Vehicle operating state monitoring method and device, storage medium and computer equipment

Abstract

The application discloses a kind of vehicle operating state monitoring method and device, storage medium, computer equipment, it is related to data processing technical field and financial service field, main purpose is to solve the problem of low accuracy of vehicle operating state monitoring.The main include obtaining the real-time stay point data of vehicle, historical position state data, and the fence area data of at least one electronic fence of the vehicle, the electronic fence is calculated based on the historical stay point data of the vehicle;According to the comparison result of the real-time stay point data and the fence area data, the position state of the vehicle is determined;If the position state is abnormal, the operating state monitoring result of the vehicle is determined according to the historical position state data and operating state determination strategy, and the operating state monitoring result is sent to the monitoring terminal corresponding to the vehicle.The main purpose is to monitor the operating state of vehicle.

Description

Technical Field

[0001] This invention relates to the fields of data processing and financial services, and in particular to a method and apparatus for monitoring the operating status of vehicles, a storage medium, and a computer device. Background Technology

[0002] Auto finance leasing is a rapidly developing financial services industry in recent years. By purchasing a car through finance leasing, the buyer pays a down payment and then gains the right to use the vehicle, paying monthly rent and interest during the usage period. To ensure the reliability of capital recovery, the leasing company or bank, as the funding party, monitors the vehicle's operational status, which reflects the lessee's business stability, thus enabling monitoring and early warning of the vehicle's operational status.

[0003] Existing methods for monitoring the operational status of rental vehicles construct an electronic fence based on the buyer's residential address and monitor the vehicle's operation both inside and outside the fence. When a rental vehicle frequently exceeds the fence, it is flagged as malfunctioning, indicating operational instability and triggering an alert. However, when the buyer's business operations change or their permanent address changes, frequent detection of abnormal vehicle operation occurs, leading to numerous false alarms and consequently, low accuracy in monitoring results. Summary of the Invention

[0004] In view of this, the present invention provides a method and apparatus, storage medium and computer equipment for monitoring vehicle operating status, the main purpose of which is to address the problem of low accuracy in existing vehicle operating status monitoring.

[0005] According to one aspect of the present invention, a method for monitoring the operating status of a vehicle is provided, comprising:

[0006] The system acquires real-time stop point data, historical location status data, and fence area data of at least one electronic fence for the vehicle, wherein the electronic fence is calculated based on the vehicle's historical stop point data.

[0007] The location status of the vehicle is determined based on the comparison results between the real-time stop point data and the fenced area data;

[0008] If the location status is abnormal, the operating status monitoring result of the vehicle is determined based on the historical location status data and the operating status determination strategy, and the operating status monitoring result is sent to the monitoring terminal corresponding to the vehicle.

[0009] Furthermore, before acquiring the vehicle's real-time stop point data, historical location status data, and fence area data of at least one electronic fence of the vehicle, the method further includes:

[0010] The historical stop point data of the vehicle is obtained, and the historical stop point data is calculated based on the historical running data of the vehicle within a first preset time interval;

[0011] By performing cluster analysis on the historical stop point data, the center location data of at least one stop point center location is obtained;

[0012] At least one electronic fence is constructed based on the central location data and preset fence area parameters, wherein the preset fence area parameters are configured based on at least one of the vehicle's operating business type and historical monitoring data.

[0013] Furthermore, before constructing at least one electronic fence based on the center location data and preset fence area parameters, the method further includes:

[0014] Obtain the vehicle's operational business type and historical monitoring data, wherein the historical monitoring data includes at least one of the following: number of abnormal operations and level of abnormal operation.

[0015] The initial fence area parameters matching the operational business type are determined from the fence area parameter mapping relationship set;

[0016] The initial fence area parameters are corrected based on the number of abnormal operations and / or the level of abnormal operation, and the result of the correction is determined as the preset fence area parameters.

[0017] Furthermore, if the location status is abnormal, determining the vehicle's operational status monitoring result based on the historical location status data and the operational status determination strategy includes:

[0018] The total number of location anomalies is calculated based on the number of location anomalies in the historical location status data within the first second preset time interval, and the location anomaly rate is calculated based on the total number of location anomalies and the total number of dwell points in the historical location status data.

[0019] If the total number of location anomalies is greater than a first preset threshold and the location anomaly rate is greater than a second preset threshold, then the vehicle's operating status monitoring result is determined to be a first abnormal state.

[0020] If the total number of location anomalies is greater than a first preset threshold or the location anomaly rate is greater than a second preset threshold, then the vehicle's operating status monitoring result is determined to be a second abnormal state.

[0021] Furthermore, before determining the vehicle's operational status monitoring result based on the historical location status data and operational status determination strategy if the location status is abnormal, the method further includes:

[0022] The average total number of location anomalies of the vehicle is calculated based on the second preset time interval and the historical location status data, and a first preset threshold is configured based on the average total number of location anomalies.

[0023] Obtain global vehicle historical location status data for all vehicles with the same operational business type as the vehicle mentioned above;

[0024] The location anomaly rate is calculated based on the global vehicle historical location status data, and a second preset threshold is configured based on the location anomaly rate.

[0025] Furthermore, if the location status is abnormal, after determining the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy, the method further includes:

[0026] If the operation status monitoring result is a first abnormal state, then an early warning message is generated to indicate that the vehicle is operating abnormally;

[0027] If the operation status monitoring result is a second abnormal state, the operation status monitoring result corresponding to the second abnormal state is counted. When the count value is greater than a preset count threshold, the count value is reset to zero, and a warning message indicating the abnormal operation of the vehicle is generated.

[0028] The warning information is sent to the monitoring terminal corresponding to the vehicle.

[0029] Furthermore, the method also includes:

[0030] The vehicle's electronic fence is updated based on at least one of the acquired historical monitoring data and electronic fence update time information, and is matched with preset fence update conditions. When the matching result is successful, the electronic fence of the vehicle is updated.

[0031] According to another aspect of the present invention, a vehicle operating status monitoring device is provided, comprising:

[0032] The acquisition module is used to acquire real-time stop point data, historical location status data, and fence area data of at least one electronic fence of the vehicle, wherein the electronic fence is calculated based on the historical stop point data of the vehicle.

[0033] The determination module is used to determine the position status of the vehicle based on the comparison result between the real-time stop point data and the fence area data;

[0034] The sending module is used to determine the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy if the location status is abnormal, and then send the operating status monitoring result to the monitoring terminal corresponding to the vehicle.

[0035] Furthermore, the device also includes:

[0036] The acquisition module is further configured to acquire the historical stop point data of the vehicle, wherein the historical stop point data is calculated based on the historical running data of the vehicle within a first preset time interval;

[0037] The processing module is used to obtain the center location data of at least one center location of a stop point by performing cluster analysis on the historical stop point data;

[0038] The construction module is used to construct at least one electronic fence based on the central location data and preset fence area parameters, wherein the preset fence area parameters are configured based on at least one of the vehicle's operation business type and historical monitoring data.

[0039] Furthermore, the device also includes:

[0040] The acquisition module is also used to acquire the vehicle's operating business type and historical monitoring data, wherein the historical monitoring data includes at least one of the following: the number of abnormal operations and the level of abnormal operation.

[0041] The determined module is used to determine the initial fence area parameters that match the operational business type from the fence area parameter mapping relationship set;

[0042] The correction module is used to correct the initial fence area parameters based on the number of abnormal runs and / or the level of abnormal runs, and to determine the correction result as the preset fence area parameters.

[0043] Furthermore, the sending module includes:

[0044] The calculation unit is used to calculate the total number of location anomalies based on the number of location anomalies in the historical location status data within the first second preset time interval, and to calculate the location anomaly rate based on the total number of location anomalies and the total number of dwell points in the historical location status data.

[0045] The first determining unit is configured to determine the vehicle's operating status monitoring result as a first abnormal state if the total number of location anomalies is greater than a first preset threshold and the location anomaly rate is greater than a second preset threshold.

[0046] The second determining unit is used to determine the vehicle's operating status monitoring result as a second abnormal state if the total number of location anomalies is greater than a first preset threshold or the location anomaly rate is greater than a second preset threshold.

[0047] Furthermore, the device also includes:

[0048] The first configuration module is used to calculate the average total number of location anomalies of the vehicle based on the second preset time interval and the historical location status data, and to configure a first preset threshold based on the average total number of location anomalies.

[0049] The acquisition module is also used to acquire global vehicle historical location status data of global vehicles with the same operating business type as the vehicle.

[0050] The second configuration module is used to calculate the location anomaly rate based on the global vehicle historical location status data, and configure a second preset threshold based on the location anomaly rate.

[0051] Furthermore, the device also includes:

[0052] The first generation module is used to generate early warning information indicating abnormal vehicle operation if the operation status monitoring result is a first abnormal state.

[0053] The second generation module is used to count the operation status monitoring results corresponding to the second abnormal state if the operation status monitoring result is a second abnormal state, and when the count value is greater than a preset count threshold, the count value is reset to zero and a warning message indicating the abnormal operation of the vehicle is generated.

[0054] The sending module is also used to send the warning information to the monitoring terminal corresponding to the vehicle.

[0055] Furthermore, the device also includes:

[0056] The update module is used to match at least one of the acquired historical monitoring data of the vehicle and the electronic fence update time information with preset fence update conditions, and update the electronic fence of the vehicle when the matching result is successful.

[0057] According to another aspect of the present invention, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the vehicle operating status monitoring method described above.

[0058] According to another aspect of the present invention, a computer device is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0059] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-described vehicle operating status monitoring method.

[0060] By employing the above-described technical solutions, the technical solutions provided by the embodiments of the present invention have at least the following advantages:

[0061] This invention provides a method, apparatus, storage medium, and computer equipment for monitoring vehicle operating status. First, it acquires real-time stop point data, historical location status data, and fence area data of at least one electronic fence for the vehicle, wherein the electronic fence is calculated based on the vehicle's historical stop point data. The vehicle's location status is determined based on a comparison between the real-time stop point data and the fence area data. If the location status is abnormal, the vehicle's operating status monitoring result is determined based on the historical location status data and an operating status determination strategy, and the operating status monitoring result is sent to the monitoring terminal corresponding to the vehicle. Compared with existing technologies, this invention monitors the vehicle's operating status by using an electronic fence determined based on the current vehicle's historical stop point data and the current vehicle's historical location status data. This achieves dynamic updates of the electronic fence, significantly reducing the probability of incorrect judgments of abnormal states, and effectively improving the accuracy of vehicle operating status monitoring.

[0062] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0063] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0064] Figure 1 A flowchart of a vehicle operation status monitoring method provided by an embodiment of the present invention is shown;

[0065] Figure 2 A flowchart of another vehicle operation status monitoring method provided by an embodiment of the present invention is shown;

[0066] Figure 3 A flowchart of another vehicle operation status monitoring method provided by an embodiment of the present invention is shown;

[0067] Figure 4 A block diagram of a vehicle operation status monitoring device provided in an embodiment of the present invention is shown;

[0068] Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention is shown. Detailed Implementation

[0069] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0070] Existing methods for monitoring the operational status of rental vehicles construct an electronic fence based on the vehicle purchaser's residential address and monitor the vehicle's operation both inside and outside the fence. When a rental vehicle frequently exceeds the fence, it is flagged as malfunctioning, indicating operational instability and triggering an early warning. However, when the vehicle purchaser's business operations change or their permanent address changes, frequent abnormal vehicle operation status detections occur, leading to numerous false alarms and low accuracy in monitoring results. This invention provides a method for monitoring vehicle operational status, such as... Figure 1 As shown, the method includes:

[0071] 101. Obtain real-time stopping point data, historical location status data, and fence area data of at least one electronic fence of the vehicle.

[0072] In this embodiment of the invention, the vehicle used as the monitoring target can be a freight vehicle, such as a pickup truck, light truck, etc., or a passenger vehicle, such as a commercial vehicle, minivan, etc. This embodiment of the invention does not impose specific limitations. Real-time stop point data is the stop location data calculated in real time based on the current vehicle's operation monitoring data. Historical location status data is the statistical data on whether the current vehicle's stop point location exceeded the electronic fence over a previous period, such as the number of times the stop point location exceeded the electronic fence, or the cumulative time the stop point location exceeded the electronic fence, etc. This embodiment of the invention does not impose specific limitations. The electronic fence area data is the range data or boundary data of the fence area corresponding to the electronic fence. The current vehicle's electronic fence is not limited to one; it can be determined based on the current vehicle's operation. For example, if the current vehicle's operating range is large or covers multiple directions of operation, there are multiple long-term stop points, requiring multiple corresponding electronic fences.

[0073] In this embodiment of the invention, the real-time stop point data is calculated based on the distance and time in the location information uploaded by the GPS positioning system installed on the current vehicle. For example, if the current location point is A1, then compared with the previous location point A2, if the distance is less than 500 meters and the reporting time is less than 30 minutes, then A1 is compared with the previous location point A3. If the distance is less than 500 meters and the reporting time for both is less than 30 minutes, then it continues to be compared with the previous location point A4, and so on until An. This process continues until A1 and An satisfy the condition that the distance is less than 500 meters and the reporting time is more than 30 minutes. At this point, it is determined that the vehicle has started stopping from the time at point An. The vehicle starts moving when the next location point Bn does not satisfy the condition that the distance is less than 500 meters and the reporting time is less than 30 minutes. The time between points An and Bn is recorded as the stop time. Taking the geometric center of these reported points yields one stop point.

[0074] It should be noted that the electronic fence is calculated based on the vehicle's historical stop point data. For example, it captures the historical stop point data of the current vehicle within a preset time interval, and defines the electronic fence based on the frequency of these historical stop points at different locations. The preset time interval can be one month, two months, or customized according to the actual application scenario requirements; this embodiment of the invention does not impose specific limitations. By calculating the electronic fence based on historical stop point data, dynamic updates to the electronic fence can be achieved. If the vehicle renter's home address changes or the business operation route changes, the vehicle's electronic fence can be flexibly updated to improve the accuracy of vehicle monitoring, avoid errors and false alarms, and thus enhance the accuracy of vehicle operation monitoring.

[0075] 102. Determine the vehicle's location status based on the comparison results between the real-time stop point data and the fenced area data.

[0076] In this embodiment of the invention, in order to determine whether the current vehicle's stopping point is within the electronic fence, the real-time stopping point data is compared with the fence area data. If the real-time stopping point data is not within the fence area data range, it indicates that the current vehicle's real-time stopping point data is not within the electronic fence, and the vehicle's position status is determined to be abnormal. If the real-time stopping point data is within the fence area data range, it indicates that the current vehicle's real-time stopping point data is within the electronic fence, and the vehicle's position status is determined to be normal.

[0077] It should be noted that by comparing the stop point data with the fence area data, it is determined whether the vehicle is within the electronic fence. The large amount of vehicle operation and positioning data is converted into several stop point data. That is, when the vehicle is in motion, there is no need to compare the data, which can greatly reduce the amount of data processing in the process of determining the vehicle's position status, thereby effectively reducing the consumption of equipment operating resources.

[0078] 103. If the location status is abnormal, the operating status monitoring result of the vehicle is determined based on the historical location status data and the operating status determination strategy, and the operating status monitoring result is sent to the monitoring terminal corresponding to the vehicle.

[0079] In this embodiment of the invention, if the vehicle's location status is abnormal, it can only be determined that the vehicle has exceeded the electronic fence once during the current monitoring period. This can only be judged as an occasional occurrence and cannot be used as a basis for determining the vehicle's operating status. Therefore, the vehicle's operating status must also be determined based on the vehicle's historical location status data and operating status determination strategy. For example, if the historical location status data shows a cumulative total of 7 times exceeding the fence, then adding the current fence exceedance, the total number of times exceeding the electronic fence is 8. If the operating status determination strategy includes a cumulative fence exceedance threshold of 7 times and a cumulative fence exceedance time threshold of 10 hours, then the current vehicle's operating status monitoring result is determined to be abnormal. The operational status determination strategy can be based on the historical location status data of the vehicle under the vehicle's operational business type. For example, if the current vehicle is an intercity passenger vehicle, then all historical monitoring data of all available intercity passenger vehicles can be acquired. If the average number of times the vehicle exceeds the electronic fence in a month in the historical monitoring data is 7, then the monthly cumulative fence exceedance threshold in the operational status determination strategy is configured to 7 times. Alternatively, it can be based on the vehicle's historical operational data. For example, if the monthly average cumulative time exceeding the electronic fence in the current vehicle's historical operational data is 10 hours, then the monthly cumulative fence exceedance time threshold in the operational status determination strategy is configured to 7 times. Of course, the operational status determination strategy can also be set by the ratio of the monthly average cumulative time exceeding the electronic fence of 10 hours to the monthly average cumulative time of normal operation. This embodiment of the invention does not impose specific limitations. The monitoring terminal corresponding to the vehicle can be the computer terminal of the leasing company or the mobile terminal of the business personnel responsible for monitoring the current vehicle. This embodiment of the invention does not impose specific limitations.

[0080] It should be noted that determining the operational status judgment strategy by using global vehicle historical location status data of the same operational business type as the current vehicle can make the configuration of the operational status judgment strategy more closely reflect the current operational status of the vehicle and thus more representative, thereby making the judgment of the operational monitoring status more accurate.

[0081] In one embodiment of the present invention, for further illustration and limitation, such as Figure 2 As shown, before obtaining the vehicle's real-time stop point data, historical location status data, and fence area data of at least one electronic fence of the vehicle, the method further includes:

[0082] 201. Obtain the historical stop point data of the vehicle.

[0083] 202. By performing cluster analysis on the historical stop data, the center location data of at least one stop center location is obtained.

[0084] 203. Construct at least one electronic fence based on the central location data and preset fence area parameters.

[0085] In this embodiment of the invention, to determine the center point of historical stop point data, the historical stop points of vehicles are clustered to obtain at least one cluster center. Specifically, k historical stop points are randomly selected as initial center points. The distance from any historical stop point to the k initial center points is calculated. Based on the distance values, the historical stop point with the smallest distance value to a certain initial center point is classified into the cluster to which that initial center point belongs. The initial center point of the cluster is updated using the mean method, resulting in one or more cluster center points among the historical stop points. The historical stop point data is calculated based on the historical operation data of the vehicle within a first preset time interval. The first preset time interval can be three months or can be customized according to actual application needs; this embodiment of the invention does not impose specific limitations. After obtaining the cluster center points of the historical stop points, the center point of the location of the center point is used as the center point of the electronic fence, and then the electronic fence is generated according to preset fence area parameters. The historical stop point data is calculated based on the historical operation data of the vehicle within the first preset time interval. The method for calculating the historical stop point data based on the historical operation data is the same as the calculation process for real-time stop point data, and this embodiment of the invention will not repeat it further. The first preset time interval can be customized according to the actual application scenario requirements, and the embodiments of the present invention do not impose specific limitations.

[0086] The requirements specify that the preset fence area parameters can be configured based on at least one of the vehicle's operational business type and historical monitoring data. Historical monitoring data includes data characterizing the degree of abnormality in the vehicle's operational status over a historical period. The preset fence area parameters are the range values ​​of the electronic fence area, such as the fence radius. For example, if vehicle A's operational business type is long-distance express delivery, the preset fence area parameter could be set to 1000km; if vehicle B's operational business type is urban delivery, the preset fence area parameter could be set to 100km. This embodiment of the invention does not impose specific limitations. Configuring the electronic fence range according to the operational business type allows the electronic fence setting to better match the actual operating conditions of the corresponding vehicle, avoiding situations where the electronic fence range is too large, resulting in inadequate monitoring, or too small, leading to misjudgments, thereby effectively ensuring the accuracy of vehicle operational status monitoring.

[0087] In one embodiment of the present invention, for further explanation and limitation, before the step of constructing at least one electronic fence based on the center location data and preset fence area parameters, the method further includes:

[0088] Obtain the vehicle's operational business type and historical monitoring data;

[0089] The initial fence area parameters matching the operational business type are determined from the fence area parameter mapping relationship set;

[0090] The initial fence area parameters are corrected based on the number of abnormal operations and / or the level of abnormal operation, and the result of the correction is determined as the preset fence area parameters.

[0091] In this embodiment of the invention, the fence area parameter mapping relationship set includes the mapping relationship between different operational business types and different fence area parameters. To further refine the range of the electronic fence, the fence area parameters determined based on the operational business type are used as the initial fence area parameters, and these initial fence area parameters are corrected based on historical monitoring data. The historical monitoring data includes at least one of the following: the number of abnormal operations and the level of abnormal operation. The initial fence area parameters are corrected based on the number of abnormal operations. For example, if the current vehicle's number of abnormal operations is greater than a first abnormal operation threshold, the correction coefficient is determined to be 1.1; if the current vehicle's number of abnormal operations is less than a second abnormal operation threshold, the correction coefficient is determined to be 0.9. Finally, the product of the initial fence area parameters and the correction coefficient is configured as the preset fence area parameters. The initial fence area parameters are also corrected based on the level of abnormal operation. For example, if the current vehicle's abnormal operation level is the highest level representing the degree of abnormality, the correction coefficient is determined to be 0.9; if the abnormal operation level is the lowest level representing the degree of abnormality, the correction coefficient is determined to be 1.1.

[0092] It should be noted that when the number of anomalies is high or the anomaly level is high, the correction coefficient can be greater than or less than 1. When it is greater than 1, the initial fence area is increased to avoid the fence range set according to the operation business type being inapplicable to the current vehicle operation, which would increase the probability of misjudging the operation status. When it is less than 1, it is equivalent to using the number of anomalies and the anomaly level as the credit judgment standard for the vehicle. Narrowing the initial fence area can trigger anomalies more quickly, allowing monitoring personnel to give the vehicle higher attention. Therefore, the correction method corresponding to different historical monitoring data can be set according to actual application needs, and this embodiment of the invention does not impose specific limitations.

[0093] In one embodiment of the present invention, for further illustration and limitation, such as Figure 3 As shown, if the location status is abnormal, the step of determining the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy includes:

[0094] 301. Calculate the total number of location anomalies based on the number of location anomalies in the historical location status data within the first second preset time interval, and calculate the location anomaly rate based on the total number of location anomalies and the total number of dwell points in the historical location status data.

[0095] 302. If the total number of location anomalies is greater than a first preset threshold and the location anomaly rate is greater than a second preset threshold, then the vehicle's operating status monitoring result is determined to be a first abnormal state.

[0096] 303. If the total number of location anomalies is greater than the first preset threshold or the location anomaly rate is greater than the second preset threshold, then the vehicle's operating status monitoring result is determined to be a second abnormal state.

[0097] In this embodiment of the invention, the total number of location anomalies is the number of location anomalies in the historical location status data within a second preset time interval plus 1. The second preset time interval can be one month or a custom value; this embodiment does not impose a specific limitation. The degree of anomaly represented by the first abnormal state is greater than that of the second abnormal state. The first preset threshold is a threshold for the total number of anomalies, and the second preset threshold is a threshold for the anomaly rate. If both the total number of location anomalies and the location anomaly rate of the current vehicle are greater than the corresponding thresholds, it indicates a high degree of anomaly, and the operation status monitoring result is determined to be the first abnormal state. If only one of the total number of location anomalies or the location anomaly rate of the current vehicle exceeds the corresponding threshold, it indicates a low degree of anomaly, and the operation status monitoring result is determined to be the second abnormal state. If both the total number of location anomalies and the location anomaly rate of the current vehicle are less than or equal to the corresponding thresholds, the operation status monitoring result is determined to be in a normal state. The first and second preset thresholds can be customized according to the actual application scenario requirements; this embodiment does not impose a specific limitation.

[0098] It should be noted that the location anomaly rate is the percentage of the total number of location anomalies in the total number of dwell points in the historical location status data. Since the number of dwell points for each vehicle in the same location varies, the total number of location anomalies cannot determine the overall dwell status of the vehicle. Therefore, the operational status monitoring results are jointly judged based on the location anomaly rate and the total number of location anomalies, and abnormal states are classified into different basic categories, thereby effectively improving the accuracy of the operational status monitoring results.

[0099] In one embodiment of the present invention, for further explanation and limitation, before determining the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy if the location status is abnormal, the method further includes:

[0100] The average total number of location anomalies of the vehicle is calculated based on the second preset time interval and the historical location status data, and a first preset threshold is configured based on the average total number of location anomalies.

[0101] Obtain global vehicle historical location status data for all vehicles with the same operational business type as the vehicle mentioned above;

[0102] The location anomaly rate is calculated based on the global vehicle historical location status data, and a second preset threshold is configured based on the location anomaly rate.

[0103] In this embodiment of the invention, the historical location status data of the current vehicle is divided into multiple groups of location status data according to a second preset time interval. The total number of historical location anomalies in each group of location status data is extracted, and the average of the total number of historical location anomalies in all groups is calculated to obtain the average total number of location anomalies. Then, a first preset threshold is configured based on the average total number of location anomalies. For example, if the average total number of location anomalies is 10, then the first preset threshold is configured as 10 or 12. This embodiment of the invention does not make specific limitations. The stop point data of other vehicles in the same city, of the same model, and with the same operating business as the current vehicle are obtained, i.e., global vehicle historical location status data. The abnormal stop time is calculated as a percentage of the total stop time or the number of abnormal stop times as a percentage of the total number of stop times within the second preset time interval based on the stop time or the number of stop times, to obtain the location anomaly rate. Then, a second preset threshold is configured based on the location anomaly rate. For example, if the location anomaly rate is 20%, then the first preset threshold is configured as 20% or 25%. This embodiment of the invention does not make specific limitations.

[0104] It should be noted that the first preset threshold is determined based on the historical location status data of the current vehicle, and the second preset threshold is determined based on the operation data of all vehicles of the same operation business type. This enables the evaluation of the vehicle's operation status from the perspective of the current vehicle and other vehicles of the same operation business type, thereby improving the accuracy of anomaly detection.

[0105] In one embodiment of the present invention, for further explanation and limitation, if the location status is abnormal, after determining the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy, the method further includes:

[0106] If the operation status monitoring result is a first abnormal state, then an early warning message is generated to indicate that the vehicle is operating abnormally;

[0107] If the operation status monitoring result is a second abnormal state, the operation status monitoring result corresponding to the second abnormal state is counted. When the count value is greater than a preset count threshold, the count value is reset to zero, and a warning message indicating the abnormal operation of the vehicle is generated.

[0108] The warning information is sent to the monitoring terminal corresponding to the vehicle.

[0109] In this embodiment of the invention, when the current vehicle's operating status monitoring result is a first abnormal state characterized by severe anomaly, a warning message is directly generated. When the current vehicle's operating status monitoring result is a second abnormal state characterized by lower anomaly, a warning message is not immediately generated. Instead, the number of times the second abnormal state occurs is counted. When the count value is greater than a preset counting threshold, a warning message is generated, and the count value is reset to zero. The preset counting threshold can be 2 or 3, or it can be customized according to the actual application scenario; this embodiment of the invention does not impose specific limitations. By employing different warning message triggering mechanisms for operating status monitoring results of different degrees of anomaly, erroneous warnings can be effectively avoided, thereby effectively improving the accuracy of warnings.

[0110] In one embodiment of the present invention, for further explanation and limitation, the method further includes:

[0111] The vehicle's electronic fence is updated based on at least one of the acquired historical monitoring data and electronic fence update time information, and is matched with preset fence update conditions. When the matching result is successful, the electronic fence of the vehicle is updated.

[0112] In this embodiment of the invention, the preset fence update conditions include at least one of a threshold for the number of abnormal operating states and a preset update time interval. When the number of abnormal operating states in the historical monitoring data of the current vehicle exceeds the threshold, the electronic fence for the current vehicle is updated. If, before the number of abnormal operating states in the historical monitoring data of the current vehicle exceeds the threshold, the time since the last update of the electronic fence reaches the preset update time interval, the electronic fence for the current vehicle is also updated. The electronic fence can be updated based solely on the number of abnormal operating states or based on the update time interval; this embodiment of the invention does not impose specific limitations. Timely updates to the electronic fence can effectively avoid errors in operating state monitoring caused by changes in the vehicle's operating route or the inapplicability of the electronic fence range, thereby effectively improving the accuracy of vehicle operating state monitoring results.

[0113] This invention provides a method for monitoring vehicle operating status. First, it acquires real-time stop point data, historical location status data, and fence area data of at least one electronic fence for the vehicle, wherein the electronic fence is calculated based on the vehicle's historical stop point data. The vehicle's location status is determined based on a comparison between the real-time stop point data and the fence area data. If the location status is abnormal, the vehicle's operating status monitoring result is determined based on the historical location status data and an operating status determination strategy, and the operating status monitoring result is sent to the monitoring terminal corresponding to the vehicle. Compared with existing technologies, this invention monitors the vehicle's operating status by using an electronic fence determined based on the current vehicle's historical stop point data and the current vehicle's historical location status data. This achieves dynamic updates of the electronic fence, significantly reducing the probability of incorrect judgments of abnormal states, and effectively improving the accuracy of vehicle operating status monitoring.

[0114] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this embodiment of the invention provides a vehicle operating status monitoring device, such as... Figure 4 As shown, the device includes:

[0115] The acquisition module 41 is used to acquire real-time stopping point data, historical location status data, and fence area data of at least one electronic fence of the vehicle, wherein the electronic fence is calculated based on the historical stopping point data of the vehicle.

[0116] The determination module 42 is used to determine the position status of the vehicle based on the comparison result between the real-time stop point data and the fence area data;

[0117] The sending module 43 is used to determine the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy if the location status is abnormal, and then send the operating status monitoring result to the monitoring terminal corresponding to the vehicle.

[0118] Furthermore, the device also includes:

[0119] The acquisition module 41 is further configured to acquire the historical stop point data of the vehicle, wherein the historical stop point data is calculated based on the historical running data of the vehicle within a first preset time interval;

[0120] The processing module is used to obtain the center location data of at least one center location of a stop point by performing cluster analysis on the historical stop point data;

[0121] The construction module is used to construct at least one electronic fence based on the central location data and preset fence area parameters, wherein the preset fence area parameters are configured based on at least one of the vehicle's operation business type and historical monitoring data.

[0122] Furthermore, the device also includes:

[0123] The acquisition module 41 is also used to acquire the vehicle's operating business type and historical monitoring data, wherein the historical monitoring data includes at least one of the following: the number of abnormal operations and the level of abnormal operation.

[0124] The determined module 42 is used to determine the initial fence area parameters that match the operational business type from the fence area parameter mapping relationship set;

[0125] The correction module is used to correct the initial fence area parameters based on the number of abnormal runs and / or the level of abnormal runs, and to determine the correction result as the preset fence area parameters.

[0126] Furthermore, the sending module 43 includes:

[0127] The calculation unit is used to calculate the total number of location anomalies based on the number of location anomalies in the historical location status data within the first second preset time interval, and to calculate the location anomaly rate based on the total number of location anomalies and the total number of dwell points in the historical location status data.

[0128] The first determining unit is configured to determine the vehicle's operating status monitoring result as a first abnormal state if the total number of location anomalies is greater than a first preset threshold and the location anomaly rate is greater than a second preset threshold.

[0129] The second determining unit is used to determine the vehicle's operating status monitoring result as a second abnormal state if the total number of location anomalies is greater than a first preset threshold or the location anomaly rate is greater than a second preset threshold.

[0130] Furthermore, the device also includes:

[0131] The first configuration module is used to calculate the average total number of location anomalies of the vehicle based on the second preset time interval and the historical location status data, and to configure a first preset threshold based on the average total number of location anomalies.

[0132] The acquisition module 41 is also used to acquire global vehicle historical location status data of global vehicles with the same operation business type as the vehicle.

[0133] The second configuration module is used to calculate the location anomaly rate based on the global vehicle historical location status data, and configure a second preset threshold based on the location anomaly rate.

[0134] Furthermore, the device also includes:

[0135] The first generation module is used to generate early warning information indicating abnormal vehicle operation if the operation status monitoring result is a first abnormal state.

[0136] The second generation module is used to count the operation status monitoring results corresponding to the second abnormal state if the operation status monitoring result is a second abnormal state, and when the count value is greater than a preset count threshold, the count value is reset to zero and a warning message indicating the abnormal operation of the vehicle is generated.

[0137] The sending module 43 is also used to send the warning information to the monitoring terminal corresponding to the vehicle.

[0138] Furthermore, the device also includes:

[0139] The update module is used to match at least one of the acquired historical monitoring data of the vehicle and the electronic fence update time information with preset fence update conditions, and update the electronic fence of the vehicle when the matching result is successful.

[0140] This invention provides a vehicle operation status monitoring device. First, it acquires real-time stop point data, historical location status data, and fence area data of at least one electronic fence for the vehicle, wherein the electronic fence is calculated based on the vehicle's historical stop point data. The device then determines the vehicle's location status based on a comparison between the real-time stop point data and the fence area data. If the location status is abnormal, the device determines the vehicle's operation status monitoring result based on the historical location status data and an operation status determination strategy, and sends the result to the monitoring terminal corresponding to the vehicle. Compared with existing technologies, this invention monitors the vehicle's operation status by using an electronic fence determined based on the current vehicle's historical stop point data and the current vehicle's historical location status data. This achieves dynamic updates of the electronic fence, significantly reducing the probability of incorrect judgments of abnormal states, and effectively improving the accuracy of vehicle operation status monitoring.

[0141] According to one embodiment of the present invention, a storage medium is provided, the storage medium storing at least one executable instruction, the computer-executable instruction being able to execute the vehicle operating status monitoring method in any of the above method embodiments.

[0142] Figure 5 The diagram illustrates a structural schematic of a computer device according to an embodiment of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the computer device.

[0143] like Figure 5 As shown, the computer device may include: a processor 502, a communications interface 504, a memory 506, and a communications bus 508.

[0144] The processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508.

[0145] Communication interface 504 is used to communicate with other network elements such as clients or other servers.

[0146] The processor 502 is used to execute program 510, specifically to execute the relevant steps in the above-described vehicle operation status monitoring method embodiment.

[0147] Specifically, program 510 may include program code that includes computer operation instructions.

[0148] Processor 502 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0149] Memory 506 is used to store program 510. Memory 506 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0150] Specifically, program 510 can be used to cause processor 502 to perform the following operations:

[0151] The system acquires real-time stop point data, historical location status data, and fence area data of at least one electronic fence for the vehicle, wherein the electronic fence is calculated based on the vehicle's historical stop point data.

[0152] The location status of the vehicle is determined based on the comparison results between the real-time stop point data and the fenced area data;

[0153] If the location status is abnormal, the operating status monitoring result of the vehicle is determined based on the historical location status data and the operating status determination strategy, and the operating status monitoring result is sent to the monitoring terminal corresponding to the vehicle.

[0154] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular hardware and software combination.

[0155] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring the operating status of a vehicle, characterized in that, include: The system acquires real-time stop point data, historical location status data, and fence area data of at least one electronic fence for the vehicle. The electronic fence is calculated based on the clustering results of the vehicle's historical stop point data and preset fence area parameters. The process of determining the preset fence area parameters includes: using the fence area parameters determined based on the vehicle's operational business type as the initial fence area parameters, and correcting the initial fence area parameters based on historical monitoring data. The historical monitoring data includes at least one of the following: the number of abnormal operations and the level of abnormal operation. The location status of the vehicle is determined based on the comparison results between the real-time stop point data and the fenced area data; If the location status is abnormal, the total number of location anomalies is calculated based on the number of location anomalies in the historical location status data within the first second preset time interval. The location anomaly rate is calculated based on the total number of location anomalies and the total number of dwell points in the historical location status data. The operation status monitoring result is determined based on the comparison result of the location anomaly rate with a first preset threshold and a second preset threshold, and the operation status monitoring result is sent to the monitoring terminal corresponding to the vehicle. The first preset threshold is determined based on the historical location status data of the vehicle, and the second preset threshold is determined based on the operation data of global vehicles with the same operation business type as the vehicle.

2. The method according to claim 1, characterized in that, Before acquiring the vehicle's real-time stop point data, historical location status data, and fence area data of at least one electronic fence of the vehicle, the method further includes: The historical stop point data of the vehicle is obtained, and the historical stop point data is calculated based on the historical running data of the vehicle within a first preset time interval; By performing cluster analysis on the historical stop point data, the center location data of at least one stop point center location is obtained; At least one electronic fence is constructed based on the central location data and preset fence area parameters.

3. The method according to claim 2, characterized in that, Before constructing at least one electronic fence based on the center location data and preset fence area parameters, the method further includes: Obtain the vehicle's operational business type and historical monitoring data, wherein the historical monitoring data includes at least one of the following: number of abnormal operations and level of abnormal operation. The initial fence area parameters matching the operational business type are determined from the fence area parameter mapping relationship set; The initial fence area parameters are corrected based on the number of abnormal operations and / or the level of abnormal operation, and the result of the correction is determined as the preset fence area parameters.

4. The method according to claim 1, characterized in that, The determination of the operational status monitoring results based on the location anomaly rate includes: If the total number of location anomalies is greater than a first preset threshold and the location anomaly rate is greater than a second preset threshold, then the vehicle's operating status monitoring result is determined to be a first abnormal state. If the total number of location anomalies is greater than a first preset threshold or the location anomaly rate is greater than a second preset threshold, then the vehicle's operating status monitoring result is determined to be a second abnormal state.

5. The method according to claim 4, characterized in that, If the location status is abnormal, before determining the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy, the method further includes: The average total number of location anomalies of the vehicle is calculated based on the second preset time interval and the historical location status data, and a first preset threshold is configured based on the average total number of location anomalies. Obtain global vehicle historical location status data for all vehicles with the same operational business type as the vehicle mentioned above; The location anomaly rate is calculated based on the global vehicle historical location status data, and a second preset threshold is configured based on the location anomaly rate.

6. The method according to claim 4, characterized in that, If the location status is abnormal, after determining the vehicle's operating status monitoring result based on the historical location status data and the operating status determination strategy, the method further includes: If the operation status monitoring result is a first abnormal state, then an early warning message is generated to indicate that the vehicle is operating abnormally; If the operation status monitoring result is a second abnormal state, the operation status monitoring result corresponding to the second abnormal state is counted. When the count value is greater than a preset count threshold, the count value is reset to zero, and a warning message indicating the abnormal operation of the vehicle is generated. The warning information is sent to the monitoring terminal corresponding to the vehicle.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: The vehicle's electronic fence is updated based on at least one of the acquired historical monitoring data and electronic fence update time information, and is matched with preset fence update conditions. When the matching result is successful, the electronic fence of the vehicle is updated.

8. A device for monitoring the operating status of a vehicle, characterized in that, The device is used to perform the operation corresponding to the vehicle operating status monitoring method according to any one of claims 1-7, including: The acquisition module is used to acquire real-time stop point data, historical location status data, and fence area data of at least one electronic fence of the vehicle. The electronic fence is calculated based on the clustering results of the historical stop point data of the vehicle and preset fence area parameters. The preset fence area parameters are configured based on at least one of the vehicle's operation business type and historical monitoring data. The determination module is used to determine the position status of the vehicle based on the comparison result between the real-time stop point data and the fence area data; The sending module is configured to, if the location status is abnormal, calculate the total number of location anomalies based on the number of location anomalies in the historical location status data within the first second preset time interval, calculate the location anomaly rate based on the total number of location anomalies and the total number of dwell points in the historical location status data, determine the operation status monitoring result based on the location anomaly rate, and send the operation status monitoring result to the monitoring terminal corresponding to the vehicle.

9. A storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the vehicle operating state monitoring method as described in any one of claims 1-7.

10. A computer device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the vehicle operating status monitoring method as described in any one of claims 1-7.

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