CN111144384A - Police affair data processing system based on video structured application - Google Patents
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
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Abstract
The invention provides a police service data processing system based on video structured application, which comprises load balancing equipment, acquisition equipment, a real-time stream processing module and a structured storage module, wherein the load balancing equipment sends structured or semi-structured data generated by a data source to the acquisition equipment, the acquisition equipment identifies the structured data of different manufacturers according to different ports, the structured data are sent to a cache after standard conversion, the real-time stream processing module reads the structured data from the cache and executes data statistics, identification, alarm and storage service, and the structured storage module is connected with the real-time stream processing module to store the acquired structured description data of the unstructured data and the service data generated by real-time stream processing; a uniform storage scheme is adopted to reduce the data storage cost and provide abundant data application for the end user; the problems that a plurality of data shares exist and a plurality of times of retrieval are needed are solved; the method can provide abundant service application for police service and security protection clients.
Description
Technical Field
The invention relates to the field of data processing, in particular to a police affair data processing system based on video structured application.
Background
In the current video structured market, products are manufactured and packaged around algorithms, competition relationships exist among algorithm manufacturers, data acquisition equipment acquires data through different protocols, data source data generated by the data acquisition equipment cannot be analyzed and processed in a unified mode, inconvenience is brought to users, data analysis and processing often need to be called among multiple manufacturers in turn, background services need to manage multiple algorithm sources, results cannot be recognized universally among the manufacturers, and certain deviation exists in the results.
Disclosure of Invention
The invention aims to provide a police affair data processing system based on video structured application, which manages data from collection, storage, management and four angles, uses a high-throughput low-delay software structure in the aspect of collection and ensures that the data safely falls to the ground; in the aspect of storage, the idea of cloud storage is adopted, so that the service life of data storage is prolonged while the safe storage of the data is ensured; in the aspect of management, secondary feature processing is carried out on the face data by carrying out unstructured processing on different data sources of the same type, and the face data are converted into unified feature data, so that the problems that multiple data exist and multiple times of retrieval are needed are solved, and in the aspect of use, rich service application can be provided for security clients by using a big data analysis technology.
The police affair data processing system based on the video structured application comprises load balancing equipment, acquisition equipment, a real-time stream processing module and a structured storage module, wherein the load balancing equipment sends structured or semi-structured data generated by a data source to the acquisition equipment, the acquisition equipment identifies the structured data of different manufacturers according to different ports, the structured data are sent to a cache after standard conversion, the real-time stream processing module reads the structured data from the cache and executes data statistics, identification, alarming and storage services, and the structured storage module is connected with the real-time stream processing module to store the acquired structured description data of the unstructured data and the service data generated by real-time stream processing.
Furthermore, the acquisition device comprises an access module, a data channel and a co-processing unit; the data channel transmits different structured data accessed by the access module to the co-processing unit, and the co-processing unit performs standard conversion on the data and forwards the data to the cache.
Furthermore, the system also comprises an offline data analysis unit connected with the structured storage module, and the offline data analysis unit is used for analyzing and processing the acquired data.
Further, the structural description data comprises acquisition source information, target structural feature data, target identification data, target alarm data, target feature value digital matrix data and target archive data.
Furthermore, the system also comprises a background service system and a client, wherein the background service system is connected with the real-time stream processing module and the structured storage module, and processes a data request from the client through a real-time analysis application module, a report form application module, a historical snapshot query application module, a control task management application module, a testimony comparison application module and a data analysis application module.
Furthermore, the real-time stream processing module adopts a distributed real-time stream processing framework to process and store each piece of data read from the cache, and sends alarm information generated by service processing to the client through the background service system.
Furthermore, the system also comprises an object storage module for realizing the unstructured storage of the pictures and the videos, wherein the object storage module is connected with the real-time stream processing module and is used for storing the scene graph, the target small graph and the alarm video media data, and the object storage module can provide a standard gateway interface for the outside so as to facilitate the retrieval of the media data by the client.
Furthermore, the real-time stream processing module is also connected with a machine learning model and provides training data required by the training of the human face features of the machine learning model.
Furthermore, the real-time stream processing module comprises an analysis unit, a distribution unit, a statistic module and an alarm detection module;
an analysis unit: analyzing original image data into scene graph data and target value object data;
a distribution unit: distributing the analyzed scene graph data to an object storage module, disassembling target value object data, and then respectively distributing the disassembled target small graph and the target structured data to the object storage module and the structured storage module;
a statistic module: carrying out real-time service statistics on data containing a target value object in a cache;
the alarm detection module: and generating alarm information for the target value object data according to the statistical result of the statistical module.
Further, the real-time stream processing comprises message analysis, face extraction, feature comparison and alarm information generation; the service data comprises original pictures, face information and feature information.
The invention has the beneficial effects that: the large data and cloud storage architecture is used, the advantages of innate data storage and processing are achieved, the difficulty of data acquisition of the platform-level structured acquisition terminal is reduced, various structured terminal sensors can be efficiently accessed and processed, the data storage cost is reduced by adopting a uniform storage scheme, and abundant data application is provided for an end user; the problems that a plurality of data shares exist and a plurality of times of retrieval are needed are solved; the method can provide abundant service application for police service and security protection clients.
Drawings
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a data processing flow diagram of the present invention;
fig. 3 is a flow chart of the real-time streaming process of the present invention.
Detailed Description
In order to more clearly understand the technical features, objects and effects of the present invention, the embodiments of the present invention will be described with reference to the drawings, wherein the data sources 1, 2 and 3 are only used for showing and illustrating multiple data sources, and the present embodiment is not limited to these 3 data sources, and is not used for further limiting the present invention, and it should be understood by those skilled in the art.
The police service data processing system based on video structured application as shown in fig. 1 includes a load balancing device, an acquisition device, a real-time stream processing module, a structured storage module, a machine learning model, and an object storage module, where the load balancing device sends structured or semi-structured data generated by a data source to the acquisition device, the acquisition device identifies structured data of different manufacturers according to different ports, performs standard conversion on the data, and sends the data to a cache, the real-time stream processing module reads the structured data from the cache and performs data statistics, identification, alarm, and storage service, and the structured storage module is connected to the real-time stream processing module to store the acquired structured description data of the unstructured data and the service data generated by real-time stream processing.
The acquisition equipment comprises an access module, a data channel and a co-processing unit, wherein the access module can carry out plug-in configuration or development according to different manufacturers, the data channel can be divided into a memory type, a file type and a message queue type, the memory type can be adopted for general small-batch application, the file type is used for data needing special conversion, the message queue type is adopted for high-concurrent data processing, the co-processing unit is used for carrying out internal standard conversion on the data to form a uniform processing format, and the co-processing unit can be connected to different platforms to form cascaded data transmission as a data outflow party; the data channel transmits different structured data accessed by the access module to the co-processing unit, and the co-processing unit performs standard conversion on the data and forwards the data to the cache.
The structured storage module is also connected with an offline data analysis unit, and the offline data analysis unit is used for analyzing and processing the acquired data; the offline data analysis mainly comprises Spark data analysis, generated data are processed to form a data warehouse, a data mart and the like, data support is provided for application of people flow, key people, tracks, reports and the like, offline calculation is also interacted with a machine learning model regularly, and blindness is compensated for feature learning.
The machine learning model is connected with the real-time stream processing module and provides training data required by the human face feature training of the machine learning model; the system is divided into online flow calculation and offline data analysis, has the characteristics of large data, infinite quantity and the like according to the characteristics of data generated by video structuring, can well support the processing of the data by using the online flow calculation, and can provide continuous learning data for an online characteristic machine learning model.
The structural description data comprises acquisition source information, target structural characteristic data, target identification data, target alarm data, target characteristic value digital matrix data and target archive data.
The system also comprises a background service system and a client, wherein the background service system is connected with the real-time stream processing module and the structured storage module and processes data requests from the client through a real-time analysis, report form, historical snapshot query, deployment and control task management, testimony comparison and data analysis application module.
The real-time stream processing module adopts a distributed real-time stream processing framework to process and store each piece of data read from the cache, and sends alarm information generated by service processing to the client through the background service system.
The object storage module is connected with the real-time stream processing module and used for realizing unstructured storage of pictures and videos, the unstructured storage comprises storage of scene graphs, target small graphs and alarm video media data, and the object storage module can provide a standard gateway interface for the outside and facilitates retrieval of the media data by a client.
As shown in the data processing flow of fig. 2, after the data source generates semi-structured and fully structured data, the load balancing device sends the data to the acquisition device, the load balancing device is responsible for forwarding the data to a certain acquisition port of the acquisition device, the acquisition device identifies the structured data of different manufacturers according to different ports, and sends the structured data to the message queue Kafka for caching after standard conversion processing, the design purpose is to eliminate peak pressure during data transmission, and the acquisition device acquiesces to use the video structured protocol of the police department 1400 to acquire the data.
And the real-time stream processing module takes out the structured data from the message queue cache by adopting a Hadoop yarn deployment mode, and performs data statistics, identification, alarm and storage services.
The system provides two types of data storage modes, namely object storage and structured data storage; the object storage is used for storing data such as a scene large image, a target small image, an alarm small video and the like, has the advantages of convenience in calling, flexibility in capacity expansion, safety and the like, breaks through the limit of the capacity of single-machine data storage, and ensures the data safety; the structured data store is used for storing the acquired structured description data of the unstructured data, and generally comprises acquisition source information, target structured feature data (age, height, wearing, and the like), target identification data (certificates, license plate numbers, and the like), target alarm data, target feature value digital matrix data, target archive data, and the like.
The off-line data analysis unit is used for analyzing and processing the acquired data, can perform business applications such as frequent, same-row, daytime and nighttime, 1: N retrieval, database collision comparison and the like according to business characteristics, and can be configured to use a server resource with a GPU to accelerate data comparison and retrieval during data retrieval.
The background service system adopts a micro-service architecture and is divided into application modules of real-time analysis, report form, historical snapshot query, deployment and control task management, testimony comparison, data analysis and the like.
The real-time stream processing module comprises an analysis unit, a distribution unit, a statistic module and an alarm detection module;
an analysis unit: receiving original image data of a data queue in a cache and analyzing the original image data into scene graph data and target value object data;
a distribution unit: distributing the analyzed scene graph data to an object storage module, disassembling target value object data, and then respectively distributing the disassembled target small graph and the target structured data to the object storage module and the structured storage module;
a statistic module: carrying out real-time service statistics on data containing a target value object in a cache;
the alarm detection module: and generating alarm information for the target value object data according to the statistical result of the statistical module.
As shown in fig. 3, the real-time stream processing includes message parsing, face extraction, feature comparison, and alarm information generation; the service data comprises original pictures, face information and feature information.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims.
Claims (10)
1. The police data processing system based on video structured application is characterized by comprising load balancing equipment, acquisition equipment, a real-time stream processing module and a structured storage module, wherein the load balancing equipment sends structured or semi-structured data generated by a data source to the acquisition equipment, the acquisition equipment identifies the structured data of different manufacturers according to different ports, the structured data are sent to a cache after standard conversion, the real-time stream processing module reads the structured data from the cache and executes data statistics, identification, alarm and storage services, and the structured storage module is connected with the real-time stream processing module to store the acquired structured description data of the unstructured data and the service data generated by real-time stream processing.
2. A police data processing system based on video structured application according to claim 1, wherein the collection device comprises an access module, a data channel and a co-processing unit, the data channel transmits different structured data accessed by the access module to the co-processing unit, and the co-processing unit performs standard transformation on the data and forwards the data to the cache.
3. A police data processing system based on video structured application according to claim 1, further comprising an offline data analysis unit connected to the structured storage module, wherein the offline data analysis unit is configured to analyze and process the collected data.
4. A police data processing system based on video structured application according to claim 1, wherein the structured description data comprises acquisition source information, target structured feature data, target identification data, target alarm data, target feature value digital matrix data and target archive data.
5. The video structured application based police data processing system of claim 1, further comprising a background service system and a client, wherein the background service system is connected to the real-time stream processing module and the structured storage module, and processes data requests from the client through the real-time analysis, report, historical snapshot query, deployment task management, testimony comparison and data analysis application module.
6. A police service data processing system based on video structured application as claimed in claim 5, wherein the real-time stream processing module employs a distributed real-time stream processing framework to process and store each piece of data read from the cache, and send alarm information generated by the service processing to the client through the background service system.
7. The police data processing system based on video structured application of claim 5, further comprising an object storage module for implementing unstructured storage of pictures and videos, wherein the object storage module is connected to the real-time stream processing module and is used for storing scene graphs, target thumbnails and alarm video media data, and the object storage module can provide a standard gateway interface for external use to facilitate retrieval of the media data by the client.
8. A police service data processing system based on video structured application as claimed in claim 1, wherein the real-time stream processing module is further connected with a machine learning model and provides training data required by human face feature training of the machine learning model.
9. A police service data processing system based on video structured application according to claim 6 or 7, characterized in that the real-time stream processing module comprises a parsing unit, a distribution unit, a statistics module and an alarm detection module;
an analysis unit: analyzing original image data into scene graph data and target value object data;
a distribution unit: distributing the analyzed scene graph data to an object storage module, disassembling target value object data, and then respectively distributing the disassembled target small graph and the target structured data to the object storage module and the structured storage module;
a statistic module: carrying out real-time service statistics on data containing a target value object in a cache;
the alarm detection module: and generating alarm information for the target value object data according to the statistical result of the statistical module.
10. A police affairs data processing system based on video structured application of claim 1, wherein the real-time stream processing comprises message parsing, face extraction, feature comparison and alarm information generation; the service data comprises original pictures, face information and feature information.
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Application publication date: 20200512 |