Smart community management system

Abstract

The invention relates to an intelligent community management system. The system comprises a picture acquisition device, an intelligent generation device, a data storage device, a classification recognition mechanism and a type issuing mechanism. The intelligent community management system is intelligent in design and has certain pertinence, and the intelligent level of the video monitoring end can be improved.

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] The most widely used technology in smart community management is video surveillance. Since the development of video surveillance systems, in addition to the continuous innovation of video surveillance technology, video surveillance products have also begun to form a powerful security monitoring system with other products. For example, the video surveillance system uses electronic fences to enclose the monitored area (such as a community or a part of it) into a closed area. The electronic fence has a blocking and alarm system. It is an active intrusion prevention fence that counterattacks against intrusion attempts, repel intruders, delays the intrusion time, and does not threaten human life. Once someone invades, the system activates the alarm, the monitoring system also monitors at the same time, and sends the intrusion signal to the monitoring equipment of the security department to ensure that the management personnel can understand the situation in the alarm area in time and deal with it quickly.

[0003] However, for users watching at the video surveillance end, the surveillance images they obtain are often subjected to various types of image processing at the video acquisition end, the video transmission end or the video receiving end. For example, image interpolation processing has been performed and the images are no longer the original real images. In order to determine the real content of the surveillance images, it is necessary to understand which type of detailed interpolation processing the surveillance images have undergone, thereby helping users watching at the video surveillance end to gain a deeper understanding of the monitored objects and their real status. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides a smart community management system that can selectively select multiple basic data and design a customized structure of an AI analysis body for performing intelligent recognition. When it is known that the real-time captured image output by a picture acquisition device has undergone image interpolation processing but it is not certain which specific sub-category of interpolation processing has been undergone, the AI ​​analysis body is used to intelligently identify which sub-category of interpolation processing the real-time captured image has undergone, thereby helping the viewing users at the video surveillance end to determine the true content of the surveillance screen.

[0005] According to the present invention, a smart community management system is provided, the system comprising: The image acquisition device is located in the set forest area under monitoring and is used to perform image signal capture action facing the set forest area to acquire and output corresponding real-time captured images; An intelligent generation device, used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body; A data storage device for storing binary coded values ​​of various processing types corresponding to various sub-classified interpolation processing under image interpolation processing; A classification identification mechanism is connected to the intelligent generation device, the image acquisition device and the data storage device respectively, and is used to synchronously input multiple component parameters of the image sensing component of the image acquisition device, various visual contents of the real-time captured image and binary coded values ​​of various processing types corresponding to various sub-classification interpolation processing to the AI ​​analysis body, and execute the AI ​​analysis body to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body; A type issuing mechanism, connected to the classification identification mechanism, is used to send the processing type corresponding to the sub-classification interpolation processing of the received real-time captured image to a remote video monitoring server through a network; Among them, multiple component parameters of the image sensing component of the picture acquisition device, each visual content of the real-time captured image, and binary coded values ​​of each processing type corresponding to various sub-classification interpolation processing are synchronously input into the AI ​​analysis body, and the AI ​​analysis body is executed to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body. The multiple component parameters of the image sensing component of the picture acquisition device are the number of pixel elements, exposure time and working voltage of the image sensing component of the picture acquisition device; Among them, the intelligent generation device is used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body, including: in the AI ​​analysis body, the number of learning actions of the single-layer neural network is positively correlated with the shutter speed of the image acquisition device.

[0006] It can be seen that the present invention mainly has the following significant technical effects: Firstly: when it is known that the real-time captured image output by the image acquisition device has been subjected to image interpolation processing but it is uncertain which sub-classification interpolation processing has been subjected to the image interpolation processing, an AI analysis body is used to intelligently identify which sub-classification interpolation processing has been subjected to the real-time captured image; Secondly: To ensure the reliability and stability of intelligent recognition results, a number of basic data were selected, including multiple component parameters of the image sensor components of the image acquisition device, various visualization contents of the real-time captured image, and binary coded values ​​of various processing types corresponding to various sub-classification interpolation processing; Again: the structural customization of the AI ​​analysis body used for intelligent recognition is manifested in: performing multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and outputting it as an AI analysis body. In the AI ​​analysis body, the number of learning actions of the single-layer neural network is positively correlated with the shutter speed of the picture acquisition device, thereby custom-designing AI analysis bodies with different structures for different picture acquisition devices.

[0007] The smart community management system of the present invention is designed to be intelligent and targeted. When it is known that the real-time captured image output by the image acquisition device has been subjected to image interpolation processing but it is uncertain which sub-classification interpolation processing has been subjected to the image interpolation processing, an AI analysis body is used to intelligently identify which sub-classification interpolation processing has been subjected to the real-time captured image, thereby improving the intelligence level of the video surveillance terminal. DETAILED DESCRIPTION

[0008] The following is a detailed description of an embodiment of the smart community management system of the present invention.

[0009] The smart community management system shown in the first embodiment of the present invention includes: The image acquisition device is located in the set forest area under monitoring and is used to perform image signal capture action facing the set forest area to acquire and output corresponding real-time captured images; An intelligent generation device, used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body; Specifically, the intelligent generation device is used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body, including: selecting and using a GAL programmable logic device to implement the intelligent generation device, used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body; A data storage device for storing binary coded values ​​of various processing types corresponding to various sub-classified interpolation processing under image interpolation processing; A classification identification mechanism is connected to the intelligent generation device, the image acquisition device and the data storage device respectively, and is used to synchronously input multiple component parameters of the image sensing component of the image acquisition device, various visual contents of the real-time captured image and binary coded values ​​of various processing types corresponding to various sub-classification interpolation processing to the AI ​​analysis body, and execute the AI ​​analysis body to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body; For example, the classification identification mechanism is connected to the intelligent generation device, the image acquisition device and the data storage device respectively, and is used to synchronously input multiple component parameters of the image sensing component of the image acquisition device, each visualization content of the real-time captured image, and each processing type corresponding to various sub-classification interpolation processing into the AI ​​analysis body, and execute the AI ​​analysis body to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body, including: selecting and using the MATLAB toolbox to complete the test and simulation of the data processing process of synchronously inputting multiple component parameters of the image sensing component of the image acquisition device, each visualization content of the real-time captured image, and each processing type corresponding to various sub-classification interpolation processing into the AI ​​analysis body, and executing the AI ​​analysis body to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body; A type issuing mechanism, connected to the classification identification mechanism, is used to send the processing type corresponding to the sub-classification interpolation processing of the received real-time captured image to a remote video monitoring server through a network; Among them, multiple component parameters of the image sensing component of the picture acquisition device, each visual content of the real-time captured image, and binary coded values ​​of each processing type corresponding to various sub-classification interpolation processing are synchronously input into the AI ​​analysis body, and the AI ​​analysis body is executed to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body. The multiple component parameters of the image sensing component of the picture acquisition device are the number of pixel elements, exposure time and working voltage of the image sensing component of the picture acquisition device; The intelligent generation device is used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body, including: in the AI ​​analysis body, the number of learning actions of the single-layer neural network is positively correlated with the shutter speed of the picture acquisition device; Among them, the data storage device is used to store the binary coded values ​​of each processing type corresponding to various sub-classification interpolation processing under image interpolation processing, including: the various sub-classification interpolation processing is one of cubic polynomial interpolation processing, bilinear interpolation processing, bicubic interpolation processing of 8 pixel × 8 pixel neighborhood and nearest neighbor interpolation processing.

[0010] Compared with the first embodiment of the present invention, the smart community management system shown in the second embodiment of the present invention may further include: An operation measurement mechanism, connected to the classification identification mechanism, the intelligent generation device, the image acquisition device and the type issuance mechanism, respectively, for respectively measuring the number of unit time operations of the classification identification mechanism, the intelligent generation device, the image acquisition device and the type issuance mechanism; Wherein, the operation measurement mechanism is respectively connected with the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, and is used to respectively measure the number of unit time operations of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, including: the operation measurement mechanism includes a plurality of operation measurement units, which are respectively connected with the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, so as to complete the measurement of the number of unit time operations of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism; Wherein, the operation measurement mechanism includes a plurality of operation measurement units, which are used to respectively connect with the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to complete the respective measurement of the number of unit time operations of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, including: the plurality of operation measurement units are a plurality of operation sensor circuits, which are used to respectively connect with the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to complete the respective measurement of the number of unit time operations of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism; The plurality of operation measurement units are a plurality of operation sensor circuits, which are respectively connected to the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to respectively measure the number of unit time operations of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, including: the plurality of operation sensor circuits have the same structure; And wherein, the multiple operation measurement units are multiple operation sensor circuits, which are used to respectively connect with the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to complete the respective measurements of the number of operations per unit time of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, and also include: the multiple operation sensor circuits have the same operation measurement upper limit value and operation measurement lower limit value.

[0011] Compared with the first embodiment of the present invention, the smart community management system shown in the third embodiment of the present invention may further include: A base structure, arranged below the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism, for providing bottom support services for the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism respectively; The base structure is arranged below the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, and is used to provide bottom support services for the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism respectively, including: a plurality of slots are arranged on the base structure to respectively accommodate the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism; And wherein, a plurality of slots are arranged on the base structure to respectively accommodate the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type release mechanism, including: the opening cross-sectional areas of the plurality of slots are the same to respectively accommodate the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type release mechanism.

[0012] In addition, in the smart community management system, multiple component parameters of the image sensing component of the image acquisition device, each visualization content of the real-time captured image, and binary coded values ​​of each processing type corresponding to various sub-classification interpolation processing are synchronously input into the AI ​​analysis body, and the AI ​​analysis body is executed to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body, which also includes: the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body is in a binary value representation; And wherein, the binary coded values ​​of multiple component parameters of the image sensing component of the picture acquisition device, the various visual contents of the real-time captured image, and the various processing types corresponding to the various sub-classification interpolation processing are synchronously input into the AI ​​analysis body, and the AI ​​analysis body is executed to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body, which also includes: using the MATLAB toolbox to complete the test and simulation of the data processing process of synchronously inputting the binary coded values ​​of multiple component parameters of the image sensing component of the picture acquisition device, the various visual contents of the real-time captured image, and the various processing types corresponding to the various sub-classification interpolation processing into the AI ​​analysis body, and executing the AI ​​analysis body to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body.

[0013] Although the present disclosure discusses the embodiments of the present invention, the present invention is not limited thereto but various modifications and changes may be made by those skilled in the art without departing from the spirit and scope of the present disclosure as claimed in the appended claims.

Claims

1. A smart community management system, characterized in that: The system comprises: The image acquisition device is located in the set forest area under monitoring and is used to perform image signal capture action facing the set forest area to acquire and output corresponding real-time captured images; An intelligent generation device, used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body; A data storage device for storing binary coded values ​​of various processing types corresponding to various sub-classified interpolation processing under image interpolation processing; A classification identification mechanism is connected to the intelligent generation device, the image acquisition device and the data storage device respectively, and is used to synchronously input multiple component parameters of the image sensing component of the image acquisition device, various visual contents of the real-time captured image and binary coded values ​​of various processing types corresponding to various sub-classification interpolation processing to the AI ​​analysis body, and execute the AI ​​analysis body to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body; A type issuing mechanism, connected to the classification identification mechanism, is used to send the processing type corresponding to the sub-classification interpolation processing of the received real-time captured image to a remote video monitoring server through a network; Among them, multiple component parameters of the image sensing component of the picture acquisition device, each visual content of the real-time captured image, and binary coded values ​​of each processing type corresponding to various sub-classification interpolation processing are synchronously input into the AI ​​analysis body, and the AI ​​analysis body is executed to obtain the processing type corresponding to the sub-classification interpolation processing of the real-time captured image output by the AI ​​analysis body. The multiple component parameters of the image sensing component of the picture acquisition device are the number of pixel elements, exposure time and working voltage of the image sensing component of the picture acquisition device; Among them, the intelligent generation device is used to perform multiple learning actions on a single-layer neural network to obtain a single-layer neural network after completing multiple learning actions and output it as an AI analysis body, including: in the AI ​​analysis body, the number of learning actions of the single-layer neural network is positively correlated with the shutter speed of the image acquisition device.

2. The smart community management system according to claim 1, characterized in that: A data storage device for storing binary coded values ​​of various processing types corresponding to various sub-classification interpolation processing under image interpolation processing, including: various sub-classification interpolation processing is one of cubic polynomial interpolation processing, bilinear interpolation processing, bicubic interpolation processing of 8 pixel × 8 pixel neighborhood and nearest neighbor interpolation processing.

3. The smart community management system according to claim 2, characterized in that: The system further comprises: An operation measurement mechanism, connected to the classification identification mechanism, the intelligent generation device, the image acquisition device and the type issuance mechanism, respectively, for respectively measuring the number of unit time operations of the classification identification mechanism, the intelligent generation device, the image acquisition device and the type issuance mechanism; Among them, the operation and measurement mechanism is respectively connected to the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, and is used to respectively measure the number of unit time operations of the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism. The operation and measurement mechanism includes: the operation and measurement mechanism includes multiple operation and measurement units, which are respectively connected to the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to complete the respective measurement of the number of unit time operations of the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism.

4. The smart community management system according to claim 3, characterized in that: The operation and measurement mechanism includes a plurality of operation and measurement units, which are used to respectively connect with the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to complete the respective measurements of the number of operations per unit time of the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism. The plurality of operation and measurement units are a plurality of operation sensor circuits, which are used to respectively connect with the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism to complete the respective measurements of the number of operations per unit time of the classification and identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism.

5. The smart community management system according to claim 4, characterized in that: The multiple operation measurement units are multiple operation sensor circuits, which are used to be connected to the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism respectively, so as to complete the respective measurements of the number of operations per unit time of the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type publishing mechanism, including: the structures of the multiple operation sensor circuits are the same.

6. The smart community management system according to claim 5, characterized in that: The multiple operation measurement units are multiple operation sensor circuits, which are used to connect to the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism respectively to complete the respective measurements of the number of operations per unit time of the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism. It also includes: the multiple operation sensor circuits have the same operation measurement upper limit value and operation measurement lower limit value.

7. The smart community management system according to claim 2, characterized in that: The system further comprises: The base structure is arranged below the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism, and is used to provide bottom support services for the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism respectively.

8. The smart community management system according to claim 7, characterized in that: The base structure is arranged below the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism, and is used to provide bottom support services for the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism respectively, including: a plurality of slots are arranged on the base structure to respectively accommodate the classification identification mechanism, the intelligent generation device, the image acquisition device and the type publishing mechanism.

9. The smart community management system according to claim 8, characterized in that: A plurality of slots are arranged on the base structure to respectively accommodate the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type release mechanism, including: the opening cross-sectional areas of the plurality of slots are the same to respectively accommodate the classification identification mechanism, the intelligent generation device, the picture acquisition device and the type release mechanism.