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

Abstract

The application belongs to the technical field of data interaction, and is a multi-terminal data interaction method and system based on Bluetooth communication, which analyzes the data interaction proportion of each terminal in a historical period, screens high interaction terminals, and then analyzes the interaction stability of the interaction data amount of each high interaction terminal in different historical periods, so that in the multi-terminal data interaction scene based on Bluetooth communication, according to the stability of the interaction data amount of each high interaction terminal in different historical periods, the task and resources are reasonably arranged, the problem of data interaction caused by unstable terminal processing capacity is avoided, and the stable interaction terminal is screened out, which is also convenient for focusing on and managing the stable interaction terminal, and improves the efficiency and quality of data interaction.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data interaction, in particular to a multi-terminal data interaction method and system based on Bluetooth communication. BACKGROUND

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

[0003] In the prior art, the data interaction proportion and processing capacity of different terminals are different, and some terminals may appear abnormal conditions to affect the overall interaction efficiency. At the same time, the periodicity of each terminal data interaction is inconsistent, which can easily cause confusion, packet loss and other problems in the interaction process, and it is difficult to realize efficient and stable data interaction.

[0004] Therefore, on the one hand, the data interaction proportion of each terminal in the historical period needs to be analyzed to screen out high interaction terminals, and then the interaction data volume of each high interaction terminal in different historical periods needs to be analyzed for stability, so as to avoid problems in data interaction caused by unstable terminal processing capacity in the multi-terminal data interaction scenario based on Bluetooth communication.

[0005] On the other hand, it is necessary to evaluate whether there is periodicity when the stable interaction terminal performs data interaction, to quantify the similarity between the interaction period analysis model and the fitted period function model, to arbitrarily combine multiple periodic key terminals, to perform periodic similarity analysis, to obtain a periodic similar group, and to set a polling period. Not only can the terminals in the periodic similar group perform data interaction in a reasonable period to avoid resource waste and improve the overall data interaction efficiency, but also can help the terminals in the group to be better synchronized during data interaction, thereby enhancing the stability of multi-terminal data interaction based on Bluetooth communication. SUMMARY

[0006] The present application aims to provide a multi-terminal data interaction method and system based on Bluetooth communication to solve at least one of the above-mentioned problems in the prior art.

[0007] In a first aspect, the present application provides a multi-terminal data interaction method based on Bluetooth communication, comprising:

[0008] The data interaction amount of each terminal in the historical period is analyzed for proportion to obtain high interaction terminals, and a high interaction terminal sequence is constructed.

[0009] The interaction stability of each high interaction terminal in the high interaction terminal sequence is analyzed to screen out stable interaction terminals, and the stable interaction terminals are integrated into a stable interaction terminal sequence.

[0010] Periodicity analysis is performed on each stable interaction terminal in the stable interaction terminal sequence, to evaluate whether the stable interaction terminal has periodicity when performing data interaction in the historical period.

[0011] If the periodicity exists, the stable interaction terminal is recorded as a periodic key terminal, and a plurality of periodic key terminals are combined for diagnosis to obtain a periodic similar group, and a polling period is further set for the periodic similar group.

[0012] As a further scheme of the application, the process for obtaining the high interaction terminal sequence is as follows:

[0013] The historical period is divided into a plurality of historical time intervals with equal time intervals.

[0014] The proportion of the interaction data amount of the terminal in the corresponding historical time interval to the data processing amount in the historical time interval is obtained, and the proportions in all historical time intervals are averaged to obtain an interaction proportion, and the terminal is sorted in descending order of the interaction proportion to obtain the high interaction terminal sequence.

[0015] As a further scheme of the application, the process for obtaining the high interaction terminal sequence is as follows:

[0016] Any high interaction terminal in the high interaction terminal sequence;

[0017] The data interaction amounts in adjacent historical time intervals are combined to obtain a plurality of interaction analysis groups, which are respectively input into the Euclidean distance model to output an interaction stability value.

[0018] As a further scheme of the application, the process for obtaining the high interaction terminal sequence is as follows:

[0019] If the interaction stability value is less than the interaction stability threshold, the terminal is recorded as a stable interaction terminal, and the corresponding interaction stability values are sorted in ascending order to obtain the stable interaction terminal sequence.

[0020] As a further scheme of the application, the process for obtaining the high interaction terminal sequence is as follows:

[0021] An interaction period analysis model is constructed based on the interaction data amount of the stable interaction terminal in all historical time intervals, and a least square method is used for fitting to obtain a fitted period function model;

[0022] The interaction period analysis model and the fitted period function model are output to obtain a period determination value through a period determination formula.

[0023] As a further scheme of the application, the process for obtaining the high interaction terminal sequence is as follows:

[0024] If the cycle determination value is less than or equal to the cycle determination threshold, a terminal cycle signal is generated, and the terminal is marked as a cycle focus terminal.

[0025] As a further scheme of the application, a plurality of cycle focus terminals are combined, and the specific process is as follows:

[0026] The cycle focus terminals are sorted from small to large according to the size of the cycle determination value, and a cycle focus sequence is obtained.

[0027] In the cycle focus sequence, two cycle focus terminals are combined at will, and a cycle focus group is obtained.

[0028] As a further scheme of the application, the cycle focus terminals in the cycle focus group are subjected to cycle deviation diagnosis, and a cycle similar group is obtained, and the process is as follows:

[0029] The distance between adjacent wave crests and the distance between adjacent wave troughs are extracted from the interaction cycle analysis model corresponding to the cycle focus terminal.

[0030] The distances between all adjacent wave crests are subjected to mean value processing, and the adjacent wave crest change period is output, and the adjacent wave crest change period corresponding to each cycle focus terminal is input into the Euclidean distance formula, and the adjacent wave crest period deviation is output.

[0031] The distances between all adjacent wave troughs are subjected to mean value processing, and the adjacent wave trough change period is output, and the adjacent wave trough change period corresponding to each cycle focus terminal is input into the Euclidean distance formula, and the adjacent wave trough period deviation is output.

[0032] The adjacent wave crest period deviation and the adjacent wave trough period deviation are summed, and the cycle similarity value is output, and if it is less than or equal to the cycle similarity threshold, it is recorded as a cycle similar group.

[0033] As a further scheme of the application, a polling cycle is set for the cycle similar group, and the process is as follows:

[0034] In the cycle similar group, the cycles of the interaction cycle analysis model corresponding to the cycle focus terminals are summed and averaged to obtain the polling cycle.

[0035] In a second aspect, the application provides a multi-terminal data interaction system based on Bluetooth communication, comprising the following modules:

[0036] Terminal high interaction analysis module: the proportion of data interaction of each terminal in the historical cycle is analyzed to obtain a high interaction terminal, and a high interaction terminal sequence is constructed.

[0037] High interaction stable screening module: each high interaction terminal in the high interaction terminal sequence is subjected to interaction stability analysis, and stable interaction terminals are screened out and integrated into a stable interaction terminal sequence;

[0038] Stable period evaluation module: each stable interaction terminal in the stable interaction terminal sequence is subjected to interaction period analysis, and whether the stable interaction terminal has periodicity when performing data interaction in the historical period is evaluated;

[0039] Similarity diagnosis setting module: if there is periodicity, the stable interaction terminal is recorded as a periodic key terminal, and a plurality of periodic key terminals are combined for diagnosis at will to obtain a periodic similar group, and a polling period is further set for the periodic similar group.

[0040] The beneficial effects of the present application are:

[0041] 1. The present application analyzes the data interaction proportion of each terminal in the historical period, screens out high interaction terminals, and then performs interaction stability analysis on the interaction data amount of each high interaction terminal in different historical periods, so that in the multi-terminal data interaction scene based on Bluetooth communication, according to the stability of the interaction data amount of each high interaction terminal in different historical periods, the task and resources are reasonably arranged, the problem of data interaction caused by unstable terminal processing capacity is avoided, and the stable interaction terminal is screened out, which is convenient for focusing on and managing the stable interaction terminal, and improves the efficiency and quality of data interaction.

[0042] 2. The present application evaluates whether the stable interaction terminal has periodicity when performing data interaction, can quantify the similarity degree between the interaction period analysis model and the fitted period function model, accurately captures the periodic change rule of data interaction, thereby distinguishing the periodic key terminal and the non-periodic key terminal, providing strong data support for the targeted optimization and management of the stable interaction terminal, combining a plurality of periodic key terminals at will, performing periodic similarity analysis, obtaining a periodic similar group, and setting a polling period, not only enabling the terminals in the periodic similar group to perform data interaction in a reasonable period, avoiding resource waste and improving the overall data interaction efficiency, but also helping the terminals in the group to be better synchronized when performing data interaction, and enhancing the stability of the multi-terminal data interaction based on Bluetooth communication. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0044] Figure 1is a flow chart of a multi-terminal data interaction method based on Bluetooth communication of the present application;

[0045] Figure 2 is a module diagram of a multi-terminal data interaction system based on Bluetooth communication of the present application. DETAILED DESCRIPTION

[0046] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0047] Embodiment One

[0048] As shown in the figure, the multi-terminal data interaction method based on Bluetooth communication provided by the embodiments of the present application specifically includes the following steps: Figure 1

[0049] Step One: Based on a terminal historical data processing report, the proportion of data interaction of each terminal in a historical period is analyzed to obtain a high-interaction terminal sequence.

[0050] In some embodiments, the terminal historical data processing report can be obtained by SQL (Structured Query Language). The specific obtaining process is as follows:

[0051] By writing a SQL query statement, the SELECT statement is used to select the required columns such as terminal ID, processing time, and processing data volume, the WHERE clause is used to filter Bluetooth communication related data, the GROUP BY is used to group by terminal, the ORDER BY is used to sort, and finally the query result can be exported to the required format of the report such as CSV or Excel to generate a terminal historical data processing report.

[0052] Among them, the terminal historical data processing report includes data processing volume, data interaction volume, etc.

[0053] The historical period is divided into several time intervals.

[0054] An arbitrary terminal is selected.

[0055] According to the terminal historical data processing report, the proportion of the interaction data volume to the data processing volume of the terminal in each historical period is obtained, and the mean value is calculated to output the interaction proportion.

[0056] ​The interaction proportions of the terminals are compared in size, and are sorted in descending order to obtain a high-interaction terminal sequence;

[0057] In step two, the interaction stability of each terminal in the high-interaction terminal sequence is analyzed, and stable interaction terminals are screened out and integrated into a stable interaction terminal sequence.

[0058] In the high-interaction terminal sequence, the interaction data amount of the terminal in each historical period is obtained, and the interaction data amounts in adjacent historical periods are combined to obtain a plurality of interaction analysis groups.

[0059] The plurality of interaction analysis groups are respectively input into the Euclidean distance model, and an interaction stability value is output.

[0060] In detail, the Euclidean distance model is: wherein, represents the total number of interaction analysis groups, represents the interaction data amount in the i-th historical period, represents the interaction data amount in the i-th historical period. Specifically, the Euclidean distance model outputs an interaction stability value, which aims to:

[0061] The Euclidean distance model is used to quantify the distance between two data points. When processing terminal historical data, the interaction data amounts in adjacent historical periods are combined as data points, and the distance (difference) between the interaction data amounts in adjacent historical periods is calculated by the Euclidean distance formula, so as to reflect the difference between the interaction data amounts in adjacent periods, thereby meeting the stability evaluation of the interaction data amount of the terminal in different historical periods.

[0062] It can be understood that the meaning of the interaction stability value is that, from the numerical point of view, the interaction stability value reflects the fluctuation of the interaction data amount of the terminal in different historical periods, and from the terminal interaction ability, it reflects that the high-interaction terminal has relatively stable ability when interacting with data, thereby helping to ensure the reliability of the entire terminal data interaction process in the terminal data interaction of Bluetooth communication.

[0063] The interaction stability value is compared with the interaction stability threshold value, and the process is as follows:

[0064] If the interaction stability value is greater than or equal to the interaction stability threshold value, it means that the high-interaction terminal has unstable ability when interacting with data, and is recorded as a non-stable interaction terminal.

[0065]

[0066] ​​​If the interaction stability value is less than the interaction stability threshold value, it indicates that the high interaction terminal has stable capability when performing interaction data, and is recorded as a stable interaction terminal;

[0067] The interaction stability values corresponding to the stable interaction terminals are sorted from small to large to obtain a stable interaction terminal sequence;

[0068] The technical scheme of the embodiment is: analyzing the data interaction proportion of each terminal in the historical period, screening out high interaction terminals, and then performing interaction stability analysis on the interaction data amount of each high interaction terminal in different historical periods, so that in the multi-terminal data interaction scene based on Bluetooth communication, according to the stability of the interaction data amount of each high interaction terminal in different historical periods, the task and resources are reasonably arranged, the problem of data interaction caused by unstable terminal processing capability is avoided, and the stable interaction terminal is screened out, which is convenient for focusing on and managing the stable interaction terminal, and improves the efficiency and quality of data interaction.

[0069] Embodiment two

[0070] As shown in Figure 1 The multi-terminal data interaction method based on Bluetooth communication provided by the embodiment of the application further includes the following steps:

[0071] Step three: analyzing the plurality of stable interaction terminals in the stable interaction terminal sequence, evaluating whether the stable interaction terminal has periodicity when performing data interaction, and obtaining an evaluation result;

[0072] The evaluation result includes a terminal periodic signal or a terminal aperiodic signal.

[0073] In some embodiments, the X-axis is time, the Y-axis is the interaction data amount of the historical period, the interaction data amount of the stable interaction terminal in all historical periods is respectively substituted into a two-dimensional coordinate system according to the time sequence of the historical period, and an interaction period analysis model is constructed;

[0074] Based on the interaction period analysis model, a fitting period function model is obtained by least square method;

[0075] It should be noted that the fitting period function model includes but is not limited to a sine function model and a cosine function model.

[0076] Specifically, the process of fitting the period function model is as follows:

[0077] S1, extracting the maximum interaction data amount and the minimum interaction data amount of the stable interaction terminal in the historical period, and inputting them into an amplitude calculation formula to output an amplitude ;

[0078] More specifically, , wherein, represents the minimum interaction data amount of the stable interaction terminal in the historical period, represents the maximum interaction data amount of the stable interaction terminal in the historical period;

[0079] S2, in the interaction period analysis model, the distance between adjacent peaks and the distance between adjacent troughs are extracted respectively;

[0080] The distances between all adjacent peaks are standardized to obtain the adjacent peak difference value;

[0081] The distances between all adjacent troughs are standardized to obtain the adjacent trough difference value;

[0082] If the adjacent peak difference value is greater than the adjacent trough difference value, it means that the difference between the adjacent troughs is small, and it is close to periodic change, then the distances between all adjacent troughs are averaged to output the period ;

[0083] If the adjacent peak difference value is less than the adjacent trough difference value, it means that the difference between the adjacent peaks is small, and it is close to periodic change, then the distances between all adjacent peaks are averaged to output the period ;

[0084] If the adjacent peak difference value is equal to the adjacent trough difference, it means that the difference between the adjacent troughs and the difference between the adjacent peaks are both small, and they are both close to periodic change, then the distances between adjacent peaks or the distances between adjacent troughs are averaged to output the period ;

[0085] S3, the maximum interaction data amount and the minimum interaction data amount of the stable interaction terminal in the historical period are input into the vertical offset calculation formula to output the vertical offset ;

[0086] More specifically, the vertical offset calculation formula is: , wherein, represents the minimum interaction data amount of the terminal in the historical period, represents the maximum interaction data amount of the terminal in the historical period;

[0087] S4, the starting coordinates in the interaction period analysis model are extracted and input into the fitting period function model together with the amplitude , the period , and the vertical offset , to output the phase ;

[0088] S5, with amplitude , period , vertical offset and phase , a fitting periodic function model is constructed;

[0089] The Y coordinates of all wave peaks and troughs on the interactive period analysis model are extracted and subjected to standard deviation processing, and the analysis standard deviation is output.

[0090] Similarly, the coordinates of all wave peaks and troughs on the fitting periodic function model are extracted and subjected to standard deviation processing, and the fitting standard deviation is output.

[0091] The model covariance Cov between the interactive period analysis model and the fitting periodic function model is obtained.

[0092] The analysis standard deviation , the fitting standard deviation and the model covariance Cov are input into the period determination formula respectively, and the period determination value is output.

[0093] Specifically, the period determination formula is: ;

[0094] It should be noted that the period determination formula is improved according to the Pearson correlation coefficient calculation formula, which can quantify the similarity between the interactive period analysis model and the fitting periodic function model, so as to capture the periodic change rule in the interactive period analysis model, help to accurately identify the terminal with obvious periodic data interaction among many terminals, accurately screen out the stable interaction terminal with periodic change from multiple stable interaction terminals, and provide data support for targeted optimization and management of stable interaction terminals.

[0095] It can be understood that the meaning represented by the period determination value is that the similarity between the interactive period analysis model and the fitting periodic function model is quantified, which helps to capture the periodic change rule in the interactive period analysis model when evaluating whether the data interaction of the stable interaction terminal has periodicity, and then screen out the stable interaction terminal with periodic change, thereby providing data support for subsequent targeted optimization and management.

[0096] The period determination value is compared with the period determination threshold, and the process is as follows:

[0097] If the period determination value is less than or equal to the period determination threshold, it means that the periodic change in the interactive period analysis model is similar to the periodic change in the fitting periodic function model in a high degree, a terminal periodic signal is generated, and is marked as a periodic key terminal.

[0098] If the cycle determination value is greater than the cycle determination threshold value, it indicates that the periodic change in the interaction cycle analysis model is less similar to the periodic change of the fitted periodic function model, a terminal non-periodic signal is generated, and is marked as a non-periodic key terminal;

[0099] Step four: combining and diagnosing any multiple periodic key terminals to obtain a periodic similar group, and further setting a polling cycle for the periodic similar group;

[0100] In some embodiments, the periodic key terminals are sorted in ascending order of the cycle determination value to obtain a periodic key sequence;

[0101] In the periodic key sequence, any two periodic key terminals are combined to obtain a periodic key group;

[0102] The periodic deviation analysis is performed on the interaction cycle analysis model corresponding to the periodic key terminals in the periodic key group, and the execution process is as follows:

[0103] On the interaction cycle analysis model corresponding to any one periodic key terminal, the distance between adjacent wave crests and the distance between adjacent wave troughs are extracted respectively;

[0104] The distances between all adjacent wave crests are averaged to output the adjacent wave crest change period;

[0105] The adjacent wave crest change periods corresponding to each periodic key terminal in the periodic key group are respectively input into the Euclidean distance formula to output the adjacent wave crest period deviation ;

[0106] Specifically, the Euclidean distance formula is: wherein, represents the adjacent wave crest change period corresponding to one of the periodic key terminals in the periodic key group, represents the adjacent wave crest change period corresponding to another periodic key terminal in the periodic key group, and and are corresponding in the time dimension, m represents the total number of adjacent wave crest change periods, and the total number of adjacent wave crest change periods corresponding to each periodic key terminal in the periodic key group is the same;

[0107] The distances between all adjacent wave troughs are averaged to output the adjacent wave trough change period;

[0108] The adjacent wave trough change periods corresponding to each periodic key terminal in the periodic key group are respectively input into the Euclidean distance formula to output the adjacent wave trough period deviation ;

[0109] Specifically, the Euclidean distance formula is: wherein, represents a neighboring peak change period corresponding to one of the periodic key terminals in the periodic key group, represents a neighboring peak change period corresponding to another periodic key terminal in the periodic key group, and and are corresponding in the time dimension, m represents the total number of neighboring peak change periods, and the total number of neighboring peak change periods corresponding to each periodic key terminal in the periodic key group is the same;

[0110] the neighboring peak period deviation and the neighboring valley period deviation are summed up, and the period similarity value is output;

[0111] If the period similarity value is less than or equal to the period similarity threshold value, the analyzed periodic key group is recorded as a period similarity group;

[0112] If the period similarity value is greater than the period similarity threshold value, the periodic key terminal is recombined with the remaining periodic key terminal until the period similarity value corresponding to the combined periodic key group is less than or equal to the period similarity threshold value;

[0113] In the period similarity group, the periods of the periodic key terminal corresponding to the interaction period analysis model are summed up and averaged to obtain the polling period;

[0114] The specific scheme of the embodiment is: to evaluate whether there is periodicity when the stable interaction terminal performs data interaction, to quantify the similarity degree between the interaction period analysis model and the fitted period function model, to accurately capture the periodic change rule of data interaction, and to distinguish the periodic key terminal and the non-periodic key terminal, thereby providing strong data support for the targeted optimization and management of the stable interaction terminal. The periodic key terminals are combined in any manner, the period similarity analysis is performed, the period similarity group is obtained, and the polling period is set. Not only can the terminals in the period similarity group perform data interaction in a reasonable period, thereby avoiding resource waste and improving the overall data interaction efficiency, but also the synchronization of the terminals in the group during data interaction is better, thereby enhancing the stability of the multi-terminal data interaction based on Bluetooth communication.

[0115] Embodiment Three

[0116] As shown in Figure 2 , the multi-terminal data interaction system based on Bluetooth communication provided by the embodiment of the application comprises the following modules:

[0117] The terminal high interaction analysis module: the proportion of the data interaction of each terminal in the historical period is analyzed to obtain the high interaction terminal, and a high interaction terminal sequence is constructed.

[0118] High interaction stable screening module: each high interaction terminal in the high interaction terminal sequence is analyzed for interaction stability, and stable interaction terminals are screened out and integrated into a stable interaction terminal sequence;

[0119] Stable period evaluation module: each stable interaction terminal in the stable interaction terminal sequence is analyzed for interaction period, and whether the stable interaction terminal has periodicity when performing data interaction in the historical period is evaluated;

[0120] Similarity diagnosis setting module: if there is periodicity, the stable interaction terminal is recorded as a periodic key terminal, and multiple periodic key terminals are combined for diagnosis at will to obtain a periodic similar group, and a polling period is further set for the periodic similar group.

[0121] The above describes one embodiment of the present application in detail, but the content described is only a preferred embodiment of the present application, and cannot be considered as limiting the scope of the present application. Any equivalent changes and improvements made within the scope of the present application should still belong to the patent coverage of the present application.

Claims

1. A multi-terminal data interaction method based on Bluetooth communication, characterized in that, Includes the following steps: The proportion of data interaction volume of each terminal in the historical period is analyzed to identify high-interaction terminals and construct a high-interaction terminal sequence. Perform interaction stability analysis on each high-interaction terminal in the high-interaction terminal sequence, screen out stable interaction terminals, and integrate them into a stable interaction terminal sequence. An interaction stability analysis was performed on a highly interactive terminal. The analysis process is as follows: Any highly interactive terminal within the sequence of highly interactive terminals; The interaction data within adjacent historical time periods are combined to obtain multiple interaction analysis groups, which are then input into the Euclidean distance model to output interaction stability values. The process of obtaining a stable interactive terminal sequence is as follows: If the interaction stability value is less than the interaction stability threshold, it is recorded as a stable interaction terminal, and the corresponding interaction stability values ​​are sorted from smallest to largest to obtain a stable interaction terminal sequence. Perform interaction cycle analysis on each stable interactive terminal in the stable interactive terminal sequence to assess whether there is periodicity when the stable interactive terminals perform data interaction in the historical period. If a periodicity exists, stable interactive terminals are marked as periodic key terminals, and multiple periodic key terminals are arbitrarily combined and diagnosed to obtain periodic similarity groups. Then, a polling period is set for the periodic similarity groups.

2. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, characterized in that, The process of obtaining the high-interaction terminal sequence is as follows: The historical cycle is divided into several historical periods with equal time intervals; Obtain the percentage of interactive data volume of the terminal in a historical period relative to the total data processing volume in that historical period. Then, average the percentages across all historical periods to output the interaction weight. Finally, sort the terminals in descending order to obtain the sequence of high-interaction terminals.

3. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, characterized in that, The interaction cycle analysis of a stable interactive terminal is performed as follows: Based on the amount of interaction data of a stable interactive terminal in all historical periods, an interaction cycle analysis model is constructed, and the least squares method is used to fit the model to obtain a fitted periodic function model. The period determination value is obtained by using the period determination formula to analyze the interaction period analysis model and the fitted periodic function model.

4. The multi-terminal data interaction method based on Bluetooth communication according to claim 3, characterized in that, The process for assessing whether a stable interactive terminal exhibits periodicity during data interaction is as follows: If the period determination value is less than or equal to the period determination threshold, a terminal period signal is generated and marked as a period key terminal.

5. The multi-terminal data interaction method based on Bluetooth communication according to claim 1, characterized in that, The process of arbitrarily combining multiple key terminals in a given cycle is as follows: Based on the size of the period determination value, the key terminals of the period are sorted from smallest to largest to obtain the key period sequence; Within a periodic key sequence, any two periodic key terminals can be combined to obtain a periodic key group.

6. The multi-terminal data interaction method based on Bluetooth communication according to claim 5, characterized in that, Perform cycle deviation diagnosis on key terminals within the cycle focus group to obtain cycle similarity groups. The process is as follows: From the interactive cycle analysis model corresponding to the key terminals in the cycle, the distance between adjacent peaks and the distance between adjacent troughs are extracted respectively. The distances between all adjacent peaks are averaged to obtain the adjacent peak variation period. The adjacent peak variation period corresponding to the key terminal of each period is then input into the Euclidean distance formula to obtain the adjacent peak period deviation. The distances between all adjacent troughs are averaged to obtain the adjacent trough variation period. The adjacent trough variation period corresponding to the key terminal of each period is then input into the Euclidean distance formula to obtain the adjacent trough period deviation. The periodic deviations of adjacent peaks and adjacent troughs are summed to obtain the periodic similarity value. If the value is less than or equal to the periodic similarity threshold, it is recorded as a periodic similarity group.

7. The multi-terminal data interaction method based on Bluetooth communication according to claim 6, characterized in that, The process for setting a polling period for groups with similar periods is as follows: Within the similar cycle group, the average of the cycles of the interaction cycle analysis model corresponding to the key cycle terminals is summed to obtain the polling cycle.

8. A multi-terminal data interaction system based on Bluetooth communication, characterized in that, Includes the following modules: Terminal high-interaction analysis module: Analyzes the proportion of data interaction volume of each terminal in the historical period to identify high-interaction terminals and construct a high-interaction terminal sequence; High-interaction stability screening module: Performs interaction stability analysis on each high-interaction terminal in the high-interaction terminal sequence, screens out stable interaction terminals, and integrates them into a stable interaction terminal sequence; An interaction stability analysis was performed on a highly interactive terminal. The analysis process is as follows: Any highly interactive terminal within the sequence of highly interactive terminals; The interaction data within adjacent historical time periods are combined to obtain multiple interaction analysis groups, which are then input into the Euclidean distance model to output interaction stability values. The process of obtaining a stable interactive terminal sequence is as follows: If the interaction stability value is less than the interaction stability threshold, it is recorded as a stable interaction terminal, and the corresponding interaction stability values ​​are sorted from smallest to largest to obtain a stable interaction terminal sequence. Stable cycle assessment module: Performs interaction cycle analysis on each stable interactive terminal in the stable interactive terminal sequence to assess whether there is periodicity when the stable interactive terminals perform data interaction in the historical period; Similarity diagnosis setting module: If there is a periodicity, the stable interactive terminal is recorded as the periodic key terminal, and multiple periodic key terminals are arbitrarily combined for diagnosis to obtain the periodic similarity group. The polling period is then set for the periodic similarity group.

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