Network quality monitoring method and system

Abstract

The invention discloses a network quality monitoring method and system. The method relates to the technical field of smart mines and unmanned driving, and comprises the steps that monitoring data corresponding to at least one vehicle are acquired, the monitoring data at least comprise network quality information and vehicle position information, the at least one vehicle is a vehicle located in a target area, and the monitoring data are data generated during operation of the corresponding vehicle; determining a network quality evaluation result corresponding to the vehicle at least based on the network quality information corresponding to any vehicle; and based on the vehicle position information corresponding to the at least one vehicle, carrying out aggregation processing on the network quality evaluation result corresponding to the at least one vehicle to obtain a network quality monitoring result corresponding to the target area, the network quality monitoring result being used for representing distribution information of network quality in the target area. According to the invention, the technical problem of low accuracy and timeliness of monitoring the network quality in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent mines and unmanned driving technology, in particular to a network quality monitoring method and system. BACKGROUND

[0002] In the construction and development of intelligent mines, unmanned vehicles and manned special equipment vehicles are increasingly becoming important tools for improving production efficiency and ensuring work safety. However, the mine operation environment is complex, including mines up to hundreds of meters deep, constantly changing topography, and electromagnetic interference from numerous large mechanical and electrical equipment. Specifically, high-frequency wireless networks have weak signal penetration in the deep part of the mine, often causing the connection between the equipment and the control system to be interrupted, affecting the stable operation of the unmanned vehicle. The mine topography will change constantly with production activities, and the network signal strength and latency at a specific location fluctuate with the mine topography, making it difficult for the monitoring means in the related technology to capture such dynamic changes. In mine operations, the electromagnetic emissions of a large number of mechanical and electrical equipment interfere with each other, causing unstable wireless network communication, affecting the real-time issuance of control commands and the reliable transmission of vehicle state information. Therefore, the accuracy and timeliness of monitoring network quality in the related technology is low.

[0003] At present, no effective solution has been proposed to solve the above problems. SUMMARY

[0004] The embodiments of the present application provide a network quality monitoring method and system to at least solve the technical problem of low accuracy and timeliness of monitoring network quality in the related art.

[0005] According to an aspect of an embodiment of the present application, a network quality monitoring method is provided, comprising: obtaining monitoring data corresponding to at least one vehicle, wherein the monitoring data at least includes network quality information and vehicle position information, the at least one vehicle is a vehicle located in a target area, and the monitoring data is data generated by the corresponding vehicle during operation; determining a network quality evaluation result corresponding to the vehicle based on at least the network quality information corresponding to any one vehicle; and performing aggregation processing on the network quality evaluation result corresponding to the at least one vehicle based on the vehicle position information corresponding to the at least one vehicle, to obtain a network quality monitoring result corresponding to the target area, wherein the network quality monitoring result is used to represent the distribution information of the network quality in the target area.

[0006] According to another aspect of the embodiments of the present application, a network quality monitoring system is also provided, comprising: at least one vehicle-mounted data collection unit, respectively deployed on at least one vehicle, for collecting monitoring data of the corresponding vehicle, wherein the monitoring data at least comprises network quality information and vehicle location information, the at least one vehicle is a vehicle located in a target area, and the monitoring data is data generated by the corresponding vehicle during operation; a data processing platform, for determining a network quality evaluation result of the vehicle based on at least the network quality information of any one vehicle, and performing aggregation processing on the network quality evaluation result of the at least one vehicle based on the vehicle location information of the at least one vehicle, to obtain a network quality monitoring result corresponding to the target area, wherein the network quality monitoring result is used to represent distribution information of network quality in the target area.

[0007] According to another aspect of the embodiments of the present application, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program performs the method in the embodiments of the present application when running.

[0008] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, comprising a stored executable program, wherein the executable program controls the device where the computer readable storage medium is located to perform the method in the embodiments of the present application when running.

[0009] According to another aspect of the embodiments of the present application, a computer program product is also provided, comprising a computer program, which, when executed by a processor, implements the method in the embodiments of the present application.

[0010] According to another aspect of the embodiments of the present application, a computer program product is also provided, comprising a non-volatile computer readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the method in the embodiments of the present application.

[0011] According to another aspect of the embodiments of the present application, a computer program is also provided, which, when executed by a processor, implements the method in the embodiments of the present application.

[0012] In the embodiment of the present application, first, the monitoring data corresponding to at least one vehicle is acquired, wherein the monitoring data at least includes network quality information and vehicle position information, the at least one vehicle is a vehicle located in a target area, and the monitoring data is data generated by the corresponding vehicle during operation; then, the network quality evaluation result corresponding to the vehicle is determined based on at least the network quality information corresponding to any one vehicle; finally, the network quality evaluation result corresponding to the at least one vehicle is aggregated based on the vehicle position information corresponding to the at least one vehicle, to obtain a network quality monitoring result corresponding to the target area, wherein the network quality monitoring result is used to represent the distribution information of the network quality in the target area. The network quality monitoring method provided in the present application realizes accurate and real-time monitoring and evaluation of the network condition in the target area by combining the network quality information and the vehicle position information. The real-time monitoring data ensures the timeliness of the network quality information. The network quality evaluation result corresponding to the vehicle can reflect the network experience in the real working environment, and the network quality information of each vehicle can be independently analyzed. The network quality evaluation result calculated according to the data uploaded by each vehicle can more accurately reflect the actual network experience of the vehicle. Based on the vehicle position information, the network quality evaluation result is aggregated in the geographical space, and the evaluation result of each vehicle is mapped to a plurality of grids in the target area. By receiving the data reported by the vehicle in real time, the network quality evaluation result is calculated in real time, and the new network quality monitoring result is displayed through geographical space aggregation, thereby solving the technical problem of low accuracy and timeliness of monitoring the network quality in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0013] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and together with the description serve to explain the present application. In the drawings:

[0014] Figure 1 FIG. 1 is a flowchart of a network quality monitoring method according to an embodiment of the present application;

[0015] Figure 2 FIG. 5 is a schematic diagram of an optional network quality monitoring result displayed in the form of a heat map according to an embodiment of the present application;

[0016] Figure 3 FIG. 6 is a schematic diagram of a network quality monitoring device according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, so that those skilled in the art can better understand the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should fall within the protection scope of the present application.

[0018] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0019] According to an aspect of the embodiments of the present application, a network quality monitoring method is provided. It should be noted that the steps shown in the flowchart of the 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 herein can be executed in an order different from that shown herein.

[0020] Figure 1 is a flowchart of a network quality monitoring method according to an embodiment of the present application, as shown in Figure 1 The method comprises the following steps:

[0021] Step S102, obtaining monitoring data corresponding to at least one vehicle.

[0022] The monitoring data at least includes network quality information and vehicle position information, and the at least one vehicle is a vehicle located in a target area, and the monitoring data is data generated by the corresponding vehicle during operation.

[0023] The network quality information mentioned above can refer to various performance indicators of the wireless network signal received by the unmanned mine truck or manned vehicle terminal in the mine area, which can include but is not limited to network delay time, received signal strength indication, signal-to-noise ratio, service base station code, and service sector code, etc. The network quality information can comprehensively reflect the real-time condition of the wireless network near the vehicle location, such as signal stability, bandwidth availability, and delay size, which can be used as an important parameter to evaluate the network health status.

[0024] The vehicle location information mentioned above can refer to information indicating the vehicle location, which can include the longitude, latitude, and elevation information of the vehicle, and can be used to accurately identify the geographical position of the vehicle in the mine, which helps to associate the network quality data with specific geographical coordinates, thereby visualizing the distribution of network quality in space.

[0025] The target area mentioned above can refer to a specific area that needs to be monitored for network quality, such as a mine pit, road, warehouse, etc. in a mine scene. The selection of the target area can be based on the daily operation needs of the mine, such as areas where unmanned vehicles frequently operate or have higher requirements for network quality.

[0026] In an optional embodiment, a combination of distributed data collection and cloud processing can be used to achieve accurate monitoring of the network quality of unmanned vehicles in the mine. Specifically, data collection devices can be installed on each unmanned mine truck and manned vehicle terminal to ensure that network quality information and vehicle location information can be captured in real time during vehicle operation. The data collection device can automatically detect and report the code of the base station and service sector currently connected by the vehicle, further refining the granularity of network quality monitoring. The data collected by the data collection unit can be sent to the data processing platform, which can receive and preprocess the data, including data cleaning, removing invalid or abnormal data, grouping by vehicle identification code, and ensuring the orderliness and efficiency of subsequent processing. The quality evaluation module can also be used to calculate the network quality score of each vehicle at a specific time and location based on the network quality information uploaded by each vehicle, such as network delay, signal strength, signal-to-noise ratio, etc., combined with the real-time running state of the vehicle, i.e. online or offline state. The calculation of the network quality score takes into account the signal quality itself and also gives appropriate penalties according to the offline time, thereby more comprehensively reflecting the actual performance of the network.

[0027] In the above process, real-time monitoring and rapid feedback of the network quality of the intelligent mine can be achieved, effectively preventing safety accidents caused by network interruption, improving the reliability and stability of the monitoring process, and providing detailed network quality distribution information to assist network improvement decisions, such as adjusting the position of the base station, increasing network equipment, etc. to meet the high real-time, high bandwidth, and high reliability requirements of the network in the mine operation.

[0028] Step S104, determining the network quality evaluation result corresponding to the vehicle based on at least the network quality information corresponding to any one vehicle.

[0029] The network quality evaluation result mentioned above can be a quantitative index for comprehensively evaluating the wireless network quality of the geographic location where the vehicle is located, can be obtained by analyzing and calculating the real-time network quality information reported by the vehicle, and can include but not limited to network delay, signal strength, signal-to-noise ratio, and offline information.

[0030] In an optional embodiment, the network quality evaluation result corresponding to the vehicle can be determined based on at least the network quality information corresponding to any one vehicle. Specifically, the data processing platform can receive network quality information and offline state information from the vehicle-mounted data acquisition unit, which can include network delay, signal strength, signal-to-noise ratio, and online or offline state of the vehicle. The data processing platform can preprocess these raw data, which can include removing invalid data, standardizing formats, etc., to ensure the accuracy and consistency of the data. For example, the three parameters of network delay, signal strength, and signal-to-noise ratio can be scored respectively, and a scoring function can be designed, which can take into account the special needs of network quality in the mine environment, such as high sensitivity to real-time and reliability of connection. When the vehicle is offline, a penalty mechanism is also used to reflect the unstable state of the network. The single-parameter score and offline time penalty can be combined to generate the network quality evaluation result. The network quality evaluation result can be stored and continuously updated to reflect the dynamic changes of network quality. For each vehicle, the network quality evaluation result can become more accurate and detailed as the time series data accumulates.

[0031] In the above process, based on the network quality evaluation result, the areas with insufficient network coverage or declining signal quality can be found in time, providing data support for subsequent improvement and upgrading of network infrastructure, and effectively preventing production inefficiency or safety accidents caused by network problems.

[0032] Step S106, based on the vehicle location information corresponding to at least one vehicle, the network quality evaluation result corresponding to at least one vehicle is aggregated to obtain the network quality monitoring result corresponding to the target area.

[0033] The network quality monitoring result is used to represent the distribution information of the network quality in the target area.

[0034] The network quality monitoring result can be a comprehensive monitoring result reflecting the network quality distribution in the target area, which is formed by aggregating the network quality evaluation results reported by at least one vehicle in the target area. The network quality monitoring result can include the network quality conditions of different location points in the target area, and can be presented in a visual form, such as a heat map to distinguish the high and low network quality. The red area can represent a strong signal and good network quality, and the green area can represent a weak signal and poor network quality.

[0035] In an optional embodiment, the target area can be divided into a series of grids according to the size and topographic features of the target area, and each grid can serve as a basic unit for data aggregation to ensure accurate spatial data processing and aggregation even in complex terrain. When the data processing platform receives the network quality evaluation results uploaded by the vehicle, the data can be distributed to the corresponding grid according to the real-time location information of the vehicle, which can include longitude, latitude and elevation. For each grid, the collected network quality evaluation results can be used as input, and for each grid, the network quality evaluation results of the vehicles within the range can be aggregated, such as weighted average processing. Finally, the aggregation results of each grid can be integrated into a complete network quality distribution map, i.e. the network quality monitoring result. The color depth of each grid in the network quality monitoring result can represent the level of network quality evaluation result, for example, the warmer the color, such as red, the higher the network quality evaluation result, i.e. the better the network quality; the cooler the color, such as blue or green, the lower the network quality evaluation result, i.e. there is a network quality problem.

[0036] In the above process, by associating the network quality evaluation result of the vehicle with the specific vehicle location information, the area with poor network quality or blind area can be quickly located, which is helpful for network troubleshooting and improvement in large mine environment. The network quality monitoring result can be continuously updated to form time series data, which is convenient for analyzing the change trend of network quality at different time points or seasons, predicting potential network fluctuation or failure risk in advance, and taking preventive measures. According to the network quality monitoring result, the base station position can be adjusted, network facilities can be added or wireless resource allocation can be improved to improve the network quality of a specific target area, such as an area where unmanned vehicles frequently operate, to ensure high standards of network real-time performance and reliability.

[0037] In the embodiment of the present application, first, monitoring data corresponding to at least one vehicle is acquired, wherein the monitoring data at least includes network quality information and vehicle position information, the at least one vehicle is a vehicle located in a target area, and the monitoring data is data generated by the corresponding vehicle during operation; then, based on at least the network quality information corresponding to any one vehicle, a network quality evaluation result corresponding to the vehicle is determined; finally, based on the vehicle position information corresponding to the at least one vehicle, the network quality evaluation result corresponding to the at least one vehicle is aggregated to obtain a network quality monitoring result corresponding to the target area, wherein the network quality monitoring result is used to represent the distribution information of the network quality in the target area. The network quality monitoring method provided in the present application realizes accurate and real-time monitoring and evaluation of the network condition in the target area by combining network quality information and vehicle position information. The acquisition of real-time monitoring data ensures the timeliness of the network quality information. The determination of the network quality evaluation result corresponding to the vehicle can reflect the network experience in the real working environment, and the network quality information of each vehicle can be independently analyzed. The network quality evaluation result is calculated according to the data uploaded by each vehicle, which can more accurately reflect the actual network experience of the vehicle. Based on the vehicle position information, the network quality evaluation result is aggregated in geographical space, and the evaluation result of each vehicle is mapped to multiple grids in the target area. By receiving the data reported by the vehicle in real time, the network quality evaluation result is calculated in real time, and the new network quality monitoring result is displayed through geographical space aggregation, thereby solving the technical problems of low accuracy and timeliness in monitoring network quality in the related art.

[0038] In the embodiment of the present application, the monitoring data further includes offline information of the vehicle, and determining the network quality evaluation result corresponding to the vehicle based on at least the network quality information corresponding to any one vehicle includes: in response to any one vehicle being in an online state, determining the network quality evaluation result corresponding to the vehicle based on the network quality information corresponding to the vehicle; or, in response to any one vehicle being in an offline state, determining the network quality evaluation result corresponding to the vehicle according to historical network quality information and offline information of the vehicle before the vehicle goes offline; preferably, determining the network quality evaluation result corresponding to the vehicle according to the historical network quality information and the offline information of the vehicle before the vehicle goes offline includes: performing weighted processing on the historical network quality information and the offline information to obtain the network quality evaluation result corresponding to the vehicle.

[0039] The offline information mentioned above can refer to information that the vehicle loses connection with the data processing platform or network communication is interrupted, and specifically can include the time when the vehicle changes from an online state to an offline state and the duration of the vehicle in the offline state.

[0040] In an optional embodiment, the offline detection module can be responsible for monitoring the online state of each vehicle, and when it is detected that a vehicle has not uploaded data for a long time, it can be determined that the vehicle is offline, and the offline information of the vehicle can be recorded to ensure that network interruption or instability can be monitored in real time. Then, for vehicles in an online state, the data processing platform can use the reported network quality information for evaluation, and can receive and process network quality information in real time to generate network quality evaluation results reflecting the current network status of the vehicle. Specifically, based on the real-time network quality information uploaded by the vehicle, a suitable evaluation algorithm such as weighted average, threshold judgment, etc. can be used to calculate the current network quality evaluation result of the vehicle. The evaluation algorithm can comprehensively consider multiple dimensions of parameters such as signal strength, delay, and signal-to-noise ratio to fully reflect the network status of the location where the vehicle is located. When the vehicle is in an offline state, historical network quality information can be used in combination with offline information for comprehensive evaluation. The evaluation process can be based on data recorded before the vehicle goes offline to evaluate the network quality status of the vehicle before it goes offline, and then adjust the evaluation result according to the offline duration. For offline vehicles, a weighted decay mechanism can also be used to combine offline information with historical network quality information. Offline time can be quantified as a decay factor, which can be multiplied by the evaluation value of the network quality information before going offline to reflect the potential decline in network quality during the offline period.

[0041] In the above process, in the case of vehicle offline, historical data and offline duration can be used to make inferences to maintain the continuity of network quality monitoring and avoid missing monitoring due to temporary vehicle offline. The addition of offline information can more accurately reflect the actual network status of the target area where the vehicle is located, and when network failures are frequent or signals are unstable, network problems can be discovered and warned in a timely manner to provide real-time and effective network quality feedback for mine operations.

[0042] In the embodiments of the present application, the offline information is obtained by determining the cumulative duration of the vehicle being continuously offline, and calculating the offline information based on the cumulative duration of the vehicle being continuously offline.

[0043] In an optional embodiment, the data processing platform can set a heartbeat timer for each vehicle, and when the vehicle is online, the vehicle can send a heartbeat packet to the data processing platform once per second to confirm the online state of the vehicle; if the data processing platform does not receive the heartbeat packet beyond a set threshold, it can be determined that the vehicle enters an offline state. When detecting that the vehicle is offline, the data processing platform starts timing until the vehicle is online again or receives an offline request sent by the vehicle actively, during which the continuous offline time can be recorded cumulatively to generate a cumulative duration. After the offline state is released, the data processing platform can update the offline information of the vehicle according to the cumulative offline duration, which can include associating the offline duration with the vehicle location, network quality historical data, etc. to facilitate subsequent network quality evaluation considering the impact of offline on network conditions.

[0044] In the above process, the calculation of the cumulative duration can help accurately determine the reason for the vehicle offline, thereby determining whether it is due to network failure or communication problem of the vehicle itself. Including the cumulative duration in the consideration of network quality monitoring can ensure the comprehensiveness of the evaluation results. During the offline period of the vehicle, by considering the length of the offline time, a certain degree of indirect evaluation of the network quality can be given, avoiding the breakage of the monitoring data.

[0045] In the embodiment of the present application, the network quality evaluation result corresponding to the vehicle is determined according to the historical network quality information and offline information before the vehicle goes offline, including: generating an initial evaluation result based on the historical network quality information; generating a decay evaluation result based on the cumulative duration of the vehicle being continuously offline; generating a network quality evaluation result based on the initial evaluation result and the decay evaluation result; preferably, generating a decay evaluation result based on the cumulative duration, including: obtaining a time duration difference between the cumulative duration and a preset offline duration, to obtain a time duration difference; generating an initial decay result based on the time duration difference; obtaining a difference between the initial decay result and a preset value to obtain a decay evaluation result.

[0046] The decay evaluation result described above can refer to a result of punishing the network quality evaluation calculated based on the historical network quality information before the vehicle goes offline and the continuous duration of offline.

[0047] The preset offline duration described above can refer to a preset upper limit of offline time. If the preset offline duration is exceeded, the evaluation of network quality will be punished more significantly. The preset offline duration can be preset according to the special needs of the mine network, for example, if the mine requires higher continuity of network service, the preset offline duration can be set shorter to respond to the unstable state of the network in time.

[0048] The preset value can be a reference value used for comparison in the process of generating the decay evaluation result, which can be an initial value of the decay evaluation result or a value of the decay evaluation result in an ideal state.

[0049] In an optional embodiment, an initial evaluation result reflecting the network condition before the vehicle goes offline can be generated based on the network quality information collected in a period of time before the vehicle goes offline by using a weighted aggregation model. Then, the continuous offline state of the vehicle can be monitored, and the cumulative duration of the vehicle can be recorded. Subsequently, the decay evaluation result can be generated based on the cumulative duration, and specifically, a time difference between the cumulative duration of the vehicle and the preset offline duration can be obtained, which can reflect the degree to which the offline state of the vehicle exceeds the normal tolerance range. Then, according to the time difference, a preliminary penalty score, i.e., an initial decay result, can be calculated. The penalty score can be designed to be incremental, i.e., the greater the time difference, the more severe the penalty, to reflect the trend that the network service quality decreases as the offline time extends. Finally, the initial decay result can be compared with the preset value, and the initial evaluation result can be adjusted according to the gap between the initial decay result and the preset value to obtain the decay evaluation result, so that the decay evaluation result obtained is more in line with the actual situation.

[0050] In the above process, by estimating the decline of the network quality during the offline period of the vehicle, approximate real-time network quality evaluation can be provided to fill the monitoring gap during the data missing period and ensure the continuity of the monitoring. By comprehensively using the historical network quality information and offline state analysis, relatively accurate network quality evaluation can be provided during the offline period of the vehicle, which effectively supports the decision improvement and continuous operation and maintenance of the mine network.

[0051] In the embodiment of the present application, the historical network quality information includes at least any two types of information in the time delay, the signal strength and the signal-to-noise ratio; the initial evaluation result is generated based on the historical network quality information, including: at least any two types of information collected at the latest time collection point before the vehicle enters the offline state are weighted to obtain the historical network quality evaluation result; preferably, the first weight value corresponding to the time delay, the second weight value corresponding to the signal strength and / or the third weight value corresponding to the signal-to-noise ratio are determined based on the region type corresponding to the target region or the task type corresponding to the vehicle.

[0052] The region type can refer to the characteristic type of different geographical regions in the mine, and the region type can be classified according to the terrain, environment, purpose, etc. of the mine. For example, the bottom of the mine pit, the slope of the mountain, the passageway, the operation platform, etc. Different region types can have different requirements or different effects on the network quality.

[0053] The task type can refer to the nature and requirements of the task performed by the vehicle in the mine. Different task types can have different requirements for network real-time performance, throughput, and connection reliability. For example, high-precision positioning of the vehicle, real-time video transmission, sending of control instructions, and other tasks, the efficiency and safety of the execution of these tasks depend on the network quality, and different weight values can be set to reflect the sensitivity of different task types to network quality evaluation.

[0054] In an optional embodiment, historical network quality information before the vehicle goes offline can be used to generate an initial evaluation result. Specifically, network quality information at a time point before the vehicle goes offline can be collected, which can include at least any two of the time delay, signal strength, and signal-to-noise ratio. For example, the signal strength and signal-to-noise ratio at the last online time can be recorded to reflect the network condition before the vehicle goes offline. The selection of the weight value can be based on the region type of the target region and the task type of the vehicle. For example, at the bottom of the mine pit, due to the closed terrain, the signal penetration ability is weak, and more emphasis can be placed on the signal strength and signal-to-noise ratio, and the weight of the time delay can be reduced; for vehicles that need to perform real-time control tasks, the weight of the time delay can be significantly increased. Then, a mathematical model such as linear weighting, exponential weighting, etc. can be used to perform weighted calculation on the collected network quality information to generate an initial evaluation result. The initial evaluation result can comprehensively reflect the pros and cons of the network quality before going offline, while considering the network requirements of specific regions and tasks. Finally, the initial evaluation result is adjusted or attenuated by further combining the offline information of the vehicle, such as the offline duration, to finally generate a network quality evaluation result reflecting the network quality of the region where the vehicle is located.

[0055] In the above process, different region types and task types have different requirements for network quality, and by dynamically adjusting the weight, these differences can be adaptively responded to, ensuring that the evaluation standard matches the actual network use scenario. By identifying the sensitivity of different regions and tasks to network quality, network resources can be reasonably improved, such as increasing the base station density, adjusting the signal transmission power, or taking other technical means, to meet the network requirements of specific regions and tasks, and to improve the overall network performance.

[0056] In the embodiments of the present application, based on the vehicle position information corresponding to at least one vehicle, the network quality evaluation results corresponding to the at least one vehicle are aggregated to obtain network quality monitoring results corresponding to a target area, including: dividing the target area to obtain a plurality of grids; based on any one vehicle position information, determining a target grid corresponding to the vehicle position information from the plurality of grids, wherein the vehicle position information is located in the target grid; for any one grid in the plurality of grids, processing the network quality evaluation results corresponding to at least one target vehicle to obtain a sub-monitoring result corresponding to the grid, wherein the vehicle position information corresponding to the target vehicle is located in the grid; based on the sub-monitoring results corresponding to the plurality of grids, obtaining the network quality monitoring results; preferably, the grid shape and / or grid size of the plurality of grids are determined based on the operation scene corresponding to the target area, the terrain of the target area and / or the size information of the target area; preferably, for any one grid in the plurality of grids, processing the network quality evaluation results corresponding to at least one target vehicle to obtain a sub-monitoring result corresponding to the grid includes: for any one grid in the plurality of grids, performing weighted average processing on the network quality evaluation results falling within the grid area to obtain a sub-monitoring result corresponding to the grid.

[0057] The above-mentioned operation scene can refer to the specific environment and operating conditions of different operation areas in the mine. For example, blasting area, loading area, transportation road, etc., different operation scenes can have unique network requirements. The operation scene can include the physical environment of the mine, and can also include the type of operation performed in a specific area, the density of equipment, the electromagnetic environment and other factors.

[0058] The above-mentioned size information can refer to the physical size containing the target area, such as length, width and height, and the complexity of spatial layout, such as whether it contains a large amount of mountains, deep pits or narrow channels, etc. The size information helps to determine the rationality and effectiveness of grid division, ensuring that each grid can cover sufficient geographical area, and will not be too large so as to be unable to reflect the change of local network quality.

[0059] In an optional embodiment, network quality monitoring of the target area can be achieved through multi-level grid division and data aggregation. Specifically, the target area can be divided into multiple grids based on the job scene, terrain and size information of the target area, using a geocoding algorithm or similar other technologies. The shape and size of the grid can be adjusted according to actual conditions. For example, in areas with high device density and serious electromagnetic interference, the grid can be smaller to capture the changes in network quality more finely. When vehicles upload location information and network quality data, the vehicles can be positioned to the grid where the vehicles are located based on the latitude, longitude and elevation data of the vehicles, ensuring that each piece of data is accurately classified to the correct geospatial location, providing a data basis for subsequent data aggregation. For each grid, the network quality evaluation results of the vehicles falling into the grid can be processed by weighted average, and the weight can be set based on multiple factors such as time, vehicle type and task type, to reflect the comprehensive state of network quality in the specific area, so as to generate the sub-monitoring result of the grid.

[0060] In the above process, the multi-level grid division and data aggregation processing strategy is adopted. The grid division takes into account the job scene and terrain characteristics, and can more accurately capture the changes in network quality in different areas, helping to identify network blind spots and improve network layout. The data aggregation in the grid uses weighted average, and the weight can be dynamically adjusted according to the vehicle task type and regional characteristics, so that the network quality condition of a specific area and time can be more accurately reflected.

[0061] In the embodiment of the application, the method further comprises: determining a display mode corresponding to each of the plurality of grids based on the sub-monitoring result corresponding to each of the plurality of grids; and displaying the network quality monitoring result according to the display mode corresponding to each of the plurality of grids. Preferably, the method further comprises: determining a network quality adjustment strategy based on the network quality monitoring result, wherein the network quality adjustment strategy comprises a base station adjustment strategy in the target area; or, preferably, the method further comprises: identifying a fault of the vehicle based on a plurality of network quality monitoring results corresponding to different time instants; or, preferably, displaying the network quality monitoring result according to the display mode corresponding to each of the plurality of grids comprises: displaying the network quality monitoring result in the form of a heat map.

[0062] The display mode described above can refer to the way in which the network quality monitoring result is presented to the user, and can include but is not limited to different colors and different shades, etc. The determination of the display mode can be based on legibility and information density, to ensure that the user can quickly understand and respond to the monitoring result.

[0063] The base station adjustment strategy described above can refer to a strategy for adjusting the network infrastructure to improve network quality, which can include adjusting the position, power and sector coverage direction of the base station. The base station adjustment strategy can be formulated based on the network quality monitoring result, aiming to improve the network coverage range, signal strength and connection stability to meet the needs of mine operations.

[0064] The heat map form described above can refer to a data visualization form using the depth of color to represent the high and low of a certain numerical attribute of a region. In network quality monitoring, the heat map can be used to display the network quality level in different grids. For example, the deeper the color, the better the network quality, so that the user can intuitively understand the spatial distribution of the network condition.

[0065] In an optional embodiment, the display and application of the network quality monitoring result can be performed. The network quality level of each grid can be determined according to the sub-monitoring results of the plurality of grids, which can be excellent, good, general or poor. The determination of the level can be based on the threshold setting, which reflects the average level of network quality. In order to make the user easily understand the network quality monitoring result, a suitable display mode can be selected. For example, a heat map can be used, which can clearly reflect the spatial distribution characteristics of the network quality, and information can also be supplemented by color alarm, digital score and the like. Then, the network quality monitoring result can be displayed by using the heat map form. Each grid can be assigned a different color according to the sub-monitoring result, and the depth of the color can reflect the good or bad of the network quality in the grid, so as to generate a complete network quality geographic heat map. The network quality monitoring result can also be further used for data analysis to identify areas and time periods with poor network quality, so as to develop a base station adjustment strategy. The base station adjustment strategy can include increasing the number of base stations, changing the location of the base station, adjusting the power of the base station or improving the sector coverage direction to solve the network failure in a specific area.

[0066] In the above process, the display of the heat map form makes the distribution and change of the network quality visualized, which facilitates the user to quickly master the network condition and develop a reasonable base station adjustment strategy, thereby improving the efficiency of network improvement work. The development of the base station adjustment strategy is based on detailed network quality monitoring results, which can accurately allocate resources to problem areas and avoid the waste of costs caused by blind increase of base stations.

[0067] In the embodiment of the application, the method further comprises: updating the network quality layer region corresponding to the target region in the map data based on the sub-monitoring results corresponding to the plurality of grids, to obtain updated map data; and sending the updated map data to other vehicles; preferably, the other vehicles are configured to perform path planning by using the updated map data.

[0068] The network quality layer region described above can refer to a map layer region for storing and displaying network quality information of each grid, which can intuitively present the network condition of the target region, including signal strength, time delay, connection reliability and coverage range, etc.

[0069] In an optional embodiment, the network quality layer area in the map data can be updated based on the sub-monitoring results of each grid. Each grid can be assigned a numerical value or color representing the network quality, thereby forming a dynamic map reflecting the distribution of network quality in real time. Then, the network quality layer area can be updated, which can include immediate modification of the map database to ensure that the map data is synchronized with the newly monitored network conditions. This update can be based on a time window, automatically updating the network quality information in the map data. The updated map data can be sent to other vehicles in the mine, including unmanned mine trucks and manned vehicle terminals. Other vehicles can access the real-time network quality map through the vehicle system or mobile application to obtain updated information about the network conditions of the driving route and work area. After receiving the updated map data, the vehicle can use this information for more intelligent path planning. For example, the vehicle can preferentially select a path with good signal display in the network quality layer area to ensure the real-time and reliability of data transmission during task execution. For unmanned vehicles, it helps to avoid entering network blind areas or weak signal areas, reducing the risk of communication delay and disconnection, and ensuring the safety of operation.

[0070] In the above process, dynamically updating the network quality layer area can ensure that the vehicle can obtain timely network condition information and avoid the risks and inconveniences caused by path planning based on outdated data. Sharing the updated map data with other vehicles enables other vehicles to make better path selection based on real-time network quality information, further promoting the intelligentization process of mine operation.

[0071] In the embodiment of the present application, based on the vehicle position information corresponding to at least one vehicle, the network quality evaluation result corresponding to at least one vehicle is aggregated, including: in response to the change rate between the network quality evaluation result and the historical network quality evaluation result being greater than the preset change rate, the network quality evaluation result corresponding to at least one vehicle is aggregated based on the vehicle position information corresponding to at least one vehicle, and the network quality monitoring result corresponding to the target area is obtained.

[0072] The above-mentioned preset change rate can refer to the threshold value of the change of the network quality evaluation result. If the change rate between the current network quality evaluation result and the historical evaluation result is greater than the preset change rate, it can be determined that the network quality has a significant fluctuation, and further monitoring and response measures can be taken. The setting of the preset change rate takes into account the normal range of natural network fluctuation and the special requirements of mine operation on network stability, aiming to filter out slight signal fluctuations and focus more on network quality mutation events that will have a greater impact on mine operation.

[0073] In an optional embodiment, the results of each network quality assessment, including signal strength, latency, signal-to-noise ratio, and the like, as well as the corresponding vehicle location information, can be continuously recorded, and these historical data form the basis for assessing changes in network quality. Then, for each new network quality assessment result uploaded by a vehicle, it can be compared with the last historical assessment result to calculate the change rate between the network quality assessment result and the historical network quality assessment result. The change rate calculation can be the proportion of individual parameter changes, or the change proportion after comprehensive evaluation of multiple parameters. Then, it can be checked whether the derived change rate exceeds the preset change rate. The setting of the preset change rate can take into account the natural fluctuations of the network signal and the demand for network stability in mine operations, and can be set in a reasonable range that can capture significant changes while ignoring daily minor fluctuations. If the change rate of the network quality assessment result is greater than the preset change rate, the aggregation process can be started, that is, the network quality assessment results of the affected vehicles are summarized to the grid where the vehicle is located, and the network quality monitoring results of the grid are updated. The aggregation process can include statistical methods such as weighted average and trend analysis to more accurately reflect the current state of network quality. After the aggregation process is completed, the updated grid network quality monitoring results can be displayed on the heat map to facilitate users to quickly locate the network problem area. If a sharp decline in network quality is detected, an alarm can be triggered to prompt immediate action, such as adjusting base station parameters, temporarily enabling a backup signal tower, and the like, to restore network service.

[0074] In the above process, the setting of the preset change rate can effectively filter the daily fluctuations of the network quality, avoid unnecessary alarms and adjustments, reduce the possibility of misjudgment, and improve the accuracy of monitoring. When the network quality changes abnormally, the aggregation process can be quickly started to update the network quality monitoring results in a timely manner, ensuring that users can intervene in time to avoid production interruptions or safety hazards caused by network problems.

[0075] In the embodiment of the present application, the method further comprises: obtaining a plurality of reported data, wherein the reported data comprises network quality information or vehicle location information; grouping the plurality of reported data based on the vehicle identification information carried in the plurality of reported data to obtain monitoring data.

[0076] The vehicle identification information described above can be data information that can uniquely identify each mine vehicle, and can include vehicle number and the like. The vehicle identification information can be uploaded together with the network quality information and the vehicle location information in the data reporting process to facilitate classification and tracking of the data.

[0077] In an alternative embodiment, the on-board terminals of each mine vehicle can periodically or under certain conditions report data to the data processing platform, which can include network quality information and vehicle location information. Vehicle identification information can also be sent along with the data to ensure clear attribution of the data. After receiving a large amount of reported data from different vehicles, the data processing platform can perform preliminary processing to separate the vehicle identification information, network quality information, and vehicle location information, which can include data cleaning, formatting, and integrity checking to ensure data quality. Then, the reported data can be grouped according to vehicle identification information, and each group of data can correspond to a specific mine vehicle. This grouping ensures that subsequent processing can be based on independent data streams for each vehicle to analyze network quality and location information, avoiding confusion between different vehicle data. For grouped vehicle data, the network quality and location changes of a specific vehicle can be tracked, and by comparing historical data, the stability of network quality can be evaluated to identify network problems or potential failures. This data processing method based on vehicle identification information provides technical support for individualized monitoring and services for vehicles.

[0078] In the above process, the use of vehicle identification information can ensure that reported data can be accurately assigned to the corresponding vehicle, improving the accuracy and reliability of data processing and avoiding the risk of misinterpreting data. When abnormal network quality information is detected from a vehicle, the precise location of the vehicle can be quickly located, facilitating user response, shortening fault processing time, and improving mine operation efficiency and safety. By analyzing the uploaded data of different vehicles separately, differences in vehicle network performance can be identified, providing individualized network improvement recommendations for each mine vehicle, such as adjusting vehicle travel routes to avoid network blind areas or improving base station configuration in specific areas to adapt to the task requirements of different vehicles.

[0079] The technical solutions proposed in this application are described below in conjunction with an alternative embodiment. This application proposes a mine network quality monitoring method based on geographic location. Based on real-time information reported by vehicles, mainly including location, network delay, and other network quality monitoring data, this application designs a network quality monitoring method based on geographic location, which can achieve network quality monitoring and evaluation of open-pit mine vehicle operation areas. The open-pit mine real-time network quality monitoring system realizes dynamic detection of regional device network quality; the open-pit mine real-time network quality monitoring system evaluates the network quality of a specific area based on geographic location; the open-pit mine real-time network quality monitoring and playback dynamically observe the time-series network quality dynamic changes in the mine area.

[0080] The system overall architecture of the application, the application mainly includes the vehicle-mounted data acquisition unit deployed on unmanned mine truck or manned vehicle terminal and the data processing platform deployed in the cloud. The data processing platform is mainly composed of four modules of data acquisition module, offline detection module, quality evaluation module and data analysis module.

[0081] The data flow and module design of the application, the vehicle-mounted data acquisition unit, is mainly responsible for collecting real-time data generated during vehicle operation, including network quality information and vehicle position information, wherein the network quality information includes network delay, signal strength, signal-to-noise ratio, service base station number, service sector number, etc. to the cloud server; the vehicle position information includes the longitude, latitude and elevation of the vehicle. After the vehicle-mounted data acquisition unit collects the above information, it adds the timestamp of data acquisition and sends it to the cloud data processing platform through the long connection of the web socket protocol at a predetermined frequency.

[0082] The data acquisition module is mainly responsible for receiving and preprocessing the network quality information and vehicle position information reported by the vehicle-mounted data acquisition unit, and grouping them according to the vehicle number and vehicle identification code to ensure the order of the data according to the vehicle. The data acquisition module must meet the high concurrency requirement to ensure the time sequence and non-loss of massive and high-frequency data.

[0083] The offline detection module can maintain a heartbeat timer for each vehicle, and update the vehicle heartbeat to a new state after receiving the vehicle real-time information. If a vehicle normal offline request is received, the vehicle state will be recorded as offline, and the heartbeat will not be updated until the vehicle is online again. If no vehicle offline request is received, and no vehicle real-time information is received for several seconds, it can be determined that the vehicle is abnormally offline due to network reasons, and the offline duration of the vehicle is recorded. After the vehicle real-time information passes through the offline detection module, the vehicle network quality information, position information and offline information are integrated and sent to the downstream quality evaluation module. Table 1 below is a selectable vehicle real-time information table:

[0084] Table 1 Selectable vehicle real-time information table

[0085]

[0086] The quality evaluation module is mainly responsible for integrating the vehicle network quality data sent by the upstream offline detection module, and calculating a network quality score (Network Quality Score, abbreviated as NQS) for each vehicle at a specific time sequence and a specific location. The network quality score can be calculated using a weighted aggregation model, and the score range can be set to 0-100, the lower the score, the worse the quality.

[0087] The calculation formula of NQS can be expressed as follows:

[0088] ;

[0089] The calculation formula of NQS (base) can be expressed as follows:

[0090] ;

[0091] Wherein, f(PING) is a delay score function, the higher the delay, the lower the score, inversely proportional relationship, w_1 is the weight of f(PING); f(RSSI) is a signal strength score function, the stronger the signal strength, the higher the score, proportional relationship, w_2 is the weight of f(RSSI); f(SNR) is a signal-to-noise ratio score function, the larger the signal-to-noise ratio, the higher the score, proportional relationship, w_3 is the weight of f(SNR).

[0092] NQS (penalty) can be calculated by using an exponential saturation function model with offline data:

[0093] ;

[0094] Wherein, NQS (penalty) is an offline time score, t is an offline time, the parameters a, b, c and d in the exponential saturation function model can be determined according to actual needs, a penalty mechanism can be used, once a vehicle is offline, the penalty mechanism takes effect, a negative score is calculated, the longer the offline time, the lower the negative value of the offline time score, inversely proportional relationship.

[0095] The data analysis module is mainly responsible for receiving the vehicle number, position and network quality score output by the quality evaluation module, performing geographic spatial aggregation, and generating a network quality geographic spatial distribution map. The aggregation algorithm can use a geographic coding algorithm to convert each vehicle data point, including latitude and longitude and network quality score, to a corresponding hexagonal grid, and use the network quality score as a weight to calculate the weighted average of each data point falling into the same grid.

[0096] ;

[0097] Wherein, The network quality evaluation result can be represented as The number of data points for weighted average calculation can be represented as

[0098] The visualization output can generate a heat map of the aggregation result, each grid and the corresponding aggregation score of each grid. Different colors and different shades can be used to represent different network quality, so as to intuitively identify the signal blind area, weak area and high-quality area in the mine.

[0099] Figure 2 is a schematic diagram of an optional network quality monitoring result display based on a heat map according to an embodiment of the present application, as shown in Figure 2As shown, the network quality evaluation results corresponding to the position information of different vehicles in the target area can be visually displayed in the heat map.

[0100] Firstly, the application can realize real-time monitoring of the network condition of a large-scale unmanned mine truck fleet in a smart mine, and realize real-time monitoring and early warning of high delay, offline and other abnormal states; secondly, based on the real-time positioning and network quality data of the unmanned mine truck and the manned vehicle equipped with a vehicle terminal, the network quality data collected from the base station is different, which is closer to the actual production operation area and can better reflect the actual production operation situation, so as to realize network quality monitoring of the production operation area in the smart mine, find the area not covered by the network and the area with poor network quality, and make timely early warning; in addition, based on the historical network quality change in the smart mine area, the influencing factors of network quality change can be efficiently analyzed, such as terrain, slope change, equipment influence, base station coverage distance, etc., and corresponding measures can be taken to ensure network quality and production safety.

[0101] Figure 3 is a schematic diagram of a network quality monitoring system according to an embodiment of the application, as shown, the system comprises the following: at least one vehicle data acquisition unit 302 and a data processing platform 304. Figure 3

[0102] Among them, at least one vehicle data acquisition unit 302 is respectively arranged on at least one vehicle, and is used for acquiring monitoring data of the corresponding vehicle, wherein the monitoring data at least includes network quality information and vehicle position information, at least one vehicle is a vehicle located in a target area, and the monitoring data is data generated during the operation of the corresponding vehicle; the data processing platform 304 is used for determining a network quality evaluation result corresponding to the vehicle based on at least the network quality information corresponding to any one vehicle, and performing aggregation processing on the network quality evaluation result corresponding to at least one vehicle based on the vehicle position information corresponding to at least one vehicle, to obtain a network quality monitoring result corresponding to the target area, wherein the network quality monitoring result is used to represent the distribution information of the network quality in the target area.

[0103] ​In the embodiments of the present application, the data processing platform comprises: an offline detection module configured to detect whether at least one vehicle is in an offline state; a quality evaluation module configured to, in response to detecting that any one vehicle is in an online state, determine a network quality evaluation result corresponding to the vehicle based on network quality information corresponding to the vehicle; or, in response to detecting that any one vehicle is in an offline state, determine a network quality evaluation result corresponding to the vehicle according to historical network quality information and offline information of the vehicle before the vehicle goes offline; and a data analysis module configured to aggregate the network quality evaluation result corresponding to at least one vehicle based on vehicle location information corresponding to the at least one vehicle, to obtain a network quality monitoring result corresponding to a target area; preferably, the network quality evaluation result corresponding to the vehicle is determined according to the historical network quality information and the offline information of the vehicle, which comprises: performing weighted processing on the historical network quality information and the offline information to obtain the network quality evaluation result corresponding to the vehicle.

[0104] The embodiments of the present application also provide an electronic device, comprising: a memory storing an executable program; and a processor configured to run the program, wherein the program is configured to execute the method in the embodiments of the present application when running.

[0105] The memory described above can refer to a device inside a computer for storing data and programs, and can include a memory, a hard disk, etc., wherein the memory can be used for temporarily storing programs and data being run, the hard disk can be used for long-term storage of programs and data, the memory can be used for enabling the computer to read and write data and execute programs; the processor described above can be responsible for executing instructions in a computer program and processing data, and can be responsible for controlling and executing various operations, including arithmetic operations, logical operations, data transmission, etc.

[0106] The embodiments of the present application also provide a computer readable storage medium, which comprises a stored executable program, wherein the executable program is configured to control a device where the computer readable storage medium is located to execute the method in the embodiments of the present application when running.

[0107] The computer storage medium described above can refer to a medium in a computer memory for storing certain discontinuous physical quantities, and the computer storage medium mainly includes semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser discs, etc.; the stored program included in the computer readable storage medium can be a set of instructions that can be recognized and executed by a computer, and can be an information tool running on an electronic computer and meeting certain needs of people.

[0108] The embodiments of the present application also provide a computer program product, comprising a computer program, wherein the computer program is configured to implement the method in the embodiments of the present application when executed by a processor.

[0109] The computer program product described above can refer to a software program that is written, tested and released, and can run on a computer or other device. The computer program product can include application programs, operating systems, tool software, etc., for implementing specific functions or solving specific problems.

[0110] Embodiments of the present application also provide a computer program product comprising a non-volatile computer readable storage medium for storing a computer program which, when executed by a processor, implements the method of any of the embodiments of the present application.

[0111] The non-volatile computer readable storage medium described above can refer to a medium for storing data, which can retain data without loss when power is off, and can be used to store long-term data such as operating systems, application programs and user files. Non-volatile storage media can include hard drives, solid state drives, optical discs and flash memory devices.

[0112] Embodiments of the present application also provide a computer program which, when executed by a processor, implements the method of any of the embodiments of the present application.

[0113] The computer program described above can refer to a set of instructions for telling a computer to perform a specific task or operation. The computer program can be written by a programmer using a specific programming language, and can include algorithms, data structures, logic and control flow, etc. The computer program can be used for various purposes, including application software, operating systems, etc.

[0114] In the above embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0115] In the several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other means. Among them, the device embodiments described above are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0116] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0117] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0118] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to make a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0119] The above is only the preferred embodiment of the present application, it should be noted that for those skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A network quality monitoring method, characterized in that, include: Acquire monitoring data corresponding to at least one vehicle, wherein the monitoring data includes at least: network quality information and vehicle location information, the at least one vehicle is a vehicle located within the target area, and the monitoring data is data generated by the corresponding vehicle during operation; The network quality assessment result for the vehicle is determined based on at least the network quality information corresponding to any one vehicle. Based on the vehicle location information corresponding to the at least one vehicle, the network quality assessment results corresponding to the at least one vehicle are aggregated to obtain the network quality monitoring results corresponding to the target area, wherein the network quality monitoring results are used to characterize the distribution information of network quality within the target area.

2. The method according to claim 1, characterized in that, The monitoring data also includes: offline information of the vehicle, and the determination of the network quality assessment result corresponding to the vehicle based on the network quality information corresponding to at least any one vehicle includes: In response to any vehicle being online, determine the network quality assessment result for that vehicle based on its corresponding network quality information; or... In response to any vehicle being offline, the network quality assessment result corresponding to the vehicle is determined based on the historical network quality information of the vehicle before it went offline and the offline information. Preferably, determining the network quality assessment result corresponding to the vehicle based on the historical network quality information before the vehicle went offline and the offline information includes: weighting the historical network quality information and the offline information to obtain the network quality assessment result corresponding to the vehicle.

3. The method according to claim 2, characterized in that, The offline information is obtained by: determining the cumulative duration of the vehicle's continuous offline status; and calculating the offline information based on the cumulative duration of the vehicle's continuous offline status.

4. The method according to claim 2 or 3, characterized in that, The step of determining the network quality assessment result corresponding to the vehicle based on the vehicle's historical network quality information before it went offline and the offline information includes: Based on the historical network quality information, an initial evaluation result is generated; Based on the cumulative duration of the vehicle being continuously offline, a degradation assessment result is generated; Based on the initial evaluation results and the attenuation evaluation results, the network quality evaluation results are generated; Preferably, generating an attenuation assessment result based on the accumulated duration includes: obtaining the difference between the accumulated duration and a preset offline duration to obtain a duration difference; generating an initial attenuation result based on the duration difference; and obtaining the difference between the initial attenuation result and a preset value to obtain the attenuation assessment result.

5. The method according to claim 4, characterized in that, The historical network quality information includes at least two types of information: latency, signal strength, and signal-to-noise ratio; the generation of initial evaluation results based on the historical network quality information includes: The historical network quality assessment result is obtained by weighting at least two types of information collected at the most recent time point before the vehicle enters offline state. Preferably, the first weight value corresponding to the time delay, the second weight value corresponding to the signal strength, and / or the third weight value corresponding to the signal-to-noise ratio are determined based on the region type corresponding to the target region or the task type corresponding to the vehicle.

6. The method according to any one of claims 1 to 5, characterized in that, The process of aggregating the network quality assessment results corresponding to at least one vehicle based on the vehicle location information of the at least one vehicle to obtain the network quality monitoring results corresponding to the target area includes: The target area is divided into multiple grids; Based on any vehicle location information, a target grid corresponding to the vehicle location information is determined from the plurality of grids, wherein the vehicle location information is located within the target grid; For any one of the plurality of grids, the network quality assessment result corresponding to at least one target vehicle is processed to obtain the sub-monitoring result corresponding to the grid, wherein the vehicle location information corresponding to the target vehicle is located within the grid; The network quality monitoring results are obtained based on the sub-monitoring results corresponding to the multiple grids; Preferably, the grid shape and / or grid size of the plurality of grids are determined based on the operation scenario corresponding to the target area, the terrain of the target area, and / or the size information of the target area; Preferably, for any one of the plurality of grids, processing the network quality assessment result corresponding to at least one target vehicle to obtain the sub-monitoring result corresponding to the grid includes: for any one of the plurality of grids, performing a weighted average processing on the network quality assessment results falling within the range of that grid area to obtain the sub-monitoring result corresponding to that grid.

7. The method according to claim 6, characterized in that, The method further includes: Based on the sub-monitoring results corresponding to the multiple grids, the display method corresponding to the multiple grids is determined; The network quality monitoring results are displayed according to the display method corresponding to the multiple grids; Preferably, a network quality adjustment strategy is determined based on the network quality monitoring results, wherein the network quality adjustment strategy includes a base station adjustment strategy within the target area; or, Preferably, the method further includes: identifying faults in the vehicle based on multiple network quality monitoring results at different times; or, Preferably, the network quality monitoring results are displayed according to the display method corresponding to the multiple grids, including: displaying the network quality monitoring results based on the heat map shape.

8. The method according to claim 6, characterized in that, The method further includes: Based on the sub-monitoring results corresponding to the multiple grids, the network quality layer region corresponding to the target area in the map data is updated to obtain the updated map data. The updated map data is sent to other vehicles; Preferably, the other vehicles are used for route planning using the updated map data.

9. The method according to any one of claims 1 to 8, characterized in that, The aggregation process of network quality assessment results corresponding to at least one vehicle based on the vehicle location information of the at least one vehicle includes: In response to the rate of change between the network quality assessment result and the historical network quality assessment result being greater than a preset rate of change, the network quality assessment results corresponding to the at least one vehicle are aggregated based on the vehicle location information corresponding to the at least one vehicle to obtain the network quality monitoring result corresponding to the target area.

10. A network quality monitoring system, characterized in that, include: At least one vehicle-mounted data acquisition unit is deployed on at least one vehicle to collect monitoring data of the corresponding vehicle. The monitoring data includes at least network quality information and vehicle location information. The at least one vehicle is located within the target area, and the monitoring data is data generated by the corresponding vehicle during operation. A data processing platform is used to determine the network quality assessment result corresponding to at least one vehicle based on the network quality information corresponding to any one vehicle; and to aggregate the network quality assessment results corresponding to at least one vehicle based on the vehicle location information corresponding to the at least one vehicle to obtain the network quality monitoring result corresponding to the target area, wherein the network quality monitoring result is used to characterize the distribution information of network quality within the target area.

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