the amount of interaction data between adjacent time periods, thereby meeting the stability evaluation of the data interaction volume of the terminal in different historical time periods; It can be understood that the meaning represented by the interaction stability value is: from a numerical perspective, the interaction stability value reflects the fluctuation of the amount of interaction data of the terminal in different historical time periods. From the perspective of the terminal's interaction ability, it reflects that the ability of the high-interaction terminal to perform interaction data is relatively stable, which helps to ensure the reliability of the entire terminal data interaction process in the terminal data interaction of Bluetooth communication; Compare the interaction stability value with the interaction stability threshold, and the process is as follows: If the interaction stability value is greater than or equal to the interaction stability threshold, it means that the ability of the high-interaction terminal to perform interaction data is relatively unstable, and it is recorded as an unstable interaction terminal; If the interaction stability value is less than the interaction stability threshold, it means that the ability of the high-interaction terminal to perform interaction data is relatively stable, and it is recorded as a stable interaction terminal; Sort the interaction stability values corresponding to the stable interaction terminals from small to large to obtain a stable interaction terminal sequence; The technical solution of this embodiment is: analyze the data interaction ratio of each terminal within the historical cycle, screen out the high-interaction terminals, and then perform interaction stability analysis on the amount of interaction data of each high-interaction terminal in different historical time periods. Thus, in the multi-terminal data interaction scenario based on Bluetooth communication, according to the stability of the amount of interaction data of each high-interaction terminal in different historical time periods, tasks and resources are reasonably arranged to avoid problems in data interaction caused by unstable terminal processing capabilities. Moreover, screening out stable interaction terminals also facilitates focusing on and managing stable interaction terminals, improving the efficiency and quality of data interaction.

[0020] Embodiment 2 Such as Figure 1 shown, the multi-terminal data interaction method based on Bluetooth communication provided by the embodiment of the present invention further includes the following steps: Step 3: Analyze multiple stable interaction terminals within the stable interaction terminal sequence, evaluate whether there is a periodicity when the stable interaction terminals perform data interaction, and obtain an evaluation result; Among them, the evaluation result includes a terminal periodic signal or a terminal aperiodic signal; In some embodiments, taking the X-axis as time and the Y-axis as the amount of interaction data in historical periods, the amount of interaction data of the stable interaction terminal in all historical periods is respectively substituted into a two-dimensional coordinate system according to the time series of historical periods to construct an interaction cycle analysis model; Based on the interaction cycle analysis model, fitting is performed by the least squares method to obtain a fitting cycle function model; It should be noted that the fitting cycle function model includes, but is not limited to, a sine function model and a cosine function model; Specifically, the process of the fitting cycle function model is as follows: S1, extract the maximum amount of interaction data and the minimum amount of interaction data of the stable interaction terminal in the historical cycle, and input them into the amplitude calculation formula, and output to obtain the amplitude ; More specifically, , where represents the minimum amount of interaction data of the stable interaction terminal in the historical cycle, represents the maximum amount of interaction data of the stable interaction terminal in the historical cycle; S2, in the interaction cycle analysis model, respectively extract the distance between adjacent wave peaks and the distance between adjacent wave valleys; Perform standard deviation processing on all the distances between adjacent wave peaks to obtain the adjacent wave peak difference value; Perform standard deviation processing on all the distances between adjacent wave valleys to obtain the adjacent wave valley difference value; If the adjacent wave peak difference value is greater than the adjacent wave valley difference value, it means that the difference degree of the distances between adjacent wave valleys is smaller and more approaches periodic change, then perform averaging processing on all the distances between adjacent wave valleys, and output to obtain the period ; If the adjacent wave peak difference value is less than the adjacent wave valley difference value, it means that the difference degree of the distances between adjacent wave peaks is smaller and more approaches periodic change, then perform averaging processing on all the distances between adjacent wave peaks, and output to obtain the period ; If the adjacent wave peak difference value is equal to the adjacent wave valley difference, it means that the difference degree of the distances between adjacent wave valleys and the difference degree of the distances between adjacent wave peaks are both smaller and both more approach periodic change, then arbitrarily perform averaging processing on the distances between adjacent wave peaks or the distances between adjacent wave valleys, and output to obtain the period ; S3, input the maximum amount of interaction data and the minimum amount of interaction data of the stable interaction terminal in the historical cycle into the vertical offset calculation formula, and output to obtain the vertical offset amount ; More specifically, the vertical offset calculation formula: , where represents the minimum interaction data volume of the terminal within the historical period, and represents the maximum interaction data volume of the terminal within the historical period; S4. Extract the starting coordinates within the interaction period analysis model and, together with the amplitude , period , and vertical offset , input them into the fitting period function model, and output to obtain the phase ; S5. Based on the amplitude , period , vertical offset , and phase , construct a fitting period function model; Extract the Y coordinates of all the peak and trough points on the interaction period analysis model, perform standard deviation processing, and output to obtain the analysis standard deviation ; Similarly, extract the coordinates of all the peak and trough points on the fitting period function model, perform standard deviation processing, and output to obtain the fitting standard deviation ; Obtain the model covariance Cov between the interaction period analysis model and the fitting period function model; Input the analysis standard deviation , the fitting standard deviation , and the model covariance Cov into the period determination formula respectively, and output to obtain the period determination value ; Specifically, the period determination formula: It should be noted that the period determination formula is improved based on the Pearson correlation coefficient calculation formula, which can quantify the similarity degree between the interaction period analysis model and the fitting period function model, thereby capturing the periodic change law in the interaction period analysis model, helping to accurately identify the terminals with obvious periodic data interaction among many terminals, and accurately screening out the stable interaction terminals with periodic changes from multiple stable interaction terminals, providing data support for the targeted optimization and management of stable interaction terminals; It can be understood that the meaning represented by the period determination value is: quantifying the similarity degree between the interaction period analysis model and the fitting period function model, helping to capture the periodic change law in the interaction period analysis model when evaluating whether there is periodicity in the data interaction of stable interaction terminals, and then screening out the stable interaction terminals with periodic changes, providing data support for subsequent targeted optimization and management; Compare the period determination value with the period determination threshold, and the process is as follows: If the period determination value is less than or equal to the period determination threshold, it indicates that the periodic change in the interaction period analysis model is highly similar to the periodic change in the fitted periodic function model. Generate a terminal periodic signal and mark it as a periodic key terminal; If the period determination value is greater than the period determination threshold, it indicates that the periodic change in the interaction period analysis model is less similar to the periodic change in the fitted periodic function model. Generate a terminal aperiodic signal and mark it as an aperiodic key terminal; Step Four: Arbitrarily combine multiple periodic key terminals for diagnosis to obtain a period similarity group, and further set a polling period for the period similarity group; In some embodiments, sort the periodic key terminals in ascending order of the period determination value to obtain a periodic key sequence; Within the periodic key sequence, arbitrarily combine two periodic key terminals to obtain a periodic key group; Perform period deviation analysis on the interaction period analysis model corresponding to the periodic key terminals within the periodic key group, and the execution process is as follows: On the interaction period analysis model corresponding to any one periodic key terminal, extract the distance between adjacent wave peaks and the distance between adjacent wave valleys respectively; Average all the distances between adjacent wave peaks and output the adjacent wave peak change period; Input the adjacent wave peak change period corresponding to each periodic key terminal within the periodic key group into the Euclidean distance formula respectively, and output the adjacent wave peak period deviation ; Specifically, the Euclidean distance formula: , where represents the adjacent wave peak change period corresponding to one of the periodic key terminals within the periodic key group, represents the adjacent wave peak change period corresponding to another periodic key terminal within the periodic key group, and and are corresponding in the time dimension. m represents the total number of adjacent wave peak change periods, and the total number of adjacent wave peak change periods corresponding to each periodic key terminal within the periodic key group is the same; Average all the distances between adjacent wave valleys and output the adjacent wave valley change period; Input the adjacent wave valley change period corresponding to each periodic key terminal within the periodic key group into the Euclidean distance formula respectively, and output the adjacent wave valley period deviation ; Specifically, the Euclidean distance formula: , where It is expressed as the adjacent trough change period corresponding to one of the periodic key terminals within the periodic key group, and is expressed as the adjacent trough change period corresponding to another periodic key terminal within the periodic key group, and is corresponding in the time dimension. m represents the total number of adjacent trough change periods, and the total number of adjacent trough change periods corresponding to each periodic key terminal within the periodic key group is the same; Sum the adjacent peak period deviation and the adjacent trough period deviation to output the period similarity value; If the period similarity value is less than or equal to the period similarity threshold, mark the analyzed periodic key group as a period similarity group; If the period similarity value is greater than the period similarity threshold, recombine with the remaining periodic key terminals until the period similarity value corresponding to the recombined periodic key group is less than or equal to the period similarity threshold; Within the period similarity group, sum and average the periods of the periodic key terminal corresponding to the interactive period analysis model to obtain the polling period; The specific solution of this embodiment is as follows: evaluating whether there is periodicity in the data interaction of stable interactive terminals can quantify the similarity degree between the interactive period analysis model and the fitting period function model, accurately capture the periodic change law of data interaction, thereby distinguishing periodic key terminals and non-periodic key terminals, providing strong data support for the targeted optimization and management of stable interactive terminals. Arbitrarily combine multiple periodic key terminals, conduct period similarity analysis, obtain a period similarity group, and set a polling period. This not only enables the terminals within the period similarity group to perform data interaction within a reasonable period, avoids resource waste, improves the overall data interaction efficiency, but also helps the terminals within the group to have better synchronization during data interaction, enhancing the stability of multi-terminal data interaction based on Bluetooth communication.

[0021] Embodiment Three As Figure 2 shown, the multi-terminal data interaction system based on Bluetooth communication provided by the embodiment of the present invention includes the following modules: Terminal High Interaction Analysis Module: Analyze the proportion of the data interaction volume of each terminal within the historical period to obtain high-interaction terminals and construct a high-interaction terminal sequence; High Interaction Stability Screening Module: Conduct interaction stability analysis on each high-interaction terminal within the high-interaction terminal sequence, screen out stable interactive terminals, and integrate them into a stable interactive terminal sequence; Stable Period Evaluation Module: Analyze the interaction period of each stable interaction terminal in the stable interaction terminal sequence to evaluate whether there is periodicity in data interaction of the stable interaction terminal in the historical period; Similar Diagnosis Setting Module: If there is periodicity, mark the stable interaction terminal as a key terminal of the period, and arbitrarily combine multiple key terminals of the period for combined diagnosis to obtain a period similarity group, and further set a polling period for the period similarity group.

[0022] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A multi-terminal data interaction method based on Bluetooth communication, characterized in that, It includes the following steps: Conduct a proportion analysis on the data interaction volume of each terminal within the historical period to obtain high-interaction terminals, and construct a high-interaction terminal sequence; Conduct an interaction stability analysis on each high-interaction terminal within the high-interaction terminal sequence, screen out stable interaction terminals, and integrate them into a stable interaction terminal sequence; Conduct an interaction cycle analysis on each stable interaction terminal within the stable interaction terminal sequence to evaluate whether there is periodicity when the stable interaction terminal conducts data interaction within the historical period; If there is periodicity, mark the stable interaction terminal as a periodic key terminal, arbitrarily combine multiple periodic key terminals for diagnosis to obtain a periodic similarity group, and further set a polling cycle for the periodic similarity group.

2. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, wherein The process of obtaining the high-interaction terminal sequence is as follows: Divide the historical period into several historical time intervals with equal time intervals; Obtain the ratio of the interaction data volume of the terminal within the historical time interval to the data processing volume within the corresponding historical time interval, perform an averaging process on the ratios within all historical time intervals, output the interaction proportion, sort the terminals in descending order, and obtain the high-interaction terminal sequence.

3. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, wherein Conduct an interaction stability analysis on the high-interaction terminals. The analysis process is as follows: Any high-interaction terminal within the high-interaction terminal sequence; Combine the interaction data volumes within adjacent historical time intervals to obtain multiple interaction analysis groups, and input them into the Euclidean distance model respectively, and output the interaction stability value.

4. The multi-terminal data interaction method based on Bluetooth communication according to claim 3, wherein The process of obtaining the stable interaction terminal sequence is: If the interaction stability value is less than the interaction stability threshold, mark it as a stable interaction terminal, and sort the corresponding interaction stability values from small to large to obtain the stable interaction terminal sequence.

5. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, wherein Conduct an interaction cycle analysis on the stable interaction terminals. The process is as follows: Based on the interaction data volume of the stable interaction terminal in all historical time intervals, construct an interaction cycle analysis model, and perform fitting through the least squares method to obtain a fitting cycle function model; Input the interaction cycle analysis model and the fitting cycle function model into the cycle determination formula to output the cycle determination value.

6. The multi-terminal data interaction method based on Bluetooth communication according to claim 5, wherein The process of evaluating whether there is periodicity when the stable interaction terminal conducts data interaction is as follows: If the cycle determination value is less than or equal to the cycle determination threshold, generate a terminal cycle signal and mark it as a periodic key terminal.

7. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, wherein, Arbitrarily combine multiple periodic key terminals. The specific process is as follows: Sort the periodic key terminals from small to large based on the magnitude of the cycle determination value to obtain a periodic key sequence; Within the periodic key sequence, arbitrarily combine two periodic key terminals to obtain a periodic key group.

8. The multi-terminal data interaction method based on Bluetooth communication according to claim 7, wherein Conduct a cycle deviation diagnosis on the periodic key terminals within the periodic key group to obtain a periodic similarity group. The process is as follows: Extract the distance between adjacent wave peaks and the distance between adjacent wave valleys respectively from the interaction cycle analysis model corresponding to the periodic key terminal; Perform an averaging process on all the distances between adjacent wave peaks, output the adjacent wave peak change period, and input the adjacent wave peak change period corresponding to each periodic key terminal into the Euclidean distance formula respectively to output the adjacent wave peak period deviation; Average the distances between all adjacent wave troughs, output the adjacent wave trough change period, and input the adjacent wave trough change periods corresponding to the key terminals of each period into the Euclidean distance formula respectively, and output the adjacent wave trough period deviation; Sum the adjacent wave peak period deviation and the adjacent wave trough period deviation, output the period similarity value, and if it is less than or equal to the period similarity threshold, it is recorded as a period similarity group.

9. The multi-terminal data interaction method based on Bluetooth communication according to claim 8, characterized in that Set a polling period for the period similarity group, and the process is as follows: Within the period similarity group, calculate the sum average of the periods of the interaction period analysis model corresponding to the key terminals of the period to obtain the polling period.

10. A multi-terminal data interaction system based on Bluetooth communication, characterized in that, It includes the following modules: Terminal high-traffic analysis module: Analyze the proportion of the data interaction volume of each terminal in the historical period to obtain high-interaction terminals, and construct a high-interaction terminal sequence; High-traffic stable screening module: Analyze the interaction stability of each high-interaction terminal in the high-interaction terminal sequence, screen out the stable interaction terminals, and integrate them into a stable interaction terminal sequence; Stable period evaluation module: Analyze the interaction period of each stable interaction terminal in the stable interaction terminal sequence to evaluate whether there is periodicity when the stable interaction terminal conducts data interaction in the historical period; Similar diagnosis setting module: If there is periodicity, record the stable interaction terminal as a key terminal of the period, and arbitrarily combine multiple key terminals of the period for diagnosis to obtain a period similarity group, and further set a polling period for the period similarity group.

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