A data sharing method and system based on city brain

Abstract

The present invention provides a data sharing method and system based on the city brain. By connecting homogeneous and heterogeneous cloud platforms, a homogeneous and heterogeneous hybrid cloud platform of the city brain is constructed to perform cross-cloud migration data scheduling, share urban area satellite navigation positioning data, road monitoring image big data within the city and urban digital map data; perform data sharing high-speed transmission and store it in a data sharing cloud disk, create an algorithm mart shared AI algorithm warehouse of the city brain; identify road-running vehicles and road gathering and distribution personnel in road monitoring images within the city through an image recognition algorithm model; access data block-level storage devices through GPU instances for reading and writing; perform vehicle distribution operation status analysis and prediction and personnel gathering and distribution trend analysis and prediction through the cloud computing power sharing platform of the city brain; perform status abnormality alarm or trend prediction abnormality alarm and unified heterogeneous shared virtual management with the same interface through an abnormality judgment and early warning module.

Description

Technical Field

[0001] The present invention relates to the field of data processing cloud shared information early warning technology, and more specifically, the present invention relates to a data sharing method and system based on a city brain. Background Art

[0002] At present, with the continuous acceleration of the development of urban data information, it is becoming increasingly important to build and improve the city brain, and the data sharing technology of the city brain is becoming more and more complex; the data sharing system in the existing technology is difficult to perform hybrid cross-cloud data scheduling and sharing, and it is difficult to perform cross-cloud migration data scheduling of the city brain, high-speed transmission of data sharing and storage to identify road-running vehicles and road-distributing personnel in road monitoring images within the city, and it is difficult to access data block-level storage devices and perform vehicle distribution operation status analysis and prediction and personnel distribution trend analysis and prediction, status abnormality alarm or trend prediction abnormality warning timeliness is poor, and the uniformity of shared management is difficult to ensure; how to perform cross-cloud migration data scheduling of the city brain, how to perform high-speed transmission of data sharing and storage to identify road-running vehicles and road-distributing personnel in road monitoring images within the city, how to access data block-level storage devices and perform vehicle distribution operation status analysis and prediction and personnel distribution trend analysis and prediction and status abnormality alarm or trend prediction abnormality warning and shared virtual management and other issues remain to be resolved; therefore, it is necessary to propose a data sharing method and system based on the city brain to at least partially solve the problems existing in the prior art. Summary of the invention

[0003] A series of simplified concepts are introduced in the content of the invention, which will be further described in detail in the specific implementation method section; the content of the invention of the present invention does not mean to attempt to limit the key features and essential technical features of the technical solution claimed for protection, nor does it mean to attempt to determine the scope of protection of the technical solution claimed for protection.

[0004] In order to at least partially solve the above problems, the present invention provides a data sharing method based on the city brain, comprising:

[0005] S100, through the connection of homogeneous and heterogeneous cloud platforms, builds a homogeneous and heterogeneous hybrid cloud platform of the city brain, performs cross-cloud migration data scheduling, and shares urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data;

[0006] S200, which performs high-speed data sharing transmission and stores it in a data sharing cloud disk, creates an algorithm market for the city brain and shares an AI algorithm warehouse; through the image recognition algorithm model, it identifies road-running vehicles and road-distributing personnel in road monitoring images within the city, and obtains road-running vehicle data and road-distributing personnel data;

[0007] S300, reads and writes data to block-level storage devices through GPU instances; analyzes and predicts vehicle distribution and operation status and personnel concentration and distribution trend through the cloud computing power sharing platform of the city brain, and obtains vehicle distribution and operation status analysis and prediction information and personnel concentration and distribution trend analysis and prediction information;

[0008] S400, based on the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, through the abnormal judgment and warning module, status abnormality alarm or trend prediction abnormality warning and unified heterogeneous shared virtual management on the same interface are performed.

[0009] Preferably, S100 includes:

[0010] S101, connecting the first cloud platform, the second cloud platform, and the third cloud platform through homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud;

[0011] S102: connect the public cloud and private cloud of the first cloud platform, the second cloud platform and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform of the city brain;

[0012] S103, perform cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, share the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform, and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform, and the third cloud platform are respectively two heterogeneous virtual platforms or two homogeneous virtual platforms.

[0013] Preferably, S200 includes:

[0014] S201, through a high-speed dual-mode communication network, urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data are transmitted at high speed for data sharing, and stored in a data sharing cloud disk; the data sharing cloud disk includes: a heterogeneous data sharing cloud disk or a homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: an urban optical fiber communication network and a local wide area wireless communication network;

[0015] S202, creating an algorithm market shared AI algorithm warehouse of the city brain in the data sharing cloud disk; hosting the image recognition algorithm model to the algorithm market shared AI algorithm warehouse through the algorithm market shared AI algorithm warehouse; calling the image recognition algorithm model of the algorithm market shared AI algorithm warehouse through the city brain;

[0016] S203, identifying road-operating vehicles and road-gathering personnel in road monitoring images within the city through an image recognition algorithm model, and obtaining road-operating vehicle data and road-gathering personnel data.

[0017] Preferably, S300 includes:

[0018] S301, read and write access to data block-level storage devices through GPU instances, synchronize data disks and automatically mount them when GPU instances are started, and switch between multiple instances freely; data is persisted after resources are released, eliminating repeated upload processes;

[0019] S302, marking the road running vehicle data and road gathering and distribution personnel data on the city digital map according to the city area satellite navigation positioning data;

[0020] S303, through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel distribution trend analysis and prediction of the road distribution personnel data are carried out to obtain the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information.

[0021] Preferably, S400 includes:

[0022] S401, setting a state abnormality determination condition and a trend prediction abnormality determination condition according to the vehicle distribution operation state analysis prediction information and the personnel distribution trend analysis prediction information;

[0023] S402, creating an abnormality determination and warning module according to the abnormality determination conditions of the state and the abnormality determination conditions of the trend prediction; through the abnormality determination and warning module, according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information, a state abnormality alarm or a trend prediction abnormality warning is performed;

[0024] S403, based on the abnormal alarm information and the abnormal early warning information, the heterogeneous virtual platforms and the heterogeneous virtual platforms are uniformly managed with the same interface, and the distribution information of the vehicles running on the roads and the distribution information of the people gathering and distributing on the roads in the urban area are displayed in real time;

[0025] Based on the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, status abnormality alarm or trend prediction abnormality warning is carried out, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis predicts that an abnormality will occur, a vehicle distribution operation status abnormality alarm or a vehicle distribution operation status trend prediction abnormality warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis predicts that an abnormality will occur, a personnel distribution status abnormality alarm or a personnel distribution trend prediction abnormality warning is issued.

[0026] The present invention provides a data sharing system based on the city brain, comprising:

[0027] The hybrid cross-cloud data dispatching and sharing subsystem builds a homogeneous and heterogeneous hybrid cloud platform for the city brain through the connection of homogeneous and heterogeneous cloud platforms, performs cross-cloud migration data dispatching, and shares urban area satellite navigation positioning data, urban road monitoring image big data, and urban digital map data;

[0028] The shared AI algorithm warehouse model recognition subsystem performs high-speed data sharing and stores it in a data sharing cloud disk, creating an algorithm market shared AI algorithm warehouse for the city brain; through the image recognition algorithm model, it can identify road-running vehicles and road gathering and distribution personnel in road monitoring images within the city, and obtain road-running vehicle data and road gathering and distribution personnel data;

[0029] The instance switches to the cloud computing power sharing prediction subsystem, and accesses the data block-level storage device through the GPU instance reading and writing; through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction and the personnel distribution trend analysis and prediction are carried out, and the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information are obtained;

[0030] The abnormal judgment and early warning shared management subsystem analyzes and predicts the information on vehicle distribution and operation status and personnel concentration and distribution trend, and through the abnormal judgment and early warning module, performs abnormal status alarm or trend prediction abnormal early warning and unified heterogeneous shared virtual management on the same interface.

[0031] Preferably, the hybrid cross-cloud data scheduling sharing subsystem includes:

[0032] The cross-cloud platform docking subsystem connects the first cloud platform, the second cloud platform, and the third cloud platform through the homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud;

[0033] The hybrid cloud platform builds a subsystem, connecting the public cloud and private cloud of the first cloud platform, the second cloud platform, and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform for the city brain;

[0034] The cross-cloud migration scheduling sharing subsystem performs cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, sharing the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform, and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform, and the third cloud platform are respectively heterogeneous virtual platforms in pairs or homogeneous virtual platforms in pairs.

[0035] Preferably, the shared AI algorithm warehouse model recognition subsystem includes:

[0036] The dual-mode communication shared cloud disk subsystem transmits urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data through high-speed dual-mode communication network, and stores them in data sharing cloud disk; data sharing cloud disk includes: heterogeneous data sharing cloud disk or homogeneous data sharing cloud disk; high-speed dual-mode communication network includes: urban optical fiber communication network and local wide area wireless communication network;

[0037] The AI ​​algorithm warehouse model hosting subsystem creates the city brain's algorithm market shared AI algorithm warehouse in the data sharing cloud disk; through the algorithm market shared AI algorithm warehouse, the image recognition algorithm model is hosted in the algorithm market shared AI algorithm warehouse; the image recognition algorithm model of the algorithm market shared AI algorithm warehouse is retrieved through the city brain;

[0038] The algorithm model data recognition subsystem uses the image recognition algorithm model to identify road-operating vehicles and road-gathering personnel in road monitoring images within the city, and obtains road-operating vehicle data and road-gathering personnel data.

[0039] Preferably, the instance switching cloud computing power sharing prediction subsystem includes:

[0040] The GPU instance automatically switches subsystems, accesses data block-level storage devices through GPU instance read and write, and synchronizes data disks that are automatically mounted as GPU instances start, allowing for free switching between multiple instances. After resources are released, data is persisted, eliminating repeated upload processes.

[0041] The positioning digital map annotation subsystem uses the road operation vehicle data and road gathering and distribution personnel data to annotate the city digital map based on the urban area satellite navigation positioning data;

[0042] The cloud computing power sharing analysis and prediction subsystem uses the cloud computing power sharing platform of the city brain to perform vehicle distribution and operation status analysis and prediction of road operation vehicle data and personnel distribution trend analysis and prediction of road distribution personnel data, and obtains vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information.

[0043] Preferably, the abnormality determination and early warning shared management subsystem includes:

[0044] The judgment condition setting subsystem sets the abnormal state judgment condition and the abnormal trend prediction judgment condition according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information;

[0045] The abnormality determination and early warning subsystem creates an abnormality determination and early warning module based on the abnormality determination conditions of the state and the abnormality determination conditions of the trend prediction. Through the abnormality determination and early warning module, the abnormality alarm of the state or the abnormality early warning of the trend prediction is carried out according to the analysis and prediction information of the vehicle distribution operation state and the analysis and prediction information of the personnel distribution trend.

[0046] The heterogeneous shared virtual management subsystem performs unified heterogeneous shared virtual management of heterogeneous virtual platforms and heterogeneous virtual platforms on the same interface based on abnormal alarm information and abnormal early warning information, and displays the distribution information of road vehicles and road gathering and distribution personnel in the urban area in real time;

[0047] Based on the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, status abnormality alarm or trend prediction abnormality warning is carried out, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis predicts that an abnormality will occur, a vehicle distribution operation status abnormality alarm or a vehicle distribution operation status trend prediction abnormality warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis predicts that an abnormality will occur, a personnel distribution status abnormality alarm or a personnel distribution trend prediction abnormality warning is issued.

[0048] Compared with the prior art, the present invention has at least the following beneficial effects:

[0049] The present invention provides a data sharing method and system based on the city brain. By connecting homogeneous and heterogeneous cloud platforms, a homogeneous and heterogeneous hybrid cloud platform of the city brain is constructed to perform cross-cloud migration data scheduling, share urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data; perform data sharing high-speed transmission and store it in a data sharing cloud disk, create an algorithm market shared AI algorithm warehouse of the city brain; identify road-running vehicles and road gathering and distribution personnel in road monitoring images within the city through an image recognition algorithm model, and obtain road-running vehicle data and road gathering and distribution personnel data; read and write access to data block-level storage devices through GPU instances; and perform vehicle distribution operation status analysis and prediction and personnel gathering and distribution trend analysis through the cloud computing power sharing platform of the city brain. Prediction, obtain vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information; according to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, through the abnormal judgment and warning module, perform status abnormal alarm or trend prediction abnormal warning and unified heterogeneous shared virtual management on the same interface; the data sharing system of the present invention can perform hybrid cross-cloud data scheduling and sharing, can perform cross-cloud migration data scheduling of the city brain, high-speed transmission of data sharing and storage to identify road-running vehicles and road-distributed personnel in road monitoring images within the city, can access data block-level storage devices and perform vehicle distribution operation status analysis and prediction and personnel distribution trend analysis and prediction, status abnormal alarm or trend prediction abnormal warning timeliness is greatly improved, and the unified sharing management is significantly enhanced.

[0050] The present invention describes a data sharing method and system based on the city brain. Other advantages, objectives and features of the present invention will be reflected in part through the following description, and in part will be understood by technical personnel in this field through research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0052] Figure 1 This is a diagram of an embodiment of a data sharing system framework based on the city brain described in the present invention.

[0053] Figure 2 This is a diagram of an embodiment of the data sharing system interface based on the city brain described in the present invention.

[0054] Figure 3 This is a diagram of an implementation example of shared virtual management of a data sharing system and method based on the city brain described in the present invention. DETAILED DESCRIPTION

[0055] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments so that those skilled in the art can implement the invention according to the instructions. Figure 1-Figure 3 As shown, the present invention provides a data sharing method based on the city brain, comprising:

[0056] S100, through the connection of homogeneous and heterogeneous cloud platforms, builds a homogeneous and heterogeneous hybrid cloud platform of the city brain, performs cross-cloud migration data scheduling, and shares urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data;

[0057] S200, which performs high-speed data sharing transmission and stores it in a data sharing cloud disk, creates an algorithm market for the city brain and shares an AI algorithm warehouse; through the image recognition algorithm model, it identifies road-running vehicles and road-distributing personnel in road monitoring images within the city, and obtains road-running vehicle data and road-distributing personnel data;

[0058] S300, reads and writes data to block-level storage devices through GPU instances; analyzes and predicts vehicle distribution and operation status and personnel concentration and distribution trend through the cloud computing power sharing platform of the city brain, and obtains vehicle distribution and operation status analysis and prediction information and personnel concentration and distribution trend analysis and prediction information;

[0059] S400, based on the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, through the abnormal judgment and warning module, status abnormality alarm or trend prediction abnormality warning and unified heterogeneous shared virtual management on the same interface are performed.

[0060] The principles and effects of the above technical solution are as follows: The present invention provides a data sharing method based on the city brain, including: building a homogeneous and heterogeneous hybrid cloud platform of the city brain through the connection of homogeneous and heterogeneous cloud platforms, performing cross-cloud migration data scheduling, sharing urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data; performing high-speed data sharing transmission and storing it in a data sharing cloud disk, creating an algorithm market shared AI algorithm warehouse of the city brain; identifying road-running vehicles and road gathering and distribution personnel in road monitoring images within the city through image recognition algorithm models, and obtaining road-running vehicle data and road gathering and distribution personnel data; accessing data block-level storage devices through GPU instances; and performing vehicle distribution operation status analysis and prediction and human resource sharing through the cloud computing power sharing platform of the city brain. Personnel distribution trend analysis and prediction, obtain vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information; according to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, through the abnormal judgment and warning module, perform status abnormal alarm or trend prediction abnormal warning and unified heterogeneous shared virtual management on the same interface; the data sharing system of the present invention can perform hybrid cross-cloud data scheduling and sharing, can perform cross-cloud migration data scheduling of the city brain, high-speed transmission of data sharing and storage to identify road-running vehicles and road-distributed personnel in road monitoring images within the city, can access data block-level storage devices and perform vehicle distribution operation status analysis and prediction and personnel distribution trend analysis and prediction, status abnormal alarm or trend prediction abnormal warning, the timeliness is greatly improved, and the unified shared management is significantly enhanced.

[0061] In one embodiment, S100 includes:

[0062] S101, connecting the first cloud platform, the second cloud platform, and the third cloud platform through homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud;

[0063] S102: connect the public cloud and private cloud of the first cloud platform, the second cloud platform and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform of the city brain;

[0064] S103, perform cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, share the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform, and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform, and the third cloud platform are respectively two heterogeneous virtual platforms or two homogeneous virtual platforms.

[0065] The principle and effect of the above technical solution are: connecting the first cloud platform, the second cloud platform and the third cloud platform through the homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud; connecting the public cloud and private cloud of the first cloud platform, the second cloud platform and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform of the city brain; performing cross-cloud migration data scheduling through the homogeneous and heterogeneous hybrid cloud platform, sharing the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform and the third cloud platform are respectively heterogeneous virtual platforms in pairs or homogeneous virtual platforms in pairs; hybrid cross-cloud data scheduling and sharing can be performed.

[0066] In one embodiment, S200 includes:

[0067] S201, through a high-speed dual-mode communication network, urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data are transmitted at high speed for data sharing, and stored in a data sharing cloud disk; the data sharing cloud disk includes: a heterogeneous data sharing cloud disk or a homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: an urban optical fiber communication network and a local wide area wireless communication network;

[0068] S202, creating an algorithm market shared AI algorithm warehouse of the city brain in the data sharing cloud disk; hosting the image recognition algorithm model to the algorithm market shared AI algorithm warehouse through the algorithm market shared AI algorithm warehouse; calling the image recognition algorithm model of the algorithm market shared AI algorithm warehouse through the city brain;

[0069] S203, identifying road-operating vehicles and road-gathering personnel in road monitoring images within the city through an image recognition algorithm model, and obtaining road-operating vehicle data and road-gathering personnel data.

[0070] The principle and effect of the above technical solution are: through the high-speed dual-mode communication network, the urban area satellite navigation positioning data, the road monitoring image big data within the city and the urban digital map data are shared and transmitted at high speed, and stored in the data sharing cloud disk; the data sharing cloud disk includes: heterogeneous data sharing cloud disk or homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: urban optical fiber communication network and local wide area wireless communication network; the algorithm mart shared AI algorithm warehouse of the city brain is created in the data sharing cloud disk; through the algorithm mart shared AI algorithm warehouse, the image recognition algorithm model is hosted to the algorithm mart shared AI algorithm warehouse; the image recognition algorithm model of the algorithm mart shared AI algorithm warehouse is retrieved through the city brain; through the image recognition algorithm model, the road-running vehicles and road-distributing personnel in the road monitoring images within the city are identified, and the road-running vehicle data and road-distributing personnel data are obtained; the city brain can perform cross-cloud migration data scheduling, data sharing high-speed transmission and storage to identify the road-running vehicles and road-distributing personnel in the road monitoring images within the city.

[0071] In one embodiment, S300 includes:

[0072] S301, read and write access to data block-level storage devices through GPU instances, synchronize data disks and automatically mount them when GPU instances are started, and switch between multiple instances freely; data is persisted after resources are released, eliminating repeated upload processes;

[0073] S302, marking the road running vehicle data and road gathering and distribution personnel data on the city digital map according to the city area satellite navigation positioning data;

[0074] S303, through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel distribution trend analysis and prediction of the road distribution personnel data are performed to obtain the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information;

[0075] Through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel distribution trend analysis and prediction of the road distribution personnel data are carried out, and the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information are obtained, including: extracting the vehicle distribution operation status of the road operation vehicle data through the cloud computing power sharing platform of the city brain; generating a dynamic cloud map of the vehicle operation at the initial moment according to the vehicle distribution operation status; dynamically forming a dynamic cloud map of the vehicle operation at the next moment according to the dynamic cloud map of the vehicle operation at the initial moment; predicting the vehicle distribution operation status at the next moment according to the dynamic cloud map of the vehicle operation at the next moment; analyzing and predicting the vehicle distribution operation status of the road operation vehicle data; extracting the personnel distribution distribution information of the road distribution personnel data through the cloud computing power sharing platform of the city brain; generating a personnel distribution distribution cloud map at the initial moment according to the personnel distribution distribution information; dynamically forming a personnel distribution distribution cloud map at the next moment according to the personnel distribution distribution cloud map at the initial moment; predicting the personnel distribution distribution at the next moment according to the personnel distribution distribution cloud map at the next moment, and performing personnel distribution trend analysis and prediction information of the road distribution personnel data; obtaining vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information.

[0076] The principle and effect of the above technical solution are: read and write access to data block-level storage devices through GPU instances, and the synchronous data disk is automatically mounted as the GPU instance is started, so that multiple instances can be switched freely; data is persisted after resources are released, and repeated upload processes are eliminated; road operation vehicle data and road gathering and distribution personnel data are annotated on the city digital map according to the satellite navigation positioning data of the urban area; through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel gathering and distribution trend analysis and prediction of the road gathering and distribution personnel data are carried out to obtain the vehicle distribution operation status analysis prediction information and the personnel gathering and distribution trend analysis prediction information; through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel gathering and distribution trend analysis and prediction information of the road gathering and distribution personnel data are carried out to obtain the vehicle distribution operation status analysis prediction information and the personnel gathering and distribution trend analysis prediction information, including: extracting the vehicle distribution operation status of the road operation vehicle data through the cloud computing power sharing platform of the city brain The vehicle distribution and operation status of road running vehicles is analyzed and predicted; through the cloud computing power sharing platform of the city brain, the personnel distribution and distribution information of road gathering and distribution personnel data is extracted; according to the personnel distribution and distribution information, a personnel distribution and distribution cloud map at the initial moment is generated; according to the personnel distribution and distribution cloud map at the initial moment, a personnel distribution and distribution cloud map at the next moment is formed in sequence; according to the personnel distribution and distribution cloud map at the next moment, the personnel distribution and distribution cloud map is predicted, and the personnel distribution and distribution trend analysis and prediction of road gathering and distribution personnel data is performed; the vehicle distribution and operation status analysis and prediction information and the personnel distribution and trend analysis and prediction information are obtained; data block-level storage devices can be accessed to perform vehicle distribution and operation status analysis and prediction and personnel distribution and trend analysis and prediction.

[0077] In one embodiment, S400 includes:

[0078] S401, setting a state abnormality determination condition and a trend prediction abnormality determination condition according to the vehicle distribution operation state analysis prediction information and the personnel distribution trend analysis prediction information;

[0079] S402, creating an abnormality determination and warning module according to the abnormality determination conditions of the state and the abnormality determination conditions of the trend prediction; through the abnormality determination and warning module, according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information, a state abnormality alarm or a trend prediction abnormality warning is performed;

[0080] S403, based on the abnormal alarm information and the abnormal early warning information, the heterogeneous virtual platforms and the heterogeneous virtual platforms are uniformly managed with the same interface, and the distribution information of the vehicles running on the roads and the distribution information of the people gathering and distributing on the roads in the urban area are displayed in real time;

[0081] According to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, the abnormal status alarm or trend prediction abnormal warning is carried out, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis and prediction will be abnormal, the vehicle distribution operation status abnormal alarm or vehicle distribution operation status trend prediction abnormal warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis and prediction will be abnormal, the personnel distribution status abnormal alarm or personnel distribution trend prediction abnormal warning is issued;

[0082] The vehicle operation status includes: the compliance of vehicle operation with speed limit, the matching degree of vehicle operation with signal lights, the degree of vehicle operation congestion, the compliance degree of vehicle operation with road signs, the stagnation status of vehicle operation and the fault status of vehicle operation;

[0083] When an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning includes: according to the vehicle distribution operation status analysis prediction information, when the vehicle distribution operation status shows that the vehicle operation and speed limit compliance is lower than the set speed limit compliance, the vehicle operation and signal light matching does not meet the signal light indication, the vehicle operation congestion level is greater than the set congestion level, the vehicle operation road sign compliance is lower than the road sign compliance, the vehicle operation stagnation time exceeds the set time and the vehicle operation failure state occurs, it is determined that the vehicle distribution operation status is abnormal; when an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning.

[0084] The principle and effect of the above technical solution are as follows: according to the vehicle distribution operation status analysis and prediction information and the personnel gathering and distribution trend analysis and prediction information, the state abnormality judgment condition and the trend prediction abnormality judgment condition are set; according to the state abnormality judgment condition and the trend prediction abnormality judgment condition, an abnormality judgment warning module is created; through the abnormality judgment warning module, according to the vehicle distribution operation status analysis and prediction information and the personnel gathering and distribution trend analysis and prediction information, a state abnormality alarm or a trend prediction abnormality warning is performed; according to the abnormality alarm information and the abnormality warning information, a heterogeneous virtual platform and a heterogeneous virtual platform with the same interface are unified and heterogeneous shared virtual management is performed, and the distribution information of road operation vehicles and the road gathering and distribution personnel gathering and distribution information in the urban area are displayed in real time; according to the vehicle distribution operation status analysis and prediction information and the personnel gathering and distribution trend analysis and prediction information, a state abnormality alarm or a trend prediction abnormality warning is performed, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis and prediction will be abnormal, a vehicle distribution operation status abnormality alarm or a vehicle distribution operation status trend prediction abnormality warning is issued; when the personnel gathering and distribution status is abnormal or before the personnel gathering and distribution trend analysis and prediction will be abnormal, a personnel gathering and distribution status abnormality alarm or a personnel gathering and distribution trend prediction abnormality warning is issued;

[0085] The vehicle operation status includes: vehicle operation and speed limit compliance, vehicle operation and signal light matching, vehicle operation congestion level, vehicle operation road sign compliance, vehicle operation stagnation state and vehicle operation fault state; when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning includes: according to the vehicle distribution operation status analysis prediction information, when the vehicle distribution operation status shows that the vehicle operation and speed limit compliance is lower than the set speed limit compliance, the vehicle operation and signal light matching does not meet the signal light indication, the vehicle operation congestion level is greater than the set congestion level, the vehicle operation road sign compliance is lower than the road sign compliance, the vehicle operation stagnation state time exceeds the set time and the vehicle operation fault state occurs, it is determined that the vehicle distribution operation status is abnormal; when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning; the timeliness of the abnormal state alarm or the trend prediction abnormal warning is greatly improved, and the unified shared management is significantly enhanced.

[0086] The present invention provides a data sharing system based on the city brain, comprising:

[0087] The hybrid cross-cloud data dispatching and sharing subsystem builds a homogeneous and heterogeneous hybrid cloud platform for the city brain through the connection of homogeneous and heterogeneous cloud platforms, performs cross-cloud migration data dispatching, and shares urban area satellite navigation positioning data, urban road monitoring image big data, and urban digital map data;

[0088] The shared AI algorithm warehouse model recognition subsystem performs high-speed data sharing and stores it in a data sharing cloud disk, creating an algorithm market shared AI algorithm warehouse for the city brain; through the image recognition algorithm model, it can identify road-running vehicles and road gathering and distribution personnel in road monitoring images within the city, and obtain road-running vehicle data and road gathering and distribution personnel data;

[0089] The instance switches to the cloud computing power sharing prediction subsystem, and accesses the data block-level storage device through the GPU instance reading and writing; through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction and the personnel distribution trend analysis and prediction are carried out, and the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information are obtained;

[0090] The abnormal judgment and early warning shared management subsystem analyzes and predicts the information on vehicle distribution and operation status and personnel concentration and distribution trend, and through the abnormal judgment and early warning module, performs abnormal status alarm or trend prediction abnormal early warning and unified heterogeneous shared virtual management on the same interface.

[0091] The principles and effects of the above technical solution are as follows: the present invention provides a data sharing system based on the city brain, including: a hybrid cross-cloud data scheduling and sharing subsystem, which builds a homogeneous and heterogeneous hybrid cloud platform of the city brain through the docking of homogeneous and heterogeneous cloud platforms, performs cross-cloud migration data scheduling, and shares urban area satellite navigation positioning data, road monitoring image big data within the city, and urban digital map data; a shared AI algorithm warehouse model recognition subsystem, which performs high-speed data sharing transmission and stores it in a data sharing cloud disk, and creates an algorithm market shared AI algorithm warehouse of the city brain; through the image recognition algorithm model, it identifies road-running vehicles and road gathering and distribution personnel in road monitoring images within the city, and obtains road-running vehicle data and road gathering and distribution personnel data; an instance switching cloud computing power sharing prediction subsystem, which reads and writes access to data block-level storage devices through GPU instances; and through the cloud computing power sharing platform of the city brain, The vehicle distribution and operation status analysis and prediction and the personnel distribution trend analysis and prediction are carried out to obtain the vehicle distribution and operation status analysis and prediction information and the personnel distribution trend analysis and prediction information; the abnormal judgment and early warning shared management subsystem, according to the vehicle distribution and operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, through the abnormal judgment and early warning module, performs status abnormality alarm or trend prediction abnormality alarm and unified heterogeneous shared virtual management on the same interface; the data sharing system of the present invention can perform hybrid cross-cloud data scheduling and sharing, can perform cross-cloud migration data scheduling of the city brain, high-speed transmission of data sharing and storage to identify road-running vehicles and road-distributed personnel in road monitoring images within the city, can access data block-level storage devices and perform vehicle distribution and operation status analysis and prediction and personnel distribution trend analysis and prediction, status abnormality alarm or trend prediction abnormality alarm, the timeliness of which is greatly improved, and the unified shared management is significantly enhanced.

[0092] In one embodiment, the hybrid cross-cloud data scheduling sharing subsystem includes:

[0093] The cross-cloud platform docking subsystem connects the first cloud platform, the second cloud platform, and the third cloud platform through the homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud;

[0094] The hybrid cloud platform builds a subsystem, connecting the public cloud and private cloud of the first cloud platform, the second cloud platform, and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform for the city brain;

[0095] The cross-cloud migration scheduling sharing subsystem performs cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, sharing the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform, and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform, and the third cloud platform are respectively heterogeneous virtual platforms in pairs or homogeneous virtual platforms in pairs.

[0096] The principles and effects of the above technical solution are as follows: the hybrid cross-cloud data scheduling and sharing subsystem includes: a cross-cloud platform docking subsystem, which connects the first cloud platform, the second cloud platform and the third cloud platform through the homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud; a hybrid cloud platform construction subsystem, which connects the public cloud and private cloud of the first cloud platform, the second cloud platform and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform of the city brain; a cross-cloud migration scheduling and sharing subsystem, which performs cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, shares the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform and the third cloud platform are respectively heterogeneous virtual platforms in pairs or homogeneous virtual platforms in pairs; hybrid cross-cloud data scheduling and sharing can be performed.

[0097] In one embodiment, the shared AI algorithm warehouse model recognition subsystem includes:

[0098] The dual-mode communication shared cloud disk subsystem transmits the satellite navigation positioning data of the urban area, the big data of road monitoring images within the urban area and the urban digital map data through the high-speed dual-mode communication network, and stores them in the data sharing cloud disk; the data sharing cloud disk includes: heterogeneous data sharing cloud disk or homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: urban optical fiber communication network and local wide area wireless communication network;

[0099] The AI ​​algorithm warehouse model hosting subsystem creates the city brain's algorithm market shared AI algorithm warehouse in the data sharing cloud disk; through the algorithm market shared AI algorithm warehouse, the image recognition algorithm model is hosted in the algorithm market shared AI algorithm warehouse; the image recognition algorithm model of the algorithm market shared AI algorithm warehouse is retrieved through the city brain;

[0100] The algorithm model data recognition subsystem uses the image recognition algorithm model to identify road-operating vehicles and road-gathering personnel in road monitoring images within the city, and obtains road-operating vehicle data and road-gathering personnel data.

[0101] The principle and effect of the above technical solution are as follows: the shared AI algorithm warehouse model recognition subsystem includes: a dual-mode communication shared cloud subsystem, which transmits urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data through a high-speed dual-mode communication network for data sharing and high-speed transmission, and stores them in a data sharing cloud disk; the data sharing cloud disk includes: a heterogeneous data sharing cloud disk or a homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: an urban optical fiber communication network and a local wide area wireless communication network; the AI ​​algorithm warehouse model hosting subsystem creates an algorithm market for the city brain in the data sharing cloud disk Shared AI algorithm warehouse; shared AI algorithm warehouse through algorithm mart, hosted image recognition algorithm model to shared AI algorithm warehouse in algorithm mart; retrieved image recognition algorithm model from shared AI algorithm warehouse in algorithm mart through city brain; algorithm model data recognition subsystem, identified road-running vehicles and road-distributing personnel in road monitoring images within the city through image recognition algorithm model, obtained road-running vehicle data and road-distributing personnel data; city brain can perform cross-cloud migration data scheduling, data sharing, high-speed transmission and storage to identify road-running vehicles and road-distributing personnel in road monitoring images within the city.

[0102] In one embodiment, the instance switching cloud computing power sharing prediction subsystem includes:

[0103] The GPU instance automatically switches subsystems, accesses data block-level storage devices through GPU instance read and write, and synchronizes data disks that are automatically mounted as GPU instances start, allowing for free switching between multiple instances. After resources are released, data is persisted, eliminating repeated upload processes.

[0104] The positioning digital map annotation subsystem uses the road operation vehicle data and road gathering and distribution personnel data to annotate the city digital map based on the urban area satellite navigation positioning data;

[0105] The cloud computing power sharing analysis and prediction subsystem uses the cloud computing power sharing platform of the city brain to analyze and predict the vehicle distribution and operation status of road running vehicle data and the personnel distribution trend analysis and prediction of road gathering and distribution personnel data, and obtains vehicle distribution and operation status analysis and prediction information and personnel distribution trend analysis and prediction information;

[0106] Through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel distribution trend analysis and prediction of the road distribution personnel data are carried out, and the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information are obtained, including: extracting the vehicle distribution operation status of the road operation vehicle data through the cloud computing power sharing platform of the city brain; generating a dynamic cloud map of the vehicle operation at the initial moment according to the vehicle distribution operation status; dynamically forming a dynamic cloud map of the vehicle operation at the next moment according to the dynamic cloud map of the vehicle operation at the initial moment; predicting the vehicle distribution operation status at the next moment according to the dynamic cloud map of the vehicle operation at the next moment; analyzing and predicting the vehicle distribution operation status of the road operation vehicle data; extracting the personnel distribution distribution information of the road distribution personnel data through the cloud computing power sharing platform of the city brain; generating a personnel distribution distribution cloud map at the initial moment according to the personnel distribution distribution information; dynamically forming a personnel distribution distribution cloud map at the next moment according to the personnel distribution distribution cloud map at the initial moment; predicting the personnel distribution distribution at the next moment according to the personnel distribution distribution cloud map at the next moment, and performing personnel distribution trend analysis and prediction information of the road distribution personnel data; obtaining vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information.

[0107] The principles and effects of the above technical solution are as follows: the instance switching cloud computing power sharing prediction subsystem includes: a GPU instance automatic switching subsystem, which accesses the data block-level storage device through the GPU instance read and write, and the synchronous data disk is automatically mounted as the GPU instance is started, so as to switch freely between multiple instances; the data is persisted after the resources are released, and the repeated upload process is eliminated; the positioning digital map annotation subsystem, which annotates the road operation vehicle data and the road distribution personnel data on the city digital map according to the urban area satellite navigation positioning data; the cloud computing power sharing analysis and prediction subsystem, through the cloud computing power sharing platform of the city brain, performs vehicle distribution operation status analysis and prediction of the road operation vehicle data and personnel distribution trend analysis and prediction of the road distribution personnel data, and obtains vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information; through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel distribution trend analysis and prediction of the road distribution personnel data are performed, and the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information are obtained, including :Extract the vehicle distribution and operation status of road operation vehicle data through the cloud computing power sharing platform of the city brain; generate a dynamic cloud map of vehicle operation at the initial moment according to the vehicle distribution and operation status; dynamically form a dynamic cloud map of vehicle operation at the next moment according to the dynamic cloud map of vehicle operation at the initial moment; predict the vehicle distribution and operation status at the next moment according to the dynamic cloud map of vehicle operation at the next moment; perform vehicle distribution and operation status analysis and prediction of road operation vehicle data; extract personnel distribution information of road distribution personnel data through the cloud computing power sharing platform of the city brain; generate a personnel distribution cloud map at the initial moment according to the personnel distribution cloud map; dynamically form a personnel distribution cloud map at the next moment according to the personnel distribution cloud map at the initial moment; predict the personnel distribution at the next moment according to the personnel distribution cloud map at the next moment, and perform personnel distribution trend analysis and prediction of road distribution personnel data; obtain vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information; can access data block-level storage devices and perform vehicle distribution operation status analysis and prediction and personnel distribution trend analysis and prediction.

[0108] In one embodiment, the abnormality determination and early warning sharing management subsystem includes:

[0109] The judgment condition setting subsystem sets the abnormal state judgment condition and the abnormal trend prediction judgment condition according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information;

[0110] The abnormality determination and early warning subsystem creates an abnormality determination and early warning module based on the abnormality determination conditions of the state and the abnormality determination conditions of the trend prediction. Through the abnormality determination and early warning module, the abnormality alarm of the state or the abnormality early warning of the trend prediction is carried out according to the analysis and prediction information of the vehicle distribution operation state and the analysis and prediction information of the personnel distribution trend.

[0111] The heterogeneous shared virtual management subsystem performs unified heterogeneous shared virtual management of heterogeneous virtual platforms and heterogeneous virtual platforms on the same interface based on abnormal alarm information and abnormal early warning information, and displays the distribution information of road vehicles and road gathering and distribution personnel in the urban area in real time;

[0112] According to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, the abnormal status alarm or trend prediction abnormal warning is carried out, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis and prediction will be abnormal, the vehicle distribution operation status abnormal alarm or vehicle distribution operation status trend prediction abnormal warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis and prediction will be abnormal, the personnel distribution status abnormal alarm or personnel distribution trend prediction abnormal warning is issued;

[0113] The vehicle operation status includes: the compliance of vehicle operation with speed limit, the matching degree of vehicle operation with signal lights, the degree of vehicle operation congestion, the compliance degree of vehicle operation with road signs, the stagnation status of vehicle operation and the fault status of vehicle operation;

[0114] When an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning includes: according to the vehicle distribution operation status analysis prediction information, when the vehicle distribution operation status shows that the vehicle operation and speed limit compliance is lower than the set speed limit compliance, the vehicle operation and signal light matching does not meet the signal light indication, the vehicle operation congestion level is greater than the set congestion level, the vehicle operation road sign compliance is lower than the road sign compliance, the vehicle operation stagnation time exceeds the set time and the vehicle operation failure state occurs, it is determined that the vehicle distribution operation status is abnormal; when an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning.

[0115] The principle and effect of the above technical solution are as follows: the abnormal judgment and early warning shared management subsystem includes: a judgment condition setting subsystem, which sets the state abnormal judgment condition and the trend prediction abnormal judgment condition according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information; the abnormal judgment and early warning subsystem, which creates an abnormal judgment and early warning module according to the state abnormal judgment condition and the trend prediction abnormal judgment condition; through the abnormal judgment and early warning module, according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information, the state abnormal alarm or the trend prediction abnormal alarm is performed; the heterogeneous shared virtual management subsystem, according to the abnormal alarm information and abnormal warning information, performs heterogeneous virtual The platform and heterogeneous virtual platforms use the same interface to unify heterogeneous shared virtual management, and display the distribution information of vehicles on roads and the distribution information of people gathering and distributing on roads in real time in the urban area; according to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, abnormal status alarm or trend prediction abnormal warning is issued, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis and prediction will be abnormal, the vehicle distribution operation status abnormal alarm or vehicle distribution operation status trend prediction abnormal warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis and prediction will be abnormal, the personnel distribution status abnormal alarm or personnel distribution trend prediction abnormal warning is issued;

[0116] The vehicle operation status includes: vehicle operation and speed limit compliance, vehicle operation and signal light matching, vehicle operation congestion level, vehicle operation road sign compliance, vehicle operation stagnation state and vehicle operation fault state; when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning includes: according to the vehicle distribution operation status analysis prediction information, when the vehicle distribution operation status shows that the vehicle operation and speed limit compliance is lower than the set speed limit compliance, the vehicle operation and signal light matching does not meet the signal light indication, the vehicle operation congestion level is greater than the set congestion level, the vehicle operation road sign compliance is lower than the road sign compliance, the vehicle operation stagnation state time exceeds the set time and the vehicle operation fault state occurs, it is determined that the vehicle distribution operation status is abnormal; when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning; the timeliness of the abnormal state alarm or the trend prediction abnormal warning is greatly improved, and the unified shared management is significantly enhanced.

[0117] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

Claims

1. A data sharing method based on the city brain, It is characterized in that include: S100, through the connection of homogeneous and heterogeneous cloud platforms, builds a homogeneous and heterogeneous hybrid cloud platform of the city brain, performs cross-cloud migration data scheduling, and shares urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data; S200, which performs high-speed data sharing transmission and stores it in a data sharing cloud disk, creates an algorithm market for the city brain and shares an AI algorithm warehouse; through the image recognition algorithm model, it identifies road-running vehicles and road-distributing personnel in road monitoring images within the city, and obtains road-running vehicle data and road-distributing personnel data; S300, reads and writes data to block-level storage devices through GPU instances; analyzes and predicts vehicle distribution and operation status and personnel concentration and distribution trend through the cloud computing power sharing platform of the city brain, and obtains vehicle distribution and operation status analysis and prediction information and personnel concentration and distribution trend analysis and prediction information; S400, based on the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, through the abnormality judgment and early warning module, abnormal status alarm or trend prediction abnormality warning and unified heterogeneous shared virtual management on the same interface; S400 includes: S401, setting a state abnormality determination condition and a trend prediction abnormality determination condition according to the vehicle distribution operation state analysis prediction information and the personnel distribution trend analysis prediction information; S402, creating an abnormality determination and warning module according to the abnormality determination conditions of the state and the abnormality determination conditions of the trend prediction; through the abnormality determination and warning module, according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information, a state abnormality alarm or a trend prediction abnormality warning is performed; S403, based on the abnormal alarm information and abnormal early warning information, unified heterogeneous shared virtual management of two heterogeneous virtual platforms with the same interface is performed to display the distribution information of road vehicles and road gathering and distribution personnel in the urban area in real time; According to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, the abnormal status alarm or trend prediction abnormal warning is carried out, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis and prediction will be abnormal, the vehicle distribution operation status abnormal alarm or vehicle distribution operation status trend prediction abnormal warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis and prediction will be abnormal, the personnel distribution status abnormal alarm or personnel distribution trend prediction abnormal warning is issued; When an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning includes: according to the vehicle distribution operation status analysis prediction information, when the vehicle distribution operation status shows that the vehicle operation and speed limit compliance is lower than the set speed limit compliance, the vehicle operation and signal light matching does not meet the signal light indication, the vehicle operation congestion level is greater than the set congestion level, the vehicle operation road sign compliance is lower than the road sign compliance, the vehicle operation stagnation time exceeds the set time and the vehicle operation failure state occurs, it is determined that the vehicle distribution operation status is abnormal; when an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning.

2. According to claim 1, a data sharing method based on the city brain, It is characterized in that S100 includes: S101, connecting the first cloud platform, the second cloud platform, and the third cloud platform through homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud; S102: connect the public cloud and private cloud of the first cloud platform, the second cloud platform and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform of the city brain; S103, perform cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, share the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform, and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform, and the third cloud platform are respectively two heterogeneous virtual platforms or two homogeneous virtual platforms.

3. According to the data sharing method based on the city brain in claim 1, It is characterized in that S200 includes: S201, through a high-speed dual-mode communication network, urban area satellite navigation positioning data, urban road monitoring image big data and urban digital map data are transmitted at high speed for data sharing, and stored in a data sharing cloud disk; the data sharing cloud disk includes: a heterogeneous data sharing cloud disk or a homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: an urban optical fiber communication network and a local wide area wireless communication network; S202, creating an algorithm market shared AI algorithm warehouse of the city brain in the data sharing cloud disk; hosting the image recognition algorithm model to the algorithm market shared AI algorithm warehouse through the algorithm market shared AI algorithm warehouse; calling the image recognition algorithm model of the algorithm market shared AI algorithm warehouse through the city brain; S203, identifying road-operating vehicles and road-gathering personnel in road monitoring images within the city through an image recognition algorithm model, and obtaining road-operating vehicle data and road-gathering personnel data.

4. According to claim 1, a data sharing method based on the city brain, It is characterized in that S300 includes: S301, read and write access to data block-level storage devices through GPU instances, synchronize data disks and automatically mount them when GPU instances are started, and switch between multiple instances freely; data is persisted after resources are released, eliminating repeated upload processes; S302, marking the road running vehicle data and road gathering and distribution personnel data on the city digital map according to the city area satellite navigation positioning data; S303, through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction of the road operation vehicle data and the personnel distribution trend analysis and prediction of the road distribution personnel data are carried out to obtain the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information.

5. A data sharing system based on the city brain, It is characterized in that include: The hybrid cross-cloud data dispatching and sharing subsystem builds a homogeneous and heterogeneous hybrid cloud platform for the city brain through the connection of homogeneous and heterogeneous cloud platforms, performs cross-cloud migration data dispatching, and shares urban area satellite navigation positioning data, urban road monitoring image big data, and urban digital map data; The shared AI algorithm warehouse model recognition subsystem performs high-speed data sharing and stores it in a data sharing cloud disk, creating an algorithm market shared AI algorithm warehouse for the city brain; through the image recognition algorithm model, it can identify road-running vehicles and road gathering and distribution personnel in road monitoring images within the city, and obtain road-running vehicle data and road gathering and distribution personnel data; The instance switches to the cloud computing power sharing prediction subsystem, and accesses the data block-level storage device through the GPU instance reading and writing; through the cloud computing power sharing platform of the city brain, the vehicle distribution operation status analysis and prediction and the personnel distribution trend analysis and prediction are carried out, and the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information are obtained; The abnormal judgment and early warning shared management subsystem analyzes and predicts the information of vehicle distribution and operation status and personnel distribution trend, and uses the abnormal judgment and early warning module to perform abnormal status alarm or trend prediction abnormal early warning and unified heterogeneous shared virtual management on the same interface; The abnormality determination and early warning shared management subsystem includes: The judgment condition setting subsystem sets the abnormal state judgment condition and the abnormal trend prediction judgment condition according to the vehicle distribution operation state analysis and prediction information and the personnel distribution trend analysis and prediction information; The abnormality determination and early warning subsystem creates an abnormality determination and early warning module based on the abnormality determination conditions of the state and the abnormality determination conditions of the trend prediction. Through the abnormality determination and early warning module, the abnormality alarm of the state or the abnormality early warning of the trend prediction is carried out according to the analysis and prediction information of the vehicle distribution operation state and the analysis and prediction information of the personnel distribution trend. The heterogeneous shared virtual management subsystem performs unified heterogeneous shared virtual management of two heterogeneous virtual platforms on the same interface based on abnormal alarm information and abnormal early warning information, and displays the distribution information of road vehicles and road personnel distribution in the urban area in real time; According to the vehicle distribution operation status analysis and prediction information and the personnel distribution trend analysis and prediction information, the abnormal status alarm or trend prediction abnormal warning is carried out, including: when the vehicle distribution operation status is abnormal or before the vehicle distribution operation status analysis and prediction will be abnormal, the vehicle distribution operation status abnormal alarm or vehicle distribution operation status trend prediction abnormal warning is issued; when the personnel distribution status is abnormal or before the personnel distribution trend analysis and prediction will be abnormal, the personnel distribution status abnormal alarm or personnel distribution trend prediction abnormal warning is issued; When an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning includes: according to the vehicle distribution operation status analysis prediction information, when the vehicle distribution operation status shows that the vehicle operation and speed limit compliance is lower than the set speed limit compliance, the vehicle operation and signal light matching does not meet the signal light indication, the vehicle operation congestion level is greater than the set congestion level, the vehicle operation road sign compliance is lower than the road sign compliance, the vehicle operation stagnation time exceeds the set time and the vehicle operation failure state occurs, it is determined that the vehicle distribution operation status is abnormal; when an abnormality occurs in the vehicle distribution operation status or before the vehicle distribution operation status analysis predicts that an abnormality will occur, issuing a vehicle distribution operation status abnormal alarm or a vehicle distribution operation status trend prediction abnormal warning.

6. A data sharing system based on the city brain according to claim 5, It is characterized in that The hybrid cross-cloud data scheduling and sharing subsystem includes: The cross-cloud platform docking subsystem connects the first cloud platform, the second cloud platform, and the third cloud platform through the homogeneous and heterogeneous cloud platforms between the public cloud and the private cloud; The hybrid cloud platform builds a subsystem, connecting the public cloud and private cloud of the first cloud platform, the second cloud platform, and the third cloud platform to build a homogeneous and heterogeneous hybrid cloud platform for the city brain; The cross-cloud migration scheduling sharing subsystem performs cross-cloud migration data scheduling through homogeneous and heterogeneous hybrid cloud platforms, sharing the urban area satellite navigation positioning data of the first cloud platform, the urban road monitoring image big data of the second cloud platform, and the urban digital map data of the third cloud platform; the first cloud platform, the second cloud platform, and the third cloud platform are respectively heterogeneous virtual platforms in pairs or homogeneous virtual platforms in pairs.

7. According to claim 5, a data sharing system based on the city brain, It is characterized in that The shared AI algorithm warehouse model recognition subsystem includes: The dual-mode communication shared cloud disk subsystem transmits the satellite navigation positioning data of the urban area, the big data of road monitoring images within the urban area and the urban digital map data through the high-speed dual-mode communication network, and stores them in the data sharing cloud disk; the data sharing cloud disk includes: heterogeneous data sharing cloud disk or homogeneous data sharing cloud disk; the high-speed dual-mode communication network includes: urban optical fiber communication network and local wide area wireless communication network; The AI ​​algorithm warehouse model hosting subsystem creates the city brain's algorithm market shared AI algorithm warehouse in the data sharing cloud disk; through the algorithm market shared AI algorithm warehouse, the image recognition algorithm model is hosted in the algorithm market shared AI algorithm warehouse; the image recognition algorithm model of the algorithm market shared AI algorithm warehouse is retrieved through the city brain; The algorithm model data recognition subsystem uses the image recognition algorithm model to identify road-operating vehicles and road-gathering personnel in road monitoring images within the city, and obtains road-operating vehicle data and road-gathering personnel data.

8. According to claim 5, a data sharing system based on the city brain, It is characterized in that The instance switching cloud computing power sharing prediction subsystem includes: The GPU instance automatically switches subsystems, accesses data block-level storage devices through GPU instance read and write, and synchronizes data disks that are automatically mounted as GPU instances start, allowing for free switching between multiple instances. After resources are released, data is persisted, eliminating repeated upload processes. The positioning digital map annotation subsystem uses the road operation vehicle data and road gathering and distribution personnel data to annotate the city digital map based on the urban area satellite navigation positioning data; The cloud computing power sharing analysis and prediction subsystem uses the cloud computing power sharing platform of the city brain to perform vehicle distribution and operation status analysis and prediction of road operation vehicle data and personnel distribution trend analysis and prediction of road distribution personnel data, and obtains vehicle distribution operation status analysis and prediction information and personnel distribution trend analysis and prediction information.

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