Method and device for rapid networking and Bluetooth device control based on Bluetooth module

Abstract

The present invention discloses a method and a device for rapid networking and Bluetooth device control based on a Bluetooth module, and relates to the technical field of wireless communication. The method comprises: scanning Bluetooth signals within a preset range through a Bluetooth Mesh gateway; extracting clients whose client ID information belongs to authorized clients for networking to generate a Mesh network; collecting operation control parameters and operation status monitoring parameters of the networking clients and sending them to a cloud IoT platform, performing data indexing in an embedded service database, and performing adjacency analysis based on adjacent non-abnormal sample collection and centralized value evaluation on the operation control parameters to obtain operation status benchmark parameters; comparing the operation status benchmark parameters with the operation status monitoring parameters to obtain the abnormal probability of the networking client; when the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold, generating a first abnormal operation alarm signal feedback, thereby achieving the technical effects of improved networking efficiency, enhanced monitoring comprehensiveness, and improved security.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method and device for rapid networking and Bluetooth device control based on a Bluetooth module. Background Art

[0002] With the rapid development of Internet of Things technology, the demand for interconnection of smart home devices is growing. As an emerging wireless communication protocol, Bluetooth Mesh technology can achieve efficient networking and collaborative work of multiple devices; however, the existing Bluetooth Mesh networking and device control methods often require users to manually pair devices and configure the network, which is cumbersome and error-prone; secondly, the remote control and status monitoring functions of devices such as smart door locks are not perfect, and users cannot grasp the operating status of the device in real time, and it is difficult to detect and handle abnormalities in the device in time; in addition, there are hidden dangers in the communication security between devices, and the data transmission process is susceptible to external interference and attacks; in summary, the existing technology has technical problems such as low networking efficiency, incomplete monitoring, and insufficient security. Summary of the invention

[0003] The present invention provides a method and device for rapid networking and Bluetooth device control based on a Bluetooth module, so as to solve the technical problems of low networking efficiency, incomplete monitoring and insufficient security in the prior art, and achieve the technical effects of improved networking efficiency, enhanced comprehensive monitoring and improved security.

[0004] In a first aspect, the present invention provides a method for rapid networking and Bluetooth device control based on a Bluetooth module, wherein the method comprises:

[0005] Scan a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information.

[0006] The client ID information of the plurality of clients belonging to the authorized clients is extracted to form a network and generate a Mesh network.

[0007] The Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to the cloud IoT platform.

[0008] The networking client ID information received by the Bluetooth Mesh gateway is used to obtain the networking client service time through the service database index embedded in the cloud IoT platform. In combination with the networking client service time and the networking client ID information, adjacency non-abnormal sample collection and centralized value evaluation are performed on the operation control parameters to achieve adjacency analysis and obtain operation status benchmark parameters.

[0009] The cloud IoT platform compares the operating status benchmark parameters with the operating status monitoring parameters to obtain the abnormal probability of the networking client.

[0010] When the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold, a first abnormal operation alarm signal is generated for the networking client and fed back to the user portable terminal.

[0011] In a second aspect, the present invention further provides a device for rapid networking and Bluetooth device control based on a Bluetooth module, wherein the device comprises:

[0012] The Bluetooth signal scanning unit is used to scan a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information.

[0013] The Mesh network generating unit is used to extract the client ID information of the plurality of clients belonging to the authorized clients for networking and generate a Mesh network.

[0014] The parameter collection and transmission unit is used for the Bluetooth Mesh gateway to collect the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and send them to the cloud IoT platform.

[0015] The operation status benchmark parameter acquisition unit is used to obtain the service time of the networking client through the networking client ID information received by the Bluetooth Mesh gateway, and the service time of the networking client and the networking client ID information. The unit performs adjacency non-abnormal sample collection and centralized value evaluation on the operation control parameters in combination with the networking client service time and the networking client ID information to realize adjacency analysis and obtain the operation status benchmark parameters.

[0016] The abnormality probability calculation unit is used to compare the operating status benchmark parameter and the operating status monitoring parameter through the cloud IoT platform to obtain the abnormality probability of the networking client.

[0017] The abnormal alarm signal generation and feedback unit is used to generate a first abnormal operation alarm signal for the networking client and feed it back to the user portable terminal when the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold.

[0018] The present invention discloses a method and apparatus for rapid networking and Bluetooth device control based on a Bluetooth module, comprising: scanning a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information; extracting a plurality of clients whose client ID information belongs to an authorized client for networking to generate a Mesh network; the Bluetooth Mesh gateway collects operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to a cloud IoT platform; the networking client ID information received by the Bluetooth Mesh gateway is used to obtain the service time of the networking client through an index in a service database embedded in the cloud IoT platform, and the service time of the networking client is combined with the service time of the networking client. The duration and networking client ID information are used to perform adjacent non-abnormal sample collection and centralized value evaluation on the operation control parameters to realize adjacent analysis and obtain the operation status benchmark parameters; the operation status benchmark parameters and the operation status monitoring parameters are compared through the cloud IoT platform to obtain the abnormal probability of the networking client; when the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold, a first abnormal operation alarm signal is generated for the networking client and fed back to the user's portable terminal. The method and device for rapid networking and Bluetooth device control based on the Bluetooth module disclosed in the present invention solve the technical problems of low networking efficiency, incomplete monitoring and insufficient security, and achieve the technical effects of improved networking efficiency, enhanced comprehensive monitoring and improved security. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a method for rapid networking and Bluetooth device control based on a Bluetooth module according to the present invention;

[0020] Figure 2 The present invention is a schematic diagram of the structure of the device for rapid networking based on Bluetooth modules and control of Bluetooth devices.

[0021] Explanation of the reference numerals: Bluetooth signal scanning unit 11, Mesh network generating unit 12, parameter collecting and transmitting unit 13, operating status reference parameter acquiring unit 14, abnormality probability calculating unit 15, abnormality alarm signal generating and feedback unit 16. DETAILED DESCRIPTION

[0022] The technical solution provided in the embodiments of the present invention is to solve the technical problems of low networking efficiency, incomplete monitoring and insufficient security in the prior art. The overall idea adopted is as follows:

[0023] First, a Bluetooth Mesh gateway is used to scan several Bluetooth signals within a preset range, including multiple client ID information. Then, these client ID information is extracted and confirmed whether it belongs to an authorized client. If it is an authorized client, the networking operation is performed to generate a Mesh network. In the Mesh network, the Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of each networking client through the network, and sends these data to the cloud IoT platform. After receiving the operation control parameters, the cloud IoT platform performs adjacency analysis based on adjacent non-abnormal sample collection and centralized value evaluation to obtain the operation status baseline parameters. Then, the cloud IoT platform compares the operation status baseline parameters with the operation status monitoring parameters to calculate the abnormal probability of the networking client. Finally, if the abnormal probability of the networking client is greater than or equal to the preset abnormal probability threshold, a first abnormal operation alarm signal is generated and fed back to the user's portable terminal.

[0024] The above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods of the specification to better understand the above technical solution. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used only to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, it should be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0025] Embodiment 1

[0026] Figure 1 The present invention is a flowchart of a method for rapid networking and Bluetooth device control based on a Bluetooth module, wherein the method comprises:

[0027] S100: Scanning a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information.

[0028] Specifically, through the automatic discovery mechanism of the Bluetooth Mesh gateway, multiple Bluetooth signals within the preset range can be quickly scanned and identified, thereby providing a basis for the subsequent extraction of the authorized client's ID information for networking. At the same time, it helps to simplify the user's operation steps and improve the networking efficiency, so that smart devices such as switches, lamps, door locks, etc. can quickly form a stable Mesh network and achieve efficient interconnection.

[0029] Specifically, the Bluetooth Mesh gateway scans the surrounding Bluetooth signals according to the preset scanning range, where the preset range can be adjusted by controlling parameters such as scanning power and scanning period; the client ID information is used to identify and distinguish the identity of the terminal device corresponding to different Bluetooth signals, including the basic information of the device and the unique identifier, such as device type, device model, device serial number, device manufacturer, MAC address, etc.

[0030] S200: extracting the plurality of client ID information belonging to the authorized clients to form a network and generate a Mesh network.

[0031] Specifically, the Bluetooth Mesh gateway stores an authorized client ID information list, which contains the IDs of all devices authorized to join the Mesh network. The gateway compares the scanned ID information with the authorization list to filter out devices belonging to authorized clients and connect to other authorized devices to form a Mesh network.

[0032] Specifically, the Bluetooth Mesh gateway is the main node or control node of the Mesh network, and each node in the Mesh network can not only send and receive data, but also act as a relay node, that is, allowing multiple devices to connect through multi-hop communication and help other nodes forward information.

[0033] Specifically, multiple authorized clients establish connections with other devices through the Bluetooth Mesh protocol and broadcast their identity information to each other, thus forming a self-organizing network structure with high redundancy; at the same time, data exchange can be achieved between the Bluetooth Mesh gateway and the client, including device status monitoring, command control, etc. Through the routing mechanism in the Mesh network, data can be transmitted between different clients, ensuring that the transmission of information is not affected by changes in the network topology.

[0034] In some embodiments, extracting the plurality of client ID information belonging to the authorized client to form a network and generate a Mesh network also includes:

[0035] Through the Bluetooth Mesh gateway, clock information is sent to the networking client of the Mesh network, and a clock feedback signal from the networking client is received; when the clock feedback signal from the networking client is not received for a preset number of consecutive times, a second abnormal operation alarm signal is generated for the networking client and fed back to the user portable terminal.

[0036] Specifically, clock information refers to the time synchronization signal sent by the Bluetooth Mesh gateway to the networking client, which is used to ensure the time consistency of all devices in the network, thereby ensuring the accuracy and coordination of data transmission; after the networking client receives the clock information, it will send a clock feedback signal back to the gateway to confirm that the device has received and processed the clock information normally.

[0037] Specifically, when the gateway fails to receive the clock feedback signal from the client for a preset number of consecutive times, it indicates that the corresponding client may have an abnormality (such as equipment failure or communication interruption), and then generates an alarm signal accordingly. The alarm signal is transmitted to the user's portable terminal via the Internet to remind the user of possible problems with the device.

[0038] Through the above steps, the normal operation and time synchronization of devices in the Mesh network are ensured, the stability and reliability of the network are improved, and the combination of real-time detection and alarm of device abnormalities facilitates users to quickly respond to and handle problems, avoiding network interruptions or data loss caused by equipment failures, thereby ensuring the normal operation of the entire Mesh network.

[0039] S300: The Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to the cloud IoT platform.

[0040] Specifically, the gateway collects operation control parameters and operation status monitoring parameters from client devices (such as smart home devices, sensors, controllers, etc.) connected to the Mesh network to reflect the configuration control status and current working status of the devices.

[0041] Exemplarily, the operation control parameters include the switch state of the device, the set working mode, temperature, humidity, brightness and other control values; the operation status monitoring parameters include the battery power of the device, workload, fault detection, data transmission status, signal strength, connection stability, etc.

[0042] Optionally, after obtaining the operation control parameters and the operation status monitoring parameters, the data are sorted and formatted according to a standard data format based on the data style definition of the cloud IoT platform. For example, the data is converted into JSON, XML and other formats to facilitate subsequent transmission and processing.

[0043] Optionally, to ensure the security of data transmission, the Bluetooth Mesh gateway will encrypt the data, such as SSL / TLS, AES, etc., to prevent the data from being stolen or tampered with during transmission.

[0044] Specifically, the frequency and amount of data transmission are set according to control requirements, including uploading data in real time or uploading according to a set time period (such as uploading once every minute or every hour).

[0045] The operation control parameters and operation status monitoring parameters of the networking client are collected through the Bluetooth Mesh gateway, and the data is sent to the cloud IoT platform, providing a decision-making basis for the subsequent remote monitoring, data analysis and intelligent decision-making of the equipment.

[0046] In some embodiments, the Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to the cloud IoT platform, including:

[0047] The operation control parameters and initial operation status monitoring parameters of the networking client are collected through the Mesh network; the initial operation status monitoring parameters are aggregated at adjacent time domain levels to obtain operation status aggregation timing information; and the operation status aggregation timing information is set as the operation status monitoring parameters.

[0048] Specifically, the adjacent time domain hierarchical aggregation aggregates the initial operating status monitoring parameters of adjacent time points to form operating status aggregated time series information to reduce the amount of data, while retaining the changing trends and laws of the equipment operating status to facilitate subsequent analysis and processing; the operating status aggregated time series information is the operating status information after the above-mentioned adjacent time domain hierarchical aggregation processing, which shows the changes in the operating status of the equipment over a period of time in the form of a time series, providing a basis for the management and maintenance of the equipment.

[0049] Specifically, first, the Bluetooth Mesh gateway collects operation control parameters and initial operation status monitoring parameters from networking clients (such as smart door locks, smart light bulbs, etc.) through the Mesh network; then, the gateway performs adjacent time domain hierarchical aggregation processing on the collected initial operation status monitoring parameters, that is, merges the data at adjacent time points to form operation status aggregation timing information; finally, the gateway sets the operation status aggregation timing information as the final operation status monitoring parameters and sends it to the cloud IoT platform.

[0050] Through the above process, efficient collection and processing of equipment data is achieved. By aggregating the initial operating status monitoring parameters into operating status aggregated timing information, the amount of data transmission and storage space occupied are reduced. At the same time, the operating status change trend of the equipment can be better displayed, which is convenient for the cloud IoT platform to perform data analysis and equipment management, and provides a more reliable basis for equipment monitoring and control.

[0051] In some implementations, performing adjacent time domain hierarchical aggregation on the initial operation status monitoring parameters to obtain operation status aggregated time series information includes:

[0052] Obtain the first attribute initial operating state monitoring time series information of the initial operating state monitoring parameter; extract the first time domain operating state monitoring value of the first attribute initial operating state monitoring time series information; extract the second time domain operating state monitoring value of the first attribute initial operating state monitoring time series information, wherein the first time domain and the second time domain are adjacent time domains; when the monitoring value deviation between the first time domain operating state monitoring value and the second time domain operating state monitoring value is less than or equal to the first attribute deviation threshold, merge the first time domain and the second time domain into a third time domain; simultaneously calculate the mean of the first time domain operating state monitoring value and the second time domain operating state monitoring value, and set it as the third time domain operating state aggregation value; after updating the first attribute initial operating state monitoring time series information according to the third time domain operating state aggregation value, obtain the first attribute updated operating state aggregation time series information; when any adjacent time domain deviation of the first attribute updated operating state aggregation time series information is greater than the first attribute deviation threshold, output the first attribute operating state aggregation time series information and add it to the operating state aggregation time series information.

[0053] Specifically, the first attribute initial operating status monitoring timing information refers to the information sequence of the initial operating status monitoring parameters of a specific attribute (such as power, temperature, etc.) arranged in chronological order; the first time domain operating status monitoring value refers to the operating status monitoring value of the first attribute at a specific time point or time period (first time domain), such as the power value of a smart door lock in a certain time period; the second time domain operating status monitoring value refers to the operating status monitoring value of the first attribute in the next time point or time period (second time domain) adjacent to the first time domain.

[0054] Specifically, the monitoring value deviation refers to the degree of difference between the operating status monitoring values ​​of the first time domain and the second time domain, such as the difference in power values ​​in two adjacent time periods; the first attribute deviation threshold is a preset standard value used to determine whether the monitoring value deviation of the first attribute is within an acceptable range. When the monitoring value deviation is less than or equal to the threshold, it can be considered that the monitoring values ​​of adjacent time domains have not changed much and can be merged.

[0055] Specifically, when the monitoring value deviation is less than or equal to the first attribute deviation threshold, the first time domain and the second time domain are merged into the third time domain, and the average of the operating status monitoring values ​​of the first time domain and the second time domain is calculated as the operating status aggregation value of the third time domain; then, the initial operating status monitoring timing information of the first attribute is updated according to the operating status aggregation value of the third time domain to form the first attribute updated operating status aggregation timing information.

[0056] Specifically, if the monitoring value deviation of any adjacent time domain in the updated time series information is greater than the deviation threshold, the current first attribute operation status aggregated time series information is output and added to the final operation status aggregated time series information. In other words, when aggregating along the time series direction, if the monitoring deviation of the adjacent time domain does not meet the deviation threshold, the previous aggregation result (i.e., the first attribute operation status aggregated time series information) is output, and the next time series in the adjacent time domain where the monitoring deviation does not meet the deviation threshold is re-aggregated until the first attribute initial operation status monitoring time series information is traversed.

[0057] Through the above process, effective aggregation and simplification of equipment operation status monitoring parameters are achieved. Specifically, the calculation of the merging and aggregation values ​​based on adjacent time domains reduces the amount of data, while retaining the changing trends and laws of the equipment operation status, providing a more concise and accurate basis for subsequent data analysis and equipment management, improving the efficiency and accuracy of data processing, and contributing to better monitoring and management of the equipment operation status.

[0058] S400: The networking client ID information received by the Bluetooth Mesh gateway is used to obtain the networking client service time in the service database index embedded in the cloud IoT platform, and in combination with the networking client service time and the networking client ID information, adjacent non-abnormal sample collection and centralized value evaluation are performed on the operation control parameters to implement adjacency analysis and obtain operation status benchmark parameters.

[0059] Specifically, adjacency analysis is an analytical method that identifies equipment behavior patterns based on the relationships between equipment states and time series similarities. Through adjacency analysis, the correlation between operating control parameters can be identified, and benchmark parameters that can represent the normal operating state of the equipment can be obtained; benchmark parameters 5C06 serve as a reference standard for future operating states and are used for anomaly detection and performance evaluation.

[0060] Specifically, the service database index is used to store equipment service information. The equipment ID information can be used to quickly retrieve information such as the equipment's service time in the service database. Adjacent non-abnormal sample collection is to select sample data without abnormalities in adjacent time periods from the equipment's operating status record data, which is used as a reference for the normal operating status of the equipment.

[0061] Specifically, the collected adjacent client operation status record data is statistically analyzed, and its central trend value, such as mean, median, etc., is calculated and set as the equipment's operation status benchmark parameter, which represents the standard operation condition of the equipment in the sense of statistical analysis.

[0062] Through the above steps, adjacent sample data without abnormalities are collected to eliminate data interference caused by equipment in abnormal states, ensure the accuracy and reliability of benchmark parameters, and consider service time to help understand the performance changes of equipment in different use stages, providing more targeted data support for equipment maintenance and management, and achieving the effect of providing a reliable and accurate reference basis for subsequent equipment status monitoring and abnormality detection.

[0063] In some implementations, combining the service time of the networking client and the networking client ID information, performing adjacency non-abnormal sample collection on the operation control parameter includes:

[0064] Abnormal sample collection is performed with the service time of the networking client and the networking client ID information as constraints to obtain first-level adjacent client operation status record data, wherein the first-level adjacent client operation status record data has operation control parameter record data; when the operation control parameter record data is consistent with the operation control mode of the operation control parameter, the first-level adjacent client operation status record data is added to the adjacent client operation status record data; when the operation control parameter record data is inconsistent with the operation control mode of the operation control parameter, the first-level adjacent client operation status record data is deleted.

[0065] Specifically, in the preliminary screening process, the service time of the networking client and the networking client ID information are used as screening constraints to obtain the operating status record data of the adjacent client and output it as the first-level adjacent client operating status record data, which includes the operating control parameter record of the device.

[0066] Specifically, the operation control mode refers to the control mode or state of the device during operation, such as unlocking, locking, standby, etc. Different control modes correspond to different operation control parameters and device behaviors. Therefore, it is necessary to ensure that the operation control parameter recording data is consistent with the operation control mode of the operation control parameter, thereby achieving the collection of abnormal samples.

[0067] Specifically, if the operation control parameter record data is consistent with the operation control mode, the first-level adjacent client operation status record data is added to the adjacent client operation status record data as valid normal operation status data; if the operation control parameter record data is inconsistent with the operation control mode, the first-level adjacent client operation status record data is deleted to exclude data that does not conform to the current control mode.

[0068] The above steps can ensure that the obtained operation status record data has qualified reliability and representativeness by collecting abnormal samples based on the service time and ID information. By judging the consistency between the operation control parameter record data and the operation control mode, the data that conforms to the current equipment operation status can be further screened out, and abnormal data that may be caused by equipment failure, operation error, etc. can be excluded, thereby improving the accuracy of the adjacent client operation status record data.

[0069] The above process provides a high-quality data basis for the subsequent centralized value evaluation and determination of operating status benchmark parameters, which helps to more accurately analyze the normal operating status of the equipment.

[0070] Further, when the operation control parameter record data is consistent with the operation control mode of the operation control parameter, it includes:

[0071] Calculate the same-attribute deviation between the operation control parameter record data and the operation control parameter to obtain an operation control deviation set; obtain an operation control deviation threshold set; based on the operation control deviation threshold set, count the proportion of the number of attributes in the operation control deviation set whose operation control deviation modulus is greater than the operation control deviation threshold, and set it as a modal evaluation parameter; when the modal evaluation parameter is less than or equal to the modal evaluation threshold, it is deemed that the operation control mode of the operation control parameter record data is consistent with that of the operation control parameter.

[0072] Specifically, the consistency between the operation control parameter record data and the operation control mode of the operation control parameter is determined. First, the same-attribute deviation between the operation control parameter record data and the current operation control parameter is calculated to obtain an operation control deviation set, wherein the same-attribute deviation is the difference between the same attribute (such as temperature, humidity, power, etc.) and the current operation control parameter.

[0073] Then, a preset operation control deviation threshold set is obtained, which includes the deviation threshold corresponding to each attribute. Based on the operation control deviation threshold set, the proportion of attributes in the operation control deviation set whose operation control deviation modulus is greater than the operation control deviation threshold is counted, that is, the frequency of not meeting the deviation constraint is obtained and set as the modal evaluation parameter.

[0074] Specifically, the modal evaluation parameter is used to evaluate the consistency between the operating control parameter recording data and the current operating control mode. When the modal evaluation parameter is less than or equal to the modal evaluation threshold, the operating control parameter recording data can be regarded as consistent with the operating control mode of the current operating control parameter.

[0075] Through the above process, the consistency and accuracy of the data are ensured, thus providing a high-quality data basis for the subsequent determination of operating status benchmark parameters and equipment status monitoring, which helps to more accurately analyze the normal operating status of the equipment and improve the accuracy and reliability of equipment status monitoring.

[0076] S500: Compare the operating status benchmark parameter and the operating status monitoring parameter through the cloud IoT platform to obtain the abnormal probability of the networking client.

[0077] Specifically, by comparing the operating status baseline parameters with the operating status monitoring parameters, the cloud IoT platform can calculate the abnormal probability of each device in real time, thereby providing a quantitative basis for the health status of the equipment, which helps the cloud IoT platform and users to identify abnormal conditions, predict equipment failures, and perform preventive maintenance, thereby optimizing equipment management, improving operational efficiency, and reducing the risk of failures.

[0078] In some embodiments, the cloud IoT platform compares the operating status benchmark parameter with the operating status monitoring parameter to obtain the abnormal probability of the networking client, including:

[0079] The operating state deviation modulus value set of the operating state baseline parameter and the operating state monitoring parameter is counted; the operating state deviation modulus value set is dedimensionalized to obtain the operating state deviation characteristic value set; the operating state attribute weight set is obtained, wherein the weight represents the importance of the operating state attribute; according to the operating state attribute weight set, the operating state deviation characteristic value set is weighted mean analyzed to obtain the operating state deviation fusion parameter; the ratio of the operating state deviation fusion parameter to the deviation fusion parameter threshold is calculated to obtain the abnormal probability of the networking client, wherein when the ratio is greater than 1, the abnormal probability of the networking client is equal to 1, and when the ratio is less than or equal to 1, the abnormal probability of the networking client is equal to the ratio.

[0080] Specifically, for each device, the deviation between each monitoring parameter and its corresponding reference parameter is calculated, and the deviation is expressed by a modulus value, that is, the absolute value of the difference between the operating status reference parameter and the operating status monitoring parameter; then, through dedimensionalization, the deviation modulus values ​​of different dimensions (such as temperature units, pressure units, current units, etc.) are converted into dimensionless eigenvalues, and a set of operating status deviation eigenvalues ​​is obtained for comprehensive comparison, wherein dedimensionalization means include standardization processing, normalization processing, etc.

[0081] Specifically, the operating state attribute weight is used to indicate the importance of different operating state parameters to the health state of the device, that is, different parameters have different effects on the abnormal prediction of the device. For example, temperature fluctuations may reflect the abnormal state of the device better than voltage fluctuations. Through methods such as expert evaluation, statistical analysis, and machine learning, the operating state attribute weights of different operating state attributes can be determined to obtain the operating state attribute weight set.

[0082] Specifically, the operating state deviation feature value set is combined with the operating state attribute weight set, and the operating state deviation fusion parameter is calculated through weighted mean analysis. The operating state deviation fusion parameter is an evaluation indicator reflecting the degree of comprehensive deviation; then, the ratio of the operating state deviation fusion parameter to the preset deviation fusion parameter threshold is determined to determine whether the equipment is in an abnormal state; if the deviation fusion parameter is greater than the deviation fusion parameter threshold, that is, the ratio is greater than 1, it means that the operating state of the equipment is relatively abnormal, and the abnormal probability is defined as 1; if the deviation fusion parameter is less than or equal to the threshold, the ratio of the abnormal probability to the deviation fusion parameter is calculated, that is, when the ratio is less than 1, it can be considered that the abnormal degree of the equipment is within the allowable range, which means that there is a linear relationship between the abnormal probability of the equipment and the operating state deviation fusion parameter, and the operating state deviation fusion parameter is output as the abnormal probability.

[0083] S600: The cloud IoT platform compares the operating status baseline parameters and monitoring parameters, and the abnormal probability calculated through multiple analysis steps provides a quantitative health assessment for each networking client, which helps to monitor the health status of the equipment in real time, detect potential faults in time, and take response measures, thereby improving the reliability and efficiency of the equipment.

[0084] When the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold, a first abnormal operation alarm signal is generated for the networking client and fed back to the user portable terminal.

[0085] Specifically, the abnormal probability threshold is a preset standard value used to determine whether the abnormal probability of the device has reached a level that requires an alarm. When the abnormal probability of the device is greater than or equal to the threshold, it indicates that the device may have a more serious abnormal situation that requires the user's attention and processing.

[0086] Specifically, the user portable terminal refers to a portable device used by the user to receive alarm signals, such as a smart phone, tablet computer, etc. The user can use these devices to understand the operating status and abnormal conditions of the equipment in real time. For example, when the abnormal probability is greater than or equal to the abnormal probability threshold, the user portable terminal uses the received alarm signal to remind the user of the abnormal condition of the device in the form of pop-up windows, notifications, text messages, etc., and provide corresponding abnormal information and handling suggestions.

[0087] By setting abnormal probability thresholds and generating alarm signals, abnormal conditions of user equipment can be discovered and notified in a timely manner, improving the real-time and effectiveness of equipment status monitoring; portable terminals help users quickly understand abnormal information of equipment and take timely measures to deal with it, thereby enhancing users' ability to control the operating status of equipment, improving equipment reliability and user experience, and ensuring the normal operation and safe use of equipment.

[0088] In summary, the method for rapid networking based on Bluetooth modules and controlling Bluetooth devices provided by the present invention has the following technical effects:

[0089] Scan a number of Bluetooth signals within a preset range through the Bluetooth Mesh gateway, wherein the several Bluetooth signals include a number of client ID information; extract a number of clients whose client ID information belongs to the authorized client to form a network and generate a Mesh network; the Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to the cloud IoT platform; the networking client ID information received by the Bluetooth Mesh gateway is used to obtain the service time of the networking client through the service database index embedded in the cloud IoT platform, and in combination with the service time of the networking client and the networking client ID information, perform adjacent non-abnormal sample collection and centralized value evaluation on the operation control parameters to achieve adjacent analysis and obtain the operation status benchmark parameters; compare the operation status benchmark parameters and the operation status monitoring parameters through the cloud IoT platform to obtain the abnormal probability of the networking client; when the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold, generate a first abnormal operation alarm signal for the networking client and feed it back to the user's portable terminal, thereby achieving the technical effects of improving networking efficiency, enhancing monitoring comprehensiveness and improving security.

[0090] Embodiment 2

[0091] Figure 2 It is a schematic diagram of the structure of the device based on the Bluetooth module rapid networking and Bluetooth device control of the present invention. For example, Figure 1 The flowchart of the method for rapid networking and Bluetooth device control based on Bluetooth modules of the present invention can be shown as follows: Figure 2 The structure shown is implemented.

[0092] Based on the same concept as the method for rapid networking based on Bluetooth modules and controlling Bluetooth devices in the above embodiment, the present invention also provides a device for rapid networking based on Bluetooth modules and controlling Bluetooth devices, including:

[0093] The Bluetooth signal scanning unit 11 is used to scan a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information.

[0094] The Mesh network generating unit 12 is used to extract the client ID information of the plurality of clients belonging to the authorized clients for networking to generate a Mesh network.

[0095] The parameter collection and transmission unit 13 is used for the Bluetooth Mesh gateway to collect the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and send them to the cloud IoT platform.

[0096] The operation status benchmark parameter acquisition unit 14 is used to obtain the service time of the networking client through the networking client ID information received by the Bluetooth Mesh gateway in the service database index embedded in the cloud IoT platform, and perform adjacent non-abnormal sample collection and centralized value evaluation on the operation control parameters in combination with the networking client service time and the networking client ID information to realize adjacency analysis and obtain the operation status benchmark parameters.

[0097] The abnormality probability calculation unit 15 is used to compare the operating status benchmark parameter and the operating status monitoring parameter through the cloud IoT platform to obtain the abnormality probability of the networking client.

[0098] The abnormal alarm signal generating and feedback unit 16 is used to generate a first abnormal operation alarm signal for the networking client and feed it back to the user portable terminal when the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold.

[0099] In some embodiments, the Mesh network generation unit 12 includes:

[0100] The verification signal transmission unit is used to send clock information to the networking client of the Mesh network through the Bluetooth Mesh gateway and receive the clock feedback signal of the networking client.

[0101] The abnormality identification response unit is used to generate a second abnormal operation alarm signal for the networking client and feed it back to the user portable terminal when the clock feedback signal of the networking client is not received for a preset number of consecutive times.

[0102] In some embodiments, the parameter acquisition and transmission unit 13 includes:

[0103] The operation parameter collection unit is used to collect the operation control parameters and initial operation status monitoring parameters of the networking client through the Mesh network.

[0104] The operation status aggregation unit is used to aggregate the initial operation status monitoring parameters at adjacent time domain levels to obtain operation status aggregation time series information.

[0105] The operation status monitoring parameter setting unit is used to set the operation status aggregation timing information as the operation status monitoring parameter.

[0106] In some implementations, the execution steps of the running status aggregation unit in the parameter collection and transmission unit 13 include:

[0107] Obtain the first attribute initial operating state monitoring time series information of the initial operating state monitoring parameter; extract the first time domain operating state monitoring value of the first attribute initial operating state monitoring time series information; extract the second time domain operating state monitoring value of the first attribute initial operating state monitoring time series information, wherein the first time domain and the second time domain are adjacent time domains; when the monitoring value deviation between the first time domain operating state monitoring value and the second time domain operating state monitoring value is less than or equal to the first attribute deviation threshold, merge the first time domain and the second time domain into a third time domain; simultaneously calculate the mean of the first time domain operating state monitoring value and the second time domain operating state monitoring value, and set it as the third time domain operating state aggregation value; after updating the first attribute initial operating state monitoring time series information according to the third time domain operating state aggregation value, obtain the first attribute updated operating state aggregation time series information; when any adjacent time domain deviation of the first attribute updated operating state aggregation time series information is greater than the first attribute deviation threshold, output the first attribute operating state aggregation time series information and add it to the operating state aggregation time series information.

[0108] In some implementations, the operating status reference parameter acquisition unit 14 includes:

[0109] The non-abnormal sample collection unit is used to perform non-abnormal sample collection based on the service time of the networking client and the networking client ID information, and obtain the first-level adjacent client operation status record data, wherein the first-level adjacent client operation status record data has operation control parameter record data.

[0110] The neighboring client operation status record data updating unit is used to add the first-level neighboring client operation status record data into the neighboring client operation status record data when the operation control parameter record data is consistent with the operation control mode of the operation control parameter.

[0111] The adjacent client operation status record data deleting unit is used to delete the first-level adjacent client operation status record data when the operation control parameter record data is inconsistent with the operation control mode of the operation control parameter.

[0112] In some implementations, the execution steps of the neighboring client operation status record data updating unit in the operation status benchmark parameter acquisition unit 14 include:

[0113] Calculate the same-attribute deviation between the operation control parameter record data and the operation control parameter to obtain an operation control deviation set; obtain an operation control deviation threshold set; based on the operation control deviation threshold set, count the proportion of the number of attributes in the operation control deviation set whose operation control deviation modulus is greater than the operation control deviation threshold, and set it as a modal evaluation parameter; when the modal evaluation parameter is less than or equal to the modal evaluation threshold, it is deemed that the operation control mode of the operation control parameter record data is consistent with that of the operation control parameter.

[0114] In some embodiments, the abnormal probability calculation unit 15 includes:

[0115] The running state deviation modulus statistical unit is used to count the running state deviation modulus value sets of the running state reference parameters and the running state monitoring parameters.

[0116] The operating state deviation characteristic value processing unit is used to perform dimensionless processing on the operating state deviation module value set to obtain the operating state deviation characteristic value set.

[0117] The running state attribute weight obtaining unit is used to obtain a running state attribute weight set, wherein the weight represents the importance of the running state attribute.

[0118] The running state deviation fusion parameter calculation unit is used to perform weighted mean analysis on the running state deviation feature value set according to the running state attribute weight set to obtain the running state deviation fusion parameter.

[0119] The networking client abnormality probability calculation unit is used to calculate the ratio of the operating state deviation fusion parameter to the deviation fusion parameter threshold to obtain the networking client abnormality probability, wherein when the ratio is greater than 1, the networking client abnormality probability is equal to 1, and when the ratio is less than or equal to 1, the networking client abnormality probability is equal to the ratio.

[0120] It should be understood that the embodiments mentioned in this specification focus on their differences from other embodiments. The specific embodiments in the aforementioned embodiment one are also applicable to the device for rapid networking based on Bluetooth modules and Bluetooth device control described in embodiment two. For the sake of brevity of the specification, they will not be further elaborated here.

[0121] It should be understood that the embodiments disclosed in the present invention and the above description can enable those skilled in the art to use the present invention to implement the present invention. At the same time, the present invention is not limited to the above-mentioned embodiments. It should be understood that those skilled in the art can still modify the technical solutions recorded in the above-mentioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for rapid networking and Bluetooth device control based on a Bluetooth module, characterized in that: include: Scanning a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information; Extract the client ID information of the plurality of clients belonging to the authorized clients to form a network and generate a Mesh network; The Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to the cloud IoT platform; The networking client ID information received by the Bluetooth Mesh gateway is used to obtain the networking client service time from the service database index embedded in the cloud IoT platform, and the adjacency non-abnormal sample collection and centralized value evaluation are performed on the operation control parameters in combination with the networking client service time and the networking client ID information to implement adjacency analysis and obtain the operation status benchmark parameters; Comparing the operating status benchmark parameter with the operating status monitoring parameter through the cloud IoT platform to obtain the abnormal probability of the networking client; When the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold, generating a first abnormal operation alarm signal for the networking client and feeding it back to the user portable terminal; The method of performing adjacency-free sample collection on the operation control parameters in combination with the service time of the networking client and the networking client ID information includes: Performing non-abnormal sample collection with the service time of the networking client and the networking client ID information as constraints to obtain the first-level adjacent client operation status record data, wherein the first-level adjacent client operation status record data has operation control parameter record data; When the operation control parameter record data is consistent with the operation control mode of the operation control parameter, adding the first-level adjacent client operation status record data into the adjacent client operation status record data; When the operation control parameter record data is inconsistent with the operation control mode of the operation control parameter, the operation status record data of the first-level adjacent client is deleted.

2. The method for rapid networking and Bluetooth device control based on Bluetooth modules according to claim 1, characterized in that: Extracting the plurality of client ID information belonging to the authorized client to form a network and generate a Mesh network, further comprising: Send clock information to the networking client of the Mesh network through the Bluetooth Mesh gateway, and receive a clock feedback signal from the networking client; When the clock feedback signal of the networking client is not received for a preset number of consecutive times, a second abnormal operation alarm signal is generated for the networking client and fed back to the user portable terminal.

3. The method for rapid networking and Bluetooth device control based on Bluetooth modules according to claim 1, characterized in that: The Bluetooth Mesh gateway collects the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and sends them to the cloud IoT platform, including: Collect the operation control parameters and initial operation status monitoring parameters of the networking client through the Mesh network; Aggregating the initial operating status monitoring parameters at adjacent time domain levels to obtain operating status aggregation time series information; The operation status aggregation timing information is set as the operation status monitoring parameter.

4. The method for rapid networking and Bluetooth device control based on Bluetooth modules as claimed in claim 3, characterized in that: Aggregating the initial operation status monitoring parameters at adjacent time domain levels to obtain operation status aggregation time series information includes: Obtaining initial operating state monitoring time sequence information of a first attribute of the initial operating state monitoring parameter; Extracting a first time domain running state monitoring value of the first attribute initial running state monitoring time series information; Extracting a second time domain operating state monitoring value of the first attribute initial operating state monitoring time series information, wherein the first time domain and the second time domain are adjacent time domains; When the monitoring value deviation between the first time domain operating state monitoring value and the second time domain operating state monitoring value is less than or equal to a first attribute deviation threshold, merging the first time domain and the second time domain into a third time domain; At the same time, the average of the first time domain operation status monitoring value and the second time domain operation status monitoring value is calculated and set as a third time domain operation status aggregate value; After updating the first attribute initial running state monitoring time series information according to the third time domain running state aggregate value, obtaining the first attribute updated running state aggregate time series information; When any adjacent time domain deviation of the first attribute updating running state aggregated time series information is greater than a first attribute deviation threshold, the first attribute running state aggregated time series information is output and added to the running state aggregated time series information.

5. The method for rapid networking and Bluetooth device control based on Bluetooth modules as claimed in claim 4, characterized in that: When the operation control parameter record data is consistent with the operation control mode of the operation control parameter, it includes: Calculating the same-attribute deviations between the operation control parameter record data and the operation control parameter to obtain an operation control deviation set; Obtaining a set of operation control deviation thresholds; Based on the operation control deviation threshold set, a percentage of attributes in the operation control deviation set whose operation control deviation modulus is greater than the operation control deviation threshold is counted and set as a modal evaluation parameter; When the modal evaluation parameter is less than or equal to the modal evaluation threshold, it is considered that the operation control parameter record data is consistent with the operation control mode of the operation control parameter.

6. The method for rapid networking and Bluetooth device control based on Bluetooth modules according to claim 1, characterized in that: The cloud IoT platform compares the operating status benchmark parameter with the operating status monitoring parameter to obtain the abnormal probability of the networking client, including: Counting the running state deviation modulus value set of the running state reference parameter and the running state monitoring parameter; De-dimensionalizing the running state deviation modulus value set to obtain a running state deviation characteristic value set; Obtaining a set of operating status attribute weights, wherein the weights represent the importance of the operating status attributes; According to the operating state attribute weight set, weighted mean analysis is performed on the operating state deviation feature value set to obtain an operating state deviation fusion parameter; The ratio of the running status deviation fusion parameter to the deviation fusion parameter threshold is calculated to obtain the abnormal probability of the networking client, wherein when the ratio is greater than 1, the abnormal probability of the networking client is equal to 1, and when the ratio is less than or equal to 1, the abnormal probability of the networking client is equal to the ratio.

7. A device for rapid networking and Bluetooth device control based on a Bluetooth module, characterized in that: The device is used to execute the method for rapid networking based on a Bluetooth module and controlling a Bluetooth device according to any one of claims 1 to 6, and the device comprises: A Bluetooth signal scanning unit, used to scan a plurality of Bluetooth signals within a preset range through a Bluetooth Mesh gateway, wherein the plurality of Bluetooth signals include a plurality of client ID information; A Mesh network generation unit, used to extract the client ID information of the plurality of clients belonging to the authorized clients for networking, and generate a Mesh network; A parameter collection and transmission unit, used for the Bluetooth Mesh gateway to collect the operation control parameters and operation status monitoring parameters of the networking client through the Mesh network and send them to the cloud IoT platform; An operation status benchmark parameter acquisition unit is used to obtain the service time of the networking client through the networking client ID information received by the Bluetooth Mesh gateway, and to obtain the service time of the networking client by indexing the service database embedded in the cloud IoT platform, and to perform adjacency non-abnormal sample collection and centralized value evaluation on the operation control parameters in combination with the networking client service time and the networking client ID information, so as to realize adjacency analysis and obtain the operation status benchmark parameters; An abnormality probability calculation unit, used to compare the operating status benchmark parameter with the operating status monitoring parameter through the cloud IoT platform to obtain the abnormality probability of the networking client; The abnormal alarm signal generation and feedback unit is used to generate a first abnormal operation alarm signal for the networking client and feed it back to the user's portable terminal when the abnormal probability of the networking client is greater than or equal to the abnormal probability threshold.

8. The device for rapid networking and Bluetooth device control based on Bluetooth modules as claimed in claim 7, characterized in that: The Mesh network generation unit includes: A verification signal transmission unit, used to send clock information to a networking client of the Mesh network through the Bluetooth Mesh gateway, and receive a clock feedback signal from the networking client; The abnormality identification response unit is used to generate a second abnormal operation alarm signal for the networking client and feed it back to the user portable terminal when the clock feedback signal of the networking client is not received for a preset number of consecutive times.

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