Bluetooth anti-interference connection optimization processing method and system based on Internet of Things

Abstract

The invention discloses a Bluetooth anti-interference connection optimization processing method and system based on the Internet of Things, and belongs to the technical field of connection optimization processing. Obtaining channel interference data and communication signal quality data of the Bluetooth device, and constructing a function type group; acquiring channel interference data and communication signal quality data of the Bluetooth equipment under the same time node; calculating the signal interference degree of a single Bluetooth device under the current time node; calculating an interference fluctuation characteristic value; calculating a future signal interference change value of a single Bluetooth device; calculating a difference value and a mean value of the signal interference change values, and calculating an interference comprehensive value of all Bluetooth devices in the function type group based on the difference value and the mean value; and presetting a threshold value, analyzing and carrying out connection optimization processing. According to the method, the function type group is constructed, the signal interference degree and the fluctuation characteristic value thereof are dynamically analyzed, and the connection optimization of the Bluetooth equipment is realized in combination with the Internet of Things technology, so that the anti-interference problem of the Bluetooth equipment in a complex industrial environment is successfully solved.

Description

Technical Field

[0001] The present invention relates to the technical field of connection optimization processing, and in particular to a method and system for optimizing Bluetooth anti-interference connection processing based on the Internet of Things. Background Art

[0002] With the rapid development of Internet of Things (IoT) technology, Bluetooth devices are increasingly used in industrial scenarios, especially in large factories, where these devices are widely used for tasks such as data collection, status monitoring, and equipment control. However, in complex industrial environments, the performance of Bluetooth devices is interfered by a variety of factors, including channel congestion, electromagnetic interference, and high device density. These interferences not only lead to a decline in communication quality, but may also cause data transmission delays or even communication interruptions. Existing technologies usually mitigate interference by optimizing spectrum allocation, power regulation, or channel switching between devices. However, these methods mostly rely on static analysis and do not fully consider the dynamics and complexity of interference in industrial scenarios. In addition, these methods cannot monitor and predict the changing trends of signal interference of Bluetooth devices in real time, resulting in limitations in their anti-interference effects.

[0003] Existing Bluetooth anti-interference technology lacks grouping optimization methods for device function types. Devices with different functions may cause interference on the same channel, reducing the overall performance of the system. It is difficult to achieve dynamic prediction and real-time response to interference trends, resulting in delayed anti-interference measures. In large-scale factory scenarios where Bluetooth devices are densely deployed, existing technologies are insufficient in their interference optimization capabilities for the global network and are unable to take into account both overall and local anti-interference needs. These problems have seriously restricted the widespread application of Bluetooth technology in industrial environments. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for optimizing Bluetooth anti-interference connection based on the Internet of Things to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A method for optimizing Bluetooth anti-interference connection based on the Internet of Things, the method comprising the following steps: obtaining channel interference data and communication signal quality data of Bluetooth devices in a large factory; classifying the Bluetooth devices based on function type to construct a function type group; interconnecting the Bluetooth devices in the function type group by using the Internet of Things technology; obtaining channel interference data and communication signal quality data of Bluetooth devices at the same time node; calculating the signal interference degree of a single Bluetooth device at the current time node based on the channel interference data and the communication signal quality data; calculating interference fluctuation characteristic values ​​based on the signal interference degree; calculating the signal interference change value of a single Bluetooth device in the future based on the signal interference degree and the interference fluctuation characteristic values; calculating the difference and mean of the signal interference change values ​​of all Bluetooth devices, and calculating the comprehensive interference value of all Bluetooth devices in the function type group based on the difference and mean; and presetting a threshold, analyzing and performing connection optimization processing.

[0007] As a preferred solution of the Bluetooth anti-interference connection optimization processing method based on the Internet of Things described in the present invention, based on the number of Bluetooth devices in a large factory, data blocks are divided in the data storage unit, and the working status of the Bluetooth device is stored in the data block, and one data block is divided corresponding to one Bluetooth device; the working status includes channel interference data and communication signal quality data; the data block includes a channel interference database and a communication signal quality database, and is used to store the channel interference data and the communication signal quality data, respectively.

[0008] Based on the functional type, the Bluetooth devices are classified to construct functional type groups, and the functional type groups are used to group Bluetooth devices with the same functional type (including devices for receiving audio, devices for input, devices for monitoring, etc.); functional type group labels are attached to the channel interference database and the communication signal quality database in the data block, and one functional type group corresponds to one channel interference database and one communication signal quality data.

[0009] It should be noted that the channel interference data is collected through a professional spectrum analyzer, and the communication signal quality data is collected through the device’s own signal strength indicator or third-party monitoring software.

[0010] As a preferred solution of the Bluetooth anti-interference connection optimization processing method based on the Internet of Things described in the present invention, the Bluetooth devices in the functional type group are interconnected by using the Internet of Things technology, and the channel interference data and communication signal quality data of the Bluetooth devices are collected in units of minutes, and stored in the channel interference database and the communication signal quality database respectively.

[0011] Extract the channel interference data and communication signal quality data from the channel interference database and communication signal quality database at the tth minute, and record them as CIDt (n) and CSQ t (n), where CID t (n) represents the channel interference data of the nth Bluetooth device in the functional type group at the tth minute, CSQ t (n) represents the communication signal quality data of the nth Bluetooth device in the functional type group at the tth minute.

[0012] As a preferred solution of the method for optimizing Bluetooth anti-interference connection based on the Internet of Things described in the present invention, based on the channel interference data CID t (n) and communication signal quality data CSQ t (n), calculate the signal interference of the nth Bluetooth device in the functional type group at the tth minute, the calculation formula is as follows:

[0013]

[0014] Among them, SD t (n) represents the signal interference degree of the nth Bluetooth device in the functional type group at the tth minute, and α represents the channel interference data CID t (n) is the adjustment factor, and β represents the communication signal quality data CSQ t (n) The adjustment factor.

[0015] It should be noted that, in the present invention, the signal interference degree formula plays a key role in quantifying the degree of interference suffered by the Bluetooth device. Through this formula, the collected channel interference data and communication signal quality data can be converted into a specific numerical indicator, namely the signal interference degree; this indicator can intuitively reflect the interference situation of each Bluetooth device at a specific moment, and provides a basic basis for subsequent interference analysis and optimization processing; for example, in a large factory, there are many Bluetooth devices with different functional types. By calculating the signal interference degree of each device, it is possible to quickly identify which devices are more seriously interfered, so as to carry out further processing and optimization in a targeted manner.

[0016] Based on the signal interference SD of the nth Bluetooth device in the functional type group at the tth minute t (n), predict the future signal interference trend of the nth Bluetooth device in the functional type group as follows:

[0017] Get the signal interference degree of the nth Bluetooth device in the functional type group within a total of M minutes in history, and calculate the interference fluctuation characteristic value. The calculation formula is as follows:

[0018]

[0019] Among them, F t (n) represents the disturbance fluctuation characteristic value, i represents the index variable, SDt-i (n) represents the signal interference level of the nth Bluetooth device in the functional type group at the tith minute.

[0020] According to the interference fluctuation characteristic value F t (n), calculate the signal interference change value of the nth Bluetooth device in the functional type group in the future, the calculation formula is as follows:

[0021]

[0022] Among them, ΔSD t+1 (n) represents the signal interference change value of the nth Bluetooth device in the function type group in the next minute, and γ and δ represent the weight adjustment factors of the preset signal interference degree and interference fluctuation characteristic value respectively.

[0023] It should be noted that in the formula It represents the derivative of signal interference with respect to time, which reflects the rate of change of signal interference with time. Through this derivative, we can understand the changing trend of signal interference at the current moment, whether it is increasing or decreasing, and the speed of change; F t (n) reflects the fluctuation of signal interference in the historical time period. The greater the fluctuation, the higher the F t The larger the value of (n); the signal interference change value formula is used in the present invention to predict the future signal interference trend of Bluetooth devices. By combining the change rate of the signal interference degree at the current moment and the historical interference fluctuation characteristic value, the signal interference change of the device in the next minute can be accurately estimated, which is of great significance for taking anti-interference measures in advance; for example, in a factory environment, if it is predicted that the signal interference of a certain Bluetooth device will increase significantly in the next minute, then the working parameters of the device can be adjusted in time, such as switching to a channel with less interference, or adjusting the transmission power, etc., to ensure the stability and reliability of the Bluetooth connection and avoid problems such as communication interruption or data transmission errors caused by interference; at the same time, by analyzing the signal interference change values ​​of multiple Bluetooth devices, the layout and resource allocation of the entire Bluetooth network can also be optimized, thereby improving the anti-interference ability and performance of the entire system.

[0024] As a preferred solution of the method for optimizing Bluetooth anti-interference connection based on the Internet of Things described in the present invention, the signal interference change values ​​of all Bluetooth devices in the function type group in the next minute are obtained, and a signal interference change value set is constructed, which is recorded as SIC = {ΔSD t+1 (n)|n∈[1,N]}, where N represents the total number of Bluetooth devices in the function type group; obtain the signal interference change value set SIC={ΔSD t+1(n)|n∈[1,N]}, calculate the difference between the maximum signal interference change value and the minimum signal interference change value, and record it as the signal interference change difference SID t+1 (n).

[0025] Calculate the signal interference change value set SIC = {ΔSD t+1 The mean of the signal interference change values ​​of all Bluetooth devices in (n)|n∈[1,N]} is recorded as the mean signal interference change value

[0026] Based on signal interference variation difference SID t+1 (n) and the mean value of signal interference variation Calculate the comprehensive interference value of all Bluetooth devices in the functional type group. The calculation formula is as follows:

[0027]

[0028] Among them, ICV t+1 Indicates the combined interference value of all Bluetooth devices in the functional type group.

[0029] Preset interference comprehensive threshold, if the interference comprehensive value ICV of all Bluetooth devices in the function type group t+1 If it is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, all Bluetooth devices in the functional type group are switched to idle channels, and the staff is notified to check for possible interference sources in the use environment.

[0030] It should be noted that the mean reflects the average interference level of devices in the functional type group, while the difference reflects the discrete degree of interference changes between devices. When the mean is in the normal range but the difference is large, it means that although the overall interference situation in the group is acceptable, there are some devices with abnormal interference changes. For example, in a Bluetooth device group used for monitoring, the mean shows that the overall interference change is not large, but the difference is large. Through further analysis, it can be found that the monitoring device in a specific location is affected by a special interference source (such as a newly added high-power device nearby), so that the device can be adjusted or maintained in time without large-scale optimization operations on the entire group, thereby improving the accuracy and efficiency of maintenance. If both the mean and the difference are small, it means that not only the overall interference changes of the devices in the group are stable, but also the interference changes between the devices are relatively consistent, the device performance and the environment are relatively similar, and the system stability is high. On the contrary, if the mean is large and the difference is also large, it means that the devices in the group are not only generally affected by strong interference, but also have a relatively stable interference. If there are large interference changes and the differences between devices are also large, it may be necessary to comprehensively re-evaluate and optimize the selection and layout of the equipment and the anti-interference strategy of the system to improve the consistency of the equipment and the overall performance of the system; according to the combination of the mean and the difference, more refined resource allocation can be achieved; when the mean is high but the difference is small, it means that all devices in the group are facing high interference changes. At this time, it is necessary to evenly increase the anti-interference resources for the entire group, such as uniformly upgrading the anti-interference modules of the equipment and adding signal repeaters; and when the mean is high and the difference is also large, in addition to adding resources for the entire group, it is also necessary to give additional resources to the devices with large interference change values, such as equipping these devices with stronger antennas or separate signal processing units to ensure their normal operation; for the case of low mean but large difference, you can focus on those devices with large interference change values ​​and allocate a small amount of targeted resources to them for optimization without large-scale resource investment for the entire group.

[0031] A Bluetooth anti-interference connection optimization processing system based on the Internet of Things, the system comprises: a data block and function type group division module, a data acquisition module, a data calculation and prediction module and an interference comprehensive value calculation and analysis module.

[0032] The data block and function type group division module is used to obtain channel interference data and communication signal quality data of Bluetooth devices in a large factory; based on the function type, the Bluetooth devices are classified to construct function type groups.

[0033] The data acquisition module: utilizes the Internet of Things technology to interconnect the Bluetooth devices in the functional type group; and obtains the channel interference data and communication signal quality data of the Bluetooth devices at the same time node.

[0034] The data calculation and prediction module: calculates the signal interference degree of a single Bluetooth device at the current time node based on the channel interference data and the communication signal quality data; calculates the interference fluctuation characteristic value based on the signal interference degree; calculates the signal interference change value of a single Bluetooth device in the future based on the signal interference degree and the interference fluctuation characteristic value.

[0035] The interference comprehensive value calculation and analysis module calculates the difference and mean of the signal interference change values ​​of all Bluetooth devices, and based on the difference and mean, calculates the interference comprehensive value of all Bluetooth devices in the functional type group; presets a threshold, analyzes and performs connection optimization processing.

[0036] Furthermore, the data block and function type group division module includes a data block division unit and a function type group division unit.

[0037] The data block division unit divides the data blocks in the data storage unit based on the number of Bluetooth devices in the large factory, stores the working status of the Bluetooth devices in the data blocks, and one data block is divided corresponding to one Bluetooth device; the working status includes channel interference data and communication signal quality data; the data block includes a channel interference database and a communication signal quality database, and is used to store the channel interference data and the communication signal quality data respectively.

[0038] The function type group division unit: classifies the Bluetooth devices based on the function type and constructs a function type group, wherein the function type group is used to group Bluetooth devices with the same function type; adds a function type group label to the channel interference database and the communication signal quality database in the data block, and one function type group corresponds to one channel interference database and one communication signal quality database.

[0039] Furthermore, the data acquisition module includes a data acquisition unit.

[0040] The data acquisition unit: utilizes the Internet of Things technology to interconnect the Bluetooth devices in the functional type group, collects the channel interference data and communication signal quality data of the Bluetooth devices in units of minutes, and stores them in the channel interference database and the communication signal quality database respectively; extracts the channel interference data and communication signal quality data in the channel interference database and the communication signal quality database in the current minute.

[0041] Furthermore, the data calculation and prediction module includes a data calculation unit and a prediction unit.

[0042] The data calculation unit calculates the current signal interference degree of a single Bluetooth device in the functional type group based on the channel interference data and the communication signal quality data.

[0043] The prediction unit predicts the future signal interference trend of a single Bluetooth device in the functional type group based on the current signal interference degree of the single Bluetooth device in the functional type group, as follows:

[0044] The historical signal interference degree of a single Bluetooth device in the functional type group is obtained, the interference fluctuation characteristic value is calculated, and the signal interference change value of the single Bluetooth device in the functional type group in the future is calculated according to the interference fluctuation characteristic value.

[0045] Furthermore, the interference comprehensive value calculation and analysis module includes an interference comprehensive value calculation unit and an analysis unit.

[0046] The interference comprehensive value calculation unit: obtains the signal interference change values ​​of all Bluetooth devices in the function type group in the next minute, and constructs a signal interference change value set; obtains the maximum signal interference change value and the minimum signal interference change value in the signal interference change value set, calculates the difference between the maximum signal interference change value and the minimum signal interference change value, and records it as the signal interference change difference; calculates the average of the signal interference change values ​​of all Bluetooth devices in the signal interference change value set, and records it as the signal interference change average.

[0047] The analysis unit: calculates the comprehensive interference value of all Bluetooth devices in the functional type group based on the signal interference change difference and the signal interference change mean; presets a comprehensive interference threshold, and if the comprehensive interference value of all Bluetooth devices in the functional type group is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, and all Bluetooth devices in the functional type group are switched to idle channels.

[0048] Compared with the prior art, the beneficial effects achieved by the present invention are: in the Bluetooth anti-interference connection optimization processing method and system based on the Internet of Things provided by the present invention,. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0050] Figure 1 It is a schematic diagram of the steps of a Bluetooth anti-interference connection optimization processing method based on the Internet of Things of the present invention;

[0051] Figure 2 It is a structural schematic diagram of a Bluetooth anti-interference connection optimization processing system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] See also Figure 1 In the first embodiment of the present invention, a method for optimizing Bluetooth anti-interference connection based on the Internet of Things is provided, and the method comprises the following steps:

[0054] Step S1: Acquire channel interference data and communication signal quality data of Bluetooth devices in a large factory; classify the Bluetooth devices based on functional types and construct functional type groups.

[0055] Specifically, based on the number of Bluetooth devices in a large factory, data blocks are divided in a data storage unit, and the working status of the Bluetooth device is stored in the data block, and one data block is divided corresponding to one Bluetooth device; the working status includes channel interference data and communication signal quality data; the data block includes a channel interference database and a communication signal quality database, and is used to store the channel interference data and the communication signal quality data, respectively.

[0056] Furthermore, based on the functional type, the Bluetooth devices are classified to construct functional type groups, which are used to group Bluetooth devices with the same functional type (including devices for receiving audio, devices for input, devices for monitoring, etc.); functional type group labels are attached to the channel interference database and the communication signal quality database in the data block, and one functional type group corresponds to one channel interference database and one communication signal quality data.

[0057] It should be noted that the channel interference data is collected through a professional spectrum analyzer, and the communication signal quality data is collected through the device’s own signal strength indicator or third-party monitoring software.

[0058] Step S2: using the Internet of Things technology to interconnect the Bluetooth devices in the functional type group; obtaining the channel interference data and communication signal quality data of the Bluetooth devices at the same time node.

[0059] Specifically, the Internet of Things technology is used to interconnect the Bluetooth devices in the functional type group, and the channel interference data and communication signal quality data of the Bluetooth devices are collected in units of minutes, and are stored in the channel interference database and the communication signal quality database respectively.

[0060] Further, the channel interference data and communication signal quality data in the channel interference database and communication signal quality database at the tth minute are extracted and recorded as CID t (n) and CSQ t (n), where CID t (n) represents the channel interference data of the nth Bluetooth device in the functional type group at the tth minute, CSQ t (n) represents the communication signal quality data of the nth Bluetooth device in the functional type group at the tth minute.

[0061] Step S3: Based on the channel interference data and the communication signal quality data, calculate the signal interference degree of a single Bluetooth device at the current time node; based on the signal interference degree, calculate the interference fluctuation characteristic value; based on the signal interference degree and the interference fluctuation characteristic value, calculate the signal interference change value of the single Bluetooth device in the future.

[0062] Specifically, based on the channel interference data CID t (n) and communication signal quality data CSQ t (n), calculate the signal interference of the nth Bluetooth device in the functional type group at the tth minute, the calculation formula is as follows:

[0063]

[0064] Among them, SD t (n) represents the signal interference degree of the nth Bluetooth device in the functional type group at the tth minute, and α represents the channel interference data CID t (n) is the adjustment factor, and β represents the communication signal quality data CSQ t (n) The adjustment factor.

[0065] For example, assuming that the channel interference data CID t The adjustment factor α of (n) is 0.6, and the communication signal quality data CSQ t The adjustment factor β of (n) is 0.4, the channel interference data CID1(1) is 25, and the communication signal quality data SCQ1(1) is 75. Substituting into the formula, we get

[0066] It should be noted that, in the present invention, the signal interference degree formula plays a key role in quantifying the degree of interference suffered by the Bluetooth device. Through this formula, the collected channel interference data and communication signal quality data can be converted into a specific numerical indicator, namely the signal interference degree; this indicator can intuitively reflect the interference situation of each Bluetooth device at a specific moment, and provides a basic basis for subsequent interference analysis and optimization processing; for example, in a large factory, there are many Bluetooth devices with different functional types. By calculating the signal interference degree of each device, it is possible to quickly identify which devices are more seriously interfered, so as to carry out further processing and optimization in a targeted manner.

[0067] Further, based on the signal interference SD of the nth Bluetooth device in the functional type group at the tth minute, t (n), predict the future signal interference trend of the nth Bluetooth device in the functional type group as follows:

[0068] Get the signal interference degree of the nth Bluetooth device in the functional type group within a total of M minutes in history, and calculate the interference fluctuation characteristic value. The calculation formula is as follows:

[0069]

[0070] Among them, F t (n) represents the disturbance fluctuation characteristic value, i represents the index variable, SD t-i (n) represents the signal interference level of the nth Bluetooth device in the functional type group at the tith minute.

[0071] For example, assuming M is 3, SD0(1) = 0.3, SD -1 (1) = 0.25, SD -2 (1)=0.35, and substituting it into the formula, we get F1(1)=0.03.

[0072] According to the interference fluctuation characteristic value F t (n), calculate the signal interference change value of the nth Bluetooth device in the functional type group in the future, the calculation formula is as follows:

[0073]

[0074] Among them, ΔSD t+1 (n) represents the signal interference change value of the nth Bluetooth device in the function type group in the next minute, and γ and δ represent the weight adjustment factors of the preset signal interference degree and interference fluctuation characteristic value respectively.

[0075] For example, assuming that γ and δ are 0.3 and 0.7 respectively,

[0076] It should be noted that in the formula It represents the derivative of signal interference with respect to time, which reflects the rate of change of signal interference with time. Through this derivative, we can understand the changing trend of signal interference at the current moment, whether it is increasing or decreasing, and the speed of change; F t (n) reflects the fluctuation of signal interference in the historical time period. The greater the fluctuation, the higher the F t The larger the value of (n); the signal interference change value formula is used in the present invention to predict the future signal interference trend of Bluetooth devices. By combining the change rate of the signal interference degree at the current moment and the historical interference fluctuation characteristic value, the signal interference change of the device in the next minute can be accurately estimated, which is of great significance for taking anti-interference measures in advance; for example, in a factory environment, if it is predicted that the signal interference of a certain Bluetooth device will increase significantly in the next minute, then the working parameters of the device can be adjusted in time, such as switching to a channel with less interference, or adjusting the transmission power, etc., to ensure the stability and reliability of the Bluetooth connection and avoid problems such as communication interruption or data transmission errors caused by interference; at the same time, by analyzing the signal interference change values ​​of multiple Bluetooth devices, the layout and resource allocation of the entire Bluetooth network can also be optimized, thereby improving the anti-interference ability and performance of the entire system.

[0077] Step S4: Calculate the difference and mean of the signal interference change values ​​of all Bluetooth devices, and based on the difference and mean, calculate the comprehensive interference value of all Bluetooth devices in the functional type group; preset a threshold, analyze and perform connection optimization processing.

[0078] Specifically, the signal interference change values ​​of all Bluetooth devices in the function type group in the next minute are obtained, and a signal interference change value set is constructed, which is recorded as SIC = {ΔSD t+1 (n)|n∈[1,N]}, where N represents the total number of Bluetooth devices in the function type group; obtain the signal interference change value set SIC={ΔSD t+1 (n)|n∈[1,N]}, calculate the difference between the maximum signal interference change value and the minimum signal interference change value, and record it as the signal interference change difference SID t+1 (n).

[0079] Further, the signal interference change value set SIC is calculated as follows: t+1 The mean of the signal interference change values ​​of all Bluetooth devices in (n)|n∈[1,N]} is recorded as the mean signal interference change value

[0080] Based on signal interference variation difference SID t+1 (n) and the mean value of signal interference variation Calculate the comprehensive interference value of all Bluetooth devices in the functional type group. The calculation formula is as follows:

[0081]

[0082] Among them, ICV t+1 Indicates the combined interference value of all Bluetooth devices in the functional type group.

[0083] For example, suppose 0.0657, SID t+1 (n) is 0.0192, and the interference comprehensive value ICV is calculated by substituting it into the formula t+1 =0.067.

[0084] Furthermore, a preset interference comprehensive threshold is set, if the interference comprehensive value ICV of all Bluetooth devices in the functional type group is t+1 If it is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, all Bluetooth devices in the functional type group are switched to idle channels, and the staff is notified to check for possible interference sources in the use environment.

[0085] For example, assuming that the interference comprehensive threshold is 0.05, the interference comprehensive value ICV of all Bluetooth devices in the functional type group is t+1 If it is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, all Bluetooth devices in the functional type group are switched to idle channels, and the staff is notified to check for possible interference sources in the use environment.

[0086] It should be noted that the mean reflects the average interference level of devices in the functional type group, while the difference reflects the discrete degree of interference changes between devices. When the mean is in the normal range but the difference is large, it means that although the overall interference situation in the group is acceptable, there are some devices with abnormal interference changes. For example, in a Bluetooth device group used for monitoring, the mean shows that the overall interference change is not large, but the difference is large. Through further analysis, it can be found that the monitoring device in a specific location is affected by a special interference source (such as a newly added high-power device nearby), so that the device can be adjusted or maintained in time without large-scale optimization operations on the entire group, thereby improving the accuracy and efficiency of maintenance. If both the mean and the difference are small, it means that not only the overall interference changes of the devices in the group are stable, but also the interference changes between the devices are relatively consistent, the device performance and the environment are relatively similar, and the system stability is high. On the contrary, if the mean is large and the difference is also large, it means that the devices in the group are not only generally affected by strong interference, but also have a relatively stable interference. If there are large interference changes and the differences between devices are also large, it may be necessary to comprehensively re-evaluate and optimize the selection and layout of the equipment and the anti-interference strategy of the system to improve the consistency of the equipment and the overall performance of the system; according to the combination of the mean and the difference, more refined resource allocation can be achieved; when the mean is high but the difference is small, it means that all devices in the group are facing high interference changes. At this time, it is necessary to evenly increase the anti-interference resources for the entire group, such as uniformly upgrading the anti-interference modules of the equipment and adding signal repeaters; and when the mean is high and the difference is also large, in addition to adding resources for the entire group, it is also necessary to give additional resources to the devices with large interference change values, such as equipping these devices with stronger antennas or separate signal processing units to ensure their normal operation; for the case of low mean but large difference, you can focus on those devices with large interference change values ​​and allocate a small amount of targeted resources to them for optimization without large-scale resource investment for the entire group.

[0087] See also Figure 2 In the second embodiment of the present invention, a Bluetooth anti-interference connection optimization processing system based on the Internet of Things is provided, and the system includes: a data block and function type group division module, a data acquisition module, a data calculation and prediction module, and an interference comprehensive value calculation and analysis module.

[0088] The data block and function type group division module is used to obtain channel interference data and communication signal quality data of Bluetooth devices in a large factory; based on the function type, the Bluetooth devices are classified to construct function type groups.

[0089] The data acquisition module: utilizes the Internet of Things technology to interconnect the Bluetooth devices in the functional type group; and obtains the channel interference data and communication signal quality data of the Bluetooth devices at the same time node.

[0090] The data calculation and prediction module: calculates the signal interference degree of a single Bluetooth device at the current time node based on the channel interference data and the communication signal quality data; calculates the interference fluctuation characteristic value based on the signal interference degree; calculates the signal interference change value of a single Bluetooth device in the future based on the signal interference degree and the interference fluctuation characteristic value.

[0091] The interference comprehensive value calculation and analysis module calculates the difference and mean of the signal interference change values ​​of all Bluetooth devices, and based on the difference and mean, calculates the interference comprehensive value of all Bluetooth devices in the functional type group; presets a threshold, analyzes and performs connection optimization processing.

[0092] Furthermore, the data block and function type group division module includes a data block division unit and a function type group division unit.

[0093] The data block division unit divides the data blocks in the data storage unit based on the number of Bluetooth devices in the large factory, stores the working status of the Bluetooth devices in the data blocks, and one data block is divided corresponding to one Bluetooth device; the working status includes channel interference data and communication signal quality data; the data block includes a channel interference database and a communication signal quality database, and is used to store the channel interference data and the communication signal quality data respectively.

[0094] The function type group division unit: classifies the Bluetooth devices based on the function type and constructs a function type group, wherein the function type group is used to group Bluetooth devices with the same function type; adds a function type group label to the channel interference database and the communication signal quality database in the data block, and one function type group corresponds to one channel interference database and one communication signal quality database.

[0095] Furthermore, the data acquisition module includes a data acquisition unit.

[0096] The data acquisition unit: utilizes the Internet of Things technology to interconnect the Bluetooth devices in the functional type group, collects the channel interference data and communication signal quality data of the Bluetooth devices in units of minutes, and stores them in the channel interference database and the communication signal quality database respectively; extracts the channel interference data and communication signal quality data in the channel interference database and the communication signal quality database in the current minute.

[0097] Furthermore, the data calculation and prediction module includes a data calculation unit and a prediction unit.

[0098] The data calculation unit calculates the current signal interference degree of a single Bluetooth device in the functional type group based on the channel interference data and the communication signal quality data.

[0099] The prediction unit predicts the future signal interference trend of a single Bluetooth device in the functional type group based on the current signal interference degree of the single Bluetooth device in the functional type group, as follows:

[0100] The historical signal interference degree of a single Bluetooth device in the functional type group is obtained, the interference fluctuation characteristic value is calculated, and the signal interference change value of the single Bluetooth device in the functional type group in the future is calculated according to the interference fluctuation characteristic value.

[0101] Furthermore, the interference comprehensive value calculation and analysis module includes an interference comprehensive value calculation unit and an analysis unit.

[0102] The interference comprehensive value calculation unit: obtains the signal interference change values ​​of all Bluetooth devices in the function type group in the next minute, and constructs a signal interference change value set; obtains the maximum signal interference change value and the minimum signal interference change value in the signal interference change value set, calculates the difference between the maximum signal interference change value and the minimum signal interference change value, and records it as the signal interference change difference; calculates the average of the signal interference change values ​​of all Bluetooth devices in the signal interference change value set, and records it as the signal interference change average.

[0103] The analysis unit: calculates the comprehensive interference value of all Bluetooth devices in the functional type group based on the signal interference change difference and the signal interference change mean; presets a comprehensive interference threshold, and if the comprehensive interference value of all Bluetooth devices in the functional type group is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, and all Bluetooth devices in the functional type group are switched to idle channels.

[0104] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0105] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A Bluetooth anti-interference connection optimization processing method based on the Internet of Things, characterized in that: The method comprises the following steps: Step S1: Acquire channel interference data and communication signal quality data of Bluetooth devices in a large factory; classify the Bluetooth devices based on functional types and construct functional type groups; Step S2: interconnecting the Bluetooth devices in the functional type group using the Internet of Things technology; obtaining channel interference data and communication signal quality data of the Bluetooth devices at the same time node; Step S3: Based on the channel interference data and the communication signal quality data, the signal interference degree of a single Bluetooth device at the current time node is calculated; based on the signal interference degree, an interference fluctuation characteristic value is calculated; based on the signal interference degree and the interference fluctuation characteristic value, a signal interference change value of the single Bluetooth device in the future is calculated; Step S4: Calculate the difference and mean of the signal interference change values ​​of all Bluetooth devices, and based on the difference and mean, calculate the comprehensive interference value of all Bluetooth devices in the functional type group; preset a threshold, analyze and perform connection optimization processing.

2. According to the method for optimizing Bluetooth anti-interference connection based on the Internet of Things in claim 1, it is characterized in that: The specific implementation process of step S1 includes: Based on the number of Bluetooth devices in a large factory, a data block is divided in a data storage unit, and the working state of the Bluetooth device is stored in the data block, and one data block is divided corresponding to one Bluetooth device; the working state includes channel interference data and communication signal quality data; the data block includes a channel interference database and a communication signal quality database, and is used to store the channel interference data and the communication signal quality data respectively; Based on the functional type, the Bluetooth devices are classified to construct functional type groups, and the functional type groups are used to group Bluetooth devices with the same functional type; functional type group labels are attached to the channel interference database and the communication signal quality database in the data block, and one functional type group corresponds to one channel interference database and one communication signal quality data.

3. According to the method for optimizing Bluetooth anti-interference connection based on the Internet of Things in claim 2, it is characterized in that: The specific implementation process of step S2 includes: Using the Internet of Things technology, the Bluetooth devices in the functional type group are interconnected, and the channel interference data and communication signal quality data of the Bluetooth devices are collected in units of minutes, and stored in the channel interference database and the communication signal quality database respectively; Extract the channel interference data and communication signal quality data from the channel interference database and communication signal quality database at the tth minute, and record them as CID t (n) and CSQ t (n), where CID t (n) represents the channel interference data of the nth Bluetooth device in the functional type group at the tth minute, CSQ t (n) represents the communication signal quality data of the nth Bluetooth device in the functional type group at the tth minute.

4. According to the method for optimizing Bluetooth anti-interference connection based on the Internet of Things in claim 3, it is characterized in that: The specific implementation process of step S3 includes: Based on channel interference data CID t (n) and communication signal quality data CSQ t (n), calculate the signal interference of the nth Bluetooth device in the functional type group at the tth minute, the calculation formula is as follows: Among them, SD t (n) represents the signal interference degree of the nth Bluetooth device in the functional type group at the tth minute, and α represents the channel interference data CID t (n) is the adjustment factor, and β represents the communication signal quality data CSQ t (n) regulatory factors; Based on the signal interference SD of the nth Bluetooth device in the functional type group at the tth minute t (n), predict the future signal interference trend of the nth Bluetooth device in the functional type group as follows: Get the signal interference degree of the nth Bluetooth device in the functional type group within a total of M minutes in history, and calculate the interference fluctuation characteristic value. The calculation formula is as follows: Among them, F t (n) represents the disturbance fluctuation characteristic value, i represents the index variable, SD t-i (n) represents the signal interference level of the nth Bluetooth device in the functional type group at the tith minute; According to the interference fluctuation characteristic value F t (n), calculate the signal interference change value of the nth Bluetooth device in the functional type group in the future, the calculation formula is as follows: Among them, ΔSD t+1 (n) represents the signal interference change value of the nth Bluetooth device in the function type group in the next minute, and γ and δ represent the weight adjustment factors of the preset signal interference degree and interference fluctuation characteristic value respectively.

5. The method for optimizing Bluetooth anti-interference connection based on the Internet of Things according to claim 4 is characterized in that: The specific implementation process of step S4 includes: Obtain the signal interference change values ​​of all Bluetooth devices in the function type group in the next minute, and construct a signal interference change value set, recorded as SIC = {ΔSD t+1 (n)|n∈[1,N]}, where N represents the total number of Bluetooth devices in the function type group; obtain the signal interference change value set SIC={ΔSD t+1 (n)|n∈[1,N]}, calculate the difference between the maximum signal interference change value and the minimum signal interference change value, and record it as the signal interference change difference SID t+1 (n); Calculate the signal interference change value set SIC = {ΔSD t+1 The mean of the signal interference change values ​​of all Bluetooth devices in (n)|n∈[1,N]} is recorded as the mean signal interference change value Based on signal interference variation difference SID t+1 (n) and the mean value of signal interference variation Calculate the comprehensive interference value of all Bluetooth devices in the functional type group. The calculation formula is as follows: Among them, ICV t+1 Indicates the combined interference value of all Bluetooth devices in the functional type group; Preset interference comprehensive threshold, if the interference comprehensive value ICV of all Bluetooth devices in the function type group t+1 If the interference value is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, and all Bluetooth devices in the functional type group are switched to idle channels.

6. A Bluetooth anti-interference connection optimization processing system based on the Internet of Things, executing a Bluetooth anti-interference connection optimization processing method based on the Internet of Things as described in any one of claims 1-5, characterized in that: The system comprises: a data block and function type group division module, a data acquisition module, a data calculation and prediction module and an interference comprehensive value calculation and analysis module; The data block and function type group division module: obtains channel interference data and communication signal quality data of Bluetooth devices in a large factory; classifies the Bluetooth devices based on function types and constructs function type groups; The data acquisition module: uses the Internet of Things technology to interconnect the Bluetooth devices in the functional type group; obtains the channel interference data and communication signal quality data of the Bluetooth devices at the same time node; The data calculation and prediction module: calculates the signal interference degree of a single Bluetooth device at the current time node based on the channel interference data and the communication signal quality data; calculates the interference fluctuation characteristic value based on the signal interference degree; calculates the signal interference change value of a single Bluetooth device in the future based on the signal interference degree and the interference fluctuation characteristic value; The interference comprehensive value calculation and analysis module calculates the difference and mean of the signal interference change values ​​of all Bluetooth devices, and based on the difference and mean, calculates the interference comprehensive value of all Bluetooth devices in the functional type group; presets a threshold, analyzes and performs connection optimization processing.

7. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 6 is characterized in that: The data block and function type group division module includes a data block division unit and a function type group division unit; The data block division unit divides the data blocks in the data storage unit based on the number of Bluetooth devices in the large factory, stores the working status of the Bluetooth devices in the data blocks, and one data block is divided corresponding to one Bluetooth device; the working status includes channel interference data and communication signal quality data; the data block includes a channel interference database and a communication signal quality database, and is used to store the channel interference data and the communication signal quality data respectively; The function type group division unit: classifies the Bluetooth devices based on the function type and constructs a function type group, wherein the function type group is used to group Bluetooth devices with the same function type; adds a function type group label to the channel interference database and the communication signal quality database in the data block, and one function type group corresponds to one channel interference database and one communication signal quality database.

8. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 7 is characterized in that: The data acquisition module includes a data acquisition unit; The data acquisition unit: utilizes the Internet of Things technology to interconnect the Bluetooth devices in the functional type group, collects the channel interference data and communication signal quality data of the Bluetooth devices in units of minutes, and stores them in the channel interference database and the communication signal quality database respectively; extracts the channel interference data and communication signal quality data in the channel interference database and the communication signal quality database in the current minute.

9. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 8, characterized in that: The data calculation and prediction module includes a data calculation unit and a prediction unit; The data calculation unit calculates the current signal interference degree of a single Bluetooth device in the functional type group based on the channel interference data and the communication signal quality data; The prediction unit predicts the future signal interference trend of a single Bluetooth device in the functional type group based on the current signal interference degree of the single Bluetooth device in the functional type group, as follows: The historical signal interference degree of a single Bluetooth device in the functional type group is obtained, the interference fluctuation characteristic value is calculated, and the signal interference change value of the single Bluetooth device in the functional type group in the future is calculated according to the interference fluctuation characteristic value.

10. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 9, characterized in that: The interference comprehensive value calculation and analysis module includes an interference comprehensive value calculation unit and an analysis unit; The interference comprehensive value calculation unit: obtains the signal interference change values ​​of all Bluetooth devices in the function type group in the next minute, and constructs a signal interference change value set; obtains the maximum signal interference change value and the minimum signal interference change value in the signal interference change value set, calculates the difference between the maximum signal interference change value and the minimum signal interference change value, and records it as the signal interference change difference; calculates the mean of the signal interference change values ​​of all Bluetooth devices in the signal interference change value set, and records it as the signal interference change mean; The analysis unit calculates the interference comprehensive value of all Bluetooth devices in the function type group based on the signal interference change difference and the signal interference change mean; A comprehensive interference threshold is preset. If the comprehensive interference value of all Bluetooth devices in the functional type group is greater than the comprehensive interference threshold, it is determined that abnormal interference exists in the functional type group, and all Bluetooth devices in the functional type group are switched to idle channels.

Images