Map service data fusion method, system and related device

Abstract

The invention discloses a map service data fusion method and system and a related device, which are used for enhancing the universality and interoperability of map functions. The method comprises the steps that in response to a map data request of a user, at least two pieces of map data are obtained, and the at least two pieces of map data are from at least two different map services; the at least two pieces of map data are fused based on preset data fusion rules, fused map data are obtained, and the preset data fusion rules comprise a unified format rule, a unified coordinate rule, a map data updating management rule and a map data precision evaluation and fusion rule; and displaying the fused map data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a map service data fusion method, system and related device. BACKGROUND

[0002] Under the impetus of digitalization and intelligentization, geographic information services have deeply integrated into people's life and work. Relying on the breakthroughs of new generation Internet technologies such as 5G, cloud computing and big data, map services have evolved from traditional location display tools into comprehensive information platforms integrating intelligent navigation, spatial analysis and decision support, becoming indispensable technical support for traffic, business decision-making and public management scenarios. Map services are a technical system supporting map application development and operation, including map data models, API interfaces, rendering engines, positioning algorithms and other core components, providing standardized tools for developers to call map data, implement functions and display interfaces. At present, there are various map services on the market, each of which has unique APIs and usage methods, and has advantages in map rendering, positioning algorithms and other aspects, providing developers with rich choices to meet different business needs.

[0003] However, the data formats of different map services differ, making it difficult to uniformly call data of different map services and limiting the universality of map functions. SUMMARY

[0004] To solve the above technical problems, the present application provides a map service data fusion method, system and related device to enhance the universality and interoperability of map functions.

[0005] The technical solutions provided in the present application are described as follows: The first aspect of the present application provides a map service data fusion method, which comprises: In response to a user's map data request, at least two map data are obtained, the at least two map data being from at least two different map services; Fusing the at least two map data based on a preset data fusion rule to obtain fused map data, the preset data fusion rule including a unified format rule, a unified coordinate rule, a map data update management rule and a map data precision evaluation and fusion rule; Displaying the fused map data.

[0006] Optionally, the fusing the at least two map data based on a preset data fusion rule to obtain fused map data comprises: Monitoring whether there is an update in the at least two map data according to a map data update management rule; format-convert the at least two map data according to a unified format rule when it is determined that there is no map data update in the at least two map data; coordinate-convert geographical coordinates in the format-converted at least two map data according to a unified coordinate rule; fuse the coordinate-converted at least two map data according to a map data precision evaluation and fusion rule to obtain fused map data.

[0007] Optionally, the method further comprises: obtain the latest map data when it is determined that there is map data update in the at least two map data; update the at least two map data by using the latest map data, and perform the step of format-converting the at least two map data according to the unified format rule.

[0008] Optionally, the format-converting the at least two map data according to the unified format rule comprises: parse the at least two map data to extract key map data, the key map data comprising a place name, geographical coordinates and an address; convert the format of the key map data into a preset format.

[0009] Optionally, the fusing the coordinate-converted at least two map data according to the map data precision evaluation and fusion rule to obtain fused map data comprises: evaluate the precision of the coordinate-converted at least two map data by using an evaluation algorithm in the map data precision evaluation and fusion rule to obtain an evaluation result; fuse the coordinate-converted at least two map data according to the evaluation result by using a fusion algorithm in the map data precision evaluation and fusion rule to obtain fused map data.

[0010] Optionally, the obtaining the at least two map data in response to a map data request of a user comprises: re-encapsulate the map data request according to API parameter requirements and calling modes of at least two different map services in response to a map data request of a user; forward the re-encapsulated map data request to corresponding map services to obtain map data returned by the at least two different map services respectively.

[0011] Optionally, the at least two different map services provide a unified service interface by a unified interface adaptation service, and the method further comprises: When receiving a request of adding a new map service or updating a current map service, the request is responded through the uniform interface adaptation service.

[0012] The second aspect of the present application provides a data fusion system of a map service, the system comprising: an acquisition unit configured to acquire at least two map data from at least two different map services in response to a map data request of a user; a fusion unit configured to fuse the at least two map data based on a preset data fusion rule to obtain fused map data, the preset data fusion rule comprising a uniform format rule, a uniform coordinate rule, a map data update management rule, and a map data precision evaluation and fusion rule; a display unit configured to display the fused map data.

[0013] Optionally, the fusion unit is specifically configured to: monitor whether there is an update in the at least two map data according to the map data update management rule; perform format conversion on the at least two map data according to the uniform format rule when it is determined that there is no map data update in the at least two map data; perform coordinate conversion on geographical coordinates in the format-converted at least two map data according to the uniform coordinate rule; fuse the coordinate-converted at least two map data according to the map data precision evaluation and fusion rule to obtain the fused map data.

[0014] Optionally, the fusion unit is specifically configured to: acquire the latest map data when it is determined that there is map data update in the at least two map data; update the at least two map data through the latest map data and perform the format conversion on the at least two map data according to the uniform format rule.

[0015] Optionally, the fusion unit is specifically configured to: analyze the at least two map data to extract key map data, the key map data comprising a place name, a geographical coordinate, and an address; convert a format of the key map data into a preset format.

[0016] Optionally, the fusion unit is specifically configured to: evaluate precision of the coordinate-converted at least two map data by using an evaluation algorithm in the map data precision evaluation and fusion rule to obtain an evaluation result; According to the evaluation result, the at least two pieces of map data after coordinate conversion are fused by using a fusion algorithm in the map data precision evaluation and fusion rule, and fused map data is obtained.

[0017] Optionally, the obtaining unit is specifically configured to: In response to a map data request of a user, the map data request is re-encapsulated according to API parameter requirements and calling manners of at least two different map services respectively; The re-encapsulated map data request is forwarded to a corresponding map service respectively, and map data returned by the at least two different map services respectively is obtained.

[0018] Optionally, the method further comprises a unified service unit, and the unified service unit is specifically configured to: When a request of adding a new map service or updating a current map service is received, the request is responded to by the unified interface adaptation service.

[0019] The third aspect of the application provides a data fusion device of a map service, and the device comprises: a processor, a memory, an input and output unit, and a bus; The processor is connected with the memory, the input and output unit, and the bus; The memory stores a program, and the processor invokes the program to execute the method of the first aspect and any optional method in the first aspect.

[0020] The fourth aspect of the application provides a computer readable storage medium, and the computer readable storage medium stores a program, and the program is executed on a computer to execute the method of the first aspect and any optional method in the first aspect.

[0021] As can be seen from the above technical solutions, the application has the following advantages: After responding to a map data request of a user, at least two pieces of map data are obtained, the map data is obtained from different map services, and then a data fusion operation is performed on the at least two pieces of map data according to preset data fusion rules including a unified format rule, a unified coordinate rule, a map data update management rule, and a map data precision evaluation and fusion rule, and finally fused map data after fusion is displayed on a map interface. By performing a data fusion operation on map data obtained from different map services according to the preset data fusion rules, the problems of inconsistent data formats, coordinate system differences, and different data update frequencies are solved, the consistency and accuracy of the data are improved, and the universality and interoperability of the map function are enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the present application, the drawings needed in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort.

[0023] Figure 1 Flowchart of an embodiment of the data fusion method for map service provided by the present application; Figure 2 Flowchart of an embodiment of data fusion based on preset data fusion rules in the data fusion method for map service provided by the present application; Figure 3 Flowchart of another embodiment of data fusion based on preset data fusion rules in the data fusion method for map service provided by the present application; Figure 4 Flowchart of an embodiment of format conversion according to unified format rules in the data fusion method for map service provided by the present application; Figure 5 Flowchart of an embodiment of data fusion according to map data precision evaluation and fusion rules in the data fusion method for map service provided by the present application; Figure 6 Flowchart of an embodiment of obtaining at least two map data in the data fusion method for map service provided by the present application; Figure 7 Structural diagram of an embodiment of the data fusion system for map service provided by the present application; Figure 8 Structural diagram of an embodiment of the data fusion device for map service provided by the present application. DETAILED DESCRIPTION

[0024] The present application provides a data fusion method, system and related device for map service, which is used to enhance the versatility and interoperability of map function.

[0025] It should be noted that the data fusion method for map service provided by the present application can be applied to terminal, system and server. For example, the terminal can be smart phone or computer, tablet computer, smart TV, smart watch, portable computer terminal or desktop computer. For convenience, the system is taken as the execution subject in the present application.

[0026] Please refer to Figure 1 The present application first provides an embodiment of a data fusion method for map service, which includes: S101, in response to a user's map data request, obtaining at least two map data, the at least two map data coming from at least two different map services; The map service refers to the systematic service of the geographical data and functions output by major geographical information manufacturers, such as Gaode, Baidu, Tencent, Google, etc. through API interface or network service form. The map data is the specific information carrier carried by the map service, covering spatial location data (such as latitude and longitude coordinates, road network), attribute data (such as place name, address description, POI type) and dynamic data (such as traffic events, business operating hours) and other multi-dimensional information. When the system detects that the user initiates a map data request, such as the user searches for a certain place in the map application, plans a route, etc. operation, it is necessary to obtain the same source geographical data from at least two map services. Obtaining at least two map data can solve the inherent defects of single map service in data coverage, accuracy, timeliness, etc. through the complementarity and cross verification of multi-source data. Different map services have differences in geographical area coverage, such as more detailed city POI of Gaode map, more comprehensive suburban roads of Baidu map, more frequent real-time traffic data update of Tencent map, etc. Obtaining at least two map data can fill the blind area of single service, avoid positioning deviation or incomplete information caused by data loss, and increase the universality and interoperability of map functions.

[0027] S102, based on a preset data fusion rule, fusing the at least two map data to obtain fused map data, the preset data fusion rule including a unified format rule, a unified coordinate rule, a map data update management rule, and a map data accuracy evaluation and fusion rule; The data format, coordinate system, update strategy and precision performance of each map service may be different, for example, Gaode map uses GCJ-02 coordinate system, and Baidu map uses BD-09 coordinate system. If these map data is directly used, there may be problems such as position deviation and information conflict. By presetting data fusion rules to fuse at least two map data, multi-source map data can be generated to have high precision, consistency and timeliness of geographic information, thereby breaking through the ability boundary of single map service and improving the universality and interoperability of map function. The preset data fusion rules include unified format rule, unified coordinate rule, map data update management rule and map data precision evaluation and fusion rule. The unified format rule can eliminate the differences in data structure and field naming of each map data through standardization processing, so that different source data can be recognized and called by a unified interface. The unified coordinate rule can solve the position deviation problem caused by different coordinate systems, establish spatial reference consistency, and provide a basis for cross-frame geographic analysis. The map data update management rule ensures that the fused map data reflects the latest state of the map data in each map service in real time through dynamic monitoring and synchronization mechanism, and avoids information lag caused by different update frequencies. The map data precision evaluation and fusion rule quantitatively evaluates the reliability of each map data and executes the fusion strategy to eliminate data conflicts and generate more accurate and comprehensive fused map data than single map data. The coordinated action of these rules enables multi-source map data to retain their respective advantages while achieving integration and complementation under unified standards, ultimately breaking through the functional limitations of single map service.

[0028] S103, display the fused map data.

[0029] Finally, the fused map data fused by the preset data fusion rules is presented to the user through the map interface, realizing the conversion from data to information. Based on the coordinate information in the fused map data, the map interface can call the point interface of the map engine to generate a label icon, and superimpose an information window beside the label icon to display detailed information such as place name, address, precision level and data source. In addition, the map interface can also support rich interactive functions, such as triggering the detail page by clicking the label icon, dynamically loading different precision data when zooming in or out the map, providing layer switching function, and providing high-precision and real-time map information for users.

[0030] In this embodiment, in response to a user's map data request, at least two map data sets are obtained from different map services. These map data sets are then fused according to pre-set data fusion rules, including unified format rules, unified coordinate rules, map data update management rules, and map data accuracy assessment and fusion rules. Finally, the fused map data is displayed on the map interface. By fusing map data obtained from different map services according to pre-set data fusion rules, issues such as inconsistent data formats, different coordinate systems, and varying data update frequencies are resolved, improving data consistency and accuracy and enhancing the versatility and interoperability of map functions.

[0031] In the above step S102, at least two map data are fused based on the preset data fusion rules, see Figure 2 , Figure 2 An embodiment of the data fusion method for map services provided in this application, which performs data fusion based on preset data fusion rules, includes: S201, monitoring whether at least two map data are updated according to a map data update management rule; After acquiring map data, map data update management rules are first used to monitor updates in at least two map data sources. These rules can reduce information lag caused by varying update frequencies among map services and provide the latest data sources for subsequent data processing. These rules can be based on scheduled polling (e.g., every 10 minutes) or event-triggered (subscribing to update push notifications from the map framework), sending data update requests to at least two map services. These rules then compare the version numbers or timestamps of the locally stored map data to determine whether changes have occurred to the same source map data (e.g., POI information modifications, road topology updates, etc.). By monitoring the map data status of each map service in real time through these rules, the timeliness of fused map data can be improved.

[0032] S202: When it is determined that there is no map data update in the at least two map data, convert the formats of the at least two map data according to a unified format rule; When it is detected that at least two map data have not been updated, the data of the at least two currently acquired map data are processed in accordance with the unified format rules, coordinate unification rules, and map data accuracy assessment and fusion rules. First, the format conversion is performed according to the unified format rules to eliminate the heterogeneity of map data structures of different map services.

[0033] S203, performing coordinate conversion on the geographic coordinates of the at least two map data after format conversion according to a unified coordinate rule; On the basis of completing format unification, the system solves the spatial reference difference problem of multi-source data through unified coordinate rules. Since different map services may adopt different coordinate systems, direct fusion will cause position deviation, therefore, the system will adopt coordinate conversion algorithms, such as projection conversion algorithm, Gauss-Kruger projection algorithm, or the coordinate conversion function provided by geographic information system (GIS) software, online coordinate conversion service API, etc., to convert all geographic coordinates into coordinates under the target coordinate system. The consistency of at least two map data in the spatial dimension is ensured, which provides a coordinate basis for subsequent data fusion.

[0034] S204, at least two map data after coordinate conversion are fused according to the map data precision evaluation and fusion rule, and fused map data is obtained.

[0035] Finally, at least two map data after coordinate conversion are fused according to the map data precision evaluation and fusion rule. Through precision evaluation of at least two map data, the evaluation result is obtained, and at least two map data are fused according to the evaluation result, the advantages of multi-source map data are retained, and finally the fused map data with accuracy, integrity and consistency is generated, which provides reliable data support for upper-layer application.

[0036] In this embodiment, through the execution of the four steps of update monitoring, format unification, coordinate conversion and precision fusion, a complete multi-source map data fusion process is formed. Firstly, the update state of each map service is captured in real time through the map data update management rule to ensure the timeliness of the map data, and after confirming that there is no update, format unification, coordinate unification and finally precision fusion are performed in sequence. Both the information lag problem caused by the difference in update frequency of different map services and the accuracy and reliability of map data are improved through standardization processing and precision fusion. The fused map data generated finally has the characteristics of timeliness, spatial consistency and high precision, and the reliability of the fused map data is improved.

[0037] In the above step S202, at least two map data are fused based on the preset data fusion rule when there is no update in the at least two map data. In addition, the present application also includes a data fusion method when there is map update in the at least two map data. Please refer to Figure 3 , Figure 3 Another embodiment of the data fusion method of the map service provided by the present application based on the preset data fusion rule for data fusion includes: S301, when it is determined that there is map data update in at least two map data, the latest map data is obtained; When the system detects that at least one map data in the at least two map services has changed according to the update management rule, a latest data acquisition mechanism is triggered immediately to acquire the latest map data in the map service in which the data has changed. The latest map data is not all map data in the map service, but only the changed map data segment. This acquisition manner can greatly reduce network transmission and processing load, while ensuring that the acquired information is the latest state of the map service, achieving dynamic updating while maintaining the efficiency of updating, avoiding resource waste and processing delay caused by full update.

[0038] S302, updating the at least two map data by the latest map data, and performing a step of converting the at least two map data into a unified format according to a unified format rule.

[0039] After acquiring the latest map data, the system automatically compares and merges it with the at least two map data stored locally, and replaces or supplements the outdated information through an incremental update strategy. After updating, a unified format conversion process is started to convert the at least two map data into a unified format.

[0040] In this embodiment, when the system detects that the map data of any one of the at least two map services has changed according to the update management rule, only the changed map data segment is acquired instead of full data, and the at least two map data are updated. After updating, a unified format conversion process is started. While ensuring that the latest map data in the map service is acquired, resource waste and processing delay caused by full update are avoided, dynamic timeliness of fused map data is achieved, and a standardized basis is laid for subsequent coordinate conversion and data fusion through format unification, improving the update efficiency and reliability of data.

[0041] In the above step S202, the at least two map data are converted into a unified format according to a unified format rule. Please refer to Figure 4 , Figure 4 An embodiment of the format conversion according to a unified format rule in the data fusion method of the map service provided in the present application includes: S401, parsing the at least two map data to extract key map data, the key map data including place names, geographic coordinates, and addresses; Since the map data can also contain redundant messages, such as advertising labels, statistical codes, non-geographical related metadata, etc., these information is not helpful for the positioning, navigation and POI query functions of the map service. Therefore, when at least two map data are converted in format, the invalid information needs to be filtered by extracting the key map data, which includes the place name, geographic coordinates and address, to support the core functions of the map service. The unified format rule can be a custom conversion logic, or a data conversion library can be used to realize the unified conversion of different map data formats. For example, by using a semantic parsing engine to structure the at least two map data, regular matching, semantic recognition and other technologies are used to locate and extract the key map data such as place name, geographic coordinates, address, etc. from the heterogeneous data structure (such as the name field of Gaode and the title field of Baidu). In the parsing and extraction process, redundant information is automatically filtered to provide standardized input for subsequent format conversion, ensuring the accuracy of the map data.

[0042] S402, convert the format of the key map data into a preset format.

[0043] After extracting the key map data, the system unifies the format of the key map data according to the preset format, for example, by mapping the configuration file, the format of the place name, geographic coordinates and address of the key map data is mapped to JSON format. JSON format has the characteristics of text and easy parsing, which can eliminate the differences in structure and naming of the original key map data, so that the key map data can be quickly recognized and processed by various programming languages and platforms. It provides a standardized data basis for subsequent coordinate conversion, data fusion and other operations.

[0044] In this embodiment, by analyzing at least two map data to extract key map data, and converting the key map data into a unified format, the differences in naming rules and hierarchical structure of the original key map data are eliminated, the filtering of redundant information such as advertising labels and statistical codes is realized, and the standardization of the key map data is also completed. Converting the key map data into a unified format provides a standardized basis for subsequent coordinate conversion and data fusion, improves the processing efficiency of map data, and enhances the data interoperability between different map services.

[0045] In the above step S204, after the coordinate conversion of the at least two map data, the map data needs to be fused according to the map data precision evaluation and fusion rule. Please refer to Figure 5 , Figure 5 An embodiment of the data fusion method of the map service provided in the present application according to the map data precision evaluation and fusion rule for data fusion, the embodiment comprises: S501, precision evaluation is performed on the at least two pieces of map data after coordinate conversion by using an evaluation algorithm in the map data precision evaluation and fusion rule, and an evaluation result is obtained; The evaluation algorithm in the map data precision evaluation and fusion rule is used to quantify the reliability of the multi-source map data and solve the problem of uneven quality of map data of different map services. Due to the differences in data collection methods, update frequency and coverage range of different map services, direct fusion may produce low-quality data and pollute the final result. The evaluation algorithm can use error analysis method, and the repeatability and consistency of the obtained map data are used as evaluation indexes. The repeatability evaluation focuses on the data fluctuation of the same geographic feature at different times or in different collection batches, and the consistency evaluation compares the matching degree of multi-source data in describing the same object, for example, by comparing the completeness and coincidence rate of the address field. Through quantitative analysis of these indexes, the precision level of each piece of map data is divided, for example, the data is divided into three levels of high precision, medium precision and low precision, and finally the evaluation result is output, which provides an objective and quantitative reliability basis for subsequent data fusion.

[0046] S502, according to the evaluation result, a fusion algorithm in the map data precision evaluation and fusion rule is used to fuse the at least two pieces of map data after coordinate conversion, and a fused map data is obtained.

[0047] Based on the evaluation result of precision, the system realizes the optimal aggregation of multi-source data through the fusion algorithm. The fusion algorithm can use various algorithms, such as weighted average method and Kalman filter method. When the weighted average method is used, the weights are allocated according to the precision levels of the map data, the high-precision data is given a higher weight, and the weight of the low-precision data is correspondingly reduced, so that the high-quality data dominates the final result in the fusion process. Finally, at least two pieces of map data are aggregated into high-precision fused map data, so as to improve the integrity and reliability of the data.

[0048] In this embodiment, by using the map data precision evaluation and fusion rule, the error analysis method is used to evaluate the map data after coordinate conversion, the precision level is divided by taking data repeatability and consistency as indexes, and then the weighted average method is used to allocate weights according to the evaluation result, so that at least two pieces of map data are aggregated into high-precision fused map data. The problem of uneven data quality is solved, and the integrity and reliability of the fused map data are improved. Through quantitative evaluation, the problem of uneven data quality is reduced, and through the precision-weighted fusion method, the pollution of low-quality data is reduced, so as to improve the integrity and reliability of the fused map data.

[0049] In the above step S101, before the fusion operation of the at least two pieces of map data, at least two pieces of map data are obtained in response to the map data request of the user, please refer to Figure 6 ,Figure 6 One embodiment of the data fusion method for map services provided by the present application for obtaining at least two map data includes the following steps: S601, in response to a user's map data request, re-encapsulating the map data request according to the API parameter requirements and calling methods of at least two different map services; When the system receives a user's map data request, it needs to adapt the request to the API interface specifications of different map services. Since the API parameters, formats and calling methods of each map service may be different, the map data request needs to be re-encapsulated according to the API parameter requirements and calling methods of at least two different map services, and the original user request is converted into a format recognizable by each map service, i.e. the map data request is adapted to each map service through the unified interface adaptation service in the present application.

[0050] S602, forwarding the re-encapsulated map data request to the corresponding map service to obtain the map data returned by each of the at least two different map services.

[0051] After completing the encapsulation of the map data request, the system needs to forward the map data request to the corresponding map service to obtain the map data returned by each of the at least two different map services. When forwarding the map data request, the request can be forwarded to the API interface of each map service through multi-threading or asynchronous mechanism to realize parallel acquisition of multi-source map data. For example, a POI search request is sent to Gaode Map at the same time as a path planning request for the same area is sent to Baidu Map to ensure the timeliness of data acquisition. When the response of the map service is received, the corresponding map data is obtained.

[0052] In some specific embodiments, when a request to add a new map service or update the current map service is received, the unified interface adaptation service responds to the request, which is described in detail as follows: Since the API parameters, formats and calling methods of each map service may be different, each map service cannot accurately identify the request to add a new map service or update the current map service (such as reducing the map service or replacing the map service), and the unified interface adaptation service can convert these requests into a format recognizable by each map service to obtain the map data in the map service. Therefore, when a request to add a new map service or update the current map service is received, the unified interface adaptation service needs to respond to the request.

[0053] In this embodiment, the unified interface adaptation service is used to solve the problem of differences in API parameters, formats and calling methods of different map services, to parse and repackage the original map data request of the user, to make the map data request into a format recognizable by each map service, and to obtain the map data in each map service. The unified interface adaptation service eliminates the interface difference between different map services and avoids repeated development and resource waste. At the same time, for the addition of a new map service or the update of an existing map service, only the interface rules in the unified interface adaptation service need to be modified, without the need to modify the underlying data on a large scale, thereby improving the flexibility of the system.

[0054] Please refer to Figure 7 The application further provides a data fusion system of a map service, comprising: An acquisition unit 701 is configured to acquire at least two map data from at least two different map services in response to a map data request of a user; A fusion unit 702 is configured to fuse the at least two map data based on a preset data fusion rule to obtain fused map data, wherein the preset data fusion rule comprises a unified format rule, a unified coordinate rule, a map data update management rule and a map data precision evaluation and fusion rule; A display unit 703 is configured to display the fused map data.

[0055] Optionally, the fusion unit 702 is specifically configured to: monitor whether there is an update in the at least two map data according to the map data update management rule; perform format conversion on the at least two map data according to the unified format rule when it is determined that there is no map data update in the at least two map data; perform coordinate conversion on geographical coordinates in the format-converted at least two map data according to the unified coordinate rule; fuse the coordinate-converted at least two map data according to the map data precision evaluation and fusion rule to obtain the fused map data.

[0056] Optionally, the fusion unit 702 is specifically configured to: acquire the latest map data when it is determined that there is map data update in the at least two map data; update the at least two map data by using the latest map data and perform the step of performing format conversion on the at least two map data according to the unified format rule.

[0057] Optionally, the fusion unit 702 is specifically configured to: analyze the at least two map data to extract key map data, wherein the key map data comprises a place name, a geographical coordinate and an address. convert the format of the key map data into a preset format.

[0058] Optionally, the fusion unit 702 is specifically configured to: perform precision evaluation on the at least two pieces of map data after coordinate conversion by using an evaluation algorithm in the map data precision evaluation and fusion rule, to obtain an evaluation result; perform fusion on the at least two pieces of map data after coordinate conversion according to the evaluation result by using a fusion algorithm in the map data precision evaluation and fusion rule, to obtain fused map data.

[0059] Optionally, the acquisition unit 701 is specifically configured to: in response to a map data request of a user, re-encapsulate the map data request according to API parameter requirements and calling manners of at least two different map services respectively; forward the re-encapsulated map data request to corresponding map services respectively, and acquire map data returned by the at least two different map services respectively.

[0060] Optionally, the application further comprises a unified service unit 704, which is specifically configured to: when receiving a request of adding a new map service or updating a current map service, respond to the request through a unified interface adaptation service.

[0061] For specific implementation modes, refer to Figures 1 to 6 Embodiments, which will not be described here.

[0062] Please refer to Figure 8 The application further provides a data fusion device of a map service, comprising: a processor 801, a memory 802, an input and output unit 803, and a bus 804; the processor 801 is connected with the memory 802, the input and output unit 803, and the bus 804; the memory 802 stores a program, and the processor 801 calls the program to execute any method described above.

[0063] The application further relates to a computer readable storage medium, which stores a program, and when the program runs on a computer, the computer executes any method described above.

[0064] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the system, device and unit described above can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0065] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the described device embodiments are merely schematic. For example, the division of the units is only a logical function division. There can be another division manner for the actual implementation. 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 displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0066] The units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0067] In addition, each functional unit in the embodiments of the present application can be integrated in one processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated in one unit. The integrated unit can be implemented in the form of hardware, or in the form of a software functional unit.

[0068] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such an understanding, the technical solutions of the present application essentially or substantially, 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, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, read-only memory), a random access memory (RAM, random access memory), a magnetic disk or an optical disk, and various other media that can store program codes.

Claims

1. A data fusion method for map services, characterized in that: The method comprises: Responding to a user's map data request, obtaining at least two map data, wherein the at least two map data are from at least two different map services; fusing the at least two map data based on preset data fusion rules to obtain fused map data, wherein the preset data fusion rules include a unified format rule, a unified coordinate rule, a map data update management rule, and a map data accuracy assessment and fusion rule; The fused map data is displayed.

2. The data fusion method according to claim 1, characterized in that: The fusing the at least two map data based on a preset data fusion rule to obtain fused map data includes: monitoring whether the at least two map data are updated according to a map data update management rule; When it is determined that there is no map data update in the at least two map data, converting the formats of the at least two map data according to a unified format rule; Performing coordinate conversion on the geographic coordinates in the at least two map data after format conversion according to a unified coordinate rule; The at least two map data after coordinate conversion are fused according to map data accuracy assessment and fusion rules to obtain fused map data.

3. The data fusion method according to claim 2, characterized in that: The method further comprises: When it is determined that there is map data update in the at least two map data, acquiring the latest map data; The at least two map data are updated using the latest map data, and the step of converting the formats of the at least two map data according to a unified format rule is performed.

4. The data fusion method according to claim 2, characterized in that: The converting the formats of the at least two map data according to a unified format rule includes: parsing the at least two map data to extract key map data, wherein the key map data includes a place name, geographic coordinates, and an address; The format of the key map data is converted into a preset format.

5. The data fusion method according to claim 2, characterized in that: The step of fusing the at least two map data after coordinate conversion according to map data accuracy assessment and fusion rules to obtain fused map data includes: Using an evaluation algorithm in a map data accuracy evaluation and fusion rule to perform accuracy evaluation on the at least two map data after coordinate conversion, to obtain an evaluation result; According to the evaluation result, the at least two map data after coordinate transformation are fused using a fusion algorithm in the map data accuracy evaluation and fusion rule to obtain fused map data.

6. The data fusion method according to claim 1, characterized in that: The step of obtaining at least two pieces of map data in response to a user's map data request includes: In response to a user's map data request, repackaging the map data request according to API parameter requirements and calling methods of at least two different map services; The repackaged map data requests are forwarded to corresponding map services respectively, and the map data returned by the at least two different map services are obtained.

7. The data fusion method according to any one of claims 1 to 6, characterized in that: The at least two different map services are provided with a unified service interface by a unified interface adaptation service, and the method further includes: When a request to add a new map service or update a current map service is received, the unified interface adaptation service responds to the request.

8. A data fusion system for multiple map services, characterized in that: The system comprises: an acquiring unit, configured to acquire at least two map data in response to a map data request from a user, wherein the at least two map data are from at least two different map services; a fusion unit, configured to fuse the at least two map data based on preset data fusion rules to obtain fused map data, wherein the preset data fusion rules include a unified format rule, a unified coordinate rule, a map data update management rule, and a map data accuracy assessment and fusion rule; A display unit is used to display the fused map data.

9. A data fusion device for multiple map services, characterized in that: The device comprises: processor, memory, input and output units, and buses; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program, and when the program is executed on a computer, the method according to any one of claims 1 to 7 is executed.

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