Parking lot wireless communication scene identification method and system, and electronic equipment

Abstract

The invention discloses a method and a system for identifying a wireless communication scene of a parking lot, and electronic equipment. The method comprises the following steps: acquiring a measurement report data set of a vehicle-mounted terminal user; based on latitude and longitude information in the measurement report data set, performing position mapping on all records in the measurement report data set, and determining a grid corresponding to each record; according to the record sequence of the user identifier with continuous timestamps in the same grid, calculating the stay duration of the vehicle-mounted terminal user corresponding to the user identifier in the grid to which the vehicle-mounted terminal user belongs; based on a preset day time period, a night time period and a staying time threshold value, judging the staying time data of each grid; performing spatial convergence processing on the candidate parking lot grids with continuous spatial positions to form a continuous area; and when the number of the grids exceeds a preset number threshold value, marking the contiguous areas as parking lot areas. According to the method, the parking lot wireless communication scene bearing the vehicle communication behavior can be automatically and accurately identified from the current network big data of the operator.

Description

Technical Field

[0001] This invention relates to the field of network communication technology, and in particular to a method, system and electronic device for identifying wireless communication scenarios in parking lots. Background Technology

[0002] With the rapid development of new energy vehicles and vehicle-to-everything (V2X) technology, vehicles have become deeply integrated into mobile communication networks, serving as key terminals reliant on cellular networks such as 4G-LTE and 5G. The normal operation of core services such as remote control, OTA software upgrades, emergency calls, and automatic parking heavily depends on stable and continuous wireless signal coverage. However, in actual network operation, parking lots, as a crucial scenario for high-frequency and long-term vehicle stays, generally suffer from weak signal coverage and even communication blind spots.

[0003] The root of this problem lies in the physical characteristics of parking lots: they are mostly constructed of reinforced concrete, which has a strong shielding effect on wireless signals; underground parking lots are far from ground-based macro base stations, resulting in significant path loss; at the same time, the densely parked metal vehicles can also cause multipath interference and signal attenuation, further reducing communication quality. To address these challenges, operators typically need to customize indoor distribution systems, micro base stations, pico base stations, or repeaters for different parking lots, forming a complex "one-stop-shop" coverage pattern.

[0004] However, the prerequisite for achieving precise network optimization is the ability to accurately identify the "parking lot wireless communication scenarios" that actually carry vehicle communication behavior from a vast geographical area. In current practice, this identification faces severe challenges: manual surveys are inefficient and data updates are lagging; parking lot information in electronic maps lacks communication dimension attributes and is difficult to distinguish between surface and underground types; and evaluation methods based on main station coverage strength or indoor signal source ledgers only reflect network-side configuration and cannot reflect the actual terminal dwell status and real user experience.

[0005] In summary, existing technologies cannot achieve automatic and accurate identification of parking lot wireless communication scenarios based on the actual communication behavior of vehicle terminals, making it difficult to meet the needs of refined network operation and maintenance in the era of vehicle networking. Summary of the Invention

[0006] The technical problem this invention aims to solve is to address the aforementioned shortcomings of existing technologies by proposing a method, system, and electronic device for identifying wireless communication scenarios in parking lots. This method can automatically and accurately identify parking lot wireless communication scenarios that actually carry vehicle communication behavior from the operator's existing network big data, thus meeting the needs of refined network operation and maintenance in the era of the Internet of Vehicles.

[0007] In a first aspect, the present invention provides a method for identifying wireless communication scenarios in parking lots, the method comprising the following steps:

[0008] Obtain the measurement report dataset of the vehicle terminal user. Each record in the measurement report dataset includes the user identifier, timestamp, and latitude and longitude information.

[0009] Based on latitude and longitude information, all records in the measurement report dataset are mapped to preset geographic rasters to determine the raster to which each record belongs;

[0010] For each user identifier, the dwell time of the vehicle terminal user corresponding to the user identifier in the grid is calculated based on the record sequence with consecutive timestamps within the same grid.

[0011] Based on preset daytime hours and daytime stay duration thresholds, as well as preset nighttime hours and nighttime stay duration thresholds, the stay duration data of each grid is determined;

[0012] Specifically, grids whose daytime stay exceeds the daytime stay threshold are identified as candidate parking grids, or grids whose nighttime stay exceeds the nighttime stay threshold are identified as candidate parking grids.

[0013] Spatial convergence processing is performed on candidate parking grids that are spatially continuous to form contiguous areas;

[0014] Count the number of grid cells contained in a contiguous area;

[0015] When the number of grids exceeds a preset threshold, the contiguous area is marked as a parking area to complete the identification of the parking lot wireless communication scenario.

[0016] Furthermore, before acquiring the measurement report dataset of the vehicle terminal users, the method also includes: identifying the vehicle terminal users;

[0017] Identifying vehicle terminal users specifically includes:

[0018] Obtain the identification information set of the vehicle terminal, which includes a set of terminal device type codes for representing vehicle hardware devices and access point name information for identifying vehicle data services;

[0019] From the core network signaling data, the International Mobile Equipment Identity (IMI), the International Mobile Subscriber Identity (IMS), and the service access point name corresponding to each IMS are extracted;

[0020] The International Mobile Equipment Identity (IMI) is matched with the set of terminal equipment type codes. If a match is found, the corresponding IMI is used as the first matching result. At the same time, the service access point name recorded in the signaling data is matched with the access point name information. If a match is found, the corresponding IMI is used as the second matching result.

[0021] Users of in-vehicle terminals who have a first matching result and / or a second matching result are identified as in-vehicle terminal users.

[0022] Furthermore, spatially contiguous candidate parking grids are spatially converged to form contiguous areas, specifically including:

[0023] Traverse all candidate parking grids and determine and establish spatial adjacency relationships between grids based on the four-neighbor connectivity algorithm or the eight-neighbor connectivity algorithm.

[0024] Based on spatial adjacency, candidate parking lots that are connected to each other are clustered and merged.

[0025] Each independent region formed after merging is assigned a unique identifier, and all raster information included in the independent region is recorded to complete the construction of contiguous regions.

[0026] Furthermore, for each user identifier, based on the record sequence with consecutive timestamps within the same grid, the dwell time of the vehicle terminal user corresponding to the user identifier within that grid is calculated, specifically including:

[0027] A sliding time window algorithm is used to determine the continuity of the recording sequence, and a maximum time interval threshold is set.

[0028] Iterate through all records with the same user ID within the same grid, sort the records by timestamp, and then check the time interval between adjacent records in turn.

[0029] When the timestamp interval between two adjacent records does not exceed the maximum time interval threshold, it is determined that the user is staying continuously, and the corresponding time interval is included in the stay duration.

[0030] When the timestamp interval between adjacent records exceeds the maximum time interval threshold, it is determined that the user's stay is interrupted, and the accumulation of the current continuous duration is stopped;

[0031] The total dwell time of a user ID within a grid is obtained by summing the time spent in all consecutive periods within the same grid.

[0032] Furthermore, the measurement report dataset of the vehicle terminal user is obtained, specifically including:

[0033] The initial measurement report is collected from the wireless network management system; the initial measurement report carries the user's temporary identifier.

[0034] Based on core network signaling data, a mapping relationship between user temporary identifiers and International Mobile Subscriber Identity (IMSI) is constructed; and by combining base station engineering parameters and wireless signal measurement values, the latitude and longitude information of vehicle terminal users is estimated.

[0035] For each initial measurement record, the International Mobile Subscriber Identity (IMSI) corresponding to the initial measurement report record is determined using the mapping relationship, and the IMSI and the estimated latitude and longitude information are then filled back into the initial measurement report record.

[0036] Integrate the backfilled data to generate a measurement report dataset containing complete user identifiers, timestamps, and latitude and longitude information.

[0037] Furthermore, after marking contiguous areas as parking areas, the method also includes:

[0038] Obtain data on underground space areas;

[0039] Obtain underground space data tables containing latitude and longitude information of the centers of various underground space scenes;

[0040] Spatial association and matching are performed between the parking area and the underground space data table;

[0041] Specifically, if the center latitude and longitude of an underground space in the underground space data table is located within the parking area, the parking area will be marked as an underground parking lot; if the center latitude and longitude of any underground space in the underground space data table is not located within the parking area, the parking area will be marked as a surface parking lot.

[0042] Secondly, the present invention provides a parking lot wireless communication scene identification system, the system comprising:

[0043] The acquisition module is used to acquire the measurement report dataset of the vehicle terminal user. Each record in the measurement report dataset includes the user identifier, timestamp, and latitude and longitude information.

[0044] The mapping module, connected to the acquisition module, is used to map all records to preset geographic rasters based on latitude and longitude information, and to determine the raster to which each record belongs.

[0045] The calculation module, connected to the mapping module, is used to calculate the dwell time of the vehicle terminal user corresponding to each user identifier in the grid based on the record sequence with consecutive timestamps in the same grid.

[0046] The identification module, connected to the calculation module, is used to identify grids whose daytime stay exceeds the daytime stay threshold as candidate parking grids, or to identify grids whose nighttime stay exceeds the nighttime stay threshold as candidate parking grids, based on preset daytime time periods and daytime stay duration thresholds, as well as preset nighttime time periods and nighttime stay duration thresholds.

[0047] The first processing module, connected to the recognition module, is used to perform spatial convergence processing on candidate parking grids with continuous spatial locations to form contiguous areas;

[0048] The second processing module, connected to the first processing module, is used to count the number of grids contained in the contiguous area, and when the number of grids exceeds a preset threshold, the contiguous area is marked as a parking area to complete the identification of the parking lot wireless communication scenario.

[0049] Furthermore, the system also includes a determination module for identifying the vehicle-mounted terminal;

[0050] The connection between the determination module and the acquisition module specifically includes:

[0051] The first acquisition submodule is used to acquire the identification information set of the vehicle terminal. The identification information set includes a set of terminal device type codes for representing vehicle hardware devices and access point name information for identifying vehicle data services.

[0052] The parsing submodule, connected to the first acquisition submodule, is used to parse the International Mobile Equipment Identity (IMI), International Mobile Subscriber Identity (IMS), and the Service Access Point Name corresponding to each IMS in the core network signaling data.

[0053] The first matching submodule, connected to the parsing submodule, is used to match the International Mobile Equipment Identity (IMI) code with the set of terminal equipment type codes. If the match is successful, the corresponding IMI code is used as the first matching result. At the same time, the service access point name recorded in the signaling data is matched with the access point name information. If the match is successful, the corresponding IMI code is used as the second matching result.

[0054] The determination submodule, connected to the first matching submodule, is used to determine the users of the vehicle terminal who have the first matching result and / or the second matching result as vehicle terminal users.

[0055] Furthermore, the system also includes a marking module, which is connected to the second processing module and is used to mark the type of parking lot;

[0056] The tagging module includes:

[0057] The second acquisition submodule is used to acquire underground space area data; it is also used to acquire underground space data tables containing latitude and longitude information of the center of each underground space scene.

[0058] The second matching submodule, connected to the second acquisition submodule, is used to spatially associate and match the parking area with the underground space data table.

[0059] The marking submodule, connected to the second matching submodule, is used to mark the parking lot based on the matching result of the second matching submodule;

[0060] Specifically, if the center latitude and longitude of an underground space in the underground space data table is located within the parking area, the marking submodule will mark the parking area as an underground parking lot; if the center latitude and longitude of any underground space in the underground space data table is not located within the parking area, the marking submodule will mark the parking area as a surface parking lot.

[0061] Thirdly, the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the parking lot wireless communication scenario identification method according to the first aspect.

[0062] This invention constructs a spatiotemporal dwell behavior model based on real wireless measurement report data from vehicle-mounted terminals, and combines day / night differentiated thresholds with spatial connectivity clustering analysis. This enables the automatic and accurate identification of parking lot wireless communication scenarios that actually carry vehicle communication behavior from the operator's existing network big data. Specific beneficial effects are as follows:

[0063] (1) Achieve dedicated scene recognition for vehicle-to-everything (V2X) users:

[0064] This invention focuses on measurement report data from in-vehicle terminal users, avoiding the analytical bias of traditional mobile phone user-centric approaches. It can accurately reflect the vehicle's dwell behavior and communication status in parking lots, solving the problem of "inconsistency between vehicle and human perception".

[0065] (2) Accurately characterize parking behavior and reduce misjudgment rate:

[0066] By differentiating between daytime commuter parking and nighttime residential parking scenarios and setting time and duration thresholds for each, interference from short stops in commercial areas and road congestion is effectively eliminated, significantly improving the accuracy of candidate parking lot grid recognition.

[0067] (3) Enhance the robustness of results by utilizing geographic rasterization and spatial convergence:

[0068] By mapping discrete user dwell points to a unified geographic grid and aggregating the connectivity of adjacent candidate grids, a structured contiguous area is formed, effectively suppressing the interference of isolated noise points and generating parking areas with clear boundaries and reasonable shapes.

[0069] (4) Full-domain automated recognition without manual intervention:

[0070] Relying entirely on the operator's existing MR and signaling data, without the need for manual surveys, road tests, or additional sensor deployments, it can achieve dynamic discovery and continuous updates of city-level parking scenarios, significantly reducing operation and maintenance costs.

[0071] (5) Provide precise target areas for network optimization:

[0072] The identified parking areas are directly related to real vehicle communication behavior and can serve as the core input for network optimization work such as indoor distribution construction, micro-site deployment, and parameter tuning. This supports the formulation of refined coverage solutions based on the principle of "one parking area, one policy" and effectively improves the business experience of vehicle-to-everything (V2X) users in parking lots.

[0073] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0074] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. The above and other features and advantages will become more apparent to those skilled in the art from the detailed description of exemplary embodiments with reference to the accompanying drawings, in which:

[0075] Figure 1 A schematic diagram of a parking lot wireless communication scenario identification method provided in an embodiment of the present invention;

[0076] Figure 2 A schematic diagram of a parking lot wireless communication scenario identification system provided in an embodiment of the present invention;

[0077] Figure 3 This is an architectural diagram of an electronic device provided in an embodiment of the present invention.

[0078] Reference numerals: 10, acquisition module; 20, mapping module; 30, calculation module; 40, identification module; 50, first processing module; 60, second processing module; 100, processor; 200, memory. Detailed Implementation

[0079] It is understood that the specific embodiments and accompanying drawings described herein are merely for explaining the invention and are not intended to limit the invention.

[0080] It is understood that, without conflict, the various embodiments and features in the embodiments of the present invention can be combined with each other.

[0081] It is understood that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, while the parts unrelated to the present invention are not shown in the drawings.

[0082] It is understood that each unit or module involved in the embodiments of the present invention may correspond to only one entity structure, or may be composed of multiple entity structures, or multiple units or modules may be integrated into one entity structure.

[0083] It is understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of this invention may occur in a different order than that marked in the accompanying drawings.

[0084] It is understood that the flowcharts and block diagrams of this invention illustrate the possible architecture, functions, and operations of systems, apparatuses, devices, and methods according to various embodiments of this invention. Each block in the flowchart or block diagram may represent a unit, module, program segment, or code, containing executable instructions for implementing the specified function. Furthermore, each block or combination of blocks in the block diagram and flowchart can be implemented using a hardware-based system to achieve the specified function, or using a combination of hardware and computer instructions.

[0085] It is understood that the units and modules involved in the embodiments of the present invention can be implemented by software or by hardware. For example, the units and modules can be located in a processor.

[0086] Example 1:

[0087] With the rapid development of new energy vehicles and vehicle-to-everything (V2X) networks, vehicles heavily rely on 4G / 5G networks for critical services such as remote control, OTA upgrades, and emergency calls, placing higher demands on the continuity and stability of wireless signal coverage. However, parking lots, as typical scenarios where vehicles reside frequently and for extended periods, often suffer from weak signal coverage or even communication interruptions due to factors such as shielding by reinforced concrete structures, attenuation from underground depths, and interference from metal vehicle bodies. To improve coverage quality, operators need to customize indoor distribution systems and micro-sites for different parking lots, forming a complex "one-stop-one-policy" operation and maintenance model. However, accurate optimization requires accurately identifying the "parking lot wireless communication scenario" that actually carries vehicle communication behavior. Existing methods mainly rely on manual surveys, static maps, or main station coverage assessments, which are not only inefficient and slow to update, but also fail to reflect the actual dwelling behavior and communication experience of vehicle terminals—especially due to the differences in radio frequency characteristics between vehicle-mounted systems and mobile phones, traditional analysis based on mobile phone data is difficult to apply to V2X scenarios. Therefore, a technological means is urgently needed to automatically and accurately identify parking lot areas based on the actual communication behavior of vehicle terminals. This embodiment provides a method for identifying wireless communication scenarios in parking lots. By fusing measurement reports and signaling data from the operator's existing network, it extracts the location and dwell characteristics of vehicle users. Combining day / night difference thresholds and spatial connectivity clustering, it automatically identifies contiguous areas that match real parking behavior. This method requires no manual intervention and can provide high-precision, dynamic scene labels for network optimization, indoor distribution system construction, high-precision map updates, and smart city management, effectively supporting high-quality communication for vehicle-to-everything (V2X) services in complex and enclosed environments.

[0088] like Figure 1As shown in the figure, this embodiment provides a method for identifying wireless communication scenarios in parking lots, which includes the following steps S1 to S6.

[0089] Step S1: Obtain the measurement report dataset of the vehicle terminal user. Each record in the measurement report dataset includes the user identifier, timestamp, and latitude and longitude information.

[0090] As a specific implementation method, before obtaining the measurement report dataset of the vehicle terminal user, the method further includes: determining the vehicle terminal user;

[0091] Identifying vehicle terminal users specifically includes:

[0092] Obtain the identification information set of the vehicle terminal, which includes a set of terminal device type codes for representing vehicle hardware devices and access point name information for identifying vehicle data services;

[0093] From the core network signaling data, the International Mobile Equipment Identity (IMI), the International Mobile Subscriber Identity (IMS), and the service access point name corresponding to each IMS are extracted;

[0094] The International Mobile Equipment Identity (IMI) is matched with the set of terminal equipment type codes. If a match is found, the corresponding IMI is used as the first matching result. At the same time, the service access point name recorded in the signaling data is matched with the access point name information. If a match is found, the corresponding IMI is used as the second matching result.

[0095] Users of in-vehicle terminals who have a first matching result and / or a second matching result are identified as in-vehicle terminal users.

[0096] As a specific implementation method, acquiring the measurement report dataset of the vehicle terminal user includes:

[0097] The initial measurement report is collected from the wireless network management system; the initial measurement report carries the user's temporary identifier.

[0098] Based on core network signaling data, a mapping relationship between user temporary identifiers and International Mobile Subscriber Identity (IMSI) is constructed; and by combining base station engineering parameters and wireless signal measurement values, the latitude and longitude information of vehicle terminal users is estimated.

[0099] For each initial measurement record, the International Mobile Subscriber Identity (IMSI) corresponding to the initial measurement report record is determined using the mapping relationship, and the IMSI and the estimated latitude and longitude information are then filled back into the initial measurement report record.

[0100] Integrate the backfilled data to generate a measurement report dataset containing complete user identifiers, timestamps, and latitude and longitude information.

[0101] Step S2: Based on latitude and longitude information, map all records in the measurement report dataset to preset geographic rasters and determine the raster corresponding to each record.

[0102] Step S3: For each user identifier, calculate the dwell time of the vehicle terminal user corresponding to the user identifier in the grid based on the record sequence with consecutive timestamps within the same grid.

[0103] As a specific implementation method, for each user identifier, based on the record sequence with consecutive timestamps within the same grid, the dwell time of the vehicle terminal user corresponding to the user identifier within that grid is calculated, specifically including:

[0104] A sliding time window algorithm is used to determine the continuity of the recording sequence, and a maximum time interval threshold is set.

[0105] Iterate through all records with the same user ID within the same grid, sort the records by timestamp, and then check the time interval between adjacent records in turn.

[0106] When the timestamp interval between two adjacent records does not exceed the maximum time interval threshold, it is determined that the user is staying continuously, and the corresponding time interval is included in the stay duration.

[0107] When the timestamp interval between adjacent records exceeds the maximum time interval threshold, it is determined that the user's stay is interrupted, and the accumulation of the current continuous duration is stopped;

[0108] The total dwell time of a user ID within a grid is obtained by summing the time spent in all consecutive periods within the same grid.

[0109] Step S4: Based on preset daytime time periods and daytime stay duration thresholds, as well as preset nighttime time periods and nighttime stay duration thresholds, determine the stay duration data for each grid. Identify grids with daytime stay durations exceeding the daytime stay duration threshold as candidate parking grids, or identify grids with nighttime stay durations exceeding the nighttime stay duration threshold as candidate parking grids.

[0110] Step S5: Spatial convergence processing is performed on candidate parking grids with continuous spatial locations to form contiguous areas.

[0111] As a specific implementation method, spatial convergence processing is performed on candidate parking grids with continuous spatial locations to form contiguous areas, specifically including:

[0112] Traverse all candidate parking grids and determine and establish spatial adjacency relationships between grids based on the four-neighbor connectivity algorithm or the eight-neighbor connectivity algorithm.

[0113] Based on spatial adjacency, candidate parking lots that are connected to each other are clustered and merged.

[0114] Each independent region formed after merging is assigned a unique identifier, and all raster information included in the independent region is recorded to complete the construction of contiguous regions.

[0115] Step S6: Count the number of grids contained in the contiguous area; when the number of grids exceeds a preset threshold, the contiguous area is marked as a parking lot area to complete the identification of the parking lot wireless communication scenario.

[0116] As a specific implementation method, after marking the contiguous area as a parking area, the method further includes:

[0117] Obtain data on underground space areas;

[0118] Obtain underground space data tables containing latitude and longitude information of the centers of various underground space scenes;

[0119] Spatial association and matching are performed between the parking area and the underground space data table;

[0120] Specifically, if the center latitude and longitude of an underground space in the underground space data table is located within the parking area, the parking area will be marked as an underground parking lot; if the center latitude and longitude of any underground space in the underground space data table is not located within the parking area, the parking area will be marked as a surface parking lot.

[0121] The technical principle of this embodiment is based on in-depth analysis and utilization of typical vehicle parking behavior in parking lot scenarios. As a concentrated area for vehicle parking, the core characteristic of parking lots is that vehicles tend to remain stationary or parked for extended periods. This characteristic exhibits differentiated patterns in different types of parking lots: for example, parking lots in public places such as commercial and office areas see a large number of vehicles gathering during the daytime due to shopping, work, and other activities, resulting in long-term parking; while parking lots in residential areas and communities show a similar high-density, long-term parking characteristic at night as vehicles return to their parking spaces. At the technical implementation level, this solution fully utilizes the existing network data governance system of telecommunications operators. To conduct accurate network quality monitoring and optimization, operators typically divide coverage areas into uniformly sized geographical grids (such as standard sizes like 50m x 50m or 100m x 100m), thereby achieving standardized management of spatial areas. When a vehicle enters the parking lot and completes its parking, its onboard terminal connects to the operator's wireless network and maintains a connection with one or more adjacent communication cells for a subsequent period. Since parking lots typically have limited coverage, the signals from these cells often project onto the same or adjacent limited geographical grids, thus providing a basis for location-based behavior analysis. The core discrimination mechanism of this method uses the duration of a vehicle's continuous stay within the same grid as a key indicator to assess the credibility of that grid as a parking scenario. Specifically, a stay duration threshold of X hours is set for daytime periods (e.g., 9:00 to 17:00), and a stay duration threshold of Y hours is set for nighttime periods (e.g., 18:00 to 6:00 the next day). If a vehicle's stay duration within a grid exceeds the corresponding time-period threshold, the grid is initially identified as a suspected parking scenario. To further improve identification accuracy, this scheme introduces multi-dimensional auxiliary judgment conditions. In terms of spatial scale, suspected grids must reach a certain area size to exclude small-scale interference such as temporary parking spaces; in terms of vehicle size, the number of independent vehicles meeting the stay duration conditions within the same time period must exceed a set threshold of S vehicles to ensure that the behavior pattern is universal rather than an isolated phenomenon. The candidate grids selected based on the above criteria are then aggregated through spatial clustering analysis to generate a precise parking area outline. Through this technical approach, this embodiment systematically establishes a parking scene information database, providing crucial scenario-based data support for tracing complaints from connected vehicle users, assessing network perception, predicting potential problems, and precisely optimizing wireless networks. This effectively improves the targeting of network optimization and the accuracy of business assurance.

[0122] For example, this embodiment, based on the aforementioned technical principles, achieves accurate identification of parking lot scenarios by comprehensively utilizing multi-source data from the operator's mobile network. The specific implementation process involves the collaborative analysis of multiple data sources, including S1-MME interface signaling from the 4G network, N1 / N2 interface signaling from the 5G network, cell engineering parameters, cell-level and user-level measurement report data, and underground space information tables. The following is a detailed description of the specific implementation method:

[0123] (1) Obtain vehicle terminal feature identifiers. In an exemplary implementation, the set of device type codes (TAC) of terminal modules from mainstream vehicle manufacturers can be collected, or the access point name (APN) configuration information used by vehicle-specific services can be collected.

[0124] (2) Identify vehicle terminal users. Collect signaling data streams from interfaces such as S1-MME and N1 / N2 in real time from the operator's core network interface, and parse the International Mobile Equipment Identity (IMEI) and its associated International Mobile Subscriber Identity (IMSI). Mark the IMSI whose first 8 digits of IMEI match the vehicle terminal's TAC number set, or the IMSI whose service APN matches the vehicle's APN information, as the vehicle terminal user group.

[0125] (3) Process user-level measurement report data. Collect the MR records actually reported by users from the wireless network management system, and use signal processing algorithms to realize the correlation and backfilling of user IMSI and latitude and longitude information to generate an enhanced MR dataset containing complete user identification and accurate location information.

[0126] (4) Screening of vehicle terminal-related records. Based on the aforementioned identification results, measurement report records corresponding to vehicle terminal users are extracted from the full MR data, effectively filtering out interference data from non-vehicle terminals.

[0127] (5) Implement geolocation raster mapping. For each vehicle terminal user's MR record, spatial matching is performed according to its latitude and longitude coordinates, using a standard 50m × 50m square raster, and corresponding raster identification information is added to each record.

[0128] (6) Calculate the dwell time at the grid level. Sort the rasterized MR records according to the time series and user identifier. By analyzing the record sequence of consecutive timestamps, accurately calculate the cumulative dwell time of each vehicle terminal in each grid.

[0129] (7) Identify suspected parking grids. Set time thresholds for daytime periods (e.g., 09:00-17:00) and nighttime periods (e.g., 18:00-06:00 the next day). When the dwell time of a vehicle in a grid meets the condition of more than X hours during the day or more than Y hours at night, mark the grid as a suspected parking grid and record the geographic coordinates of its center point to form a set of candidate grids.

[0130] (8) Determine the parking area. Perform connectivity analysis on the spatially distributed candidate grids. When the number of consecutive grids exceeds the preset threshold S, the contiguous area is officially marked as a parking area.

[0131] (9) Differentiate the spatial attributes of parking lots. Based on the urban underground space database, perform spatial correlation analysis between the identified parking areas and the coordinates of the underground space centers. If the center point of an underground space is located within a parking area, it is determined to be an underground parking lot; otherwise, it is determined to be a surface parking lot.

[0132] This implementation scheme effectively avoids interference from ordinary mobile phone user data by focusing on the unique communication behavior characteristics of vehicle terminals, achieving accurate separation of parking lot scenarios from complex wireless environments. Simultaneously, this method deeply integrates existing operator parameter data, signaling data, and spatial information, innovatively constructing a parking lot scenario identification system. In practical applications, this solution can provide data support for network optimization in parking areas and provide accurate scenario perception capabilities for services such as vehicle-to-everything (V2X) services, charging pile deployment, and smart parking, significantly improving the operational efficiency and service quality of related services.

[0133] Example 2:

[0134] like Figure 2 As shown, this embodiment provides a parking lot wireless communication scene identification system, which includes:

[0135] The acquisition module 10 is used to acquire the measurement report dataset of the vehicle terminal user. Each record in the measurement report dataset includes user identifier, timestamp, and latitude and longitude information.

[0136] The mapping module 20, connected to the acquisition module 10, is used to map all records to preset geographic grids based on latitude and longitude information, and to determine the grid to which each record belongs.

[0137] The calculation module 30, connected to the mapping module 20, is used to calculate the dwell time of the vehicle terminal user corresponding to each user identifier in the grid according to the record sequence with consecutive timestamps in the same grid.

[0138] The identification module 40, connected to the calculation module 30, is used to identify grids whose daytime stay exceeds the daytime stay threshold as candidate parking grids, or to identify grids whose nighttime stay exceeds the nighttime stay threshold as candidate parking grids, based on preset daytime time periods and daytime stay duration thresholds, as well as preset nighttime time periods and nighttime stay duration thresholds.

[0139] The first processing module 50, connected to the recognition module 40, is used to perform spatial convergence processing on candidate parking grids with continuous spatial locations to form contiguous areas.

[0140] The second processing module 60, connected to the first processing module 50, is used to count the number of grids contained in the contiguous area, and when the number of grids exceeds a preset threshold, the contiguous area is marked as a parking area to complete the identification of the parking lot wireless communication scenario.

[0141] As one specific implementation, the system also includes a determination module for determining the vehicle-mounted terminal;

[0142] The connection between the determination module and the acquisition module 10 specifically includes:

[0143] The first acquisition submodule is used to acquire the identification information set of the vehicle terminal. The identification information set includes a set of terminal device type codes for representing vehicle hardware devices and access point name information for identifying vehicle data services.

[0144] The parsing submodule, connected to the first acquisition submodule, is used to parse the International Mobile Equipment Identity (IMI), International Mobile Subscriber Identity (IMS), and the Service Access Point Name corresponding to each IMS in the core network signaling data.

[0145] The first matching submodule, connected to the parsing submodule, is used to match the International Mobile Equipment Identity (IMI) code with the set of terminal equipment type codes. If the match is successful, the corresponding IMI code is used as the first matching result. At the same time, the service access point name recorded in the signaling data is matched with the access point name information. If the match is successful, the corresponding IMI code is used as the second matching result.

[0146] The determination submodule, connected to the first matching submodule, is used to determine the users of the vehicle terminal who have the first matching result and / or the second matching result as vehicle terminal users.

[0147] In one specific implementation, the system also includes a marking module, which is connected to the second processing module and is used to mark the type of parking lot;

[0148] The tagging module includes:

[0149] The second acquisition submodule is used to acquire underground space area data; it is also used to acquire underground space data tables containing latitude and longitude information of the center of each underground space scene.

[0150] The second matching submodule, connected to the second acquisition submodule, is used to spatially associate and match the parking area with the underground space data table.

[0151] The marking submodule, connected to the second matching submodule, is used to mark the parking lot based on the matching result of the second matching submodule;

[0152] Specifically, if the center latitude and longitude of an underground space in the underground space data table is located within the parking area, the marking submodule will mark the parking area as an underground parking lot; if the center latitude and longitude of any underground space in the underground space data table is not located within the parking area, the marking submodule will mark the parking area as a surface parking lot.

[0153] The system in this embodiment is capable of executing the method in Embodiment 1.

[0154] Example 3:

[0155] like Figure 3 As shown, this embodiment provides an electronic device, which includes a memory 200 and a processor 100. The memory 200 stores a computer program. When the processor 100 runs the computer program stored in the memory 200, the processor 100 executes the parking lot wireless communication scenario identification method according to Embodiment 1.

[0156] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for identifying wireless communication scenarios in parking lots, characterized in that, The method includes the following steps: Obtain the measurement report dataset of the vehicle terminal user, wherein each record in the measurement report dataset includes user identifier, timestamp, and latitude and longitude information; Based on the latitude and longitude information, all records in the measurement report dataset are mapped to preset geographic rasters to determine the raster corresponding to each record; For each user identifier, based on the record sequence with consecutive timestamps within the same grid, the dwell time of the vehicle terminal user corresponding to the user identifier within the grid is calculated. Based on preset daytime hours and daytime stay duration thresholds, as well as preset nighttime hours and nighttime stay duration thresholds, the stay duration data of each grid is determined; Specifically, grids whose daytime stay exceeds the daytime stay threshold are identified as candidate parking grids, or grids whose nighttime stay exceeds the nighttime stay threshold are identified as candidate parking grids. The candidate parking grids that are spatially continuous are spatially converged to form a contiguous area; Count the number of grid cells contained in the contiguous area; When the number of grids exceeds a preset threshold, the contiguous area is marked as a parking area to complete the identification of the parking lot wireless communication scenario.

2. The method for identifying parking lot wireless communication scenarios according to claim 1, characterized in that, Before obtaining the measurement report dataset of the vehicle terminal user, the method further includes: determining the vehicle terminal user; The determination of the vehicle terminal user specifically includes: Obtain a set of identification information for the vehicle-mounted terminal, the set of identification information including a set of terminal device type codes for representing vehicle-mounted hardware devices and access point name information for identifying vehicle-mounted data services; From the core network signaling data, the International Mobile Equipment Identity (IMI), the International Mobile Subscriber Identity (IMS), and the service access point name corresponding to each IMS are extracted; The International Mobile Equipment Identity (IMSI) is matched with the set of terminal device type codes. If a match is found, the corresponding IMSI is used as the first matching result. At the same time, the service access point name recorded in the signaling data is matched with the access point name information. If a match is found, the corresponding IMSI is used as the second matching result. Users of in-vehicle terminals who have the first matching result and / or the second matching result are identified as in-vehicle terminal users.

3. The method for identifying parking lot wireless communication scenarios according to claim 1, characterized in that, The spatial convergence processing of spatially continuous candidate parking grids to form contiguous areas specifically includes: Traverse all the candidate parking grids and determine and establish the spatial adjacency relationship between grids based on the four-neighbor connectivity algorithm or the eight-neighbor connectivity algorithm. Based on the spatial adjacency relationship, the candidate parking lots that are connected to each other are clustered and merged; Each independent region formed after merging is assigned a unique identifier, and all raster information included in the independent region is recorded to complete the construction of contiguous regions.

4. The method for identifying parking lot wireless communication scenarios according to claim 1, characterized in that... For each user identifier, the calculation of the dwell time of the vehicle terminal user corresponding to the user identifier within the grid cell based on the record sequence of consecutive timestamps within the same grid cell specifically includes: A sliding time window algorithm is used to determine the continuity of the recording sequence, and a maximum time interval threshold is set. Iterate through all records with the same user ID within the same grid, sort the records by timestamp, and then check the time interval between adjacent records in turn. When the timestamp interval between two adjacent records does not exceed the maximum time interval threshold, it is determined that the user is staying continuously, and the corresponding time interval is included in the stay duration. When the timestamp interval between adjacent records exceeds the maximum time interval threshold, it is determined that the user's stay is interrupted, and the accumulation of the current continuous duration is stopped; The total dwell time of the user ID within the same grid is obtained by summing the time of all consecutive dwell periods within the same grid.

5. The method for identifying parking lot wireless communication scenarios according to claim 1, characterized in that, The acquisition of the measurement report dataset for the vehicle terminal user specifically includes: The initial measurement report record is collected from the wireless network management system; the initial measurement report record carries a temporary user identifier. Based on core network signaling data, a mapping relationship between the user temporary identifier and the International Mobile Subscriber Identity is constructed; and by combining base station engineering parameters and wireless signal measurement values, the latitude and longitude information of the vehicle terminal user is estimated. For each of the initial measurement records, the International Mobile Subscriber Identity (IMSI) corresponding to the initial measurement report record is determined using the mapping relationship, and the IMSI and the estimated latitude and longitude information are then filled back into the initial measurement report record. Integrate the backfilled data to generate a measurement report dataset containing complete user identifiers, timestamps, and latitude and longitude information.

6. The method for identifying a parking lot wireless communication scenario according to any one of claims 1 to 5, characterized in that, After marking the contiguous area as a parking area, the method further includes: Obtain data on underground space areas; Obtain underground space data tables containing latitude and longitude information of the centers of various underground space scenes; Perform spatial association matching between the parking area and the underground space data table; Specifically, if the center latitude and longitude of an underground space in the underground space data table is located within the parking area, the parking area is marked as an underground parking lot; if the center latitude and longitude of any underground space in the underground space data table is not located within the parking area, the parking area is marked as a surface parking lot.

7. A system for identifying wireless communication scenarios in parking lots, characterized in that, The system includes: The acquisition module is used to acquire the measurement report dataset of the vehicle terminal user. Each record in the measurement report dataset includes user identifier, timestamp, and latitude and longitude information. The mapping module, connected to the acquisition module, is used to map all records to a preset geographic grid based on the latitude and longitude information, and to determine the grid to which each record belongs. The calculation module, connected to the mapping module, is used to calculate the dwell time of the vehicle terminal user corresponding to each user identifier in the grid according to the record sequence with consecutive timestamps in the same grid. The identification module, connected to the calculation module, is used to identify grids whose daytime stay exceeds the daytime stay threshold as candidate parking grids, or to identify grids whose nighttime stay exceeds the nighttime stay threshold as candidate parking grids, based on preset daytime time periods and daytime stay duration thresholds, and preset nighttime time periods and nighttime stay duration thresholds. The first processing module, connected to the identification module, is used to perform spatial convergence processing on the candidate parking grids that are spatially continuous, forming a contiguous area; The second processing module, connected to the first processing module, is used to count the number of grids contained in the contiguous area, and when the number of grids exceeds a preset threshold, the contiguous area is marked as a parking area to complete the identification of the parking lot wireless communication scenario.

8. The parking lot wireless communication scene identification system according to claim 7, characterized in that, The system also includes a determination module for identifying the vehicle-mounted terminal; The determining module is connected to the acquiring module, and specifically includes: The first acquisition submodule is used to acquire a set of identification information of the vehicle terminal. The set of identification information includes a set of terminal device type codes for representing vehicle hardware devices and access point name information for identifying vehicle data services. The parsing submodule, connected to the first acquisition submodule, is used to parse the International Mobile Equipment Identity (IMI), International Mobile Subscriber Identity (IMS), and the Service Access Point Name corresponding to each IMS in the core network signaling data. The first matching submodule, connected to the parsing submodule, is used to match the International Mobile Equipment Identity (IMSI) with the set of terminal device type codes. If the match is successful, the corresponding IMSI is used as the first matching result. At the same time, the service access point name recorded in the signaling data is matched with the access point name information. If the match is successful, the corresponding IMSI is used as the second matching result. A determination submodule, connected to the first matching submodule, is used to determine users of vehicle terminals who have the first matching result and / or the second matching result as vehicle terminal users.

9. The parking lot wireless communication scene identification system according to claim 7 or 8, characterized in that, The system also includes a marking module, which is connected to the second processing module and is used to mark the type of parking lot. The marking module includes: The second acquisition submodule is used to acquire underground space area data; it is also used to acquire underground space data tables containing latitude and longitude information of the center of each underground space scene. The second matching submodule, connected to the second acquisition submodule, is used to perform spatial association matching between the parking area and the underground space data table; A marking submodule, connected to the second matching submodule, is used to mark the parking lot based on the matching result of the second matching submodule; If the center latitude and longitude of an underground space in the underground space data table is located within the parking area, the marking submodule marks the parking area as an underground parking lot; if the center latitude and longitude of any underground space in the underground space data table is not located within the parking area, the marking submodule marks the parking area as a surface parking lot.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the parking lot wireless communication scenario identification method according to any one of claims 1 to 6.

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