CN113535870B - Traffic information visual analysis method, system and terminal based on big data - Google Patents
Traffic information visual analysis method, system and terminal based on big data Download PDFInfo
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Abstract
The application relates to the technical field of comprehensive data analysis, in particular to a traffic information visual analysis method based on big data, aiming at solving the following defects in the prior art: data are stored in different systems, so that data storage is dispersed, an information isolated island state is presented, and in the data analysis process, the data correlation is weak, so that the quality of a data analysis result is poor. The technical scheme is that the traffic information visualization analysis method based on big data comprises the following steps: acquiring geographic information data and original data of each field; carrying out data format conversion to obtain initial data with the same format; establishing a database, wherein the database is provided with a plurality of data layers; the initial data are endowed with geospatial attributes and are mapped in the data layers, the data layers are overlapped, a comprehensive data platform is obtained, traffic analysis and operation management are carried out, and the method and the device have the effects of enhancing the relevance of the data and improving the efficiency of data analysis application.
Description
Technical Field
The application relates to the technical field of comprehensive data analysis, in particular to a traffic information visual analysis method, a traffic information visual analysis system and a traffic information visual analysis terminal based on big data.
Background
Urban traffic is a large and complex system and is an important mark for measuring the management level of a modern city, and the problems of traffic congestion, frequent traffic accidents and the like affect the operation efficiency of the city, so that the improvement of the management level of the modern urban traffic is an objective requirement for urban development and is a necessary route for improving the management level of the modern city.
With the continuous development of communication network technology in recent years, big data technology has gained rapid progress, and the development of big data technology makes big data technology meet the application requirement in urban traffic management gradually. Big data refers to a data set that is diverse in source, diverse in type, large and complex, potentially valuable, but difficult to process and analyze in a desired time. In application, the traffic big data is a data set formed by data directly generated by urban traffic operation management, data of urban traffic related industries or fields, and traffic condition data provided by public interaction.
At present, a method for analyzing and processing traffic big data generally includes collecting data of traffic related industries or fields, respectively establishing storage and analysis systems for different types of data, processing data in the respective systems, and then analyzing the data to obtain a result.
With respect to the related art among the above, the inventors consider that the following drawbacks exist: data are stored in different systems respectively and show an information isolated island state, and in the data analysis process, the data are weak in correlation, so that the quality of a data analysis result is poor.
Disclosure of Invention
In order to enhance the relevance of data from different sources and improve the analysis and application efficiency of the data, the application provides a traffic information visual analysis method, system and terminal based on big data.
In a first aspect, the traffic information visualization analysis method based on big data provided by the application adopts the following technical scheme:
a traffic information visual analysis method based on big data comprises the following steps:
acquiring geographic information data and original data of each field related to traffic;
carrying out data format conversion on the original data to obtain the original data with the same data format in each field of traffic;
the method comprises the steps that a database is established in advance, a plurality of data layers based on geographic information data are arranged in the database, and the data layers correspond to the source fields of original data one by one;
giving geospatial attributes to the initial data, mapping the initial data in data layers of corresponding fields based on the geospatial attributes, and superposing the data layers to obtain a comprehensive data platform;
and carrying out traffic analysis and operation management based on the comprehensive data platform.
By adopting the technical scheme, the geographic information data and the original data of each field related to traffic are obtained when the data are collected, so that the data range for reference is enlarged, and the quality of data analysis is improved; format conversion is carried out on the data, so that integration of data of different sources and different formats is facilitated, the interoperability among the data is enhanced, comprehensive analysis of the data is facilitated, and the reliability of a data analysis result is improved; the geographic information is used as the basis of data integration, so that the difficulty of data integration is reduced, and the efficiency of data integration work is improved; and a plurality of data layers are superposed to form a comprehensive data platform, which is beneficial to improving the efficiency of data correlation analysis and comprehensive study and judgment implemented by industry managers.
Optionally, the method further includes:
adding a time axis in the database, giving time attributes to the initial data in each data layer, and synchronizing each layer on the time axis based on the time attributes.
By adopting the technical scheme, on the basis of integrating the data layers by using the general geographic information, the data layers are subjected to secondary calibration by using the time attribute, so that the data from different sources can be integrated from two dimensions of time and space, the stability of data fusion from different sources is enhanced, and the accuracy of the comprehensive analysis result of the data is promoted.
Optionally, the method further includes:
performing statistical analysis on the dynamically changed initial data to obtain steady statistical data of the dynamically changed initial data;
and adding a data sub-layer in the data layer corresponding to the dynamic initial data, and storing the steady-state statistical data in the data sub-layer.
By adopting the technical scheme, the data layer with dynamic change is subjected to deep analysis to obtain the steady-state statistical data of the dynamic data, so that the steady-state statistical data of the dynamic data can be referred to when the dynamic data layer is analyzed, the accuracy of an analysis result can be improved, and the possibility that the analysis result has errors due to the fact that the data has contingency due to the dynamic property of the data is reduced; the steady-state statistical data divided from the dynamic data layer are stored in the independent data sub-layer, so that the relevance between the steady-state statistical data and the dynamic data is ensured, the independent storage is realized, and the safety of data storage is improved.
Optionally, before performing data format conversion on the original data and obtaining the original data with the same data format in each traffic field, the method further includes:
preprocessing raw data, wherein the preprocessing comprises the following steps:
acquiring original data, classifying information contained in the original data, and acquiring a plurality of feature sets;
and performing relevance analysis between the feature set and the traffic information, setting a relevance threshold value, and removing the feature set of which the relevance with the traffic information is lower than the relevance threshold value.
By adopting the technical scheme, the information in the original data is classified, the information with low relevance to the application is removed, the workload of data conversion is reduced, the efficiency of data conversion is improved, the occupation of the storage space during data storage is reduced, the utilization rate of the storage space is improved, and the data retrieval speed is improved.
Optionally, the method further includes:
extracting common features from a plurality of data layers in a database, and developing a common management tool based on the common features;
and utilizing the common management tool to carry out common management on different data layers with the same common characteristics.
By adopting the technical scheme, the common management tool developed by the common characteristics extracted from the database improves the management range of the common management tool to the data layers, further reduces the difficulty in developing and updating the database management tool, adopts a small amount of tools to manage most of the data layers, is favorable for simplifying the difficulty in database management, and further improves the efficiency of database management.
Optionally, the method further includes:
acquiring abnormal original data with abnormal data format conversion, and acquiring evaluation analysis of the abnormal original data by manpower;
if the evaluation analysis result is that the abnormal original data has no analysis value, removing the abnormal original data;
and if the evaluation analysis result indicates that the abnormal original data has analysis value, adding an independent data layer and storing the abnormal original data in the independent data layer.
By adopting the technical scheme, the evaluation analysis is carried out on the data which can not be subjected to format conversion, the value of the data is favorably judged, useless data is removed, and the possibility of losing the data with analysis value is reduced.
In a second aspect, the application provides a traffic information visualization analysis system based on big data, which adopts the following technical scheme:
a traffic information visualization analysis system based on big data is characterized in that: the system comprises:
the data collecting module is used for collecting original data, geographic information data and the like related to each traffic field;
the data processing module is used for processing the original data to enable the original data to meet the condition of data fusion;
the database module is used for integrating and hierarchically storing the processed original data from different sources;
and the analysis application module is used for comprehensively analyzing the data in the database module and actually applying the data based on the analysis result.
By adopting the technical scheme, the geographic information data and the original data of each field related to traffic are acquired when the data are collected, so that the data range for reference is expanded, and the quality of data analysis is improved; format conversion is carried out on the data, so that integration of data of different sources and different formats is facilitated, interoperability among the data is enhanced, comprehensive analysis of the data is facilitated, and reliability of data analysis results is improved; the geographic information is used as the basis of data integration, so that the difficulty of data integration is reduced, and the efficiency of data integration work is improved; and a plurality of data layers are superposed to form a comprehensive data platform, which is beneficial to improving the efficiency of data correlation analysis and comprehensive study and judgment implemented by industry managers.
Optionally, the system further includes:
the extended application module is used for performing secondary application in other fields by using the data in the database module;
and the application interface module is used for realizing the connection between the database module and the extended application module.
By adopting the technical scheme, the secondary development is carried out on the data application in the database, the use range of the data in the database is favorably expanded, and the application performance of the database is improved.
In a third aspect, the present application provides an intelligent terminal, which adopts the following technical scheme:
an intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes the method.
By adopting the technical scheme, the processor in the intelligent terminal can realize the traffic information visual analysis method based on the big data according to the related computer program stored in the memory, so that the data of different fields related to traffic are integrated, the relevance among the data is enhanced, and the efficiency of comprehensive analysis and application of the data is improved.
In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer-readable storage medium storing a computer program that can be loaded by a processor and executes the above-mentioned method.
By adopting the technical scheme, corresponding programs can be stored, so that data in different traffic-related fields are integrated, the relevance among the data is enhanced, and the efficiency of comprehensive analysis and application of the data is improved.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the geographic information data and the original data of each field related to traffic are obtained when the data are collected, so that the data range for reference is expanded, and the quality of data analysis is improved; format conversion is carried out on the data, so that integration of data of different sources and different formats is facilitated, the interoperability among the data is enhanced, comprehensive analysis of the data is facilitated, and the reliability of a data analysis result is improved; the geographic information is used as the basis of data integration, so that the difficulty of data integration is reduced, and the efficiency of data integration work is improved; the data layers are overlapped to form a comprehensive data platform, so that the efficiency of data correlation analysis and comprehensive study and judgment implemented by industry managers is improved;
2. the data layer with data presented as dynamic change is subjected to deep analysis to obtain the steady-state statistical data of the dynamic data, so that the steady-state statistical data of the dynamic data can be referred when the dynamic data layer is analyzed, the accuracy of an analysis result can be improved, and the possibility that the analysis result has errors due to the fact that the data has contingency due to the dynamic property of the data is reduced; the steady-state statistical data differentiated in the dynamic data layer are stored in the independent data sub-layer, so that the relevance between the steady-state statistical data and the dynamic data is ensured, the independent storage is realized, and the safety of data storage is improved;
3. the common characteristic management tool developed by the common characteristic extracted from the database improves the management range of the common characteristic management tool to the data layers, further reduces the difficulty of development and updating of the database management tool, adopts a small amount of tools to manage most of the data layers, is beneficial to simplifying the difficulty of database management, and further improves the efficiency of database management.
Drawings
Fig. 1 is a block flow diagram of a traffic information visualization analysis method based on big data shown in an embodiment of the present application;
fig. 2 is a system block diagram of a big data-based traffic information visualization analysis system shown in an embodiment of the present application.
Description of the reference numerals: 1. a data collection module; 2. a data processing module; 3. a database module; 4. an analysis application module; 5. expanding an application module; 6. and an application interface module.
Detailed Description
To make the objects, technical solutions and advantages of the present invention more apparent, the present application will be described in further detail with reference to fig. 1-2.
The embodiment of the application discloses a traffic information visual analysis method based on big data, which can be applied to a traffic information visual analysis system based on big data, such as a distributed content acquisition network, wherein an execution main body can be an intelligent terminal and is assisted by detection equipment which is included in the traffic information visual analysis system based on big data and is used for detecting data in various traffic fields.
Referring to fig. 1, a traffic information visualization analysis method based on big data includes the following steps:
s100, acquiring geographic information data and original data of each field related to traffic;
in implementation, the geographic information data mainly includes geographic information based on spatial information in a city, and the raw data of each field related to traffic may mainly include ten fields, and the sources of the raw data may be detection data provided by a government affair cloud platform and traffic data provided by each traffic operation unit party, which are respectively:
the public transportation field: the original data in the bus field mainly comprises passenger flow analysis data, line analysis data, vehicle analysis data and station analysis data of bus operation management;
the field of leasing: the method mainly comprises the steps of getting-on and getting-off hotspot analysis, getting-on and getting-off migration diagrams, order analysis data, vehicle aggregation data and the like;
the rail transit field: the method mainly comprises passenger flow analysis data on different time scales;
the field of highway management: the method mainly comprises basic point location analysis, overload timeout period analysis and site overload analysis;
the field of maritime data: the method mainly comprises ship distribution data, crew statistical data and the like;
the field of channel management: mainly comprises channel distribution data, channel monitoring data and the like;
the port management field: the system mainly comprises storage distribution data, storage management data, storage utilization data and the like;
the field of law enforcement of administrative operations: the method mainly comprises analysis data of two-passenger one-dangerous vehicles, electronic waybill migration data and the like;
the field of emergency treatment: the method mainly comprises accident analysis data, emergency event full-process monitoring data and the like;
the field of video monitoring: the method mainly comprises global analysis data, analysis data in various fields and the like.
Optionally, in the process of collecting the original traffic data, due to the diversity of data sources, repeated data may easily occur in the original data, which may cause invalid occupation of a storage space, and therefore, the following processing is correspondingly performed after step S100: after the raw data is collected, the raw data contained in each field is preprocessed, and the preprocessing mainly comprises the following steps:
extracting information in the original data, classifying the original data according to the content of the original data, obtaining a plurality of feature sets after classifying the original data, analyzing each feature set, specifically analyzing the relevance between the feature sets and the traffic information, grading the relevance between the feature sets and the traffic information, removing the feature sets with the relevance smaller than a preset value, deleting the data with high repeatability in the original data, and improving the utilization rate of a storage space.
S200, converting the data format of the original data to obtain the original data with the same data format in each traffic field;
specifically, all the digitized data in the data of each field, such as length, quantity, time, distance, etc., are subjected to format conversion on the basis of the quantity unit, distance unit, time unit and size unit of the international standard, and the data of different sources of each field related to traffic are converted into the same unit.
Optionally, in the data conversion process, due to the diversity of the data types, a situation that the data format is difficult to convert may occur, and accordingly, after the step S200, the following processing is performed: acquiring abnormal data occurring in the format conversion process of the original data, sending the abnormal data to a manager, and acquiring evaluation analysis of the manager on the abnormal original data;
if the evaluation analysis result is that the abnormal original data has no analysis value, removing the abnormal original data;
and if the evaluation analysis result indicates that the abnormal original data has analysis value, adding an independent data layer and storing the abnormal original data in the independent data layer.
S300, a database is pre-established, wherein a plurality of data layers based on geographic information data are arranged in the database, and the data layers correspond to the source fields of original data one by one;
specifically, the data layers are set to correspond to the traffic-related fields one to one, the data in each field is stored in the corresponding data layer, the original data in each data layer is identified, and in the data layer in which the original data has the characteristics of a dynamic change, the original data with dynamic change is subjected to statistical analysis to obtain the steady-state statistical data of the data with dynamic change, for example, as follows: in the field of public transport, public transport passenger flow data are dynamically changed, and relatively stable statistical data such as public transport daily average passenger flow data, passenger flow data change curves and the like are obtained through statistical analysis in the step.
After the steady-state statistical data are obtained, the category number of the steady-state statistical data is counted, data sub-layers with the number equal to the category number of the steady-state statistical data are divided in the data layers, the steady-state statistical data are stored in the data sub-layers respectively and are updated according to a preset period, the preset period can be based on the attribute of the data, and a corresponding period can be designed according to the frequency of data change, and can be twelve hours, one day, one week, fifteen days, one month and the like.
S400, giving geospatial attributes to the initial data, mapping the initial data in data layers of corresponding fields based on the geospatial attributes, and superposing the data layers to obtain a comprehensive data platform;
specifically, geospatial information acquired or related to each field of data is acquired, the geospatial information is bound with initial data, and then distribution of the initial data in the data layer is adjusted according to the geospatial information, so that the initial data in the data layer corresponds to the geospatial information.
And meanwhile, setting a time axis in the database, and calibrating and corresponding each data layer according to the time attribute in each layer.
S500, carrying out traffic analysis and operation management based on a comprehensive data platform;
optionally, after the data are integrated and correlated, in order to enhance the practicability of the data, the following process may be performed after step S500: extracting common features from a plurality of data layers in a database, and developing a common management tool based on the common features;
utilizing the common management tool to carry out common management on different data layers with the same common characteristics, wherein the common management tool mainly comprises:
the method comprises the following steps of layer management, point data drawing, line data drawing, polygon data drawing, thermodynamic diagrams, area diagrams, tool bars, track playback and the like, and therefore convenience of layer management is improved.
Based on the above method, the embodiment of the application further discloses a traffic information visualization analysis system based on big data, and the reference diagram includes:
the data collecting module 1 is used for collecting original data, geographic information data and the like related to each field of traffic;
the data processing module 2 is used for processing the original data so that the original data meet the condition of data fusion;
the database module 3 is used for integrating and hierarchically storing processed original data from different sources;
the analysis application module 4 is used for carrying out comprehensive analysis on the data in the database module and actually carrying out application based on the analysis result;
the extended application module 5 is used for performing secondary application in other fields by using the data in the database module;
and the application interface module 6 is used for realizing the connection between the database module and the expansion application module.
The embodiment of the application also discloses an intelligent terminal, which comprises a memory and a processor, wherein the memory is stored with a computer program which can be loaded by the processor and can execute the traffic information visualization analysis method based on the big data.
The embodiment of the present application further discloses a computer-readable storage medium, which stores a computer program that can be loaded by a processor and execute a big data based traffic information visualization analysis method as described above, and the computer-readable storage medium includes, for example: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
The above examples are only used to illustrate the technical solutions of the present application, and do not limit the scope of protection of the application. It is to be understood that the embodiments described are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from these embodiments without making any inventive step, are within the scope of the present application.
Claims (8)
1. A traffic information visual analysis method based on big data is characterized by comprising the following steps:
acquiring geographic information data and original data of each field related to traffic;
carrying out data format conversion on the original data to obtain the original data with the same data format in each field of traffic;
the method comprises the steps that a database is established in advance, a plurality of data layers based on geographic information data are arranged in the database, and the data layers correspond to the source fields of original data one by one;
giving geospatial attributes to the initial data, mapping the initial data in data layers of corresponding fields based on the geospatial attributes, and superposing the data layers to obtain a comprehensive data platform;
carrying out traffic analysis and operation management based on a comprehensive data platform;
before the data format conversion is performed on the original data and the original data with the same data format in each traffic field is obtained, the method further comprises the following steps:
preprocessing raw data, wherein the preprocessing comprises the following steps:
acquiring original data, classifying information contained in the original data, and acquiring a plurality of feature sets;
performing relevance analysis between the feature set and the traffic information, setting a relevance threshold value, and removing the feature set of which the relevance with the traffic information is lower than the relevance threshold value;
the pre-established database is divided into a plurality of data layers based on geographic information data, and the data layers are in one-to-one correspondence with the source fields of the original data, specifically:
setting the data layers to be in one-to-one correspondence with traffic-related fields, respectively storing data of each field in the corresponding data layers, identifying original data in each data layer, and performing statistical analysis on the dynamically-changed original data in the data layers with the dynamically-changed characteristics of the original data to obtain steady-state statistical data of the dynamically-changed data; after the steady-state statistical data are obtained, the category number of the steady-state statistical data is counted, data sub-layers with the number equal to the category number of the steady-state statistical data are divided in the data layers, and the steady-state statistical data are stored in the data sub-layers respectively and are updated according to a preset period;
the method further comprises the following steps:
extracting common characteristics from a plurality of data layers in the database, and developing a common management tool based on the common characteristics;
using the common management tool to carry out common management on different data layers with the same common characteristics;
wherein, the commonality management tool includes: layer management, point data drawing, line data drawing, polygon data drawing, thermodynamic diagrams, region diagrams, tool bars, and trajectory playback.
2. The big data-based traffic information visualization analysis method according to claim 1, wherein the method further comprises:
adding a time axis in the database, giving time attributes to the initial data in each data layer, and synchronizing each layer on the time axis based on the time attributes.
3. The traffic information visualization analysis method based on big data according to claim 1, characterized in that: the method further comprises the following steps:
carrying out statistical analysis on the dynamically changed initial data to obtain steady-state statistical data of the dynamically changed initial data;
and adding a data sub-layer in a data layer corresponding to the dynamic initial data, and storing the steady-state statistical data in the data sub-layer.
4. The big data-based traffic information visual analysis method according to claim 1, wherein the method further comprises:
acquiring abnormal original data with abnormal data format conversion, and acquiring evaluation analysis of the abnormal original data manually;
if the evaluation analysis result is that the abnormal original data has no analysis value, removing the abnormal original data;
and if the evaluation analysis result indicates that the abnormal original data has analysis value, adding an independent data layer and storing the abnormal original data in the independent data layer.
5. A traffic information visualization analysis system based on big data is characterized in that: the system comprises:
the data collecting module (1) is used for collecting original data and geographic information data related to each traffic field;
the data processing module (2) is configured to process raw data so that the raw data meets a condition for performing data fusion, and specifically includes: carrying out data format conversion on the original data to obtain the original data with the same data format in each traffic field;
the database module (3) is used for integrating and hierarchically storing processed original data from different sources;
the analysis application module (4) is used for comprehensively analyzing the data in the database module and actually applying the data based on the analysis result;
the data processing module (2) is further configured to: preprocessing raw data, wherein the preprocessing comprises the following steps:
acquiring original data, classifying information contained in the original data, and acquiring a plurality of feature sets;
performing relevance analysis between the feature set and the traffic information, setting a relevance threshold value, and removing the feature set of which the relevance with the traffic information is lower than the relevance threshold value;
the database module (3) is also used for: the method comprises the steps that a database is established in advance, a plurality of data layers based on geographic information data are arranged in the database, and the data layers correspond to the source fields of original data one by one; setting the data layers to be in one-to-one correspondence with traffic-related fields, respectively storing data of each field in the corresponding data layers, identifying original data in each data layer, and performing statistical analysis on the dynamically-changed original data in the data layers with the dynamically-changed characteristics of the original data to obtain steady-state statistical data of the dynamically-changed data; after the steady-state statistical data are obtained, the category number of the steady-state statistical data is counted, data sub-layers with the number equal to that of the categories of the steady-state statistical data are divided in the data layers, and the steady-state statistical data are stored in the data sub-layers respectively and are updated according to a preset period;
the analysis application module (4) is further configured to: extracting common features from a plurality of data layers in the database, and developing a common management tool based on the common features; utilizing the common management tool to carry out common management on different data layers with the same common characteristics;
wherein, the commonality management tool includes: layer management, point data drawing, line data drawing, polygon data drawing, thermodynamic diagrams, region diagrams, tool bars and track playback;
the analysis application module (4) is further configured to: giving geospatial attributes to the initial data, mapping the initial data in data layers of corresponding fields based on the geospatial attributes, and superposing the data layers to obtain a comprehensive data platform; and carrying out traffic analysis and operation management based on the comprehensive data platform.
6. The big data based traffic information visualization and analysis system according to claim 5, further comprising:
the extended application module (5) is used for carrying out secondary application by utilizing the data in the database module;
and the application interface module (6) is used for realizing the connection between the database module and the extended application module.
7. An intelligent terminal, comprising a memory and a processor, the memory having stored thereon a computer program which can be loaded by the processor and which performs the method of any of claims 1 to 4.
8. A computer-readable storage medium, in which a computer program is stored which can be loaded by a processor and which executes the method of any one of claims 1 to 4.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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