Smart city traffic management system based on big data

Abstract

The invention relates to a smart city traffic management system based on big data. The smart city traffic management system comprises a preview analysis device, a filter sharpening device, a signal processing device, a contrast reservation device, a visual analysis device and an acoustic alarm device. According to the invention, automatic management of smart city traffic can be realized.

Description

Technical Field

[0001] The present invention relates to the field of smart cities, and in particular to a smart city traffic management system based on big data. Background Art

[0002] The development of smart cities involves all aspects of the city, among which traffic information is the most important aspect. The traffic environment is the sum of all external influences and forces acting on road traffic participants, including road conditions, traffic facilities, landforms, meteorological conditions, and traffic activities of other traffic participants.

[0003] Traffic environment, by definition, is the various external or internal conditions that regulate and limit people's traffic actions. The words "regulate" and "limit" are used here, which means that all actions of the driver when driving are determined by the traffic environment and are restricted by the traffic environment. They must not do whatever they want. It can be said that most traffic accidents are caused by drivers not adapting to the traffic environment. Therefore, as a driver, it is very important to understand the relationship between oneself and the traffic environment and the impact of the traffic environment on one's driving behavior. For traffic management personnel, understanding and mastering the traffic environment in their jurisdiction will be of great help to their work.

[0004] CN117974075A discloses a smart city public information management system based on big data, including: by establishing a target DFTGCN smart city public information identification model; obtaining real-time public information data in the city server, inputting the real-time public information data into the target DFTGCN smart city public information identification model for identification, and obtaining the city public status data; judging whether the public transportation status of the smart city is in a congested state based on the city public status data, and if it is judged to be in a congested state, the public transportation status is input into the public broadcasting system, the public media communication system and the traffic bureau command system. It can realize real-time monitoring and prediction of traffic flow in smart cities, and provide strong support for traffic planning and scheduling. Summary of the invention

[0005] In order to solve the technical problems in the prior art, the present invention provides a smart city traffic management system based on big data, which can identify the image areas corresponding to the first hull target and the second hull target respectively from the contrast-preserved image based on the standard appearance patterns of the first hull target and the second hull target respectively, and analyze the shortest distance between the first hull target and the second hull target according to the shortest visual distance between the image areas corresponding to the first hull target and the second hull target respectively, thereby completing high-precision distance analysis at the pixel level, and when the shortest distance between the visually analyzed first hull target and the second hull target is less than or equal to the set distance limit, an acoustic safety alarm information corresponding to the close distance between the two ships is issued, otherwise, the issuance of the acoustic safety alarm information corresponding to the close distance between the two ships is temporarily suspended, thereby realizing automatic management of the traffic environment of the port entrance area.

[0006] According to the present invention, the system comprises: A preview analysis device, configured to perform existence analysis of a hull target on a preview screen corresponding to an image collected from an entry area of ​​a seaport, and output a real-shot screen corresponding to the preview screen when it is analyzed that there are two hull targets in the preview screen, wherein the two hull targets include a first hull target and a second hull target; A filter sharpening device, connected to the preview analysis device, for performing high-pass filter sharpening processing on the received real-shot picture to obtain and output a corresponding filter sharpened image; A signal processing device, connected to the filtering and sharpening device, for performing FRANGI filtering on the received filtered and sharpened image to obtain and output a corresponding live filtered image; A contrast preserving device, connected to the signal processing device, for performing processing on the received live filtered image to preserve the junction of two parts with obvious color or light-dark contrast in the image, so as to obtain and output a corresponding contrast preserving image; A visual analysis device, connected to the contrast retention device and comprising a feature application device, a combination processing device and an interval analysis device, wherein the combination processing device is respectively connected to the feature application device and the interval analysis device, wherein the interval recognition device is used to identify the image areas corresponding to the first hull target and the second hull target from the received contrast retention image based on the respective standard shape patterns of the first hull target and the second hull target, and output them as reference image areas and adjacent image areas respectively, taking the constituent pixels of the reference image area as reference pixels, taking the constituent pixels of the adjacent image area as adjacent pixels, obtaining the number of interval pixels between two pixels in any combination of adjacent pixels of the reference pixel to determine the physical distance corresponding to any combination of adjacent pixels of the reference pixel, and outputting the physical distance with the smallest value among the physical distances corresponding to the respective combinations of adjacent pixels of the reference pixel as the visual analysis distance of the first hull target and the second hull target; The acoustic alarm device is placed in the ground control room corresponding to the seaport and connected to the visual analysis device. It is used to send out an acoustic safety alarm message corresponding to the close distance between the two ships when the visual analysis distance between the first hull target and the second hull target is less than or equal to the set distance limit. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The embodiments of the present invention will be described below with reference to the accompanying drawings.

[0008] Figure 1 It is a structural block diagram of a smart city traffic management system based on big data according to the primary embodiment of the present invention.

[0009] Figure 2 It is a structural block diagram of a smart city traffic management system based on big data according to a secondary embodiment of the present invention.

[0010] Figure 3 The present invention is a block diagram of the structure of a smart city traffic management system based on big data according to another embodiment of the present invention. DETAILED DESCRIPTION

[0011] In the sea traffic environment, it is common for two ships to meet. Since the two ships belong to two different traffic control systems, it is easy for two parts of the two ships to come into too close contact during the driving process, which can easily cause a ship collision accident. How to accurately identify the relative status of the two ships and detect and warn of subtle contact status is one of the technical problems that need to be solved in the existing technology.

[0012] The following will describe in detail an embodiment of the smart city traffic management system based on big data of the present invention with reference to the accompanying drawings.

[0013] Figure 1 The structure block diagram of the smart city traffic management system based on big data according to the primary embodiment of the present invention is shown, and the system includes: A preview analysis device, configured to perform existence analysis of a hull target on a preview screen corresponding to an image collected from an entry area of ​​a seaport, and output a real-shot screen corresponding to the preview screen when it is analyzed that there are two hull targets in the preview screen, wherein the two hull targets include a first hull target and a second hull target; For example, an ASIC chip may be selected to implement the preview analysis device, which is used to perform existence analysis of a hull target on a preview screen corresponding to an image collected from an entry area of ​​a seaport, and output a real-shot screen corresponding to the preview screen when it is analyzed that there are two hull targets in the preview screen, wherein the two hull targets include a first hull target and a second hull target; A filter sharpening device, connected to the preview analysis device, for performing high-pass filter sharpening processing on the received real-shot picture to obtain and output a corresponding filter sharpened image; A signal processing device, connected to the filtering and sharpening device, for performing FRANGI filtering on the received filtered and sharpened image to obtain and output a corresponding live filtered image; A contrast preserving device, connected to the signal processing device, for performing processing on the received live filtered image to preserve the junction of two parts with obvious color or light-dark contrast in the image, so as to obtain and output a corresponding contrast preserving image; A visual analysis device, connected to the contrast retention device and comprising a feature application device, a combination processing device and an interval analysis device, wherein the combination processing device is respectively connected to the feature application device and the interval analysis device, wherein the interval recognition device is used to identify the image areas corresponding to the first hull target and the second hull target from the received contrast retention image based on the respective standard shape patterns of the first hull target and the second hull target, and output them as reference image areas and adjacent image areas respectively, taking the constituent pixels of the reference image area as reference pixels, taking the constituent pixels of the adjacent image area as adjacent pixels, obtaining the number of interval pixels between two pixels in any combination of adjacent pixels of the reference pixel to determine the physical distance corresponding to any combination of adjacent pixels of the reference pixel, and outputting the physical distance with the smallest value among the physical distances corresponding to the respective combinations of adjacent pixels of the reference pixel as the visual analysis distance of the first hull target and the second hull target; An acoustic alarm device is placed in a ground control room corresponding to the seaport and connected to the visual analysis device, and is used to send an acoustic safety alarm message corresponding to the two ships being too close to each other when the visual analysis distance between the first ship target and the second ship target is less than or equal to a set distance limit; Wherein, the acoustic alarm device is also used to temporarily suspend the issuance of acoustic safety alarm information corresponding to the close distance between the two ships when the visual analysis distance between the first hull target and the second hull target is greater than the set distance limit.

[0014] Figure 2 It is a structural block diagram of a smart city traffic management system based on big data according to a secondary embodiment of the present invention.

[0015] Compared to Figure 1 , Figure 2 The big data-based smart city traffic management system can also include: A humidity detection device, which is arranged near the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is connected to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively; Among them, the humidity detection device is arranged near the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is respectively connected to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device, including: the humidity detection device is used to realize on-site measurement of the current humidity of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device, respectively.

[0016] Figure 3 It is a structural block diagram of a smart city traffic management system based on big data according to a secondary embodiment of the present invention.

[0017] Compared to Figure 1 , Figure 3 The big data-based smart city traffic management system can also include: A thickness detection device, which is arranged near the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is connected to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively; Among them, the thickness detection device is arranged near the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is respectively connected to the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device, including: the thickness detection device is used to realize on-site measurement of the current thickness of the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device, respectively.

[0018] Next, the specific structure of the smart city traffic management system based on big data of the present invention is further explained.

[0019] In the smart city traffic management system based on big data according to various embodiments of the present invention: An embedded processing device is used to perform image data processing on the output data of the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain output processing data corresponding to the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

[0020] And in the smart city traffic management system based on big data according to various embodiments of the present invention: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing color scale adjustment on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

[0021] And in the smart city traffic management system based on big data according to various embodiments of the present invention: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing image restoration on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

[0022] And in the smart city traffic management system based on big data according to various embodiments of the present invention: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing rotation correction on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

[0023] And in the smart city traffic management system based on big data according to various embodiments of the present invention: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing alpha mean filtering processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

[0024] In addition, in the smart city traffic management system based on big data, performing an existence analysis of a hull target on a preview screen corresponding to an image collected from an entry area of ​​a seaport, and when it is analyzed that there are two hull targets in the preview screen, outputting a real shot screen corresponding to the preview screen includes: the preview screen and the real shot screen corresponding to the preview screen have the same content and different resolutions; The preview picture and the real shot picture corresponding to the preview picture have the same content but different resolutions, which includes: the resolution of the real shot picture corresponding to the preview picture is several times the resolution of the preview picture.

[0025] It can be seen that the present invention has at least the following four main inventive concepts: Inventive concept A: Based on the respective standard shape patterns of the first hull target and the second hull target, the image regions corresponding to the first hull target and the second hull target are respectively identified from the contrast-preserved image, and the shortest distance between the first hull target and the second hull target is resolved according to the shortest visual distance between the image regions corresponding to the first hull target and the second hull target, thereby completing high-precision distance resolution at the pixel level; Inventive concept B: When the shortest distance between the first ship target and the second ship target in the visual analysis is less than or equal to the set distance limit, an acoustic safety alarm message corresponding to the close distance between the two ships is issued; otherwise, the acoustic safety alarm message corresponding to the close distance between the two ships is temporarily suspended, thereby realizing automatic management of the traffic environment of the port entry area; Inventive concept C: High-pass filter sharpening processing, FRANGI filter processing, and retaining processing of the junction of two parts with obvious color or light-dark contrast in the image are sequentially performed on the real-shot images of the harbor entrance, so as to provide reliable basic data for subsequent visual analysis; Inventive concept D: Only when there are two hull targets in the preview picture corresponding to the image collected from the port entrance area, the real-shot picture corresponding to the preview picture is output, thereby reducing the amount of computation for on-site data processing and reducing the power consumption of the data processing system.

[0026] The big data-based smart city traffic management system of the present invention can identify the slight changes in the closest distance between two adjacent ship targets in the sea surface traffic environment based on a targeted visual analysis mechanism to address the technical problem in the prior art that it is difficult to accurately identify the slight changes in the distance between two adjacent ship targets in the sea surface traffic environment, so as to decide whether to issue an acoustic safety alarm message corresponding to the close distance between the two ships, thereby realizing automatic management of the traffic environment in the port entrance area.

[0027] The present embodiments are to be considered in all respects as illustrative and not restrictive, and all changes coming within the meaning and equivalency range of the appended claims are intended to be embraced within their scope.

Claims

1. A smart city traffic management system based on big data, characterized in that: The system comprises: A preview analysis device, configured to perform existence analysis of a hull target on a preview screen corresponding to an image collected from an entry area of ​​a seaport, and output a real-shot screen corresponding to the preview screen when it is analyzed that there are two hull targets in the preview screen, wherein the two hull targets include a first hull target and a second hull target; A filter sharpening device, connected to the preview analysis device, for performing high-pass filter sharpening processing on the received real-shot picture to obtain and output a corresponding filter sharpened image; A signal processing device, connected to the filtering and sharpening device, for performing FRANGI filtering on the received filtered and sharpened image to obtain and output a corresponding live filtered image; A contrast preserving device, connected to the signal processing device, for performing processing on the received live filtered image to preserve the junction of two parts with obvious color or light-dark contrast in the image, so as to obtain and output a corresponding contrast preserving image; A visual analysis device, connected to the contrast retention device and comprising a feature application device, a combination processing device and an interval analysis device, wherein the combination processing device is respectively connected to the feature application device and the interval analysis device, wherein the interval recognition device is used to identify the image areas corresponding to the first hull target and the second hull target from the received contrast retention image based on the respective standard shape patterns of the first hull target and the second hull target, and output them as reference image areas and adjacent image areas respectively, taking the constituent pixels of the reference image area as reference pixels, taking the constituent pixels of the adjacent image area as adjacent pixels, obtaining the number of interval pixels between two pixels in any combination of adjacent pixels of the reference pixel to determine the physical distance corresponding to any combination of adjacent pixels of the reference pixel, and outputting the physical distance with the smallest value among the physical distances corresponding to the respective combinations of adjacent pixels of the reference pixel as the visual analysis distance of the first hull target and the second hull target; The acoustic alarm device is placed in the ground control room corresponding to the seaport and connected to the visual analysis device. It is used to send out an acoustic safety alarm message corresponding to the close distance between the two ships when the visual analysis distance between the first hull target and the second hull target is less than or equal to the set distance limit.

2. The smart city traffic management system based on big data as claimed in claim 1, characterized in that: The acoustic alarm device is also used to temporarily suspend the issuance of acoustic safety alarm information corresponding to the close distance between the two ships when the visual analysis distance between the first hull target and the second hull target is greater than the set distance limit.

3. The smart city traffic management system based on big data as claimed in claim 2, characterized in that: The system further comprises: A humidity detection device, which is arranged near the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is connected to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively; Among them, the humidity detection device is arranged near the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is respectively connected to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device, including: the humidity detection device is used to realize on-site measurement of the current humidity of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device, respectively.

4. The smart city traffic management system based on big data as claimed in claim 2, characterized in that: The system further comprises: A thickness detection device, which is arranged near the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is connected to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively; Among them, the thickness detection device is arranged near the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device and is respectively connected to the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device, including: the thickness detection device is used to realize on-site measurement of the current thickness of the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device, respectively.

5. The smart city traffic management system based on big data as described in any one of claims 2 to 4, characterized in that: An embedded processing device is used to perform image data processing on the output data of the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain output processing data corresponding to the filtering and sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

6. The smart city traffic management system based on big data as claimed in claim 5, characterized in that: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing color scale adjustment on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

7. The smart city traffic management system based on big data as claimed in claim 5, characterized in that: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing image restoration on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

8. The smart city traffic management system based on big data as claimed in claim 5, characterized in that: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing rotation correction on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

9. The smart city traffic management system based on big data as claimed in claim 5, characterized in that: Using an embedded processing device to perform image data processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively includes: performing alpha mean filtering processing on the output data of the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device to obtain the output processing data corresponding to the filter sharpening device, the signal processing device, the contrast retention device and the visual analysis device respectively.

Images