Urban one-network unified management system and abnormal event information sending method

Abstract

The embodiment of the invention discloses a city one-network unified management system and an abnormal event information sending method. One specific embodiment of the system comprises a data integration sharing layer, an event center layer, a visual decision command layer and a system integration compatibility layer, wherein the data integration sharing layer is configured to execute the following data integration sharing steps: receiving each heterogeneous data; storing each piece of heterogeneous data; the event center layer is configured to execute the following automatic processing steps: for each piece of heterogeneous data, executing the following steps: determining the heterogeneous data as target heterogeneous data; generating abnormal event information; the visual decision command layer is configured to perform visual processing on the abnormal event information; the system integration compatible layer is configured to construct a loose coupling architecture to support operation of the data integration sharing layer, the event center layer and the visual decision command layer in different system environments. According to the embodiment, the system stability is improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular to a city one-network unified management system and a method for sending abnormal event information. Background Art

[0002] With the rapid development of global information technology and smart cities, the complexity of urban management is also increasing. The city one-network unified management system is a system that shares various heterogeneous data (that is, data from different departments or different systems) and sends various abnormal event information to the corresponding terminals. At present, when sharing various heterogeneous data and sending various abnormal event information to the corresponding terminals, the usual method is to directly physically splice various business systems (that is, various department systems) at the hardware level, connect them through the basic network, and make simple docking configurations on the software interface to forcibly associate different systems to achieve the sharing of various heterogeneous data from various business systems.

[0003] However, when the above method is used to share heterogeneous data, the following technical problems often occur: Directly physically splice each business system (i.e., each department system) at the hardware level, connect through the basic network, and then make a simple docking configuration on the software interface to forcibly associate different systems in order to share the heterogeneous data from each business system. Since the spliced ​​system lacks a special processing and distribution mechanism for abnormal event information, it may not be possible to send the information of various abnormal events corresponding to each business system to the corresponding terminal. At the same time, forcibly associating different systems may cause extremely unstable system operation, frequent compatibility failures, and poor system stability.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0005] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0006] Some embodiments of the present disclosure propose a city one-network unified management system and a method for sending abnormal event information to solve one or more of the technical intentions mentioned in the above background technology section.

[0007] In a first aspect, some embodiments of the present disclosure provide a city one-network unified management system, the system comprising: a data integration and sharing layer, an event hub layer, a visual decision-making and command layer, and a system integration and compatibility layer, wherein: the data integration and sharing layer is configured to perform the following data integration and sharing steps: receiving various heterogeneous data sent by various heterogeneous data sources, wherein one heterogeneous data among the various heterogeneous data corresponds to a corresponding heterogeneous data source among the various heterogeneous data sources; sending the various heterogeneous data to the event hub layer; storing the various heterogeneous data, and generating data views and data access interfaces corresponding to the various heterogeneous data, so that various preset upper-layer applications can access the data through the data views and data access interfaces. The above-mentioned heterogeneous data; the above-mentioned event center layer is configured to perform the following automated processing steps: for each of the above-mentioned heterogeneous data, perform the following steps: determine the above-mentioned heterogeneous data as target heterogeneous data; based on the above-mentioned target heterogeneous data, generate abnormal event information; send the above-mentioned abnormal event information to at least one task receiving terminal; send the generated each abnormal event information to the above-mentioned visualization decision-making command layer; the above-mentioned visualization decision-making command layer is configured to perform visualization processing on the above-mentioned each abnormal event information; the above-mentioned system integration compatibility layer is configured to build a loosely coupled architecture to support the operation of the above-mentioned data integration and sharing layer, the above-mentioned event center layer, and the above-mentioned visualization decision-making command layer in different system environments.

[0008] In a second aspect, some embodiments of the present disclosure provide a method for sending abnormal event information, the method comprising: receiving various heterogeneous data sent by the above-mentioned data integration sharing layer; for each of the above-mentioned heterogeneous data, performing the following steps: determining the above-mentioned heterogeneous data as target heterogeneous data; generating abnormal event information based on the above-mentioned target heterogeneous data; and sending the above-mentioned abnormal event information to at least one task receiving terminal.

[0009] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: through the city one-network unified management system of some embodiments of the present disclosure, it is possible to send information of various abnormal events to the corresponding terminals and improve system stability. Specifically, the reason why it is difficult to send information of various abnormal events to the corresponding terminals and the system stability is poor is that: the various business systems (i.e., the systems of various departments) are directly physically spliced ​​at the hardware level, and after being connected through the basic network, a simple docking configuration is made on the software interface, and different systems are forcibly associated to achieve the sharing of various heterogeneous data from various business systems. Since the spliced ​​system lacks a special processing and distribution mechanism for abnormal event information, it may not be possible to send information of various abnormal events corresponding to each business system to the corresponding terminal. At the same time, forcibly associating different systems may cause extremely unstable system operation, frequent compatibility failures, and poor system stability. Based on this, the city one-network unified management system of some embodiments of the present disclosure includes: a data integration and sharing layer, an event center layer, a visual decision-making command layer, and a system integration compatibility layer, wherein: the data integration and sharing layer is configured to perform the following data integration and sharing steps: first, receiving each heterogeneous data sent by each heterogeneous data source, wherein one of the above heterogeneous data corresponds to a corresponding heterogeneous data source in the above heterogeneous data sources. Thus, each heterogeneous data sent by each heterogeneous data source (i.e., each business system) can be received. Then, the above heterogeneous data is sent to the above event center layer. Thus, each heterogeneous data can be sent to the event center layer so that the above event center layer can send abnormal event information to at least one task receiving terminal. Next, the above heterogeneous data is stored, and a data view and a data access interface corresponding to the above heterogeneous data are generated, so that each preset upper layer application can access the above heterogeneous data through the above data view and the data access interface. Thus, each heterogeneous data can be stored, and a data view and a data access interface for sharing and accessing each heterogeneous data can be generated. Through the above-mentioned data integration and sharing layer, various heterogeneous data from various heterogeneous data sources (i.e., various business systems) can be received, thereby realizing the integration and sharing of various heterogeneous data. The above-mentioned event hub layer is configured to perform the following automated processing steps: Step 1, for each of the above-mentioned heterogeneous data, the following steps are performed: Sub-step 1, determining the above-mentioned heterogeneous data as target heterogeneous data. Thus, the target heterogeneous data for generating abnormal event information can be determined. Sub-step 2, generating abnormal event information based on the above-mentioned target heterogeneous data. Thus, abnormal event information representing the occurrence of abnormal events corresponding to the above-mentioned heterogeneous data sources (i.e., business systems) can be generated. Sub-step 3, sending the above-mentioned abnormal event information to at least one task receiving terminal. Thus, the abnormal event information corresponding to a heterogeneous data source can be sent to at least one task receiving terminal corresponding to it.In the second step, each abnormal event information generated is sent to the above-mentioned visualization decision command layer. Thus, each abnormal event information can be sent to the visualization decision command layer so that the above-mentioned visualization decision command layer can visualize the above-mentioned abnormal event information. The above-mentioned event center layer realizes the special processing and distribution of the abnormal event information (i.e., each abnormal event information) existing in each heterogeneous data source (i.e., each business system). The above-mentioned visualization decision command layer is configured to perform visualization processing on the above-mentioned each abnormal event information. Thus, each abnormal event information can be visualized through the visualization decision command layer. The above-mentioned system integration compatibility layer is configured to build a loosely coupled architecture to support the operation of the above-mentioned data integration sharing layer, the above-mentioned event center layer, and the above-mentioned visualization decision command layer in different system environments. Thus, a loosely coupled architecture can be built through the system integration compatibility layer, which reduces the compatibility failures caused by the operation of the above-mentioned data integration sharing layer, the above-mentioned event center layer, and the above-mentioned visualization decision command layer in different system environments, and improves the stability of the system. Because the city network management system uses the event center layer to process and distribute the abnormal event information (i.e., each abnormal event information) in each heterogeneous data source (i.e., each business system), it can send the abnormal event information to at least one corresponding task receiving terminal. At the same time, the city network management system builds a loosely coupled architecture through the system integration compatibility layer, which reduces the compatibility failures caused by the operation of the above data integration and sharing layer, the above event center layer, and the above visual decision-making and command layer in different system environments, and improves the stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0011] Figure 1 is an architectural diagram of an exemplary system of a city one-network unified management system according to the present disclosure; Figure 2 Flowcharts of some embodiments of the method for sending abnormal event information according to the present disclosure. DETAILED DESCRIPTION

[0012] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0013] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0014] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0015] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0016] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0017] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0018] Figure 1 An exemplary system architecture 100 of a heterogeneous data exchange system is shown to which some embodiments of the present disclosure may be applied.

[0019] like Figure 1 As shown, the system architecture 100 may include: a data integration and sharing layer 101, an event hub layer 102, a visualization decision command layer 103, and a system integration and compatibility layer 104. The data integration and sharing layer 101 is communicated with the event hub layer 102. The event hub layer 102 is communicated with the visualization decision command layer 103. The system integration and compatibility layer 104 is communicated with the data integration and sharing layer 101, the event hub layer 102, and the visualization decision command layer 103 respectively. The above communication connection can be connected through the medium of the communication link (for example, a wired or wireless communication link or an optical fiber cable, etc.).

[0020] In some embodiments, the data integration and sharing layer 101 may be configured to perform the following data integration and sharing steps: The first step is to receive various heterogeneous data sent by various heterogeneous data sources. Among them, one heterogeneous data in the above-mentioned heterogeneous data corresponds to a corresponding heterogeneous data source in the above-mentioned heterogeneous data sources. Each heterogeneous data source in the above-mentioned heterogeneous data sources can be, but is not limited to, one of the following: an independent business system (such as a weather forecast business system, etc.), a database (such as a MySQL database, an Oracle database, etc.), a sensor (such as an environmental monitoring sensor, etc.). The above-mentioned data integration and sharing layer can be a data integration layer that collects, organizes, cleans, converts and stores data from different heterogeneous data sources. For example, the above-mentioned heterogeneous data can be "2023-10-01 08:30, the PM2.5 concentration in the XX area is 150μg / m³".

[0021] The second step is to send the above-mentioned heterogeneous data to the above-mentioned event hub layer. The above-mentioned event hub layer can be a layer (for example, an event bus) in the system architecture that processes the received heterogeneous data to generate and push abnormal event information.

[0022] The third step is to store the above-mentioned heterogeneous data, and generate data views and data access interfaces corresponding to the above-mentioned heterogeneous data, so that each preset upper-layer application can access the above-mentioned heterogeneous data through the data views and data access interfaces.

[0023] In some optional implementations of some embodiments, the data integration and sharing layer 101 may store the above-mentioned heterogeneous data and generate data views and data access interfaces corresponding to the above-mentioned heterogeneous data through the following steps: The first step is to store the above heterogeneous data in the preset data warehouse and generate data views corresponding to the above heterogeneous data. In practice, the data integration and sharing layer can use the preset ETL (Extract, Transform, Load) tool to store the above heterogeneous data in the preset data warehouse and generate data views corresponding to the above heterogeneous data.

[0024] The second step is to generate a data access interface for accessing the above-mentioned heterogeneous data. In practice, the above-mentioned data integration and sharing layer can use a preset ETL (Extract, Transform, Load) tool to generate a data access interface for accessing the above-mentioned heterogeneous data. Among them, the above-mentioned data access interface can be an API interface, a database connection interface, and other interfaces for accessing various heterogeneous data.

[0025] In some embodiments, the event hub layer 102 may be configured to perform the following automated processing steps: In the first step, for each of the above heterogeneous data, perform the following steps: The first sub-step is to determine the above heterogeneous data as target heterogeneous data.

[0026] The second sub-step is to generate abnormal event information based on the above target heterogeneous data.

[0027] The third sub-step is to send the abnormal event information to at least one task receiving terminal. Each of the at least one task receiving terminal may be a software system (e.g., a software system of a water conservancy department and a city construction department) or a hardware device (a computer, a tablet computer, or a smart phone) for receiving event information.

[0028] The second step is to send the generated abnormal event information to the above-mentioned visualization decision-making command layer. The above-mentioned visualization decision-making command layer can be a layer (for example, a presentation layer) in the system architecture for visually displaying each abnormal event information. For example, the above-mentioned visualization decision-making command layer can be an interactive console.

[0029] In some optional implementations of some embodiments, the event hub layer 102 may generate abnormal event information based on the target heterogeneous data through the following steps: The first step is to determine the target heterogeneous data as the target meteorological forecast heterogeneous data in response to determining that the target heterogeneous data is the meteorological forecast heterogeneous data. The target meteorological forecast heterogeneous data includes various meteorological forecast sub-data, and each meteorological forecast sub-data in the various meteorological forecast sub-data includes meteorological forecast information, regional information, and forecast time. The meteorological forecast heterogeneous information may be data from a meteorological forecast business system. The meteorological forecast information represents information about the weather forecast of a region. For example, the meteorological forecast information may be "the rainfall is expected to exceed 50 mm within 24 hours". The regional information may represent information about the location of the region. The forecast time may be the time when the weather is predicted to obtain the meteorological forecast sub-data.

[0030] In the second step, for each meteorological forecast sub-data included in the target meteorological forecast heterogeneous data, the following steps are performed: The first sub-step is to determine the weather forecast information included in the weather forecast sub-data as the target weather forecast information.

[0031] The second sub-step is, in response to determining that the target weather forecast information satisfies a trigger condition corresponding to a preset trigger condition information in the preset trigger condition information set, determining the weather forecast sub-data as the target weather forecast sub-data. Each trigger condition information in the preset trigger condition information set may represent a trigger condition. For example, the trigger condition may be "the maximum rainfall within 24 hours exceeds 40 mm".

[0032] The third sub-step is to generate abnormal event sub-information based on the above-mentioned target meteorological forecast sub-data. Among them, the above-mentioned abnormal event sub-information includes event type information, location information, and time information. In practice, first, the above-mentioned event hub layer can determine the meteorological forecast information included in the above-mentioned target meteorological forecast sub-data as event type information. Then, the regional information included in the target meteorological forecast sub-data is determined as location information. Next, the forecast time included in the target meteorological forecast sub-data is determined as time information. Finally, the above-mentioned event hub layer can determine the determined event type information, location information and time information as abnormal event sub-information. For example, the above-mentioned abnormal event sub-information can be {event type information: rainfall is expected to exceed 50 mm within 24 hours, location information: area A, time information: 12:18 on February 14, 2025}.

[0033] The third step is to determine each generated abnormal event sub-information as abnormal event information.

[0034] In some optional implementations of some embodiments, the event hub layer 102 may be further configured to perform the following steps: The first step is to determine the target heterogeneous data as traffic capture heterogeneous data in response to determining that the target heterogeneous data is traffic capture heterogeneous data. The target traffic capture heterogeneous data includes individual capture data. Each of the individual capture data includes capture imaging data, capture location information and capture time. The traffic capture heterogeneous data may be data from a traffic system. The capture imaging data may be a video or image captured by a camera (e.g., a camera) installed at a preset point (e.g., an intersection of a main traffic artery in a city). The capture location information may indicate the regional location where the camera is installed (e.g., the intersection of ×× Road and ×× Road in ×× District, ×× City). The capture time may be the time when the camera captures the image.

[0035] The second step is to generate abnormal event information based on the above-mentioned target traffic capture heterogeneous data.

[0036] In the process of adopting technical solutions to solve the problems mentioned in the background technology, the following problems are often accompanied: When the captured image data included in the target traffic captured heterogeneous data is identified to obtain the license plate identification (such as license plate number) of the vehicle in the captured image data for generating abnormal event information, the conventional solution is generally to directly identify the license plate identification of the vehicle in the captured image data. However, when the license plate identification of the vehicle in the captured image data is directly identified, the captured image corresponding to the captured image data may contain a large amount of background information (such as roads, buildings, vehicles, etc.) in addition to the license plate. This background information may increase the complexity of image processing and reduce the accuracy of license plate recognition. At the same time, when the vehicle is driving, the license plate in the captured image data captured by the camera device may be tilted, and the projection of the tilted license plate characters in the image may change, making the relative position relationship between the characters complicated, increasing the difficulty of recognition, and reducing the accuracy of license plate recognition. Due to the low accuracy of license plate recognition, the accuracy of abnormal event information generated based on license plate number recognition information is low. When the generated abnormal event information is wrong, it is necessary to re-identify the license plate in the captured image data and regenerate the abnormal event information, which increases the waste of computer computing resources.

[0037] In some optional implementations of some embodiments, the event hub layer may generate abnormal event information based on the target traffic capture heterogeneous data through the following steps: In the first step, each captured data included in the target traffic captured heterogeneous data is determined as each captured data to be identified.

[0038] In the second step, for each of the above-mentioned captured data to be identified, the following identification steps are performed: In the first sub-step, the captured position information included in the captured data to be identified is determined as the position information.

[0039] The second sub-step is to determine the capture time included in the captured data to be identified as the time information.

[0040] The third sub-step is to determine the captured image data included in the captured image data to be identified as the target captured image data.

[0041] The fourth sub-step is, in response to determining that the target captured image data is static image data, determining the image corresponding to the target captured image data as the image to be identified. The static image data may be data in a picture format.

[0042] In a fifth sub-step, in response to determining that the target captured image data is video data, a video frame is extracted from a video frame set corresponding to the target captured image data as an image to be identified. The video data may be data in a video format.

[0043] The sixth sub-step is to perform denoising on the image to be identified to obtain a denoised identification image. In practice, the event hub layer may use image denoising technology to perform denoising on the image to be identified. The denoised identification image may be an image after denoising the image to be identified.

[0044] The seventh sub-step is to grayscale the denoised recognition image to obtain a grayscale recognition image. In practice, the event core layer can grayscale the denoised recognition image by using an average grayscale processing technique to obtain a grayscale recognition image.

[0045] The eighth sub-step is to perform license plate area recognition processing on the grayscale recognition image to obtain license plate location information. In practice, the event center layer can perform license plate area recognition processing on the grayscale recognition image through template matching technology to obtain license plate location information. As an example, the event center layer can match a pre-prepared template image (here is the template of the license plate) with the grayscale image to be recognized, so as to find the area that best matches the template and obtain the license plate location information. Among them, the license plate location information can represent the position of the license plate in the grayscale recognition image.

[0046] The ninth sub-step is to segment the grayscale recognition image based on the license plate position information to obtain a background-removed license plate recognition image after the background is removed. In practice, the event hub layer can crop the grayscale recognition image based on the license plate position information and determine the image within the license plate position information as the background-removed license plate recognition image.

[0047] The tenth sub-step is to perform tilt correction processing on the above-mentioned background-removed license plate recognition image to obtain a tilt-corrected license plate recognition image. In practice, first, the above-mentioned event hub layer can use a corner detection algorithm (such as Harris corner detection) to locate the four corner points of the license plate in the background-removed license plate recognition image to obtain the coordinates of the four corner points. Then, the above-mentioned event hub layer can generate a perspective transformation matrix according to a preset function (for example, cv2.getPerspectiveTransform function) based on the preset target license plate aspect ratio (that is, the ratio of the length and width of the real license plate) and the above-mentioned four corner point coordinates. Afterwards, the above-mentioned event hub layer can perform perspective transformation processing on the above-mentioned background-removed license plate recognition image according to the above-mentioned perspective transformation matrix to obtain a tilt-corrected license plate recognition image.

[0048] The eleventh sub-step is to perform license plate number recognition on the tilt-corrected license plate recognition image to obtain license plate number recognition information. In practice, the event center layer can input the tilt-corrected license plate recognition image into a pre-trained license plate number recognition model to obtain license plate number recognition information. The pre-trained license plate number recognition model can be a neural network model (e.g., a convolutional neural network (CNN) model) for recognizing images to obtain license plate number recognition information. The license plate number recognition information can represent the license plate number.

[0049] In the twelfth sub-step, based on the time information and the license plate number recognition information, the positioning information corresponding to the time information and the license plate number recognition information is searched from a preset database to obtain the search positioning information. The search positioning information may be GPS information corresponding to the time information and the license plate number recognition information. The preset database may be a database storing vehicle GPS information.

[0050] In the thirteenth sub-step, in response to determining that the query positioning information is empty, determining the information indicating that the vehicle corresponding to the license plate number recognition information has not been positioned as event type information. The information indicating that the vehicle has not been positioned can be text information indicating that the vehicle has not been positioned.

[0051] The fourteenth sub-step is to determine the determined location information, time information, and event type information as abnormal event sub-information.

[0052] The third step is to determine each determined abnormal event sub-information as abnormal event information.

[0053] The above technical solution and its related contents, as an inventive point of an embodiment of the present disclosure, solve the technical problem of "waste of computer computing resources". The factors that lead to the waste of computer computing resources are often as follows: directly identifying the license plate identification of the vehicle in the captured imaging data, the captured image corresponding to the captured imaging data may contain a large amount of background information other than the license plate (for example, roads, buildings, vehicles, etc.), and these background information may increase the complexity of image processing and reduce the accuracy of license plate recognition. At the same time, when the vehicle is driving, the license plate in the captured imaging data captured by the camera device may be tilted, and the projection of the tilted license plate characters in the image may change, making the relative position relationship between the characters complicated, increasing the difficulty of recognition, and reducing the accuracy of license plate recognition. Due to the low accuracy of license plate recognition, the accuracy of the abnormal event sub-information generated based on the license plate number recognition information is low. When the generated abnormal event sub-information is wrong, it is necessary to re-identify the license plate in the captured imaging data and regenerate the abnormal event sub-information, which increases the waste of computer computing resources. If the above factors are solved, the effect of reducing the waste of computer computing resources can be achieved. In order to achieve this effect, first, each captured data included in the above-mentioned target traffic captured heterogeneous data is determined as each captured data to be identified. Then, for each captured data to be identified in the above-mentioned captured data to be identified, the following identification steps are performed: the first step is to determine the captured location information included in the above-mentioned captured data to be identified as location information. Thus, the location information required to be included in the abnormal event sub-information can be determined. The second step is to determine the capture time included in the above-mentioned captured data to be identified as time information. Thus, the time information required to be included in the abnormal event sub-information can be determined. The third step is to determine the captured imaging data included in the above-mentioned captured data to be identified as the target captured imaging data. The fourth step is to determine that the above-mentioned target captured imaging data is static image data in response to determining that the above-mentioned target captured imaging data is static image data, and determine the image corresponding to the above-mentioned target captured imaging data as the image to be identified. The fifth step is to extract a video frame from the video frame set corresponding to the above-mentioned target captured imaging data as the image to be identified in response to determining that the above-mentioned target captured imaging data is video data. Thus, the image to be identified for identifying the license plate number can be obtained. The sixth step is to perform denoising on the image to be identified to obtain a denoised identification image. In this way, the image to be identified can be denoised to reduce the noise in the image to be identified. The seventh step is to perform grayscale processing on the denoised identification image to obtain a grayscale identification image. In this way, the color information of the denoised identification image can be removed, and the edge, texture and other features of the image can be highlighted. The eighth step is to perform license plate area recognition processing on the grayscale identification image to obtain the license plate position information. In this way, the license plate position in the grayscale identification image can be determined. The ninth step is to perform segmentation processing on the grayscale identification image based on the license plate position information to obtain a background-removed license plate recognition image after the background is removed.Thus, the background information other than the license plate in the grayscale recognition image can be removed, and the interference of subsequent background information on the license plate number recognition can be reduced. The tenth step is to perform tilt correction processing on the above-mentioned background-removed license plate recognition image to obtain a tilt-corrected license plate recognition image. Thus, the background-removed license plate recognition image can be tilt-corrected to ensure that the license plate characters are correctly arranged in the vertical direction. The eleventh step is to perform license plate number recognition on the above-mentioned tilt-corrected license plate recognition image to obtain license plate number recognition information. Thus, the license plate number recognition information used to generate event type information can be obtained. The twelfth step is to query the positioning information corresponding to the above-mentioned time information and the above-mentioned license plate number recognition information from the preset database based on the above-mentioned time information and the above-mentioned license plate number recognition information to obtain the query positioning information. Thus, the positioning information of the vehicle corresponding to the license plate number recognition information at the time point corresponding to the above-mentioned event information can be queried from the preset database. The thirteenth step is to determine that the above-mentioned query positioning information is empty in response to determining that the above-mentioned query positioning information is empty, and to determine the information that the vehicle corresponding to the above-mentioned license plate number recognition information is not located as the event type information. Thus, when the camera captures the vehicle in motion but cannot find the location information of the vehicle, the information indicating that the vehicle corresponding to the license plate number recognition information has not been located can be determined as event type information. In the fourteenth step, the determined location information, time information, and event type information are determined as abnormal event sub-information. Thus, abnormal event sub-information can be obtained. In the fifteenth step, each determined abnormal event sub-information is determined as abnormal event information. Also, before the license plate number recognition is performed on the image to be recognized corresponding to the captured imaging data, the grayscale recognition image is segmented based on the license plate position information to obtain a background-removed license plate recognition image after removing the background information, thereby reducing the interference of subsequent background information on the license plate number recognition and improving the accuracy of the license plate recognition. At the same time, the background-removed license plate recognition image is tilt-corrected to ensure that the license plate characters are correctly arranged in the vertical direction, further improving the accuracy of the license plate recognition. The accuracy of the abnormal event sub-information generated based on the license plate number recognition information is improved, the number of times of re-recognition and re-generation of abnormal event sub-information is reduced, and the waste of computer computing resources is reduced.

[0054] In some optional implementations of some embodiments, the event hub layer 102 may send the abnormal event information to at least one task receiving terminal through the following steps: The first step is to perform the following steps for each abnormal event sub-information in each abnormal event sub-information included in the abnormal event information: The first sub-step is to determine at least one task receiving terminal identifier corresponding to the above-mentioned abnormal event sub-information through a preset workflow engine. As an example, the above-mentioned abnormal event sub-information may be {event type information: rainfall is expected to exceed 50 mm within 24 hours, location information: Region A, time information: 12:18 on February 14, 2025}. The at least one task receiving terminal identifier determined may be the task receiving terminal of the water conservancy department in Region A and the task receiving terminal of the urban construction department in Region A. In practice, the above-mentioned event hub layer 102 may match the event type information and location information included in the abnormal event sub-information through the business process rules and logic built into the preset workflow engine to obtain at least one task receiving terminal identifier. Among them, each of the above-mentioned at least one task receiving terminal identifier may be the name of the task receiving terminal.

[0055] The second sub-step is to send the above-mentioned abnormal event sub-information to at least one task receiving terminal corresponding to the above-mentioned at least one task receiving terminal identifier.

[0056] In some embodiments, the visualization decision command layer 103 may be configured to visualize the above-mentioned various abnormal event information. Among them, the visualization decision command layer includes a spatiotemporal information platform and a visualization data analysis platform. The spatiotemporal information platform may be a platform for visualizing various abnormal event information. The visualization data analysis platform may be a platform for generating corresponding decision prediction information based on various abnormal event information. Among them, the decision prediction information may be text information of response information made for each abnormal event information. For example, the decision prediction information may be "inspection and cleaning of drainage system".

[0057] In some optional implementations of some embodiments, the visualization decision command layer 103 may visualize the above-mentioned various abnormal event information through the following steps: In the first step, the above-mentioned spatiotemporal information platform is configured to perform the following visualization steps: The first sub-step is to mark the abnormal event sub-information in the preset plane map for each abnormal event sub-information in the above-mentioned abnormal event information. In practice, first, the above-mentioned spatiotemporal information platform can determine the location information included in the abnormal event sub-information as the target location information. Then, the above-mentioned spatiotemporal information platform can query the location corresponding to the target location information in the preset plane map. Afterwards, the spatiotemporal information platform can mark the above-mentioned abnormal event sub-information in the preset plane map corresponding to the above-mentioned target location information through the label thematic map annotation technology.

[0058] In the second sub-step, a preset plane map with sub-information of each abnormal event marked is displayed on the preset decision-making command page.

[0059] The third sub-step is, in response to detecting a click operation on a piece of abnormal event sub-information in the above-mentioned preset plane map, determining the location information included in the above-mentioned abnormal event sub-information as the abnormal event occurrence location information.

[0060] The fourth sub-step is to display a preset three-dimensional geographic model centered on the location corresponding to the location information of the abnormal event. The three-dimensional geographic model may be a three-dimensional map.

[0061] In the second step, the above-mentioned visual data analysis platform is configured to generate various decision prediction information corresponding to the above-mentioned various abnormal event information based on the above-mentioned various abnormal event information, and display the above-mentioned various decision prediction information. In practice, for each abnormal event information in the above-mentioned various abnormal event information, the above-mentioned visual data analysis platform can input the abnormal event information into a pre-trained decision information generation model to obtain decision prediction information. Among them, the above-mentioned decision information generation model can be a generative model (for example, a CHAT model) that takes abnormal event information as input and decision prediction information as output.

[0062] In some embodiments, the system integration compatibility layer 104 may be configured to build a loosely coupled architecture to support the operation of the data integration sharing layer, the event center layer, and the visual decision command layer in different system environments. The system integration compatibility layer may be a middleware or an adaptation layer for building a loosely coupled integration architecture. For example, the system integration compatibility layer may be an interface converter.

[0063] Figure 2 The process 200 of some embodiments of the method for sending abnormal event information of the event hub layer included in the above-mentioned city one network unified management system according to the present disclosure is shown. The abnormal event information sending method includes the following steps: Step 201: receiving various heterogeneous data sent by the data integration and sharing layer.

[0064] In some embodiments, the execution entity of abnormal event information transmission (eg, the event center layer included in the city one-network management system) can receive various heterogeneous data sent by the above-mentioned data integration and sharing layer.

[0065] Step 202: for each heterogeneous data, perform the following steps: Step 2021, determining the heterogeneous data as target heterogeneous data.

[0066] In some embodiments, the execution entity may determine the heterogeneous data as target heterogeneous data.

[0067] Step 2022, generating abnormal event information based on the target heterogeneous data.

[0068] In some embodiments, the execution entity may generate abnormal event information based on the target heterogeneous data.

[0069] Step 2023: Send the abnormal event information to at least one task receiving terminal.

[0070] In some embodiments, the execution entity may send the abnormal event information to at least one task receiving terminal.

[0071] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: through the abnormal event information sending method applied to the event center layer included in the above-mentioned city one-network unified management system in some embodiments of the present disclosure, the abnormal event information (i.e., each abnormal event information) existing in each heterogeneous data source (i.e., each business system) is specially processed and distributed. The abnormal event information sending method applied to the event center layer included in the above-mentioned city one-network unified management system in some embodiments of the present disclosure includes: first, receiving each heterogeneous data sent by the above-mentioned data integration and sharing layer. Thus, each heterogeneous data sent by each heterogeneous data source (i.e., each business system) can be received. Then, for each heterogeneous data in the above-mentioned heterogeneous data, the following steps are performed: Sub-step 1, determining the above-mentioned heterogeneous data as target heterogeneous data. Thus, the target heterogeneous data for generating abnormal event information can be determined. Sub-step 2, generating abnormal event information based on the above-mentioned target heterogeneous data. Thus, abnormal event information characterizing abnormal events corresponding to the above-mentioned heterogeneous data source (i.e., business system) can be generated. Sub-step 3, sending the above-mentioned abnormal event information to at least one task receiving terminal. Thus, the abnormal event information corresponding to a heterogeneous data source can be sent to at least one task receiving terminal corresponding thereto. Thus, through the above steps, the abnormal event information (i.e., each abnormal event information) existing in each heterogeneous data source (i.e., each business system) can be specially processed and distributed.

[0072] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: through the city one-network unified management system of some embodiments of the present disclosure, it is possible to send information of various abnormal events to the corresponding terminals and improve system stability. Specifically, the reason why it is difficult to send information of various abnormal events to the corresponding terminals and the system stability is poor is that: the various business systems (i.e., the systems of various departments) are directly physically spliced ​​at the hardware level, and after being connected through the basic network, a simple docking configuration is made on the software interface, and different systems are forcibly associated to achieve the sharing of various heterogeneous data from various business systems. Since the spliced ​​system lacks a special processing and distribution mechanism for abnormal event information, it may not be possible to send information of various abnormal events corresponding to each business system to the corresponding terminal. At the same time, forcibly associating different systems may cause extremely unstable system operation, frequent compatibility failures, and poor system stability. Based on this, the city one-network unified management system of some embodiments of the present disclosure includes: a data integration and sharing layer, an event center layer, a visual decision-making command layer, and a system integration compatibility layer, wherein: the data integration and sharing layer is configured to perform the following data integration and sharing steps: first, receiving each heterogeneous data sent by each heterogeneous data source, wherein one of the above heterogeneous data corresponds to a corresponding heterogeneous data source in the above heterogeneous data sources. Thus, each heterogeneous data sent by each heterogeneous data source (i.e., each business system) can be received. Then, the above heterogeneous data is sent to the above event center layer. Thus, each heterogeneous data can be sent to the event center layer so that the above event center layer can send abnormal event information to at least one task receiving terminal. Next, the above heterogeneous data is stored, and a data view and a data access interface corresponding to the above heterogeneous data are generated, so that each preset upper layer application can access the above heterogeneous data through the above data view and the data access interface. Thus, each heterogeneous data can be stored, and a data view and a data access interface for sharing and accessing each heterogeneous data can be generated. Through the above-mentioned data integration and sharing layer, various heterogeneous data from various heterogeneous data sources (i.e., various business systems) can be received, thereby realizing the integration and sharing of various heterogeneous data. The above-mentioned event hub layer is configured to perform the following automated processing steps: Step 1, for each of the above-mentioned heterogeneous data, the following steps are performed: Sub-step 1, determining the above-mentioned heterogeneous data as target heterogeneous data. Thus, the target heterogeneous data for generating abnormal event information can be determined. Sub-step 2, generating abnormal event information based on the above-mentioned target heterogeneous data. Thus, abnormal event information representing the occurrence of abnormal events corresponding to the above-mentioned heterogeneous data sources (i.e., business systems) can be generated. Sub-step 3, sending the above-mentioned abnormal event information to at least one task receiving terminal. Thus, the abnormal event information corresponding to a heterogeneous data source can be sent to at least one task receiving terminal corresponding to it.In the second step, each abnormal event information generated is sent to the above-mentioned visualization decision command layer. Thus, each abnormal event information can be sent to the visualization decision command layer so that the above-mentioned visualization decision command layer can visualize the above-mentioned abnormal event information. The above-mentioned event center layer realizes the special processing and distribution of the abnormal event information (i.e., each abnormal event information) existing in each heterogeneous data source (i.e., each business system). The above-mentioned visualization decision command layer is configured to perform visualization processing on the above-mentioned each abnormal event information. Thus, each abnormal event information can be visualized through the visualization decision command layer. The above-mentioned system integration compatibility layer is configured to build a loosely coupled architecture to support the operation of the above-mentioned data integration sharing layer, the above-mentioned event center layer, and the above-mentioned visualization decision command layer in different system environments. Thus, a loosely coupled architecture can be built through the system integration compatibility layer, which reduces the compatibility failures caused by the operation of the above-mentioned data integration sharing layer, the above-mentioned event center layer, and the above-mentioned visualization decision command layer in different system environments, and improves the stability of the system. Because the city network management system uses the event center layer to process and distribute the abnormal event information (i.e., each abnormal event information) in each heterogeneous data source (i.e., each business system), it can send the abnormal event information to at least one corresponding task receiving terminal. At the same time, the city network management system builds a loosely coupled architecture through the system integration compatibility layer, which reduces the compatibility failures caused by the operation of the above data integration and sharing layer, the above event center layer, and the above visual decision-making and command layer in different system environments, and improves the stability of the system.

[0073] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of technical features, but should also cover other technical solutions formed by any combination of technical features or their equivalent features without departing from the inventive concept. For example, a technical solution formed by replacing a feature with a technical feature with similar functions disclosed in the embodiments of the present disclosure (but not limited to).

Claims

1. A city one-network unified management system, comprising: Data integration and sharing layer, event center layer, visual decision-making and command layer, system integration and compatibility layer, including: The data integration and sharing layer is configured to perform the following data integration and sharing steps: Receiving various heterogeneous data sent by various heterogeneous data sources, wherein one heterogeneous data among the various heterogeneous data corresponds to a corresponding one heterogeneous data source among the various heterogeneous data sources; Sending the various heterogeneous data to the event hub layer; Storing the various heterogeneous data, and generating data views and data access interfaces corresponding to the various heterogeneous data, so that various preset upper layer applications can access the various heterogeneous data through the data views and data access interfaces; The event hub layer is configured to perform the following automated processing steps: For each heterogeneous data in the various heterogeneous data, the following steps are performed: determining the heterogeneous data as target heterogeneous data; Based on the target heterogeneous data, generating abnormal event information; Sending the abnormal event information to at least one task receiving terminal; Sending each generated abnormal event information to the visualization decision-making command layer; The visualization decision-making command layer is configured to perform visualization processing on each abnormal event information; The system integration compatibility layer is configured to build a loosely coupled architecture to support the operation of the data integration sharing layer, the event hub layer, and the visualization decision-making command layer in different system environments.

2. The city one network unified management system according to claim 1, wherein: The data integration and sharing layer is further configured to store the various heterogeneous data and generate data views and data access interfaces corresponding to the various heterogeneous data through the following steps: Storing each of the heterogeneous data in a preset data warehouse, and generating a data view corresponding to each of the heterogeneous data; Generate a data access interface for accessing the various heterogeneous data.

3. The city one network unified management system according to claim 1, wherein: The various heterogeneous data include traffic capture heterogeneous data and weather forecast heterogeneous data, and the event hub layer is further configured to generate abnormal event information based on the target heterogeneous data through the following steps, including: In response to determining that the target heterogeneous data is meteorological forecast heterogeneous data, determining the target heterogeneous data as target meteorological forecast heterogeneous data, wherein the target meteorological forecast heterogeneous data includes various meteorological forecast sub-data, and each meteorological forecast sub-data in the various meteorological forecast sub-data includes meteorological forecast information, regional information, and forecast time; For each meteorological forecast sub-data in each meteorological forecast sub-data included in the target meteorological forecast heterogeneous data, the following steps are performed: determining the weather forecast information included in the weather forecast sub-data as target weather forecast information; In response to determining that the target weather forecast information satisfies a trigger condition corresponding to a preset trigger condition information in a preset trigger condition information set, determining the weather forecast sub-data as the target weather forecast sub-data; Generate abnormal event sub-information based on the target meteorological forecast sub-data, wherein the abnormal event sub-information includes event type information, location information, and time information; The generated individual abnormal event sub-information is determined as abnormal event information.

4. The city one network unified management system according to claim 1, wherein: The event hub layer is further configured to perform the following steps: In response to determining that the target heterogeneous data is traffic captured heterogeneous data, determining the target heterogeneous data as target traffic captured heterogeneous data, wherein the target traffic captured heterogeneous data includes individual captured data, wherein each captured data in the individual captured data includes captured imaging data, captured location information, and captured time; Based on the target traffic captured heterogeneous data, abnormal event information is generated.

5. The city one network unified management system according to claim 1, wherein: The event hub layer is further configured to send the abnormal event information to at least one task receiving terminal through the following steps, including: For each abnormal event sub-information in each abnormal event sub-information included in the abnormal event information, the following steps are performed: Determine, by means of a preset workflow engine, at least one task receiving terminal identifier corresponding to the abnormal event sub-information; The abnormal event sub-information is sent to at least one task receiving terminal corresponding to the at least one task receiving terminal identifier.

6. The city one network unified management system according to claim 1, wherein: The visualization decision-making command layer includes: a spatiotemporal information platform and a visualization data analysis platform; and the visualization decision-making command layer is further configured to visualize the information of each abnormal event through the following steps, including: The spatiotemporal information platform is configured to perform the following visualization steps: For each abnormal event sub-information in each abnormal event information, marking the abnormal event sub-information in a preset plane map; Display a preset plane map with sub-information of each abnormal event marked on the preset decision-making command page; In response to detecting a click operation on a piece of abnormal event sub-information in the preset plane map, determining the location information included in the abnormal event sub-information as the abnormal event occurrence location information; Displaying a preset three-dimensional geographic model centered on the location corresponding to the location information of the abnormal event; The visual data analysis platform is configured to generate each decision prediction information corresponding to each abnormal event information based on the each abnormal event information, and display the each decision prediction information.

7. A method for sending abnormal event information, applied to the event center layer included in the city one network unified management system according to any one of claims 1 to 6, the method comprising: Receiving various heterogeneous data sent by the data integration and sharing layer; For each heterogeneous data in the various heterogeneous data, the following steps are performed: determining the heterogeneous data as target heterogeneous data; Based on the target heterogeneous data, generating abnormal event information; The abnormal event information is sent to at least one task receiving terminal.

Images