A real-time monitoring method for abnormal disconnection of vehicle Bluetooth

Abstract

The present invention discloses a real-time monitoring method for abnormal disconnection of vehicle-mounted Bluetooth, comprising the following steps: S1: defining the buried point information of Bluetooth, and setting different Bluetooth buried point messages for different Bluetooth states; S2: when the vehicle-end Bluetooth meets the message condition, triggering the Bluetooth message to be uploaded to the cloud, and at the same time collecting all vehicle data information within a set time before and after this moment, and uploading it to the cloud; S3: the cloud analyzes and determines the reasons for the change of Bluetooth state according to the acquired Bluetooth buried point message data and all vehicle data information, and according to the judgment rules, saves all acquired data and the analysis and judgment results. The present invention can monitor the connection method of abnormal disconnection of vehicle-mounted Bluetooth in real time in the cloud, and the rules are flexibly configured in the cloud system, thereby realizing the monitoring and statistical analysis of abnormal disconnection of vehicle-mounted Bluetooth.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent automobiles, and in particular to a real-time monitoring method for abnormal disconnection of Bluetooth of a vehicle computer. Background Art

[0002] As smart cars enter the market, a new definition of cars is impacting the market. Traditional cars are like frightened birds, and they have proposed company transformation. Subsequently, concepts such as "software-defined cars" and "Internet of Everything" have gradually spread in the automotive industry. The concept and role of cars have been redefined again. It is no longer a simple means of transportation, but a smart friend that accompanies you anytime and anywhere. However, Bluetooth, as a popular function, a wireless connection technology within a smaller range, can achieve convenient, fast, flexible, safe, low-cost, and low-power data and voice communications between multiple devices. Therefore, it has become one of the mainstream technical means of wireless LAN communication. More and more car functions have begun to rely on Bluetooth to communicate with the owner's mobile phone, such as Bluetooth keys, Bluetooth music, etc.

[0003] At present, the vehicle's Bluetooth key, Bluetooth music, Bluetooth file transfer and other functions all need to be connected to the car's Bluetooth. There will be more and more application scenarios for Bluetooth, and the stability of the connection is particularly important. Abnormal disconnection of Bluetooth will greatly reduce customer satisfaction and cause user complaints. Moreover, most of the abnormal disconnection events of Bluetooth are sporadic and difficult to reproduce. Patent CN201838125U Bluetooth monitoring and alarm system discloses that objects and mobile phones are connected via Bluetooth. When the connection distance between the mobile phone and the object exceeds the effective distance, the vibration and ringing device on the mobile phone is triggered to remind the user that the Bluetooth connection is disconnected. However, this method is based on the local mobile phone for rule judgment. The local computing power is limited, and the judgment rules are not configurable and relatively simple. There are many signals on the vehicle side, and the computing power and storage cannot be met locally. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a real-time monitoring method for abnormal disconnection of vehicle Bluetooth, so as to solve the problems in the prior art that abnormal Bluetooth disconnection events are sporadic, difficult to reproduce, and unable to monitor the abnormal status of Bluetooth.

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

[0006] A real-time monitoring method for abnormal disconnection of vehicle Bluetooth includes the following steps:

[0007] S1: Define Bluetooth tracking information and set different Bluetooth tracking messages for different Bluetooth states;

[0008] S2: When the vehicle-side Bluetooth meets the message conditions, the Bluetooth message is triggered to be uploaded to the cloud. At the same time, all vehicle data information within the set time before and after this moment is collected and uploaded to the cloud;

[0009] S3: The cloud analyzes and determines the cause of the change in the Bluetooth status based on the acquired Bluetooth buried point message data and all vehicle data information, and according to the judgment rules, saves all the acquired data and the analysis and judgment results.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] 1. The method described in the present invention needs to develop Bluetooth tracking points in the vehicle program in advance according to the defined rules. When the vehicle Bluetooth changes to a different state or is abnormal, different tracking point messages are triggered. At the same time, the vehicle log files and vehicle condition data within the set time before and after the moment are packaged into files and uploaded to the cloud, so as to obtain relevant data when the Bluetooth state changes in time, and provide data support for the subsequent analysis of the reasons for the change in the Bluetooth state.

[0012] 2. The method of the present invention analyzes the cause of the change in the Bluetooth status according to the judgment rules, and pushes the analysis results and related data to the business personnel, and saves the analysis results and related data at the same time, so that the technical personnel can also obtain the real-time data changes when the Bluetooth status changes afterwards, providing data support for the technical personnel; at the same time, the method of the present invention can display the abnormal data appearing in the vehicle condition signal data when the Bluetooth status changes, so that the technical personnel can intuitively understand which abnormal data may be related to the change in the Bluetooth status, which is convenient for the technical personnel to analyze. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 Schematic diagram of data flow of the present invention.

[0014] Figure 2 This is a diagram of the cloud system architecture of the present invention.

[0015] Figure 3 This is a flow chart of the cloud-based real-time rule determination monitoring module of the present invention.

[0016] Figure 4 This is a flow chart of the log parsing module of the present invention.

[0017] Figure 5 Flow chart of the statistical analysis module of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present invention. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present invention.

[0019] The present invention provides a real-time monitoring method for abnormal disconnection of vehicle Bluetooth, comprising the following steps:

[0020] S1: Define Bluetooth tracking information and set different Bluetooth tracking messages for different Bluetooth states. Figure 1 As shown, in the data generation module, the data source comes from the vehicle system. The main data includes Bluetooth vehicle tracking points, vehicle logs, vehicle condition data, etc. The trigger points of the three types of data are vehicle tracking point messages.

[0021] S2: When the vehicle-side Bluetooth meets the message conditions, the Bluetooth message is triggered to be uploaded to the cloud. At the same time, all vehicle data information within the set time before and after this moment is collected and uploaded to the cloud. All vehicle data information includes vehicle log files and vehicle condition data information. The cloud obtains the log level according to different vehicle series settings. After the vehicle obtains the latest configuration file of the corresponding vehicle series from the cloud, the vehicle filters the vehicle log files, filters the Bluetooth log files, parses the Bluetooth log files, and writes the parsed structured data to HDFS for storage. After filtering the vehicle log files, the vehicle does not parse log files that are not related to Bluetooth. For example, Figure 1 As shown in the figure, when the vehicle-side Bluetooth meets the conditions of the message, the Bluetooth message upload is triggered, and the vehicle log file and vehicle condition data of one minute before and after this moment are collected. The log data mainly includes the CPU usage rate of each process of the vehicle and the process error information, mainly to extract Bluetooth-related information from it, and the vehicle condition data mainly includes vehicle speed, network strength, GPS and other general vehicle condition information, mainly to understand the environment of the vehicle when the Bluetooth status changes.

[0022] S3: The cloud analyzes and determines the cause of the change in Bluetooth status based on the acquired Bluetooth buried point message data and all vehicle data information, and according to the judgment rules, saves all acquired data and the analysis and judgment results. The judgment rules are as follows:

[0023] When the Bluetooth status in the Bluetooth buried point message is disconnected, if abnormal data appears in the vehicle condition signal data, it is determined that the Bluetooth disconnection type is related to the abnormal data.

[0024] The determination rules also include:

[0025] When the number of disconnections of a vehicle's Bluetooth exceeds a predetermined value within a specified time, and the average connection duration is less than a set threshold, it is determined that the vehicle's Bluetooth is unstable.

[0026] The cloud will push the analysis and judgment results and the corresponding data obtained to the backend for query and download.

[0027] like Figure 2 As shown in the figure, this is an architecture diagram of the cloud system of the present invention. After the vehicle sends the data to the cloud, the cloud system actively pulls the data in Kafka for analysis. The analysis program is the flink program. The rules are read into the flink program for one-by-one judgment. If the conditions are met, user or group messages are pushed. At the same time, the data and the judgment results are written to HDFS for storage, and the massive data is used for subsequent analysis and statistics.

[0028] like Figure 3 As shown in the figure, this is a flow chart of the cloud real-time rule judgment monitoring module. The technical components used in this monitoring module are mainly flink, kafka, mysql, etc. Flink is used as a program computing framework to analyze the Bluetooth buried point message data and vehicle condition data in kafka in real time, and read the rule data in mysql into the program as the basis for rule judgment. The rule data is configured by the administrator through the page and saved in mysql. The rules are as follows:

[0029] In a certain car series, when the Bluetooth status in the Bluetooth message is disconnected and the CPU usage signal in the vehicle condition signal is >95%, the abnormal Bluetooth disconnection type is determined to be CPU disconnection, and the disconnection reason is that the CPU usage is too high and the car computer is stuck. If the flink program meets the conditions in the judgment, it returns true, otherwise it returns false. When true is returned, the data is pushed to the relevant business personnel according to the demand text, and finally the source data and the results after judgment are written to HDFS for storage, and then used for offline data analysis.

[0030] like Figure 4 As shown, the figure is the vehicle log parsing module of the present invention. The cloud will obtain the log level for each vehicle series configuration. After the vehicle is powered on and passes the vehicle authentication, it will pull the latest configuration file of the corresponding vehicle series from the cloud. After obtaining the latest configuration, the vehicle side will only upload the corresponding configured log file to the file cloud. The background program framework used is springboot, which is mainly responsible for pulling log files from the file cloud and filtering Bluetooth log files. Other log files do not need to be parsed later. The Bluetooth log file is parsed according to the protocol, and the parsed structured data is written to HDFS for storage.

[0031] like Figure 5As shown, this figure is the statistical analysis module of the present invention. The data source of this module includes three types of data: vehicle machine buried points, vehicle condition data, and Bluetooth log files. Combined with the offline judgment rule, if the number of disconnections of a single vehicle Bluetooth is greater than 20 times a day, and the average connection time is less than 10 minutes, it is judged that the vehicle machine Bluetooth is unstable, and the reason is that the vehicle machine Bluetooth module transmits an abnormal signal. Finally, the judgment result is written into mysql, and springboot is used as the background program for query and download. The query dimensions include province, car series, abnormal type, abnormal cause, time, etc., so that the business party can see the statistical results of abnormal Bluetooth disconnection from many aspects.

[0032] The method described in the present invention requires the development of Bluetooth tracking points in the vehicle computer program in advance according to the defined rules. When the vehicle computer Bluetooth changes to a different state or is abnormal, different tracking point messages are triggered. At the same time, the vehicle computer log files and vehicle condition data within the set time before and after the moment are packaged into files and uploaded to the cloud, so as to obtain relevant data when the Bluetooth state changes in time, and provide data support for the subsequent analysis of the reasons for the change in the Bluetooth state.

[0033] The method described in the present invention analyzes the cause of the change in the Bluetooth status according to the judgment rules, and pushes the analysis results and related data to the business personnel, and saves the analysis results and related data at the same time, so that the technical personnel can also obtain the real-time data changes when the Bluetooth status changes afterwards, providing data support for the technical personnel; at the same time, the method described in the present invention can display the abnormal data appearing in the vehicle condition signal data when the Bluetooth status changes, so that the technical personnel can intuitively understand which abnormal data may be related to the change in the Bluetooth status, which is convenient for the technical personnel to analyze.

[0034] As described above, the reminder system of the present invention is not limited to the configuration described above, and other systems that can implement the embodiments of the present invention may fall within the scope of protection of the present invention.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the technical solution. Those skilled in the art should understand that those modifications or equivalent substitutions of the technical solution of the present invention that do not depart from the purpose and scope of the technical solution should be included in the scope of the claims of the present invention.

Claims

1. A real-time monitoring method for abnormal disconnection of vehicle Bluetooth, characterized in that: The steps include: S1: Define Bluetooth tracking information and set different Bluetooth tracking messages for different Bluetooth states; S2: When the vehicle-side Bluetooth meets the message conditions, the Bluetooth message is triggered to be uploaded to the cloud, and all vehicle data information within the set time before and after this moment is collected and uploaded to the cloud; in S2, all vehicle data information includes the vehicle computer log file and vehicle condition data information; the cloud obtains the log level according to different vehicle series settings, and after the vehicle computer obtains the latest configuration file of the corresponding vehicle series from the cloud, the vehicle computer filters the vehicle computer log file, filters the Bluetooth log file, parses the Bluetooth log file, and writes the parsed structured data into HDFS for storage; S3: The cloud analyzes and determines the cause of the change in the Bluetooth status based on the acquired Bluetooth buried point message data and all vehicle data information and the judgment rules, and saves all acquired data and the analysis and judgment results; the judgment rules are as follows: When the Bluetooth status in the Bluetooth buried point message is disconnected, if abnormal data appears in the vehicle condition signal data, it is determined that the Bluetooth disconnection type is related to the abnormal data; when the number of disconnections of a vehicle Bluetooth within the specified time exceeds a predetermined value, and the average connection time is less than the set threshold, it is determined that the vehicle Bluetooth is unstable.

2. According to the real-time monitoring method of abnormal Bluetooth disconnection of vehicle machine according to claim 1, it is characterized in that: After filtering the log files, the car computer does not parse the log files not related to Bluetooth.

3. The real-time monitoring method for abnormal Bluetooth disconnection of a vehicle computer according to claim 1 is characterized in that: In S3, the cloud pushes the analysis and judgment results and the corresponding data obtained to the backend for query and download.

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