Intelligent community access control coping system

Abstract

The invention relates to an intelligent community access control response system. The system comprises layer-by-layer construction equipment, step-by-step enhancement equipment, instant imaging equipment, an intelligent judgment mechanism, a monitoring processing mechanism and the like. The intelligent community access control response system is reliable in logic and intelligent in design.

Description

Technical Field

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

[0002] The smart access control system can effectively protect people's safety. It uses high-definition cameras and face recognition technology to accurately identify the identity information of every person entering and leaving, ensuring that only authorized personnel can enter the building. Not only that, the system can also monitor the door area in real time, promptly detect and record any suspicious behavior, and provide reliable evidence for later investigation. Whether it is a residential area, a commercial area or an office area, the smart access control system can effectively protect the safety of every resident and staff. The smart access control system has brought great convenience to people's lives. Traditional access control systems require keys or cards to enter, which undoubtedly brings some inconvenience to people's lives. The smart access control system is connected to the access control system through a mobile phone APP, and the door can be opened with just a click. No matter where you go, as long as the mobile phone is in hand, people can open the door remotely without worrying about the embarrassment of forgetting to bring keys or swipe cards. In addition, the system also supports the visitor access function. Visitors only need to submit an application on the APP, and after being authorized, they can enter and exit the building by themselves, so that visitors do not need to find the interviewee, saving time for both parties.

[0003] The smart access control system will save the real-time surveillance images. Obviously, the amount of surveillance data saved in this way is huge, and it is necessary to select and store video images of different importance in different ways. For example, when two adjacent human targets in the video surveillance image need to be in physical contact, the video surveillance image should be stored as a key storage image, otherwise, the video surveillance image should be stored as a non-key storage image. However, it is difficult to accurately identify whether two adjacent human targets in the video surveillance image are in a physical contact state. Summary of the invention

[0004] In order to solve the technical problems in the related fields, the present invention provides a smart community access control response system, which uses two adjacent human targets in the front scene picture of the smart access control after targeted enhancement, that is, the step-by-step enhancement picture as the first target and the second target respectively, to determine the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the real-time imaging device, and calculates the horizontal coordinate value and vertical coordinate value of each pixel point in the area occupied by the first target in the step-by-step enhancement picture, the horizontal coordinate value and vertical coordinate value of each pixel point in the area occupied by the second target in the step-by-step enhancement picture, and the horizontal coordinate value and vertical coordinate value of each pixel point in the area occupied by the first target in the step-by-step enhancement picture. The overall depth of field value of the occupied area in the picture, the overall depth of field value of the occupied area of ​​the second target in the step-by-step enhanced picture, and the imaging focal length of the real-time imaging device are input into the convolutional neural network model in parallel, and the convolutional neural network model is executed to obtain a status identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact. When it is intelligently determined that two adjacent human targets in the step-by-step enhanced picture are in physical contact, the step-by-step enhanced picture is stored as a key storage picture, otherwise, the step-by-step enhanced picture is stored as a non-key storage picture, wherein the storage time of the key storage picture is greater than the storage time of the non-key storage picture, thereby completing the intelligent sorting and response of the key storage pictures.

[0005] According to the present invention, a smart community access control response system is provided, the system comprising: Constructing equipment layer by layer, for performing multiple learning operations on the convolutional neural network to obtain the convolutional neural network after completing the multiple learning operations and outputting it as a convolutional neural network model, wherein the number of learning operations of the convolutional neural network is positively correlated with the resolution of the instant imaging device of the smart access control; A step-by-step enhancement device is used to perform a sharpening operation using a Kirsch operator, a piecewise linear grayscale transformation operation, and a histogram correction operation on an image of the instant imaging device in steps, so as to obtain and output a corresponding step-by-step enhanced image; An instant imaging device, which is arranged above the smart access control and connected to the step-by-step enhancement device, is used to perform an instant imaging operation on the scene in front of the smart access control when the smart access control is in operation, so as to obtain and output a corresponding imaging picture; an intelligent judgment mechanism, connected to the step-by-step enhancement device and the layer-by-layer construction device, respectively, for taking two adjacent human targets in the step-by-step enhancement picture as the first target and the second target, respectively, determining the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the instant imaging device, inputting the horizontal coordinate value and the vertical coordinate value of each pixel point of the area occupied by the first target in the step-by-step enhancement picture, the horizontal coordinate value and the vertical coordinate value of each pixel point of the area occupied by the second target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the instant imaging device into the convolutional neural network model in parallel, and executing the convolutional neural network model to obtain a state identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact; A monitoring processing mechanism connected to the intelligent judgment mechanism, for storing the step-by-step enhanced picture as a key storage picture when the received status identifier indicates that the first target and the second target entity are in contact, otherwise, storing the step-by-step enhanced picture as a non-key storage picture; Among them, when the received status identifier indicates that the first target and the second target entity are in contact, the step-by-step enhanced picture is stored as a key storage picture, otherwise, the step-by-step enhanced picture is stored as a non-key storage picture, including: the storage time of the key storage picture is greater than the storage time of the non-key storage picture.

[0006] It can be seen that the present invention mainly has the following four significant technical effects: Technical effect A: The front scene picture of the smart access control after targeted enhancement, i.e., two adjacent human targets in the step-by-step enhanced picture, are respectively used as the first target and the second target, and the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the instant imaging device are determined, thereby obtaining targeted basic data for subsequent intelligent identification; Technical effect B: the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the area occupied by the first target in the step-by-step enhanced picture, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the area occupied by the second target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the instant imaging device are input into the convolutional neural network model in parallel, and the convolutional neural network model is executed to obtain a state identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact; Technical effect C: when it is intelligently determined that two adjacent human target entities are in contact in a step-by-step enhanced picture, the step-by-step enhanced picture is stored as a key storage picture, otherwise, the step-by-step enhanced picture is stored as a non-key storage picture, wherein the storage time of the key storage picture is longer than the storage time of the non-key storage picture, thereby completing the intelligent sorting and response of the key storage pictures; Technical effect D: The targeted enhancement processing of the front scene image of the smart access control is to perform the Kirsch operator sharpening operation, piecewise linear grayscale transformation operation and histogram correction operation on the imaging image of the real-time imaging device in steps, so as to provide better quality image content for subsequent intelligent judgment.

[0007] The smart community access control response system of the present invention has reliable logic and intelligent design. Since it can use an artificial intelligence model to intelligently identify whether two adjacent human targets in the monitoring screen are in physical contact based on multiple visual information, and then use different screen storage strategies, the intelligent level of monitoring screen storage management is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein: Figure 1 It is a schematic diagram of the internal structure of the smart community access control response system according to the first embodiment of the present invention.

[0009] Figure 2 Schematic diagram of the internal structure of a smart community access control system according to the second embodiment of the present invention.

[0010] Figure 3 Schematic diagram of the internal structure of a smart community access control system according to the third embodiment of the present invention. DETAILED DESCRIPTION

[0011] The following is a detailed description of an embodiment of the smart community access control response system of the present invention with reference to the accompanying drawings.

[0012] Figure 1This is a schematic diagram of the internal structure of a smart community access control system according to a first embodiment of the present invention, wherein the system comprises: Constructing equipment layer by layer, for performing multiple learning operations on the convolutional neural network to obtain the convolutional neural network after completing the multiple learning operations and outputting it as a convolutional neural network model, wherein the number of learning operations of the convolutional neural network is positively correlated with the resolution of the instant imaging device of the smart access control; Specifically, the layer-by-layer construction device is used to perform multiple learning operations on the convolutional neural network to obtain the convolutional neural network after completing the multiple learning operations and output it as a convolutional neural network model, and the number of learning operations of the convolutional neural network is positively correlated with the resolution of the instant imaging device of the smart access control. The device includes: an FPGA chip can be used to implement the layer-by-layer construction device, which is used to perform multiple learning operations on the convolutional neural network to obtain the convolutional neural network after completing the multiple learning operations and output it as a convolutional neural network model, and the number of learning operations of the convolutional neural network is positively correlated with the resolution of the instant imaging device of the smart access control; A step-by-step enhancement device is used to perform a sharpening operation using a Kirsch operator, a piecewise linear grayscale transformation operation, and a histogram correction operation on an image of the instant imaging device in steps, so as to obtain and output a corresponding step-by-step enhanced image; An instant imaging device, which is arranged above the smart access control and connected to the step-by-step enhancement device, is used to perform an instant imaging operation on the scene in front of the smart access control when the smart access control is in operation, so as to obtain and output a corresponding imaging picture; an intelligent judgment mechanism, connected to the step-by-step enhancement device and the layer-by-layer construction device, respectively, for taking two adjacent human targets in the step-by-step enhancement picture as the first target and the second target, respectively, determining the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the instant imaging device, inputting the horizontal coordinate value and the vertical coordinate value of each pixel point of the area occupied by the first target in the step-by-step enhancement picture, the horizontal coordinate value and the vertical coordinate value of each pixel point of the area occupied by the second target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the instant imaging device into the convolutional neural network model in parallel, and executing the convolutional neural network model to obtain a state identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact; A monitoring processing mechanism connected to the intelligent judgment mechanism, for storing the step-by-step enhanced picture as a key storage picture when the received status identifier indicates that the first target and the second target entity are in contact, otherwise, storing the step-by-step enhanced picture as a non-key storage picture; Wherein, when the received state identifier indicates that the first target and the second target entity are in contact, the step-by-step enhanced picture is stored as a key storage picture, otherwise, the step-by-step enhanced picture is stored as a non-key storage picture, including: the storage time length of the key storage picture is longer than the storage time length of the non-key storage picture; Among them, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the area occupied by the first target in the step-by-step enhanced picture, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the area occupied by the second target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the real-time imaging device are input into the convolutional neural network model in parallel, and the convolutional neural network model is executed to obtain a state identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact, including: the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the area occupied by the first target in the step-by-step enhanced picture, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the area occupied by the second target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the real-time imaging device are converted into binary values ​​respectively and then synchronously input into the convolutional neural network model.

[0013] Figure 2 Schematic diagram of the internal structure of a smart community access control system according to the second embodiment of the present invention.

[0014] Compared to Figure 1 The smart community access control system according to the second embodiment of the present invention may further include: A power detection mechanism, comprising a plurality of power detection units, for respectively detecting the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device; The power detection mechanism includes a plurality of power detection units, and is used to respectively detect the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device, including: calculating the current input power of each of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device by respectively measuring the real-time power supply voltage and the real-time power supply current for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device; The calculation of the respective current input powers by measuring the real-time power supply voltage and the real-time power supply current for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device respectively includes: for any device of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device, the current input power is the product of its real-time power supply voltage and its real-time power supply current; The power detection mechanism includes a plurality of power detection units for respectively detecting the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device, and further includes: the plurality of power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device have the same power measurement upper limit threshold and power measurement lower limit threshold; Among them, the power detection mechanism includes multiple power detection units, which are used to respectively detect the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement equipment and the layer-by-layer construction equipment. It also includes: the internal structures of the multiple power detection units respectively used for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement equipment and the layer-by-layer construction equipment are the same.

[0015] Figure 3 Schematic diagram of the internal structure of a smart community access control system according to the third embodiment of the present invention.

[0016] Compared to Figure 1 According to the third embodiment of the present invention, the smart community access control system may further include: an on-site notification mechanism, connected to a plurality of power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device, for performing corresponding power notification operations based on power measurement results of the plurality of power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device; The on-site notification mechanism is respectively connected to a plurality of power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, and is used to perform corresponding power notification operations based on power measurement results of the plurality of power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, including: the on-site notification mechanism includes a static storage unit for storing a power notification threshold; And wherein, the on-site notification mechanism is respectively connected to multiple power detection units respectively used by the monitoring processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, and is used to perform corresponding power notification operations based on the power measurement results of the multiple power detection units respectively used by the monitoring processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device. It also includes: the on-site notification mechanism performs corresponding power notification operations for the monitoring processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device based on the voice playback mode.

[0017] In addition, in the smart community access control response system, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the area occupied by the first target in the step-by-step enhanced picture, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the area occupied by the second target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the real-time imaging device are input into the convolutional neural network model in parallel, and the convolutional neural network model is executed to obtain a status identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact, which also includes: the status identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact is represented in the form of a binary value.

[0018] It should be understood by those skilled in the art that the embodiments of the present invention shown in the above description are only examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments, and the embodiments of the present invention may be deformed or modified in any way without departing from the principles.

Claims

1. A smart community access control response system, characterized in that: The system comprises: Constructing equipment layer by layer, for performing multiple learning operations on the convolutional neural network to obtain the convolutional neural network after completing the multiple learning operations and outputting it as a convolutional neural network model, wherein the number of learning operations of the convolutional neural network is positively correlated with the resolution of the instant imaging device of the smart access control; A step-by-step enhancement device is used to perform a sharpening operation using a Kirsch operator, a piecewise linear grayscale transformation operation, and a histogram correction operation on an image of the instant imaging device in steps, so as to obtain and output a corresponding step-by-step enhanced image; An instant imaging device, which is arranged above the smart access control and connected to the step-by-step enhancement device, is used to perform an instant imaging operation on the scene in front of the smart access control when the smart access control is in operation, so as to obtain and output a corresponding imaging picture; an intelligent judgment mechanism, connected to the step-by-step enhancement device and the layer-by-layer construction device, respectively, for taking two adjacent human targets in the step-by-step enhancement picture as the first target and the second target, respectively, determining the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the instant imaging device, inputting the horizontal coordinate value and the vertical coordinate value of each pixel point of the area occupied by the first target in the step-by-step enhancement picture, the horizontal coordinate value and the vertical coordinate value of each pixel point of the area occupied by the second target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhancement picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhancement picture, and the imaging focal length of the instant imaging device into the convolutional neural network model in parallel, and executing the convolutional neural network model to obtain a state identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact; A monitoring processing mechanism connected to the intelligent judgment mechanism, for storing the step-by-step enhanced picture as a key storage picture when the received status identifier indicates that the first target and the second target entity are in contact, otherwise, storing the step-by-step enhanced picture as a non-key storage picture; Among them, when the received status identifier indicates that the first target and the second target entity are in contact, the step-by-step enhanced picture is stored as a key storage picture, otherwise, the step-by-step enhanced picture is stored as a non-key storage picture, including: the storage time of the key storage picture is greater than the storage time of the non-key storage picture.

2. The smart community access control response system according to claim 1, characterized in that: The horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the area occupied by the first target in the step-by-step enhanced picture, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the area occupied by the second target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the real-time imaging device are input into the convolutional neural network model in parallel, and the convolutional neural network model is executed to obtain a state identifier output by the convolutional neural network model indicating whether the first target and the second target are in physical contact, including: the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the area occupied by the first target in the step-by-step enhanced picture, the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the area occupied by the second target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the first target in the step-by-step enhanced picture, the overall depth of field value of the area occupied by the second target in the step-by-step enhanced picture, and the imaging focal length of the real-time imaging device are converted into binary values ​​respectively and then synchronously input into the convolutional neural network model.

3. The smart community access control response system as claimed in claim 2, characterized in that: The system further comprises: A power detection mechanism, comprising a plurality of power detection units, for respectively detecting the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device, and the layer-by-layer construction device; Among them, the power detection mechanism includes multiple power detection units, which are used to respectively detect the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, including: by respectively measuring the real-time power supply voltage and the real-time power supply current for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device to complete the calculation of their respective current input powers.

4. The smart community access control response system as claimed in claim 3, characterized in that: The calculation of the respective current input powers is completed by respectively measuring the real-time power supply voltage and the real-time power supply current for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, including: for any device of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, its current input power is the product of its real-time power supply voltage and its real-time power supply current.

5. The smart community access control response system as claimed in claim 3, characterized in that: The power detection mechanism includes multiple power detection units, which are used to respectively detect the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device. It also includes: the multiple power detection units respectively used for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device have the same power measurement upper limit threshold and power measurement lower limit threshold.

6. The smart community access control response system as claimed in claim 5, characterized in that: The power detection mechanism includes multiple power detection units, which are used to respectively detect the current input power of the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device. It also includes: the internal structures of the multiple power detection units respectively used for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device are the same.

7. The smart community access control response system as claimed in claim 3, characterized in that: The system further comprises: The on-site notification mechanism is respectively connected to multiple power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, and is used to perform corresponding power notification operations based on the power measurement results of the multiple power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device.

8. The smart community access control response system as claimed in claim 7, characterized in that: The on-site notification mechanism is respectively connected to multiple power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, and is used to perform corresponding power notification operations based on the power measurement results of the multiple power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, including: the on-site notification mechanism includes a static storage unit for storing power notification thresholds.

9. The smart community access control response system as claimed in claim 8, characterized in that: The on-site notification mechanism is respectively connected to multiple power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device, and is used to perform corresponding power notification operations based on the power measurement results of the multiple power detection units respectively used by the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device. It also includes: the on-site notification mechanism performs corresponding power notification operations for the monitoring and processing mechanism, the intelligent judgment mechanism, the step-by-step enhancement device and the layer-by-layer construction device based on the voice playback mode.

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