CN112258370A - Regional vision AI platform and data processing method based on regional vision AI platform - Google Patents
Regional vision AI platform and data processing method based on regional vision AI platform Download PDFInfo
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Abstract
The embodiment of the invention provides a regional vision AI platform and a data processing method based on the regional vision AI platform, wherein the regional vision AI platform is deployed in a fusion data innovation center, and the fusion data innovation center is connected with a regional Internet of things sensing system through a regional Internet of things platform in a space-time Internet of things engine; the regional vision AI platform acquires visual data through the regional Internet of things sensing system; and the regional visual AI platform analyzes and processes the visual data so as to provide support for a regional application portal platform through the fusion data creation center. According to the embodiment of the invention, the regional visual AI platform is constructed in the region so as to uniformly process the visual data and avoid the situation of repeated processing or function overlapping, and the acquired visual data is transmitted to the regional application portal after being calculated and processed by the regional visual AI platform, so that service support can be provided for the regional application portal in time.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a regional vision AI platform and a data processing method based on the regional vision AI platform.
Background
At present, while the development and application of big data are rapidly developed, there are many problems, such as: insufficient data opening and sharing, not wide application field, insufficient development and utilization of data resources, serious disorder abuse phenomenon and the like.
In smart city construction, big data plays an important role, and according to the experience of smart city construction in the past, due to the lack of a unified development management platform, each city application can only be independently constructed, so that the problems of data barriers and application barriers exist among all the city applications, a large amount of information islands are formed, and the function and value of the big data cannot be played. Therefore, a unified cloud platform which can be popularized and used is urgently needed to be explored for breaking the stripe division among urban applications, eliminating the information gap and realizing the quality fusion of big data.
In the process of constructing a unified development management platform, a large number of different services such as traffic services and road condition services are often involved, so that when visual data from different services are processed, the visual data are difficult to be processed in a unified manner, repeated processing or overlapping functions are easy to occur in the processing process, and platform resources are wasted.
Disclosure of Invention
In view of the above problems, it is proposed to provide a regional visual AI platform and a data processing method based on the same that overcome or at least partially solve the above problems, comprising:
a regional vision AI platform is deployed in a fusion data innovation center, and the fusion data innovation center is connected with a regional Internet of things sensing system through a regional Internet of things platform in a space-time Internet of things engine;
the regional vision AI platform acquires visual data through the regional Internet of things sensing system;
and the regional visual AI platform analyzes and processes the visual data so as to provide support for a regional application portal platform through the fusion data creation center.
Optionally, the regional visual AI platform is connected to a regional cloud computing platform through the spatio-temporal internet-of-things engine, and the regional visual AI platform calls the regional cloud computing platform to perform data computation.
Optionally, the regional visual AI platform includes a large-scale visual computing platform, a full-time global traffic dynamic perception engine, and a progressive video search engine;
the large-scale visual computing platform is used for performing basic computing on the visual data, the full-time global traffic dynamic perception engine is used for performing traffic event monitoring on the visual data, and the progressive video search engine is used for performing target identification on the visual data.
Optionally, the large-scale visual computing platform has any one or more of the following functions:
data access function, data calculation function, visual search function.
Optionally, the full-time global traffic dynamics perception engine has any one or more of the following functions:
a traffic event awareness function, and a traffic event alert function.
Optionally, the progressive video search engine has any one or more of the following functions:
a target search function, a target analysis function.
A data processing method based on a regional visual AI platform is characterized in that the regional visual AI platform is deployed in a fusion data innovation center, and the fusion data innovation center is connected with a regional Internet of things sensing system through a regional Internet of things platform in a space-time Internet of things engine;
the regional vision AI platform acquires visual data through the regional Internet of things sensing system;
and the regional visual AI platform analyzes and processes the visual data so as to provide support for a regional application portal platform through the fusion data creation center.
Optionally, the area vision AI platform is connected to an area cloud computing platform through the spatiotemporal internet of things engine;
and the regional vision AI platform calls the regional cloud computing platform to perform data computing.
An electronic device comprising a processor, a memory and a computer program stored on the memory and capable of running on the processor, the computer program, when executed by the processor, implementing the data processing method based on the area vision AI platform as described above.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, implements the above data processing method based on the area vision AI platform.
The embodiment of the invention has the following advantages:
in the embodiment of the invention, the regional visual AI platform is deployed in the fusion data innovation center, the fusion data innovation center is connected with the regional Internet of things sensing system through the regional Internet of things platform in the spatio-temporal Internet of things engine, the regional visual AI platform acquires visual data through the regional Internet of things sensing system, the regional visual AI platform analyzes and processes the visual data to provide support for the regional application portal platform through the fusion data innovation center, the regional visual AI platform is constructed in a region to uniformly process the visual data, the repeated processing or function overlapping is avoided, the acquired visual data is transmitted to the regional application portal through the regional visual AI platform after calculation, and service support can be provided for the regional application portal in time.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is an overall architecture diagram of a cloud platform according to an embodiment of the present invention;
FIG. 2 is a diagram of a service architecture of a regional visual AI platform according to an embodiment of the invention;
FIG. 3 is a system architecture diagram of a local vision AI platform according to an embodiment of the invention;
FIG. 4 is a diagram illustrating a large-scale visual computing platform of a regional visual AI platform according to an embodiment of the invention;
FIG. 5 is a schematic diagram of a data computation service of a regional visual AI platform according to an embodiment of the invention;
FIG. 6 is a diagram of a data architecture of a local visual AI platform according to an embodiment of the invention;
FIG. 7 is a schematic diagram illustrating data transmission and data output of a local-vision AI platform according to an embodiment of the invention;
FIG. 8 is a deployment architecture diagram of a regional vision AI platform according to an embodiment of the invention;
FIG. 9 is a network layout diagram of a regional visual AI platform according to an embodiment of the invention;
FIG. 10 is a schematic diagram of a platform security architecture of a regional visual AI platform according to an embodiment of the invention;
FIG. 11 is a schematic structural diagram of a local area visual AI platform according to an embodiment of the invention;
fig. 12 is a flowchart illustrating steps of a data processing method based on a regional visual AI platform according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the construction of the smart city, a cross-domain multidimensional big data public service cloud platform with unified standards, unified entries, unified acquisition, unified management, unified service and unified data is built, an urban-level unified data standard is built, a data barrier is broken, the Internet of Things (IOT) and system data resources of a region are converged, all service systems of the smart city are borne, and the smart city ecology is created through data open sharing, platform capability opening and the smart city ecology creation.
The construction target of the cross-domain multi-dimensional big data public service cloud platform is that various main bodies, all levels of business coordination mechanisms and intelligent application in various fields of a smart city are built by introducing advanced technologies such as cloud computing, big data, Internet of things, mobile interconnection and the like to form an open, interconnected and intelligent smart city ecological system, so that data sharing in various fields of city management, social civilian life, resource environment and economic industry is promoted, administrative efficiency, city management capability and resident life quality are improved, industry fusion development is promoted, industry transformation and upgrading are promoted, business modes are innovated, and popularization and application of the cross-domain multi-dimensional big data public service cloud platform are realized.
A cross-domain multi-dimensional big data public service cloud platform mainly relates to leading-edge IT information technologies such as cloud computing, big data, Internet of things and artificial intelligence:
1. cloud computing technology: the cloud computing mainly comprises six core components including elastic computing, a network, storage, a database, safety and middleware, and provides elastic, quick, stable and safe resources and computing power services.
2. Big data technology: the data construction and management are taken as the core, and the capabilities of data communication, data integration, data management, data sharing and the like are provided through related components such as data calculation, data development, data analysis, data visualization and the like.
3. The technology of the Internet of things comprises the following steps: the Internet of things platform provides one-stop services such as equipment access, equipment management, monitoring operation and maintenance, safety guarantee and the like, can provide basic capability support of the Internet of things as an important component of a space-time Internet of things engine, and meets the requirement of intelligent management of a novel smart city in the future.
4. Artificial intelligence technology: an AI algorithm development platform is taken as a core, and a series of intelligent services are provided through related components such as a visual AI, text voice recognition, a Natural Language Processing (NLP) platform, a map service and the like.
As shown in fig. 1, an internet engine, a space-time internet of things engine, a cross-domain multi-dimensional big data engine, a regional internet of things sensing system, an open service gateway, a regional application portal, a secure operation and maintenance system, an open operation system, and other structures are deployed in a cloud platform, wherein the open service gateway includes a fusion service sharing center and a fusion data innovation center.
The following describes the details of the cloud platform:
space-time internet of things engine
The space-time internet of things engine is composed of a Geographic Information System (GIS), a Building Information Model (BIM) and a regional internet of things platform and is used for applying space data and a three-dimensional model to regional internet of things.
The geographic information system is a special and very important spatial information system, and can collect, store, manage, calculate, analyze, display and describe relevant geographic distribution data in the whole or part of space under the support of a computer hardware and software system.
The building information model is based on a three-dimensional digital technology, integrates engineering data models of various related information of a building engineering project, and the built model is in continuous deepening and changing along with the progress of the project.
(II) Internet Engine
Cloud efficient (DevOps) and distributed middleware are deployed in an Internet engine and used for achieving efficient resource sharing and efficient function sharing of data.
Wherein, DevOps is a combination word of Development and Operations, which is a collective name of a group of processes, methods and systems, and is used for promoting Development of application programs/software engineering, communication, cooperation and integration between technical operation and quality assurance departments.
The distributed middleware is a kind of software between the application system and the system software, and links each part of the application system or different applications on the network by using the basic service or function provided by the system software, thereby achieving the purpose of resource sharing and function sharing.
(III) Cross-domain multidimensional big data engine
The cross-domain multi-dimensional big data engine is provided with a unified data management platform and a big data engine and used for realizing the unified management of cross-domain data.
(IV) regional Internet of things sensing system
The regional Internet of things sensing system is composed of relevant sensing equipment and equipment data such as pressure, humidity, a camera, a light source, infrared sensing and temperature.
(V) converged service sharing center and converged data innovation center
The fusion service sharing center may create different data sharing centers after fusing the data of each region according to service classification, for example: the system comprises a personal information center, a credit information center, a legal information center, a financial service center, a travel service center, a comprehensive treatment service center, a space-time service center, an Internet of things service center and other sharing centers.
The fusion data innovation center realizes the innovative application of fusion data through a data fusion system and an AI algorithm system, wherein the AI algorithm system comprises the following components: a full-time global traffic dynamic perception engine, a progressive video search engine and a large-scale visual computing platform.
The fusion service sharing center and the fusion data creation center fuse the data and then can present the processed data through the area application portal.
(VI) regional application Portal
In the regional application portal, the system is mainly divided into blocks such as ecological environmental protection, global tourism, property cities, enterprise intelligent services, electronic fences, intelligent communities, international talent islands, regional economic brains, cross-border e-commerce and cross-domain authentication. The user enters each plate through the regional application portal and acquires the information corresponding to each plate formed by the processed data.
(VII) safety operation and maintenance system
The safe operation and maintenance system comprises safety guarantee, multi-cloud management, regional cloud unified management, a platform interface and the like and is used for guaranteeing the safe operation of the whole cloud platform.
(eighth) open operation system
The open operation system comprises a uniform entrance, an ability open, an operation platform and the like, and is used for establishing a uniform entrance of data and accessing the data of each area.
(nine) other structures
In addition, data can be processed through a supercomputing cluster, a regional cloud computing platform and an openstackfirmware cluster (one open-source cloud computing management platform project is a combination of a series of software open-source projects).
The area vision AI platform is described in detail below: the area vision AI platform includes: platform planning, network planning, and platform security planning, wherein the platform planning may fully resolve the area vision AI platform from the business architecture, the system architecture, the data architecture, and the deployment architecture according to different dimensions, the network planning may include the network architecture, and the platform security planning may include the platform security architecture.
One, platform planning
(1) Business framework
As shown in FIG. 2, the business architecture exposes the business functions and computational models in the area vision AI platform.
The service functions of the full-time global traffic dynamic perception engine comprise a traffic accident monitoring function and a traffic jam monitoring function, and the service functions of the progressive video search engine comprise character recognition, non-motor vehicle recognition and motor vehicle recognition.
Wherein, the calculation model comprises a person/non-motor vehicle detection model, a person/non-motor vehicle characteristic detection model, a motor vehicle detection model and other detection models, and the other detection models can comprise a traffic accident monitoring model.
(2) System architecture
As shown in fig. 3, the system architecture shows the architecture of a full-time global traffic dynamics awareness engine, progressive video search engine deployed in a local vision AI platform.
The full-time global traffic dynamic perception engine and the progressive video search engine are supported by a large-scale visual computing platform and are deployed in a local visual AI platform in a Docker (application container engine) manner, and the dependent components in the local visual AI platform include OSS (Object Storage Service), ECS (electronic computer Service, cloud server), RDS (Relational Database Service), and the like.
As shown in FIG. 4, the large-scale visual computing platform includes a data access service, an image search service, and a data computing service.
The data access service is deployed in a proprietary cloud platform of the virtual cloud host in a Docker mode, and comprises a data access service, a data resource scheduling service, a worker (workbench) service and a metadata (metadata) service, wherein the data access service comprises a visual data normalization sub-service and other data normalization sub-services, the data access service is used for receiving video data, view data and other structural data, transmitting the video data, the view data and other structural data to an image search service and a data calculation service in a video stream, a picture stream and other data stream mode, and providing support for industry application and an industry visual algorithm engine, and the industry visual algorithm engine is a full-time global traffic dynamic perception engine and a progressive video search engine;
the data computing service is deployed on the heterogeneous virtual cloud host in a Docker mode, comprises the services of sequence computing, map computing, graph computing, real-time analysis, offline analysis, graph computation, model encryption and service authorization, model optimization, model concurrency, model scheduling and the like, and is used for providing support for image searching service;
the image search service comprises a distributed query engine and a feature index engine, wherein the distributed query engine comprises a node query service, a path query service, a sub-graph query service and a full-graph query service, the feature index engine comprises a visual index service, an atlas index service and a geometric index service, and the image search service is used for providing support for industry applications and industry visual algorithm engines.
As shown in fig. 5, the data computing service specifically includes an algorithm program, third party authorization authentication hardware and service, VPC (Virtual Private Cloud), security authentication, kubernets (open source platform for automated container operation), Flink (open source stream processing framework), and ECS, where the algorithm program includes a visual algorithm library, UDTF (User-Defined Table-Generating Functions), and Docker mirror image.
(3) Data architecture
As shown in fig. 6, the data architecture shows the inflow and outflow of business data and device data of a large-scale visual computing platform, a full-time global traffic dynamic perception engine, and a progressive video search engine deployed in a local visual AI platform.
The large-scale visual computing platform comprises a computing engine, wherein the computing engine comprises an access front end, a data access module, a computing front end, a computing module, a storage and search front end and a storage and search module, and the large-scale visual computing platform is used for supporting a full-time global traffic dynamic perception engine and a progressive video search engine.
The data access module comprises an internet video access sub-module, a view access sub-module, a streaming media forwarding service sub-module, a coil management sub-module, a pull frame and preset bit management sub-module, an MQ (Message Queue) and a DataHub (streaming data bus) pushing sub-module, and the data access module is used for receiving data provided by the internet video platform, the video sharing platform and the video image information base, processing the data and transmitting the processed data to data calculation service;
the computing module comprises a video and data input MQ submodule, an algorithm processing submodule and a structured output submodule, and is used for receiving the data transmitted by the data access module and transmitting the processed data to the image searching service;
the storage and search module comprises submodules such as a search engine, MQ, DataHub, RDS, ES (electronic search, search engine), OSS and the like, and is used for receiving the data transmitted by the calculation module.
As shown in fig. 7, the transmission of data in the data architecture includes a streaming media expansion service, the streaming media expansion service includes a streaming processing module group, a streaming output module group, and a central management server, the streaming processing module group includes a plurality of streaming processing modules, the streaming processing module group is configured to receive data transmitted by the video monitoring platform and various information provided by the central management server, and transmit the processed data to the streaming output module group, the streaming output module group includes a plurality of streaming output modules, the streaming output module group is configured to receive data transmitted by the streaming processing module group, and transmit the processed data to other applications, and the other applications may be large-scale visual computing platforms.
The data transmitted by the video monitoring platform can be data provided by an internet video platform, a video sharing platform and a video image information base.
The output of data in the data architecture may be represented by the following table:
(4) deployment architecture
As shown in fig. 8, the deployment architecture shows a deployment relationship architecture in the area vision AI platform, which can be divided into an OXS area and an outer pipe area.
The OXS area comprises a console, a RAM (Random Access Memory), an API (Application Programming Interface) gateway, an ECS (electronic communications system), a VIP (Virtual IP Address), wherein the RAM provides user authentication service for the console and provides authority authentication service for the API gateway, the console comprises a front-end Interface uniform inlet, the front-end Interface uniform inlet is connected with a streaming service interaction Interface, a computing service interaction Interface and a service monitoring Interface, the console is connected with a user and the API gateway in an HTTPS (hypertext Transfer Protocol over secure Protocol), and the API is connected with service Application in an HTTPS manner.
The outer pipe area comprises sNET (source address conversion), cloud monitoring, log service, VPC, user resource pool, MQ, ECS and RDS.
The sNET is used for acquiring Video streams in IPC (IP Camera)/NVR (Network Video Recorder)/lower-level platform, transmitting the Video streams to the VPC, and connecting the cloud monitoring and log service with the VPC;
the VPC comprises a local intermediate service, the local intermediate service comprises a data access module, a calculation module and a storage and search module, and the VPC is connected with an ECS and a VIP in an OXS area;
the data access module comprises a Video access center, a Video on demand center, a Video forwarding center, a Video Plan center and a Video streaming center, the Video access center, the Video on demand center and the Video forwarding center are respectively connected with the Video Plan center and the Video streaming center, and the data access module is used for receiving data transmitted by the sNET and transmitting the data to the computing module after processing;
the computing module comprises a Video Flow, a task management, a dispatching center, a computer Plan and a distributed large-scale Flow computing platform, the Video Flow, the task management and the dispatching center are respectively connected with the computer Plan and the distributed large-scale Flow computing platform, and the computing module is used for receiving data transmitted by the data access module, processing the data and transmitting the processed data to the user resource pool and the searching module;
the Search module comprises a deployment service, an algorithm service, an engine service, an index center and a Search Plan, wherein the algorithm service is connected with the deployment service, the engine service and the Search Plan, and the deployment service and the engine service are respectively connected with the Search Plan and the index center.
Second, network planning
Network architecture
As shown in fig. 9, for network planning of the regional visual AI platform, a large-scale visual computing platform in the regional visual AI platform may be deployed in a VPC of a cross-domain multidimensional proprietary cloud, and connected to a video monitoring private network through an internal diversion access area in an access area.
The large-scale visual computing platform comprises an equipment access platform and a computing server, and is connected with a full-time global traffic dynamic perception engine and a progressive video search engine;
the access area comprises an internet access area, an internal transfer access area, an external network access area and an external transfer access area.
Platform safety planning
Platform security architecture
As shown in fig. 10, for the platform security system of the area vision AI platform, security protection can be performed on the area vision AI platform respectively for the key point that a service provider needs to protect and the key point that an algorithm provider needs to protect.
The platform security architecture specifically comprises a service provider, an algorithm client, an algorithm library, a TW-KMS (Key Server), a TQ-Auth (authorization Server), and a Key protection (Codify).
A service provider is connected with an algorithm client through a client certificate (client. crt) and a client private key (client. key), and is connected with an authorization server certificate through an authorization server certificate (tqauth. crt) and an authorization server private key (tqauth. key);
the algorithm provider transmits the algorithm to the algorithm library, the algorithm library is embedded into the algorithm client, the algorithm provider is connected with the key server, and the algorithm provider transmits the model file to the key protection;
the key protection provides an extraction code, an encryption model and a private key for the algorithm library, and provides a key file for the key server, wherein the key file comprises the extraction code, the secret key and a public key;
the authorization server is connected with the key server through one-way SSL (Secure Sockets Layer) verification and model decryption, the algorithm client is connected with the authorization server through two-way SSL verification, service authorization and model decryption, and the algorithm client is connected with the authorization server and the key server through a service provider root certificate (CA.crt).
The algorithm client and the authorization server are connected through bidirectional SSL verification, service authorization and model decryption, and the method specifically comprises the following steps:
model and private key provided by algorithm library[1]Embedding a client certificate, a client private key and a service root certificate into a computerIn a legal Client (Client), an authorization server certificate, an authorization server private key and a service root certificate are embedded into an authorization server, and the service root certificate is also a service provider root certificate.
The method comprises the steps that an algorithm client and an authorization server are connected through bidirectional SSL verification encryption, service authorization in the algorithm client sends License data flow to a verification numerical signature in the authorization server, the verification numerical signature in the authorization server verifies the License online state, the data flow comprising License information is sent to model decryption in the algorithm client, the model decryption in the algorithm client sends the data flow comprising extraction codes and random numbers to a query key server in the authorization server, the query key server in the authorization server sends the data flow comprising the random numbers and decryption keys to a License renewal period in the algorithm client, and the decryption keys comprise public keys[2]And encrypting, wherein the License in the algorithm client sends a License data stream to the authorization server, and the authorization server sends the data stream containing the License information to the algorithm client.
[1] And [2] the algorithm provider uses a public key and a private key generated when an encryption model in the key protection, the private key is embedded in the algorithm library, and the key server stores the public key.
Referring to fig. 11, which illustrates a schematic structural diagram of a regional visual AI platform according to an embodiment of the present invention, a regional visual AI platform 110 is deployed in a converged data innovation center 100, and the converged data innovation center 100 is connected to a regional internet of things sensing system 300 through a regional internet of things platform 201 in a spatio-temporal internet of things engine 200;
the area can be a city, the fusion data innovation center 100 comprises a data fusion system and an AI algorithm system, the AI algorithm system comprises a full-time global traffic dynamic perception engine, a progressive video search engine and a large-scale visual computation platform, and the fusion data innovation center 100 realizes the innovative application of the fusion data through the data fusion system and the AI algorithm system;
the spatio-temporal internet-of-things engine 200 is composed of a Geographic Information System (GIS), a Building Information Model (BIM) and a regional internet-of-things platform 201, for applying spatial data and three-dimensional models to regional internet of things, such as city internet of things, a geographic information system is a special and very important spatial information system, and can be supported by computer hardware and software systems, the construction information model is based on three-dimensional digital technology and integrates engineering data models of various related information of construction engineering projects, the established model is in continuous deepening and changing along with the progress of the project, and the regional Internet of things platform 201 meets the requirement of future urban management by providing basic capability support of the Internet of things;
the regional internet of things sensing system 300 is composed of pressure, temperature, cameras, light sources, infrared sensing, and other related sensing devices and device data, the visual data can be acquired through the devices in the regional internet of things sensing system 300, such as the camera sensing devices, and the visual data can be video data and picture data;
the regional application portal platform 400 is mainly divided into blocks such as ecological environment protection, global tourism, property cities, enterprise intelligent services, electronic fences, intelligent communities, international talent islands, regional economic brains, cross-border e-commerce, cross-domain authentication, electronic fences and the like, and a user enters each block through the regional application portal and acquires information corresponding to each block formed by processed data.
In practical applications, the regional visual AI platform 110 may be deployed in the fusion data innovation center 100, and may be connected to the regional internet of things sensing system 300 through the regional internet of things platform 201 in the spatio-temporal internet of things engine 200.
The regional visual AI platform 110 collects visual data through the regional internet of things sensing system 300; the regional visual AI platform 110 analyzes and processes the visual data to provide support for the regional application portal platform 400 through the converged data innovation center 100.
After the regional internet of things sensing system 300 is connected, the regional internet of things sensing system 300 can collect visual data, the regional visual AI platform 110 can calculate the collected visual data, and further can analyze and process the visual data according to the calculation result, so as to provide support for the regional application portal platform 400 through the fusion data innovation center 100, for example, can provide visual service support for services in the regional application portal platform 400 according to the result of the visual data processing.
In an embodiment of the present invention, the regional visual AI platform 110 is connected to a regional cloud computing platform through the spatio-temporal internet-of-things engine 200, and the regional visual AI platform 110 invokes the regional cloud computing platform to perform data computation.
The regional cloud computing platform is used for processing data, such as data computing.
In practical application, the regional visual AI platform 110 may be connected to a regional cloud computing platform through the spatio-temporal internet-of-things engine 200, and may further invoke the regional cloud computing platform to perform data computation.
For example, the collected visual data may be transmitted to the regional cloud computing platform, the visual data may be calculated by the regional cloud computing platform, and the calculated result and the visual data are returned to the regional visual AI platform 110, and the regional visual AI platform 110 may analyze the calculated result and the visual data.
In an embodiment of the present invention, the local visual AI platform 110 includes a large-scale visual computing platform, a full-time global traffic dynamic perception engine, and a progressive video search engine; the large-scale visual computing platform is used for performing basic computing on the visual data, the full-time global traffic dynamic perception engine is used for performing traffic event monitoring on the visual data, and the progressive video search engine is used for performing target identification on the visual data.
The basic calculation can be to calculate the calculated result and the visual data returned by the regional cloud computing platform, to build an index for the visual data according to the calculated result, to provide search support for the full-time global traffic dynamic perception engine and the progressive video search engine, the traffic event can be a traffic accident event, a road congestion event, and the target can be a person or a bicycle.
In practical application, the regional visual AI platform 110 may collect visual data through the regional internet of things sensing system 300, further may invoke a regional cloud computing platform to compute the data, and receives a computed result and the visual data returned by the regional cloud computing platform through the large-scale visual computing platform, may perform basic computation on the large-scale visual computing platform, and may establish an index for the visual data according to the computed result.
After the index is established, the full-time global traffic dynamic perception engine searches traffic events for the visual data according to the index, so that the traffic events can be monitored, the progressive video search engine can search the visual data according to the index, and then the target can be identified according to the search result.
In an embodiment of the present invention, when the large-scale visual computing platform performs basic computing on the visual data, the large-scale visual computing platform may be specifically configured to:
performing data access on the visual data, performing data calculation on the visual data, and performing visual search on the visual data.
In practical application, the large-scale visual computing platform can be accessed to visual data acquired by the regional Internet of things sensing system, then the regional cloud computing platform can be called to perform data computing on the visual data, the visual data can be classified according to the computed result to obtain one or more classification categories corresponding to the visual data, indexes can be built according to different classification categories, then the corresponding visual data can be determined according to different indexes, and visual data searching service is provided.
In an embodiment of the present invention, when the full-time global traffic dynamic sensing engine monitors the visual data for a traffic event, the full-time global traffic dynamic sensing engine may be specifically configured to:
and carrying out traffic event perception on the visual data and carrying out traffic event warning on the visual data.
In practical application, the full-time global traffic dynamic sensing engine may respond to a search operation of a user, and further may determine one or more corresponding indexes according to the search operation, determine one or more corresponding visual data according to the indexes, determine corresponding traffic information according to the one or more visual data, determine a corresponding traffic event according to the traffic information, and determine corresponding warning information according to the traffic event to warn.
For example, a target in the visual data may be determined, speed information for the target may be determined according to the plurality of visual data, it may be further determined that the corresponding traffic event is a road congestion event according to the speed information, warning information corresponding to the road congestion event may be determined, and a traffic congestion warning may be performed on a vehicle traveling on the road.
In an embodiment of the present invention, when performing target recognition on the visual data, the progressive video search engine may specifically be configured to:
and performing target search and target analysis on the visual data.
In practical application, the progressive video search engine may respond to a search operation of a user, and further may determine one or more corresponding indexes according to the search operation, may determine one or more corresponding visual data according to the indexes, may perform contour information recognition on the visual data, and further may determine a target, such as a vehicle target, a pedestrian target, according to the contour information.
After the target is determined, the target can be subjected to characteristic information identification to obtain characteristic information of the target, such as clothing characteristics, color characteristics and height characteristics.
In the embodiment of the invention, the regional visual AI platform is deployed in the fusion data innovation center, the fusion data innovation center is connected with the regional Internet of things sensing system through the regional Internet of things platform in the spatio-temporal Internet of things engine, the regional visual AI platform acquires visual data through the regional Internet of things sensing system, the regional visual AI platform analyzes and processes the visual data to provide support for the regional application portal platform through the fusion data innovation center, the regional visual AI platform is constructed in a region to uniformly process the visual data, the repeated processing or function overlapping is avoided, the acquired visual data is transmitted to the regional application portal through the regional visual AI platform after calculation, and service support can be provided for the regional application portal in time.
Referring to fig. 12, a flowchart illustrating steps of a data processing method based on a regional visual AI platform according to an embodiment of the present invention is shown, where the regional visual AI platform is deployed in a fusion data innovation center, and the fusion data innovation center is connected to a regional internet of things sensing system through a regional internet of things platform in a spatio-temporal internet of things engine, and specifically includes the following steps:
in practical application, the regional visual AI platform can be deployed in a fusion data innovation center, and can be connected with a regional Internet of things sensing system through a regional Internet of things platform in a space-time Internet of things engine, so that visual data can be acquired through the regional Internet of things sensing system.
And 1202, analyzing and processing the visual data by the regional visual AI platform to provide support for a regional application portal platform through the fusion data creation center.
After the visual data is collected, the regional visual AI platform can calculate the collected visual data, and then can analyze and process the visual data according to the calculation result, so as to provide support for the regional application portal platform through the fusion data innovation center, for example, can provide visual service support for services such as global tourism, property cities and the like in the regional application portal platform according to the result of the visual data processing.
In an embodiment of the present invention, the area vision AI platform may be connected to the area cloud computing platform through the spatiotemporal internet-of-things engine, and the method may further include:
and the regional vision AI platform calls the regional cloud computing platform to perform data computing.
The regional cloud computing platform is used for processing data, such as data computing.
In practical application, the area vision AI platform can be connected with the area cloud computing platform through the space-time internet of things engine, and then the area cloud computing platform can be called to perform data computing.
For example, the collected visual data may be transmitted to a regional cloud computing platform, the visual data may be computed by the regional cloud computing platform, and the computed result and the visual data are returned to the regional visual AI platform, and the regional visual AI platform may analyze the computed result and the visual data.
In an embodiment of the present invention, the local visual AI platform may include a large-scale visual computing platform, a full-time global traffic dynamic perception engine, and a progressive video search engine, and the method may include:
the large-scale visual computing platform carries out basic computing on the visual data, the full-time global traffic dynamic perception engine carries out traffic event monitoring on the visual data, and the progressive video search engine carries out target identification on the visual data.
The basic calculation can be to calculate the calculated result and the visual data returned by the regional cloud computing platform, to build an index for the visual data according to the calculated result, to provide search support for the full-time global traffic dynamic perception engine and the progressive video search engine, the traffic event can be a traffic accident event, a road congestion event, and the target can be a person or a bicycle.
In practical application, the regional vision AI platform can acquire visual data through the regional Internet of things sensing system, further can call the regional cloud computing platform to compute the data, and receive computed results and visual data returned by the regional cloud computing platform through the large-scale visual computing platform, can perform basic computation on the large-scale visual computing platform, and can establish indexes on the visual data according to the computed results.
After the index is established, the full-time global traffic dynamic perception engine searches traffic events for the visual data according to the index, so that the traffic events can be monitored, the progressive video search engine can search the visual data according to the index, and then the target can be identified according to the search result.
In an embodiment of the invention, the large-scale visual computing platform may have any one or more of the following capabilities:
data access function, data calculation function, visual search function.
The data access function can be accessing visual data such as video data, picture data and multimedia data, the data calculation function can comprise calling a regional cloud computing platform to calculate the visual data, and can also comprise carrying out basic calculation on a calculated result and the visual data returned by the regional cloud computing platform so as to establish an index on the visual data, and the visual search function can be classified according to the visual data subjected to the basic calculation and establish the index.
In an embodiment of the present invention, the global traffic dynamics awareness engine may have any one or more of the following functions:
a traffic event awareness function, and a traffic event alert function.
The traffic event perception function may search for a traffic event from the visual data according to the index, and the traffic event warning function may warn according to the traffic event after searching for the traffic event.
For example, when the searched traffic event is a road congestion event, a vehicle traveling on the road may be alerted by the traffic event alerting function.
In an embodiment of the invention, the progressive video search engine may have any one or more of the following functions:
a target search function, a target analysis function.
The target search function may search the visual data according to the index, and may further identify the target according to the search result, and the target analysis function may analyze the identified target, such as analyzing the characteristics of the target.
For example, when the recognized target is a person, the target may be analyzed by a target analysis function to analyze features of the person such as height, clothes, etc., and when the recognized target is an object such as a bicycle, the target may be analyzed by a target analysis function to analyze features of the bicycle such as type, color, etc.
In the embodiment of the invention, the regional visual AI platform is deployed in the fusion data innovation center, the fusion data innovation center is connected with the regional Internet of things sensing system through the regional Internet of things platform in the spatio-temporal Internet of things engine, the regional visual AI platform acquires visual data through the regional Internet of things sensing system, the regional visual AI platform analyzes and processes the visual data to provide support for the regional application portal platform through the fusion data innovation center, the regional visual AI platform is constructed in a region to uniformly process the visual data, the repeated processing or function overlapping is avoided, the acquired visual data is transmitted to the regional application portal through the regional visual AI platform after calculation, and service support can be provided for the regional application portal in time.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
An embodiment of the present invention further provides an electronic device, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the computer program, when executed by the processor, implements the data processing method based on the area vision AI platform.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the data processing method based on the area vision AI platform is implemented.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The regional visual AI platform and the data processing method based on the regional visual AI platform are introduced in detail, and a specific example is applied in the text to explain the principle and the implementation of the present invention, and the description of the above embodiment is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. The area vision AI platform is characterized in that the area vision AI platform is deployed in a fusion data innovation center, and the fusion data innovation center is connected with an area Internet of things sensing system through an area Internet of things platform in a space-time Internet of things engine;
the regional vision AI platform acquires visual data through the regional Internet of things sensing system;
and the regional visual AI platform analyzes and processes the visual data so as to provide support for a regional application portal platform through the fusion data creation center.
2. The platform of claim 1, wherein the regional visual AI platform is connected to a regional cloud computing platform via the spatiotemporal-internet of things engine, and the regional visual AI platform invokes the regional cloud computing platform for data computation.
3. The platform of claim 1 or 2, wherein the local visual AI platform comprises a large-scale visual computing platform, a full-time global traffic dynamics perception engine, a progressive video search engine;
the large-scale visual computing platform is used for performing basic computing on the visual data, the full-time global traffic dynamic perception engine is used for performing traffic event monitoring on the visual data, and the progressive video search engine is used for performing target identification on the visual data.
4. The platform of claim 3, wherein the large-scale visual computing platform, when performing the base computation on the visual data, is specifically configured to:
performing data access on the visual data, performing data calculation on the visual data, and performing visual search on the visual data.
5. The platform of claim 3 or 4, wherein the full-time global traffic dynamics awareness engine, when performing traffic event monitoring on the visual data, is specifically configured to:
and carrying out traffic event perception on the visual data and carrying out traffic event warning on the visual data.
6. The platform of claim 3, wherein the progressive video search engine, when performing target recognition on the visual data, is specifically configured to:
and performing target search and target analysis on the visual data.
7. A data processing method based on a regional visual AI platform is characterized in that the regional visual AI platform is deployed in a fusion data innovation center, the fusion data innovation center is connected with a regional Internet of things sensing system through a regional Internet of things platform in a space-time Internet of things engine, and the method comprises the following steps:
the regional vision AI platform acquires visual data through the regional Internet of things sensing system;
and the regional visual AI platform analyzes and processes the visual data so as to provide support for a regional application portal platform through the fusion data creation center.
8. The method of claim 7, wherein the regional visual AI platform is connected to a regional cloud computing platform via the spatiotemporal internet of things engine, the method further comprising:
and the regional vision AI platform calls the regional cloud computing platform to perform data computing.
9. An electronic device, comprising a processor, a memory and a computer program stored on the memory and capable of running on the processor, the computer program, when executed by the processor, implementing the steps of the data processing method based on a regional visual AI platform according to any of claims 7 to 8.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the data processing method based on a regional visual AI platform according to any one of claims 7 to 8.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104486429A (en) * | 2014-12-22 | 2015-04-01 | 北京创鑫汇智科技发展有限责任公司 | Public and unified video service cloud platform |
| US9516281B1 (en) * | 2014-04-10 | 2016-12-06 | Smartvue Corporation | Systems and methods for automated cloud-based analytics for security surveillance systems with mobile input capture devices |
| CN111800507A (en) * | 2020-07-06 | 2020-10-20 | 湖北经济学院 | Traffic monitoring method and traffic monitoring system |
-
2020
- 2020-11-17 CN CN202011288450.7A patent/CN112258370A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9516281B1 (en) * | 2014-04-10 | 2016-12-06 | Smartvue Corporation | Systems and methods for automated cloud-based analytics for security surveillance systems with mobile input capture devices |
| CN104486429A (en) * | 2014-12-22 | 2015-04-01 | 北京创鑫汇智科技发展有限责任公司 | Public and unified video service cloud platform |
| CN111800507A (en) * | 2020-07-06 | 2020-10-20 | 湖北经济学院 | Traffic monitoring method and traffic monitoring system |
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