Method and device for detecting abnormal data

Abstract

The invention relates to the technical field of computers, and discloses a method and device for detecting abnormal data. The method comprises the steps of obtaining a target log; wherein the target log is used for indicating the log of the target vehicle before the time point when the positioning problem occurs; analyzing the target log to obtain longitude and latitude information in the target log; determining target longitude and latitude information according to the longitude and latitude information in the target log; wherein the target longitude and latitude information is used for indicating abnormal data.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and device for detecting abnormal data. Background Art

[0002] At present, the cockpit system of the vehicle is usually equipped with a TBOX (Telematics Box) to support the normal operation of map applications. TBOX (Telematics Box): used to receive and transmit location data and satellite ephemeris data from satellite navigation systems such as GPS / Beidou.

[0003] However, when there is a problem with the GPS / Beidou location data transmitted by TBOX, positioning becomes difficult. It is difficult for developers to intuitively confirm whether the problem is with the original latitude and longitude data transmitted by TBOX or with other data fusion. This makes the debugging and diagnosis process very cumbersome and time-consuming. Summary of the invention

[0004] In view of this, the present invention provides a method and device for detecting abnormal data.

[0005] In a first aspect, the present invention provides a method for detecting abnormal data, the method comprising: obtaining a target log; wherein the target log is used to indicate a log before a time point when a positioning problem occurs of a target vehicle; parsing the target log to obtain longitude and latitude information in the target log; determining target longitude and latitude information based on the longitude and latitude information in the target log; wherein the target longitude and latitude information is used to indicate abnormal data.

[0006] The method for detecting abnormal data provided by the present embodiment, when there is a problem with the GPS / Beidou location data transmitted by TBOX, firstly, it is necessary to obtain the log of the target vehicle before the positioning problem occurs, parse and process the obtained target log, and extract the longitude and latitude information in the log, which is the key to determine whether the positioning is accurate. In the parsed longitude and latitude information, find the data related to the time point of the positioning problem. These data will be used as the target longitude and latitude information, and the target longitude and latitude information will be compared and analyzed with the known accurate location information (such as map data, other sensor data, etc.). This helps to determine whether the problem is caused by the original longitude and latitude data transmitted by TBOX, or due to the problem after the fusion of other data, so that the cause of the problem can be more accurately located.

[0007] In one possible implementation, the target longitude and latitude information is determined based on the longitude and latitude information in the target log, including: obtaining the longitude and latitude information of other vehicles associated with the target vehicle; comparing the longitude and latitude information in the target log with the longitude and latitude information of the other vehicles to determine the difference between the longitude and latitude information in the target log and the longitude and latitude information of the other vehicles; and using the different longitude and latitude information as the target longitude and latitude information.

[0008] The method for detecting abnormal data provided by the present embodiment can realize cross-verification of the position of the target vehicle by comparing the latitude and longitude information of the target vehicle with other associated vehicles. This verification method can reduce the errors that may be caused by a single data source, thereby improving the accuracy of positioning. If the latitude and longitude information of the target vehicle is significantly different from the latitude and longitude information of other vehicles, this may indicate that the positioning data of the target vehicle is abnormal. This method can detect and mark these abnormal data in a timely manner, which is helpful for subsequent problem investigation and correction.

[0009] In one possible implementation, the target longitude and latitude information is determined based on the longitude and latitude information in the target log, including: obtaining historical longitude and latitude information associated with the target vehicle; comparing the longitude and latitude information in the target log with the historical longitude and latitude information to determine the difference between the longitude and latitude information in the target log and the historical longitude and latitude information; and using the different longitude and latitude information as the target longitude and latitude information.

[0010] The method for detecting abnormal data provided by this embodiment can use historical data as a reference by comparing the latitude and longitude information in the target log with the historical latitude and longitude information of the target vehicle, thereby more accurately judging the rationality of the current positioning data. This helps to reduce positioning errors caused by abnormal data at a single time point. If the latitude and longitude information in the target log is significantly different from the historical data, this may indicate that the current positioning data is abnormal. Through comparison, these abnormal data can be discovered and marked in a timely manner, thereby improving the reliability of positioning.

[0011] In one possible implementation, determining the target longitude and latitude information based on the longitude and latitude information in the target log includes: retrieving the longitude and latitude information in the target log according to the index order of the list; encapsulating the retrieved longitude and latitude information to obtain a target character string; inputting the target character string into a map application to determine the driving route of the target vehicle in the map application; and comparing the driving route with the historical driving route to determine the target longitude and latitude information.

[0012] The method for detecting abnormal data provided in this embodiment can accurately locate the positioning anomaly or path deviation that occurs during vehicle driving by comparing the driving route, which helps to quickly find the cause of the problem. And by using the historical driving route as a reference, it is easier to judge the rationality of the current driving route and reduce the possibility of false alarms and missed alarms.

[0013] In a possible implementation, the method further includes: when the location is abnormal, obtaining all logs in the log directory; and screening all logs in the log directory to obtain the target log.

[0014] The method for detecting abnormal data provided in this embodiment can ensure that no log files that may contain useful information are missed by obtaining all logs in the log directory, and can accurately find log files that are directly related to the location of the abnormality by screening all logs.

[0015] In a second aspect, the present invention provides a device for detecting abnormal data, the device comprising: a log acquisition module, used to acquire a target log; wherein the target log is used to indicate a log before a time point when a positioning problem occurs of a target vehicle; a parsing and processing module, used to parse and process the target log to obtain longitude and latitude information in the target log; a first determination module, used to determine target longitude and latitude information based on the longitude and latitude information in the target log; wherein the target longitude and latitude information is used to indicate data where an abnormality has occurred.

[0016] In one possible implementation, the determination module includes: a latitude and longitude information acquisition module, used to acquire the latitude and longitude information of other vehicles associated with the target vehicle; a comparison module, used to compare the latitude and longitude information in the target log with the latitude and longitude information of other vehicles, and determine the different longitude and longitude information between the latitude and longitude information in the target log and the latitude and longitude information of other vehicles; a second determination module, used to use the different longitude and longitude information as the target longitude and longitude information.

[0017] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for detecting abnormal data according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for detecting abnormal data according to the first aspect or any corresponding embodiment thereof.

[0019] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the method for detecting abnormal data according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 is a flow chart of a method for detecting abnormal data according to an embodiment of the present invention;

[0022] Figure 2 is a structural block diagram of a device for detecting abnormal data according to an embodiment of the present invention;

[0023] Figure 3 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0025] Based on relevant technologies, it is known that at present, the cockpit system of the vehicle is usually equipped with a TBOX (Telematics Box) to support the normal operation of the map application. TBOX (Telematics Box): used to receive and transmit location data and satellite ephemeris data of satellite navigation systems such as GPS / Beidou.

[0026] However, when there is a problem with the GPS / Beidou location data transmitted by TBOX, positioning becomes difficult. It is difficult for developers to intuitively confirm whether the problem is with the original latitude and longitude data transmitted by TBOX or with other data fusion. This makes the debugging and diagnosis process very cumbersome and time-consuming.

[0027] Based on this, the present invention provides a method for detecting abnormal data. When there is a problem with the GPS / Beidou location data transmitted by TBOX, it is first necessary to obtain the log of the target vehicle before the positioning problem occurs, parse the obtained target log, and extract the longitude and latitude information in the log. These information are the key to determine whether the positioning is accurate. In the parsed longitude and latitude information, find the data related to the time point of the positioning problem. These data will be used as the target longitude and latitude information, and the target longitude and latitude information will be compared and analyzed with the known accurate location information (such as map data, other sensor data, etc.). This helps to determine whether the problem is caused by the original longitude and latitude data transmitted by TBOX, or due to the problem after the fusion of other data, so that the cause of the problem can be more accurately located.

[0028] According to an embodiment of the present invention, a method embodiment for detecting abnormal data is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0029] In this embodiment, a method for detecting abnormal data is provided, which can be used in computer devices, such as computers, servers, etc. Figure 1 is a flow chart of a method for detecting abnormal data according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0030] Step S101, obtaining a target log; wherein the target log is used to indicate a log before a time point when a positioning problem occurs of a target vehicle.

[0031] The target log may indicate log records related to the target vehicle before the time point when the positioning problem occurs. These logs usually contain key data such as the vehicle's operating status, location information (such as latitude and longitude), and timestamps. Specifically, the log records related to the target vehicle before the time point when the positioning problem occurs are retrieved from the log storage system. These log records are usually stored in a server, database, or log file. For example: If a positioning problem occurs to the target vehicle at 12:00 on October 1, 2023, the log records of the vehicle from 00:00 to 12:00 on October 1, 2023 can be obtained through the log query interface as the target log.

[0032] In one possible implementation, the target log can be obtained by calling the log management system through an API interface. The target log can be retrieved from the database using a database query statement (such as SQL). The target log can be obtained by reading a log file stored on a local or remote server.

[0033] Step S102, parsing the target log to obtain the longitude and latitude information in the target log.

[0034] Longitude and latitude information refers to the longitude and latitude values ​​used to represent a location on the earth in a geographic coordinate system. Longitude indicates the position in the east-west direction, and latitude indicates the position in the north-south direction. Specifically, use a log parsing tool or write parsing code to extract longitude and latitude information from the target log. This information is usually stored in the log in text or binary format. For example: the target log contains the following text: "2023-10-0111:55:00, longitude: 116.397128, latitude: 39.916527". You can use regular expression matching or string segmentation methods to extract longitude and latitude information: "longitude: 116.397128, latitude: 39.916527".

[0035] In a possible implementation, a regular expression library in a programming language such as Python or Java can be used to match and extract longitude and latitude information. A string segmentation and conversion method can be used to extract longitude and latitude information from a log. A specialized log parsing library or tool can be used to parse the target log and extract longitude and latitude information.

[0036] Step S103, determining the target longitude and latitude information according to the longitude and latitude information in the target log; wherein the target longitude and latitude information is used to indicate abnormal data.

[0037] By comparing and analyzing the latitude and longitude information in the target log, find the latitude and longitude data related to the positioning anomaly. This data may appear as longitude and latitude values ​​that suddenly change, are missing, or are inconsistent with other data.

[0038] The method for detecting abnormal data provided by the present embodiment, when there is a problem with the GPS / Beidou location data transmitted by TBOX, firstly, it is necessary to obtain the log of the target vehicle before the positioning problem occurs, parse and process the obtained target log, and extract the longitude and latitude information in the log, which is the key to determine whether the positioning is accurate. In the parsed longitude and latitude information, find the data related to the time point of the positioning problem. These data will be used as the target longitude and latitude information, and the target longitude and latitude information will be compared and analyzed with the known accurate location information (such as map data, other sensor data, etc.). This helps to determine whether the problem is caused by the original longitude and latitude data transmitted by TBOX, or due to the problem after the fusion of other data, so that the cause of the problem can be more accurately located.

[0039] In a possible implementation, the above step S102 includes:

[0040] Step a1, obtaining the latitude and longitude information of other vehicles associated with the target vehicle.

[0041] Other vehicles associated with the target vehicle may refer to other vehicles associated with the target vehicle or in the same environment, network, fleet, etc. Specifically, the latitude and longitude information of other vehicles operating in the same time period as the target vehicle is collected. Such information comes from log records of other vehicles, real-time location data, or fleet management systems.

[0042] Step a2, comparing the latitude and longitude information in the target log with the latitude and longitude information of other vehicles, and determining the different latitude and longitude information between the latitude and longitude information in the target log and the latitude and longitude information of other vehicles.

[0043] Through algorithms or tools, each longitude and latitude information in the target log is compared with the longitude and latitude information of other vehicles at the corresponding time points one by one to find out the differences or inconsistent data.

[0044] In one possible implementation, a spatial distance algorithm (such as Euclidean distance) is used to calculate the position difference between the target vehicle and other vehicles at the same time point. Through time series analysis, the change trend of the position of the target vehicle and other vehicles over time is compared. A clustering algorithm is used to group the position data of the target vehicle and other vehicles to identify abnormal groups.

[0045] Step a3: using different longitude and latitude information as target longitude and latitude information.

[0046] The different or inconsistent longitude and latitude information identified in step a2 is used as the target longitude and latitude information.

[0047] The method for detecting abnormal data provided by the present embodiment can realize cross-verification of the position of the target vehicle by comparing the latitude and longitude information of the target vehicle with other associated vehicles. This verification method can reduce the errors that may be caused by a single data source, thereby improving the accuracy of positioning. If the latitude and longitude information of the target vehicle is significantly different from the latitude and longitude information of other vehicles, this may indicate that the positioning data of the target vehicle is abnormal. This method can detect and mark these abnormal data in a timely manner, which is helpful for subsequent problem investigation and correction.

[0048] In a possible implementation, the above step S102 includes:

[0049] Step b1, obtaining historical latitude and longitude information associated with the target vehicle.

[0050] Extract the longitude and latitude data of the target vehicle running in a certain period of time in the past from the log record of the target vehicle, the database or the storage system of the vehicle itself.

[0051] Step b2, comparing the latitude and longitude information in the target log with the historical latitude and longitude information, and determining the different latitude and longitude information between the latitude and longitude information in the target log and the historical latitude and longitude information.

[0052] Use algorithms or tools to compare each longitude and latitude information in the target log with the historical longitude and latitude information one by one to find out the differences or inconsistencies. This can be done by calculating the distance between two longitude and latitude points, or by comparing the position changes at two time points.

[0053] In one possible implementation, a spatial distance algorithm (such as Euclidean distance) is used to calculate the position difference between the target vehicle and other vehicles at the same time point. Through time series analysis, the change trend of the position of the target vehicle and other vehicles over time is compared. A clustering algorithm is used to group the position data of the target vehicle and other vehicles to identify abnormal groups.

[0054] Step b3, using different longitude and latitude information as target longitude and latitude information.

[0055] The different or inconsistent longitude and latitude information identified in step b2 is used as the target longitude and latitude information.

[0056] The method for detecting abnormal data provided by this embodiment can use historical data as a reference by comparing the latitude and longitude information in the target log with the historical latitude and longitude information of the target vehicle, thereby more accurately judging the rationality of the current positioning data. This helps to reduce positioning errors caused by abnormal data at a single time point. If the latitude and longitude information in the target log is significantly different from the historical data, this may indicate that the current positioning data is abnormal. Through comparison, these abnormal data can be discovered and marked in a timely manner, thereby improving the reliability of positioning.

[0057] In a possible implementation, the above step S102 includes:

[0058] Step c1, retrieve the longitude and latitude information in the target log according to the index order of the list.

[0059] In programming, a list is a data structure used to store a series of elements. Each element has an index (or position) corresponding to it, and the index usually starts at 0. The index order of the list refers to the order of these indexes from low to high (or from 0 to the end of the list). Read the longitude and latitude information from the target log and arrange them in the order they appear in the log (that is, the index order of the list). Specifically, you can use the list or array data structure in the programming language to store the longitude and latitude information and traverse it in index order. Use database query statements to extract the longitude and latitude information in chronological order.

[0060] Step c2, encapsulating the retrieved longitude and latitude information to obtain a target character string.

[0061] The latitude and longitude information obtained in step c1 is encapsulated in a specific format (such as comma separation, JSON format, etc.) to form a string. This string will be used to interact with the map application.

[0062] Step c3, inputting the target character string into the map application to determine the driving route of the target vehicle in the map application.

[0063] Input the target character string obtained in step c2 into the map application, and use the drawing function of the map application to draw the driving route of the target vehicle on the map according to the longitude and latitude information. Specifically, the API interface provided by the map application can be used to input the longitude and latitude information and draw the driving route. Use the SDK or API of a third-party map service (such as Google Maps, Baidu Maps, etc.) to realize the drawing of the driving route.

[0064] Step c4, comparing the driving route with the historical driving route to determine the target longitude and latitude information.

[0065] Compare the route obtained in step c3 with the historical route of the target vehicle to find out the differences or inconsistencies. These differences may indicate abnormal driving or positioning of the target vehicle, thereby determining the target longitude and latitude information. Specifically, a spatial distance algorithm (such as the Haversine formula) can be used to calculate the distance between each point in the route and compare it with the historical route. Time series analysis or machine learning algorithms can also be used to identify abnormal patterns or changes in the route.

[0066] As an example, the original data transmitted by TBOX is once a second. In the cockpit system, log printing is added. When printing, a specific mark (lon_lat:) is added to record the longitude and latitude data of each second. After each print, a new line is processed. The logs printed by the Android application will be saved in the system log directory (log) in chronological order by the log system. When the map application has a positioning exception, all logs in the log directory (log) of the Android system are retrieved through the command line of the Android system (adb pull / log / / local / logl).

[0067] There are many logs in the log directory of the Android system. Take out the logs before the problem occurs and save them in a custom GpsLoc.txt file.

[0068] First, create an ArrayList list mLocData to store the latitude and longitude data parsed by subsequent programs as follows:

[0069] private ArrayList <string>mLocData=new ArrayList<>().

[0070] Put the GpsLoc.txt file in the specified / map / directory and add read and write permissions. The following code obtains GpsLoc.txt for subsequent parsing operations:

[0071] File file=new File(" / map / GpsLoc.txt").

[0072] The log in the GpsLoc.txt file is read line by line through bufferedReader.readLine() in Java. The string line read out contains the required longitude and latitude information.

[0073] By marking lon_lat: as the split node of the line string, the string line is split and a string data loc is obtained.

[0074] The first data in the string data loc is the longitude and latitude data. And add this longitude and latitude data to the data list mLocData.

[0075]

[0076] Take out the data in the mLocData list containing longitude and latitude data in the order of the list index.

[0077] for(String loc:mLocData){

[0078] }

[0079] The extracted data is packaged in the following format: the var lnglats array is filled with all the longitude and latitude data in the mLocData list, and the var path data is also filled with all the longitude and latitude data in the mLocData list. Then a complete StringBuilder string locMarkers can be obtained.

[0080]

[0081]

[0082] By putting the locMarkers data into the map application, you can automatically draw points and lines on the map. By checking the points on the map application, developers can clearly determine which original longitude and latitude data transmitted by TBOX is abnormal or normal data.

[0083] The method for detecting abnormal data provided in this embodiment can accurately locate the positioning anomaly or path deviation that occurs during vehicle driving by comparing the driving route, which helps to quickly find the cause of the problem. And by using the historical driving route as a reference, it is easier to judge the rationality of the current driving route and reduce the possibility of false alarms and missed alarms.

[0084] In a possible implementation, the method further includes:

[0085] Step d1, when the location is abnormal, obtain all logs in the log directory.

[0086] Refers to the situation where the positioning data of a vehicle or mobile device does not meet expectations or has significant deviations. This may be due to equipment failure, signal interference, human interference, or other reasons. Specifically, when a positioning anomaly is detected, the directory where the log files are stored is automatically or manually accessed and all log files in the directory are read. These log files may contain the positioning data of the device at different time points, system status information, error logs, etc.

[0087] Step d2, filter all logs in the log directory to obtain the target log.

[0088] Analyze all the logs obtained in step d1 one by one, and filter out the log files related to the positioning anomaly based on the timestamp, positioning data, error code and other information in the log content. These target logs will be used for further analysis and problem location. Specifically, keyword-based filtering can be used: search for keywords related to positioning anomalies (such as "positioning failure", "signal loss", etc.) in log files to filter out target logs. Timestamp-based filtering: According to the time range in which the positioning anomaly occurs, filter out the log files generated within that time period. Data format-based filtering: If the log file has a specific data format (such as JSON, CSV, etc.), you can use the corresponding parsing library to parse the log file, and filter out the target log based on the field value of the positioning data.

[0089] The method for detecting abnormal data provided in this embodiment can ensure that no log files that may contain useful information are missed by obtaining all logs in the log directory, and can accurately find log files that are directly related to the location of the abnormality by screening all logs.

[0090] In this embodiment, a device for detecting abnormal data is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0091] This embodiment provides a device for detecting abnormal data, such as Figure 2 As shown, the device includes: a log acquisition module 201, used to acquire a target log; wherein the target log is used to indicate a log before a time point when a positioning problem occurs in the target vehicle; a parsing and processing module 202, used to parse and process the target log to obtain longitude and latitude information in the target log; a first determination module 203, used to determine the target longitude and latitude information based on the longitude and latitude information in the target log; wherein the target longitude and latitude information is used to indicate data where an abnormality occurs.

[0092] In one possible implementation, the first determination module 203 includes: a latitude and longitude information acquisition module, used to acquire the latitude and longitude information of other vehicles associated with the target vehicle; a comparison module, used to compare the latitude and longitude information in the target log with the latitude and longitude information of other vehicles, and determine the different longitude and longitude information between the latitude and longitude information in the target log and the latitude and longitude information of other vehicles; a second determination module, used to use the different longitude and longitude information as the target longitude and longitude information.

[0093] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0094] The device for detecting abnormal data in this embodiment is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0095] The embodiment of the present invention also provides a computer device having the above Figure 2 The device for detecting abnormal data is shown.

[0096] See also Figure 3 , Figure 3 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 3 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 10 is taken as an example.

[0097] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0098] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0099] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0100] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0101] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0102] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0103] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0104] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.< / string>

Claims

1. A method for detecting abnormal data, characterized in that: The method comprises: Obtaining a target log; wherein the target log is used to indicate a log before a time point when a positioning problem occurs of the target vehicle; Parsing the target log to obtain longitude and latitude information in the target log; The target longitude and latitude information is determined according to the longitude and latitude information in the target log; wherein the target longitude and latitude information is used to indicate abnormal data.

2. The method for detecting abnormal data according to claim 1, characterized in that: Determining target longitude and latitude information according to the longitude and latitude information in the target log includes: Obtaining the latitude and longitude information of other vehicles associated with the target vehicle; Comparing the latitude and longitude information in the target log with the latitude and longitude information of the other vehicles, and determining the different latitude and longitude information between the latitude and longitude information in the target log and the latitude and longitude information of the other vehicles; Different longitude and latitude information is used as target longitude and latitude information.

3. The method for detecting abnormal data according to claim 1, characterized in that: Determining target longitude and latitude information according to the longitude and latitude information in the target log includes: Obtaining historical latitude and longitude information associated with the target vehicle; Comparing the latitude and longitude information in the target log with the historical latitude and longitude information to determine the latitude and longitude information that is different between the latitude and longitude information in the target log and the historical latitude and longitude information; Different longitude and latitude information is used as target longitude and latitude information.

4. The method for detecting abnormal data according to claim 1, characterized in that: Determining the target longitude and latitude information according to the longitude and latitude information in the target log includes: Retrieving the latitude and longitude information in the target log according to the index order of the list; Encapsulate the extracted longitude and latitude information to obtain the target character string; inputting the target character string into a map application to determine a driving route of the target vehicle in the map application; The driving route is compared with the historical driving route to determine the target longitude and latitude information.

5. The method for detecting abnormal data according to any one of claims 1 to 4, characterized in that: The method further comprises: In case of location exception, obtain all logs in the log directory; All logs in the log directory are screened to obtain target logs.

6. A device for detecting abnormal data, characterized in that: The device comprises: A log acquisition module, used to acquire a target log; wherein the target log is used to indicate the log before the time point when the positioning problem occurs of the target vehicle; The parsing module is used to parse the target log to obtain the longitude and latitude information in the target log; The first determination module is used to determine the target longitude and latitude information according to the longitude and latitude information in the target log; wherein the target longitude and latitude information is used to indicate abnormal data.

7. The device for detecting abnormal data according to claim 6, characterized in that: The modules are determined to include: A latitude and longitude information acquisition module is used to acquire the latitude and longitude information of other vehicles associated with the target vehicle; A comparison module, used for comparing the latitude and longitude information in the target log with the latitude and longitude information of the other vehicles, and determining the different latitude and longitude information between the latitude and longitude information in the target log and the latitude and longitude information of the other vehicles; The second determination module is used to use different longitude and latitude information as target longitude and latitude information.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for detecting abnormal data according to any one of claims 1 to 5 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for detecting abnormal data according to any one of claims 1 to 5.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for detecting abnormal data according to any one of claims 1 to 5.

Images