A bluetooth anti-interference connection optimization processing method and system based on an internet of things

Abstract

The application discloses a kind of based on Internet of Things's bluetooth anti-interference connection optimization processing method and system, belong to connection optimization processing technical field;The channel interference data and communication signal quality data of bluetooth device are acquired, and function type group is constructed;The channel interference data and communication signal quality data of bluetooth device under the same time node are acquired;Signal interference degree of single bluetooth device under current time node is calculated;Interference fluctuation eigenvalue is calculated;Signal interference change value of single bluetooth device in future is calculated;Difference and mean of signal interference change value are calculated, based on the difference and mean, the interference comprehensive value of all bluetooth devices in function type group is calculated;Preset threshold value, analysis and connection optimization processing are carried out.The application constructs function type group, dynamically analyzes signal interference degree and its fluctuation eigenvalue, and realizes the connection optimization of bluetooth device in combination with Internet of Things technology, successfully solves the anti-interference problem of bluetooth device in complex industrial environment.

Description

Technical Field

[0001] This invention relates to the field of connectivity optimization processing technology, specifically to a Bluetooth anti-interference connectivity optimization processing method and system based on the Internet of Things. Background Technology

[0002] With the rapid development of Internet of Things (IoT) technology, Bluetooth devices are increasingly used in industrial scenarios, especially in large factories, where they are widely used for tasks such as data acquisition, status monitoring, and equipment control. However, in complex industrial environments, the performance of Bluetooth devices is affected by various factors, including channel congestion, electromagnetic interference, and high device density. These interferences not only degrade communication quality but may also cause data transmission delays or even communication interruptions. Existing technologies typically mitigate interference through spectrum allocation optimization, power regulation, or channel switching between devices. However, these methods largely rely on static analysis and do not fully consider the dynamic and complex nature of interference in industrial scenarios. Furthermore, these methods cannot monitor and predict the signal interference trends of Bluetooth devices in real time, resulting in limitations in their anti-interference effectiveness.

[0003] Existing Bluetooth anti-interference technologies lack grouping optimization methods based on device function types. Devices with different functions may cause interference on the same channel, reducing the overall performance of the system. Furthermore, it is difficult to dynamically predict and respond to interference trends in real time, resulting in delayed anti-interference measures. In large-scale factory scenarios with dense deployment of Bluetooth devices, existing technologies are insufficient in their ability to optimize interference for the entire network and cannot simultaneously meet the anti-interference requirements of the whole and the local areas. These problems severely restrict the widespread application of Bluetooth technology in industrial environments. Summary of the Invention

[0004] The purpose of this invention is to provide a Bluetooth anti-interference connection optimization processing method and system based on the Internet of Things to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] A Bluetooth anti-interference connection optimization method based on the Internet of Things (IoT) includes the following steps: acquiring channel interference data and communication signal quality data of Bluetooth devices in a large factory; classifying the Bluetooth devices according to their function type to construct function type groups; interconnecting the Bluetooth devices in the function type groups using IoT technology; acquiring channel interference data and communication signal quality data of Bluetooth devices at the same time point; calculating the signal interference degree of a single Bluetooth device at the current time point based on the channel interference data and communication signal quality data; calculating the interference fluctuation characteristic value based on the signal interference degree; calculating the future signal interference change value of a single Bluetooth device based on the signal interference degree and interference fluctuation characteristic value; calculating the difference and mean of the signal interference change values ​​of all Bluetooth devices; calculating the comprehensive interference value of all Bluetooth devices in the function type group based on the difference and mean; and setting a preset threshold for analysis and connection optimization processing.

[0007] As a preferred embodiment of the Bluetooth anti-interference connection optimization processing method based on the Internet of Things described in this 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 devices is stored in the data blocks. Each Bluetooth device corresponds to one data block. The working status includes channel interference data and communication signal quality data. The data blocks include a channel interference database and a communication signal quality database, which are used to store the channel interference data and the communication signal quality data, respectively.

[0008] Based on their function type, the Bluetooth devices are classified to form function type groups. These function type groups are used to group Bluetooth devices with the same function type (including devices for receiving audio, devices for input, devices for monitoring, etc.). Function type group labels are added to the channel interference database and 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.

[0009] It should be noted that channel interference data is collected using a professional spectrum analyzer, while communication signal quality data is collected using the device's built-in signal strength indicator or third-party monitoring software.

[0010] As a preferred embodiment of the Bluetooth anti-interference connection optimization processing method based on the Internet of Things described in this invention, the Bluetooth devices in the functional type group are interconnected using Internet of Things technology. Channel interference data and communication signal quality data of the Bluetooth devices are collected in 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 minute t, and denot them as CID respectively.t (n) and CSQ t (n), where CID t (n) represents the channel interference data of the nth Bluetooth device in the function type group at minute t, CSQ t (n) represents the communication signal quality data of the nth Bluetooth device in the function type group at minute t.

[0012] As a preferred embodiment of the Bluetooth anti-interference connection optimization processing method based on the Internet of Things described in this invention, it is based on channel interference data (CID). t (n) and communication signal quality data CSQ t (n), calculates the signal interference of the nth Bluetooth device in the function type group at minute t, using the following formula:

[0013]

[0014] Among them, SD t (n) represents the signal interference level of the nth Bluetooth device in the function type group at minute t, and α represents the Channel Interference Data (CID). t The adjustment factor of (n), where β represents the communication signal quality data CSQ t (n) is a regulating factor.

[0015] It should be noted that in this invention, the signal interference degree formula plays a key role in quantifying the degree of interference experienced by Bluetooth devices. Through this formula, the collected channel interference data and communication signal quality data can be transformed 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, providing a basis for subsequent interference analysis and optimization. For example, in a large factory, there are many Bluetooth devices with different functions. By calculating the signal interference degree of each device, it is possible to quickly identify which devices are experiencing more severe interference, thereby enabling targeted further processing and optimization.

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

[0017] To obtain the signal interference level of the nth Bluetooth device in the function type group over a historical period of M minutes, calculate the interference fluctuation characteristic value using the following formula:

[0018]

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

[0020] Based on the characteristic value F of the disturbance fluctuation t (n) is used to calculate the future signal interference change value of the nth Bluetooth device in the function type group. The calculation formula is as follows:

[0021]

[0022] Wherein, 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 preset weight adjustment factors of signal interference degree and interference fluctuation characteristic value, respectively.

[0023] It should be noted that in the formula This represents the derivative of signal interference with respect to time, reflecting the rate of change of signal interference over time. Through this derivative, we can understand the 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 over a historical period; the greater the fluctuation, the higher the F... t The larger the value of (n), the greater the signal interference change value. In this invention, the signal interference change value formula is used to predict the future signal interference trend of Bluetooth devices. By combining the rate of change of signal interference 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. This 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, the operating parameters of the device can be adjusted in time, such as switching to a channel with less interference or adjusting the transmission power, to ensure the stability and reliability of the Bluetooth connection and avoid 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 be optimized, and the anti-interference capability and performance of the entire system can be improved.

[0024] As a preferred embodiment of the Bluetooth anti-interference connection optimization processing method based on the Internet of Things described in this invention, the signal interference change values ​​of all Bluetooth devices in the function type group are obtained in the next minute, and a set of signal interference change values ​​is constructed, denoted 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 set of signal interference change values ​​SIC={ΔSD t+1The maximum and minimum signal interference changes in the set (n)|n∈[1,N]} are used to calculate the difference between the maximum and minimum signal interference changes, denoted as the signal interference change difference SID. t+1 (n).

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

[0026] Based on the difference in signal interference (SID) t+1 (n) and mean change in signal interference The overall interference value for all Bluetooth devices in the function type group is calculated using the following formula:

[0027]

[0028] Among them, ICV t+1 This represents the overall interference value for all Bluetooth devices in the function type group.

[0029] The preset interference threshold is set if the combined interference value (ICV) of all Bluetooth devices in the function type group is lower than the threshold value. t+1 If the interference exceeds the comprehensive interference threshold, it is determined that there is abnormal interference in the function type group. In this case, all Bluetooth devices in the function type group are switched to an idle channel, and staff are notified to investigate possible sources of interference in the usage environment.

[0030] It should be noted that the mean reflects the average interference level of devices within a functional group, while the difference reflects the dispersion of interference changes between devices. When the mean is within the normal range but the difference is large, it indicates that although the overall interference situation within the group is acceptable, there are individual devices with abnormally prominent interference changes. For example, in a group of Bluetooth devices used for monitoring, the mean shows that the overall interference change is not significant, but the difference is large. Further analysis can identify a monitoring device in a specific location that is affected by a special interference source (such as a newly added high-power device nearby), allowing for timely adjustment or maintenance of that device without the need for large-scale optimization of the entire group, thus improving the accuracy and efficiency of maintenance. If both the mean and the difference are small, it indicates that the devices within the group not only have stable overall interference changes, but also that the interference changes between devices are relatively consistent, indicating that the device performance and the environment are similar, resulting in high system stability. Conversely, if both the mean and the difference are large, it indicates that the devices within the group are not only generally affected by strong interference, but also... The interference variations are significant, and the differences between devices are also substantial. Therefore, a comprehensive reassessment and optimization of device selection, layout, and anti-interference strategies may be necessary to improve device consistency and overall system performance. A more refined resource allocation can be achieved based on the combined mean and difference values. When the mean is high but the difference is small, it indicates that all devices in the group face high interference variations. In this case, anti-interference resources need to be increased evenly across the entire group, such as uniformly upgrading anti-interference modules or adding signal repeaters. When both the mean and the difference are high, in addition to increasing resources for the entire group, additional resources should be allocated to devices with large interference variations, such as equipping them with stronger antennas or dedicated signal processing units to ensure their normal operation. For cases with low mean but large difference values, the focus can be on devices with large interference variations, allocating a small amount of targeted resources for optimization without requiring large-scale resource investment across the entire group.

[0031] A Bluetooth anti-interference connection optimization processing system based on the Internet of Things 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.

[0032] The data block and function type group division module: acquires channel interference data and communication signal quality data of Bluetooth devices in a large factory; classifies the Bluetooth devices based on their function type and constructs function type groups.

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

[0034] The data calculation and prediction module: calculates the signal interference level of a single Bluetooth device at the current time point based on channel interference data and communication signal quality data; calculates the interference fluctuation characteristic value based on the signal interference level; and calculates the future signal interference change value of a single Bluetooth device based on the signal interference level 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 calculates the interference comprehensive value of all Bluetooth devices in the function type group based on the difference and mean; it also presets a threshold, analyzes and performs connection optimization processing.

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

[0037] The data block partitioning unit: Based on the number of Bluetooth devices in the large factory, it partitions the data storage unit into data blocks, stores the working status of the Bluetooth devices in the data blocks, and assigns one data block to each 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 grouping unit: classifies the Bluetooth devices based on their function type and constructs function type groups, which are used to group Bluetooth devices with the same function type; and adds function type group labels to the channel interference database and communication signal quality database in the data block, wherein one function type group corresponds to one channel interference database and one communication signal quality data.

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

[0040] The data acquisition unit: uses Internet of Things (IoT) technology to interconnect the Bluetooth devices in the functional type group, collects channel interference data and communication signal quality data of the Bluetooth devices on a minute-by-minute basis, and stores them in the channel interference database and the communication signal quality database respectively; and extracts the channel interference data and communication signal quality data from the channel interference database and the communication signal quality database for 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 level of a single Bluetooth device in the function type group based on channel interference data and communication signal quality data.

[0043] The prediction unit: Based on the current signal interference level of a single Bluetooth device in the function type group, predicts the future signal interference trend of that single Bluetooth device in the function type group, as follows:

[0044] Obtain the historical signal interference level of a single Bluetooth device in the function type group, calculate the interference fluctuation characteristic value, and calculate the future signal interference change value of a single Bluetooth device in the function type group based on 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 value 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 value; 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 mean of the signal interference change value.

[0047] The analysis unit calculates the comprehensive interference value of all Bluetooth devices in the function type group based on the difference and mean of signal interference changes; it presets a comprehensive interference threshold, and if the comprehensive interference value of all Bluetooth devices in the function type group is greater than the comprehensive interference threshold, it determines that there is abnormal interference in the function type group, and then switches all Bluetooth devices in the function type group to an idle channel.

[0048] Compared with the prior art, the beneficial effects achieved by the present invention are: the present invention provides a Bluetooth anti-interference connection optimization processing method and system based on the Internet of Things. Attached Figure Description

[0049] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

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

[0051] Figure 2 This is a schematic diagram of the structure of a Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Please see Figure 1 In this first embodiment: a Bluetooth anti-interference connection optimization processing method based on the Internet of Things is provided, which includes the following steps:

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

[0055] Specifically, 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 devices is stored in the data blocks. Each Bluetooth device corresponds to one data block. The working status includes channel interference data and communication signal quality data. The data blocks include a channel interference database and a communication signal quality database, which are used to store the channel interference data and the communication signal quality data, respectively.

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

[0057] It should be noted that channel interference data is collected using a professional spectrum analyzer, while communication signal quality data is collected using the device's built-in signal strength indicator or third-party monitoring software.

[0058] Step S2: Using Internet of Things (IoT) technology, interconnect the Bluetooth devices in the functional type group; obtain channel interference data and communication signal quality data of the Bluetooth devices at the same time point.

[0059] Specifically, using Internet of Things (IoT) technology, Bluetooth devices in the functional type group are interconnected, and channel interference data and communication signal quality data of the Bluetooth devices are collected on a minute-by-minute basis, and stored in the channel interference database and the communication signal quality database respectively.

[0060] Furthermore, channel interference data and communication signal quality data are extracted from the channel interference database and communication signal quality database at minute t, and denoted as CID respectively. t (n) and CSQ t (n), where CID t (n) represents the channel interference data of the nth Bluetooth device in the function type group at minute t, CSQ t (n) represents the communication signal quality data of the nth Bluetooth device in the function type group at minute t.

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

[0062] Specifically, based on channel interference data CID t (n) and communication signal quality data CSQ t (n), calculates the signal interference of the nth Bluetooth device in the function type group at minute t, using the following formula:

[0063]

[0064] Among them, SD t (n) represents the signal interference level of the nth Bluetooth device in the function type group at minute t, and α represents the Channel Interference Data (CID). t The adjustment factor of (n), where β represents the communication signal quality data CSQ t (n) is a regulating factor.

[0065] For example, suppose 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 these values ​​into the formula, we can obtain the following results.

[0066] It should be noted that in this invention, the signal interference degree formula plays a key role in quantifying the degree of interference experienced by Bluetooth devices. Through this formula, the collected channel interference data and communication signal quality data can be transformed 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, providing a basis for subsequent interference analysis and optimization. For example, in a large factory, there are many Bluetooth devices with different functions. By calculating the signal interference degree of each device, it is possible to quickly identify which devices are experiencing more severe interference, thereby enabling targeted further processing and optimization.

[0067] Furthermore, based on the signal interference SD of the nth Bluetooth device in the function type group at minute t. t (n) predicts the future signal interference trend of the nth Bluetooth device in the function type group, as follows:

[0068] To obtain the signal interference level of the nth Bluetooth device in the function type group over a historical period of M minutes, calculate the interference fluctuation characteristic value using the following formula:

[0069]

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

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

[0072] Based on the characteristic value F of the disturbance fluctuation t (n) is used to calculate the future signal interference change value of the nth Bluetooth device in the function type group. The calculation formula is as follows:

[0073]

[0074] Wherein, 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 preset weight adjustment factors of signal interference degree and interference fluctuation characteristic value, respectively.

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

[0076] It should be noted that in the formula This represents the derivative of signal interference with respect to time, reflecting the rate of change of signal interference over time. Through this derivative, we can understand the 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 over a historical period; the greater the fluctuation, the higher the F... t The larger the value of (n), the greater the signal interference change value. In this invention, the signal interference change value formula is used to predict the future signal interference trend of Bluetooth devices. By combining the rate of change of signal interference 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. This 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, the operating parameters of the device can be adjusted in time, such as switching to a channel with less interference or adjusting the transmission power, to ensure the stability and reliability of the Bluetooth connection and avoid 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 be optimized, and the anti-interference capability and performance of the entire system can be improved.

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

[0078] Specifically, obtain the signal interference change values ​​of all Bluetooth devices in the function type group for the next minute, construct a set of signal interference change values, denoted 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 set of signal interference change values ​​SIC={ΔSD t+1 The maximum and minimum signal interference changes in the set (n)|n∈[1,N]} are used to calculate the difference between the maximum and minimum signal interference changes, denoted as the signal interference change difference SID. t+1 (n).

[0079] Furthermore, the set of signal interference variation values ​​SIC = {ΔSD} is calculated. t+1 The mean value of the signal interference variation of all Bluetooth devices in the range (n)|n∈[1,N]} is denoted as the mean value of the signal interference variation.

[0080] Based on the difference in signal interference (SID) t+1 (n) and mean change in signal interference The overall interference value for all Bluetooth devices in the function type group is calculated using the following formula:

[0081]

[0082] Among them, ICV t+1 This represents the overall interference value for all Bluetooth devices in the function type group.

[0083] For example, suppose The value is 0.0657, SID t+1 (n) is 0.0192. Substituting this into the formula, we obtain the comprehensive interference value ICV. 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 function type group is... t+1 If the interference exceeds the comprehensive interference threshold, it is determined that there is abnormal interference in the function type group. In this case, all Bluetooth devices in the function type group are switched to an idle channel, and staff are notified to investigate possible sources of interference in the usage environment.

[0085] For example, assuming the interference synthesis threshold is 0.05, the interference synthesis value (ICV) for all Bluetooth devices in the function type group is... t+1 If the interference exceeds the comprehensive interference threshold, it is determined that there is abnormal interference in the function type group. In this case, all Bluetooth devices in the function type group are switched to an idle channel, and staff are notified to investigate possible sources of interference in the usage environment.

[0086] It should be noted that the mean reflects the average interference level of devices within a functional group, while the difference reflects the dispersion of interference changes between devices. When the mean is within the normal range but the difference is large, it indicates that although the overall interference situation within the group is acceptable, there are individual devices with abnormally prominent interference changes. For example, in a group of Bluetooth devices used for monitoring, the mean shows that the overall interference change is not significant, but the difference is large. Further analysis can identify a monitoring device in a specific location that is affected by a special interference source (such as a newly added high-power device nearby), allowing for timely adjustment or maintenance of that device without the need for large-scale optimization of the entire group, thus improving the accuracy and efficiency of maintenance. If both the mean and the difference are small, it indicates that the devices within the group not only have stable overall interference changes, but also that the interference changes between devices are relatively consistent, indicating that the device performance and the environment are similar, resulting in high system stability. Conversely, if both the mean and the difference are large, it indicates that the devices within the group are not only generally affected by strong interference, but also... The interference variations are significant, and the differences between devices are also substantial. Therefore, a comprehensive reassessment and optimization of device selection, layout, and anti-interference strategies may be necessary to improve device consistency and overall system performance. A more refined resource allocation can be achieved based on the combined mean and difference values. When the mean is high but the difference is small, it indicates that all devices in the group face high interference variations. In this case, anti-interference resources need to be increased evenly across the entire group, such as uniformly upgrading anti-interference modules or adding signal repeaters. When both the mean and the difference are high, in addition to increasing resources for the entire group, additional resources should be allocated to devices with large interference variations, such as equipping them with stronger antennas or dedicated signal processing units to ensure their normal operation. For cases with low mean but large difference values, the focus can be on devices with large interference variations, allocating a small amount of targeted resources for optimization without requiring large-scale resource investment across the entire group.

[0087] Please see Figure 2 In this second embodiment, a Bluetooth anti-interference connection optimization processing system based on the Internet of Things is provided. 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: acquires channel interference data and communication signal quality data of Bluetooth devices in a large factory; classifies the Bluetooth devices based on their function type and constructs function type groups.

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

[0090] The data calculation and prediction module: calculates the signal interference level of a single Bluetooth device at the current time point based on channel interference data and communication signal quality data; calculates the interference fluctuation characteristic value based on the signal interference level; and calculates the future signal interference change value of a single Bluetooth device based on the signal interference level 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 calculates the interference comprehensive value of all Bluetooth devices in the function type group based on the difference and mean; it also presets a threshold, analyzes and performs connection optimization processing.

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

[0093] The data block partitioning unit: Based on the number of Bluetooth devices in the large factory, it partitions the data storage unit into data blocks, stores the working status of the Bluetooth devices in the data blocks, and assigns one data block to each 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 grouping unit: classifies the Bluetooth devices based on their function type and constructs function type groups, which are used to group Bluetooth devices with the same function type; and adds function type group labels to the channel interference database and communication signal quality database in the data block, wherein one function type group corresponds to one channel interference database and one communication signal quality data.

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

[0096] The data acquisition unit: uses Internet of Things (IoT) technology to interconnect the Bluetooth devices in the functional type group, collects channel interference data and communication signal quality data of the Bluetooth devices on a minute-by-minute basis, and stores them in the channel interference database and the communication signal quality database respectively; and extracts the channel interference data and communication signal quality data from the channel interference database and the communication signal quality database for 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 level of a single Bluetooth device in the function type group based on channel interference data and communication signal quality data.

[0099] The prediction unit: Based on the current signal interference level of a single Bluetooth device in the function type group, predicts the future signal interference trend of that single Bluetooth device in the function type group, as follows:

[0100] Obtain the historical signal interference level of a single Bluetooth device in the function type group, calculate the interference fluctuation characteristic value, and calculate the future signal interference change value of a single Bluetooth device in the function type group based on 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 value 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 value; 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 mean of the signal interference change value.

[0103] The analysis unit calculates the comprehensive interference value of all Bluetooth devices in the function type group based on the difference and mean of signal interference changes; it presets a comprehensive interference threshold, and if the comprehensive interference value of all Bluetooth devices in the function type group is greater than the comprehensive interference threshold, it determines that there is abnormal interference in the function type group, and then switches all Bluetooth devices in the function type group to an idle channel.

[0104] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0105] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A Bluetooth anti-interference connection optimization method based on the Internet of Things, characterized in that, The method includes the following steps: Step S1: Obtain channel interference data and communication signal quality data of Bluetooth devices in a large factory; classify the Bluetooth devices based on their function type and construct function type groups; Step S2: Using Internet of Things (IoT) technology, interconnect the Bluetooth devices in the functional type group; obtain channel interference data and communication signal quality data of the Bluetooth devices at the same time point; Step S3: Based on channel interference data and communication signal quality data, calculate the signal interference level of a single Bluetooth device at the current time point; based on the signal interference level, calculate the interference fluctuation characteristic value; based on the signal interference level and the interference fluctuation characteristic value, calculate the future signal interference change value of a single Bluetooth device. Step S4: Calculate the difference and mean of the signal interference change values ​​of all Bluetooth devices; based on the difference and mean, calculate the comprehensive interference value of all Bluetooth devices in the function type group; preset a threshold, analyze and perform connection optimization processing; The specific implementation process of step S3 includes: Based on Channel Interference Data (CID) t (n) and communication signal quality data CSQ t (n), calculates the signal interference of the nth Bluetooth device in the function type group at minute t, using the following formula: Among them, SD t (n) represents the signal interference level of the nth Bluetooth device in the function type group at minute t, and α represents the Channel Interference Data (CID). t The adjustment factor of (n), where β represents the communication signal quality data CSQ t The regulating factor of (n); Based on the signal interference SD of the nth Bluetooth device in the function type group at minute t. t (n) predicts the future signal interference trend of the nth Bluetooth device in the function type group, as follows: To obtain the signal interference level of the nth Bluetooth device in the function type group over a historical period of M minutes, calculate the interference fluctuation characteristic value using the following formula: Among them, F t (n) represents the characteristic value of disturbance fluctuation, i represents the index variable, and SD t-i (n) represents the signal interference level of the nth Bluetooth device in the function type group at minute ti; Based on the characteristic value F of the disturbance fluctuation t (n) is used to calculate the future signal interference change value of the nth Bluetooth device in the function type group. The calculation formula is as follows: Wherein, 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 preset weight adjustment factors of signal interference degree and interference fluctuation characteristic value, respectively. The specific implementation process of step S4 includes: Obtain the signal interference change values ​​of all Bluetooth devices in the function type group for the next minute, and construct a set of signal interference change values, denoted 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 set of signal interference change values ​​SIC={ΔSD t+1 The maximum and minimum signal interference changes in the set (n)|n∈[1,N]} are used to calculate the difference between the maximum and minimum signal interference changes, denoted as the signal interference change difference SID. t+1 (n); Calculate the set of signal interference variation values ​​SIC = {ΔSD} t+1 The mean value of the signal interference variation of all Bluetooth devices in (n)|n∈[1,N]} is denoted as the mean value of the signal interference variation. Based on the difference in signal interference (SID) t+1 (n) and mean change in signal interference The overall interference value for all Bluetooth devices in the function type group is calculated using the following formula: Among them, ICV t+1 This represents the combined interference value for all Bluetooth devices in the function type group; The preset interference threshold is set if the combined interference value (ICV) of all Bluetooth devices in the function type group is lower than the threshold value. t+1 If the interference exceeds the comprehensive interference threshold, it is determined that there is abnormal interference in the function type group, and all Bluetooth devices in the function type group are switched to the idle channel.

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

3. The Bluetooth anti-interference connection optimization processing method based on the Internet of Things according to claim 2, characterized in that, The specific implementation process of step S2 includes: Using Internet of Things (IoT) technology, Bluetooth devices in the functional type group are interconnected, and channel interference data and communication signal quality data of the Bluetooth devices are collected in minutes and stored in the channel interference database and 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 minute t, and denot them as CID respectively. t (n) and CSQ t (n), where CID t (n) represents the channel interference data of the nth Bluetooth device in the function type group at minute t, CSQ t (n) represents the communication signal quality data of the nth Bluetooth device in the function type group at minute t.

4. A Bluetooth anti-interference connection optimization processing system based on the Internet of Things, executing the Bluetooth anti-interference connection optimization processing method based on the Internet of Things as described in any one of claims 1-3, characterized in that, 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; The data block and function type group division module: acquires channel interference data and communication signal quality data of Bluetooth devices in a large factory; classifies the Bluetooth devices based on their function type and constructs function type groups; The data acquisition module utilizes Internet of Things (IoT) technology to interconnect Bluetooth devices in the functional type group; and acquires channel interference data and communication signal quality data of Bluetooth devices at the same time point. The data calculation and prediction module: calculates the signal interference level of a single Bluetooth device at the current time point based on channel interference data and communication signal quality data; calculates the interference fluctuation characteristic value based on the signal interference level; and calculates the future signal interference change value of a single Bluetooth device based on the signal interference level 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 calculates the interference comprehensive value of all Bluetooth devices in the function type group based on the difference and mean; it also presets a threshold, analyzes and performs connection optimization processing.

5. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 4, characterized in that: The data block and function type group partitioning module includes a data block partitioning unit and a function type group partitioning unit; The data block partitioning unit: Based on the number of Bluetooth devices in the large factory, it partitions the data storage unit into data blocks, stores the working status of the Bluetooth devices in the data blocks, and assigns one data block to each 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 grouping unit: classifies the Bluetooth devices based on their function type and constructs function type groups, which are used to group Bluetooth devices with the same function type; and adds function type group labels to the channel interference database and communication signal quality database in the data block, wherein one function type group corresponds to one channel interference database and one communication signal quality data.

6. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 5, characterized in that: The data acquisition module includes a data acquisition unit; The data acquisition unit: uses Internet of Things (IoT) technology to interconnect the Bluetooth devices in the functional type group, collects channel interference data and communication signal quality data of the Bluetooth devices on a minute-by-minute basis, and stores them in the channel interference database and the communication signal quality database respectively; and extracts the channel interference data and communication signal quality data from the channel interference database and the communication signal quality database for the current minute.

7. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 6, 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 level of a single Bluetooth device in the function type group based on channel interference data and communication signal quality data. The prediction unit: Based on the current signal interference level of a single Bluetooth device in the function type group, predicts the future signal interference trend of that single Bluetooth device in the function type group, as follows: Obtain the historical signal interference level of a single Bluetooth device in the function type group, calculate the interference fluctuation characteristic value, and calculate the future signal interference change value of a single Bluetooth device in the function type group based on the interference fluctuation characteristic value.

8. The Bluetooth anti-interference connection optimization processing system based on the Internet of Things according to claim 7, 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 value 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 mean of the signal interference change. The analysis unit calculates the comprehensive interference value of all Bluetooth devices in the function type group based on the signal interference variation difference and the signal interference variation mean. If a preset interference threshold is set, and the overall interference value of all Bluetooth devices in the function type group is greater than the interference threshold, then it is determined that there is abnormal interference in the function type group, and all Bluetooth devices in the function type group are switched to an idle channel.

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