Smart community management system

Abstract

The invention relates to an intelligent community management system, which comprises a rod lifting identification device, a visual operation device, a multiple conversion device, an analysis processing mechanism and an amplitude comparison mechanism. The intelligent community management system is stable in operation and intelligent in control.

Description

Technical Field

[0001] The present invention relates to the field of smart community management, and in particular to a smart community management system. Background Art

[0002] Image information processing is a multi-stage, multi-path, and multi-target information processing process. Image processing theory systematically explains and demonstrates the common and basic knowledge in image information processing, as well as the front-end processing theories, methods, and techniques. Mathematical knowledge related to image information processing, visual knowledge, mathematical description of images, image digitization, image transformation, image enhancement, image restoration, etc. are the various technical points required for image processing.

[0003] Due to the development of express delivery in China, super communities, that is, communities with a large number of residents, have begun to appear in first- and second-tier cities. The rate of residents owning their own vehicles is increasing, so the management of vehicles is an important indicator of community management. In particular, for communities that are committed to building smart communities, vehicle management is an important aspect of improving happiness.

[0004] Specifically, for parking lot management, the video surveillance images of the parking lot entrance environment are the most important monitoring information. However, with the change of time, the content of each frame of video surveillance images is constantly changing. It is difficult to obtain the same set of interpolation algorithms that can meet the interpolation requirements of the content of all frames of video surveillance images. The existing technology also lacks a set of dynamic interpolation algorithms that can match the high-quality requirements of all frames of video surveillance images after interpolation. Summary of the invention

[0005] In order to solve the technical problems in related fields, the present invention provides a smart community management system, which can use various interpolation algorithms respectively to obtain the interpolation algorithm corresponding to the smallest maximum noise amplitude among the maximum noise amplitudes obtained by the BP neural network model after multiple learning as the target interpolation algorithm, thereby completing the intelligent analysis of the best interpolation algorithm for the clear processing image, and triggering the visual operation device arranged on the opposite side of the parking lot entrance to execute a snapshot processing of the entrance environment of the parking lot only when the lifting bar recognition device recognizes that the driving motor completes the lifting driving action of the lifting bar each time, thereby avoiding excessive invalid actions and invalid data.

[0006] According to the present invention, a smart community management system is provided, the system comprising: A lifting bar identification device is connected to a driving motor of the lifting bar at the entrance of the parking lot, and is used to send an entry identification signal every time the driving motor completes a lifting driving action of the lifting bar; A visual operation device is arranged at the opposite side of the parking lot entrance close to the interior of the parking lot and is connected to the lifting bar identification device, and is used to perform a capture process of the parking lot entrance environment each time an entry identification signal is received, so as to obtain and output a corresponding entry capture picture; A multiple conversion device, connected to the visual operation device and comprising a first conversion device, a second conversion device and a third conversion device, wherein the second conversion device is respectively connected to the first conversion device and the third conversion device, and the first conversion device is also connected to the visual operation device, and is used to perform high-pass filtering and sharpening processing on the received entry snapshot image to obtain and output a corresponding filtered sharpened image, the second conversion device is used to perform image content enhancement processing based on exponential transformation on the received filtered sharpened image to obtain and output a corresponding exponentially enhanced image, and the third conversion device is used to perform geometric mean filtering processing on the received exponentially enhanced image to obtain and output a corresponding sharpened processed image; An analysis and processing mechanism is arranged in the control room of the parking lot, connected to the multiple conversion device and includes an information extraction device, a parameter measurement device and a network application device, wherein the network application device is respectively connected to the information extraction device and the parameter measurement device, and the analysis and processing mechanism is used to obtain the resolution of the received clear processing image, the number of foreground pixels and the brightness values ​​corresponding to the pixels, and simultaneously obtain the signal-to-noise ratio and contrast of the clear processing image, and use the BP neural network model after completing multiple learning to intelligently identify the maximum noise amplitude of the processed image obtained after the clear processing image is interpolated using the interpolation algorithm based on the algorithm mark data corresponding to the interpolation algorithm used, the resolution of the clear processing image, the number of foreground pixels and the brightness values ​​corresponding to the pixels, and the signal-to-noise ratio and contrast of the clear processing image; An amplitude comparison mechanism, connected to the analysis and processing mechanism, is used to use the interpolation algorithm corresponding to the smallest maximum noise amplitude among the maximum noise amplitudes obtained by the BP neural network model after multiple learning as the target interpolation algorithm. Among them, various interpolation algorithms include nearest neighbor interpolation algorithm, bilinear interpolation algorithm, bicubic interpolation algorithm of 4×4 pixel neighborhood, Lanczos interpolation algorithm of 8×8 pixel neighborhood and cubic polynomial interpolation algorithm.

[0007] Therefore, the present invention has the following outstanding technical effects: Technical effect A: introducing a customized analysis and processing mechanism including an information extraction device, a parameter measurement device and a network application device, wherein the network application device is connected to the information extraction device and the parameter measurement device respectively, thereby providing necessary hardware resources for analyzing the optimal interpolation algorithm; Technical effect B: obtaining the resolution of the received clear processed image, the number of foreground pixels and the brightness values ​​corresponding to each pixel, and obtaining the signal-to-noise ratio and contrast of the clear processed image, and using the BP neural network model after completing multiple learning to intelligently identify the maximum noise amplitude of the processed image obtained after the clear processed image is interpolated using the interpolation algorithm based on the algorithm mark data corresponding to the interpolation algorithm used, the resolution of the clear processed image, the number of foreground pixels and the brightness values ​​corresponding to each pixel, the signal-to-noise ratio and contrast of the clear processed image; Technical effect C: The interpolation algorithm corresponding to the maximum noise amplitude with the smallest value among the maximum noise amplitudes obtained by the BP neural network model after multiple learning is used as the target interpolation algorithm for various interpolation algorithms, thereby completing the intelligent analysis of the best interpolation algorithm for the clear processing image; Technical effect D: Only when the lifting bar identification device recognizes that the driving motor completes the lifting driving action of the lifting bar, the visual operation device arranged on the opposite side of the parking lot entrance is triggered to perform a snapshot processing of the entrance environment of the parking lot, thereby avoiding excessive invalid actions and invalid data.

[0008] The smart community management system of the present invention is stable in operation and intelligent in control. Since the interpolation algorithm corresponding to the minimum maximum noise amplitude among the maximum noise amplitudes obtained by various interpolation algorithms using the BP neural network model can be used as the target interpolation algorithm to be put into the interpolation processing of the monitoring screen at the entrance of the parking lot, the dynamic matching of the optimal interpolation algorithm is completed. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0010] Figure 1 The figure is a structural block diagram of a smart community management system according to the first embodiment of the present invention.

[0011] Figure 2 The figure is a structural block diagram of a smart community management system according to the second embodiment of the present invention.

[0012] Figure 3 The structure block diagram of the smart community management system according to the third embodiment of the present invention is shown. DETAILED DESCRIPTION

[0013] The following is a detailed description of an embodiment of the smart community management system of the present invention with reference to the accompanying drawings.

[0014] Figure 1 The structure block diagram of the smart community management system according to the first embodiment of the present invention is shown, and the system includes: A lifting bar identification device is connected to a driving motor of the lifting bar at the entrance of the parking lot, and is used to send an entry identification signal every time the driving motor completes a lifting driving action of the lifting bar; Specifically, the lifting bar identification device is connected to the driving motor of the lifting bar at the entrance of the parking lot, and is used to send an entry identification signal every time the driving motor completes a lifting driving action of the lifting bar. The driving motor is a permanent magnet brushless motor; A visual operation device is arranged at the opposite side of the parking lot entrance close to the interior of the parking lot and is connected to the lifting bar identification device, and is used to perform a capture process of the parking lot entrance environment each time an entry identification signal is received, so as to obtain and output a corresponding entry capture picture; A multiple conversion device, connected to the visual operation device and comprising a first conversion device, a second conversion device and a third conversion device, wherein the second conversion device is respectively connected to the first conversion device and the third conversion device, and the first conversion device is also connected to the visual operation device, and is used to perform high-pass filtering and sharpening processing on the received entry snapshot image to obtain and output a corresponding filtered sharpened image, the second conversion device is used to perform image content enhancement processing based on exponential transformation on the received filtered sharpened image to obtain and output a corresponding exponentially enhanced image, and the third conversion device is used to perform geometric mean filtering processing on the received exponentially enhanced image to obtain and output a corresponding sharpened processed image; An analysis and processing mechanism is arranged in the control room of the parking lot, connected to the multiple conversion device and includes an information extraction device, a parameter measurement device and a network application device, wherein the network application device is respectively connected to the information extraction device and the parameter measurement device, and the analysis and processing mechanism is used to obtain the resolution of the received clear processing image, the number of foreground pixels and the brightness values ​​corresponding to the pixels, and simultaneously obtain the signal-to-noise ratio and contrast of the clear processing image, and use the BP neural network model after completing multiple learning to intelligently identify the maximum noise amplitude of the processed image obtained after the clear processing image is interpolated using the interpolation algorithm based on the algorithm mark data corresponding to the interpolation algorithm used, the resolution of the clear processing image, the number of foreground pixels and the brightness values ​​corresponding to the pixels, and the signal-to-noise ratio and contrast of the clear processing image; An amplitude comparison mechanism, connected to the analysis and processing mechanism, is used to use the interpolation algorithm corresponding to the smallest maximum noise amplitude among the maximum noise amplitudes obtained by the BP neural network model after multiple learning as the target interpolation algorithm. Among them, various interpolation algorithms include nearest neighbor interpolation algorithm, bilinear interpolation algorithm, bicubic interpolation algorithm of 4×4 pixel neighborhood, Lanczos interpolation algorithm of 8×8 pixel neighborhood and cubic polynomial interpolation algorithm; Among them, the lifting bar identification device is connected to the driving motor of the lifting bar at the entrance of the parking lot, and is used to execute the sending operation of the entry identification signal every time the driving motor completes the lifting driving action of the lifting bar. The operation includes: the driving motor is a DC brushless motor, and the entry identification signal is based on a rectangular pulse waveform.

[0015] Figure 2 The figure is a structural block diagram of a smart community management system according to the second embodiment of the present invention.

[0016] Compared to Figure 1 , Figure 2 The smart community management system can also include: a volume detection component, connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, respectively, and used to measure the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively; Wherein, the volume detection component is respectively connected with the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, and is used to respectively measure the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: the volume detection component includes a plurality of volume measurement units, which are respectively connected with the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, so as to respectively measure the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism; Wherein, the volume detection component includes a plurality of volume measurement units, which are respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism to complete the measurement of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively, including: the plurality of volume measurement units are a plurality of visual detectors, which are respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism to complete the measurement of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively; Wherein, the plurality of volume measurement units are a plurality of visual detectors, which are respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism to respectively measure the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: the plurality of visual detectors have the same structure; Among them, the multiple volume measurement units are multiple visual detectors, which are used to be connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively to complete the respective measurements of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, and also include: each of the multiple visual detectors includes a stereo camera.

[0017] Figure 3 The structure block diagram of the smart community management system according to the third embodiment of the present invention is shown.

[0018] Compared to Figure 1 , Figure 3 The smart community management system can also include: a synchronous operation mechanism, connected to the first conversion device, the second conversion device, the third conversion device and the plurality of volume measurement units of the analysis and processing mechanism respectively, and used to perform synchronous operations between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism; The synchronous operation mechanism is respectively connected to the first conversion device, the second conversion device, the third conversion device and the plurality of volume measurement units of the analysis and processing mechanism, and is used to perform the synchronous operation between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: the synchronous operation mechanism performs the synchronous operation between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism based on a square wave waveform; Among them, the synchronous operation mechanism is respectively connected to the first conversion device, the second conversion device, the third conversion device and multiple volume measurement units of the analysis and processing mechanism, and is used to perform synchronous operations between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: using an ASIC chip to implement the synchronous operation mechanism.

[0019] In addition, in the smart community management system, the lifting barrier identification device is connected to the driving motor of the lifting barrier at the entrance of the parking lot, and is used to execute the sending operation of the entry identification signal each time the driving motor completes the lifting driving action of the lifting barrier. The operation also includes: using each rising edge of the rectangular pulse waveform as an entry identification signal, or using each falling edge of the rectangular pulse waveform as an entry identification signal.

[0020] The previous description of the disclosed embodiments is provided to enable a person skilled in the art to make or use the present invention. A person skilled in the art will readily appreciate the various modifications to these embodiments, and the general principles defined herein may be applicable to other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but should conform to the entire scope consistent with the claims, wherein reference to an element in the singular is not intended to represent "one and only one" (unless explicitly stated), but rather represents "one or more". All structural and functional equivalents of the elements of the various embodiments described in this entire disclosure (known or later to those skilled in the art) are expressly incorporated herein by reference and are intended to be covered by the claims.

Claims

1. A smart community management system, characterized in that: The system comprises: A lifting bar identification device is connected to a driving motor of the lifting bar at the entrance of the parking lot, and is used to send an entry identification signal every time the driving motor completes a lifting driving action of the lifting bar; A visual operation device is arranged at the opposite side of the parking lot entrance close to the interior of the parking lot and is connected to the lifting bar identification device, and is used to perform a capture process of the parking lot entrance environment each time an entry identification signal is received, so as to obtain and output a corresponding entry capture picture; A multiple conversion device, connected to the visual operation device and comprising a first conversion device, a second conversion device and a third conversion device, wherein the second conversion device is respectively connected to the first conversion device and the third conversion device, and the first conversion device is also connected to the visual operation device, and is used to perform high-pass filtering and sharpening processing on the received entry snapshot image to obtain and output a corresponding filtered sharpened image, the second conversion device is used to perform image content enhancement processing based on exponential transformation on the received filtered sharpened image to obtain and output a corresponding exponentially enhanced image, and the third conversion device is used to perform geometric mean filtering processing on the received exponentially enhanced image to obtain and output a corresponding sharpened processed image; An analysis and processing mechanism is arranged in the control room of the parking lot, connected to the multiple conversion device and includes an information extraction device, a parameter measurement device and a network application device, wherein the network application device is respectively connected to the information extraction device and the parameter measurement device, and the analysis and processing mechanism is used to obtain the resolution of the received clear processing image, the number of foreground pixels and the brightness values ​​corresponding to the pixels, and simultaneously obtain the signal-to-noise ratio and contrast of the clear processing image, and use the BP neural network model after completing multiple learning to intelligently identify the maximum noise amplitude of the processed image obtained after the clear processing image is interpolated using the interpolation algorithm based on the algorithm mark data corresponding to the interpolation algorithm used, the resolution of the clear processing image, the number of foreground pixels and the brightness values ​​corresponding to the pixels, and the signal-to-noise ratio and contrast of the clear processing image; An amplitude comparison mechanism, connected to the analysis and processing mechanism, is used to use the interpolation algorithm corresponding to the smallest maximum noise amplitude among the maximum noise amplitudes obtained by the BP neural network model after multiple learning as the target interpolation algorithm. Among them, various interpolation algorithms include nearest neighbor interpolation algorithm, bilinear interpolation algorithm, bicubic interpolation algorithm of 4×4 pixel neighborhood, Lanczos interpolation algorithm of 8×8 pixel neighborhood and cubic polynomial interpolation algorithm.

2. The smart community management system according to claim 1, characterized in that: The lifting bar identification device is connected to the driving motor of the lifting bar at the entrance of the parking lot, and is used to execute the sending operation of the entry identification signal every time the driving motor completes the lifting driving action of the lifting bar. The operation includes: the driving motor is a DC brushless motor, and the entry identification signal is based on a rectangular pulse waveform.

3. The smart community management system according to claim 2, characterized in that: The system further comprises: a volume detection component, connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, respectively, and used to measure the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively; Among them, the volume detection component is respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, and is used to respectively measure the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism. The volume detection component includes a plurality of volume measurement units, which are respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism to complete the respective measurements of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism.

4. The smart community management system according to claim 3, characterized in that: The volume detection component includes a plurality of volume measurement units, which are used to be respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism to complete the respective measurement of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: the plurality of volume measurement units are a plurality of visual detectors, which are used to be respectively connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism to complete the respective measurement of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism.

5. The smart community management system according to claim 4, characterized in that: The multiple volume measurement units are multiple visual detectors, which are used to be connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively to complete the respective measurements of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: the structures of the multiple visual detectors are the same.

6. The smart community management system according to claim 5, characterized in that: The multiple volume measurement units are multiple visual detectors, which are used to be connected to the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism respectively to complete the respective measurements of the current real-time volume values ​​of the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism. It also includes: each of the multiple visual detectors includes a stereo camera.

7. The smart community management system according to any one of claims 3 to 6, characterized in that: The system further comprises: The synchronous operation mechanism is respectively connected to the first conversion device, the second conversion device, the third conversion device and the plurality of volume measuring units of the analysis and processing mechanism, and is used to perform synchronous operations between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism.

8. The smart community management system according to claim 7, characterized in that: A synchronous operation mechanism is respectively connected to the first conversion device, the second conversion device, the third conversion device and multiple volume measurement units of the analysis and processing mechanism, and is used to perform synchronous operations between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: the synchronous operation mechanism performs synchronous operations between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism based on a square wave waveform.

9. The smart community management system according to claim 7, characterized in that: The synchronous operation mechanism is respectively connected to the first conversion device, the second conversion device, the third conversion device and the multiple volume measurement units of the analysis and processing mechanism, and is used to perform synchronous operations between the first conversion device, the second conversion device, the third conversion device and the analysis and processing mechanism, including: using an ASIC chip to implement the synchronous operation mechanism.

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