Intelligent building entrance guard dynamic control system

Abstract

The invention relates to a dynamic control system for intelligent building access control. The dynamic control system comprises a dynamic control mechanism, a multi-layer learning mechanism, an information input mechanism, a data analysis mechanism and a target conversion device. According to the invention, the intelligent level of building access control management can be improved.

Description

Technical Field

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

[0002] As the name implies, the entrance and exit access control system is a system for controlling the entrance and exit channels. It is developed on the basis of traditional door locks. Traditional mechanical door locks are just simple mechanical devices. No matter how reasonable the structural design is or how strong the material is, people can always open it by various means. In channels with many people entering and exiting, key management is very troublesome. If the key is lost or the personnel are replaced, the lock and the key must be replaced together. In order to solve these problems, electronic magnetic card locks and electronic password locks have appeared. The emergence of these two locks has improved people's management of entrance and exit channels to a certain extent, and channel management has entered the electronic age. However, with the continuous application of these two electronic locks, their own defects have gradually been exposed. The problem with magnetic card locks is that information is easy to copy, there is a lot of wear between the card and the card reader, the failure rate is high, and the safety factor is low. The problem with password locks is that the password is easy to leak and there is no way to check it, so the safety factor is very low. At the same time, since most of the products of this period use the card reader part (password input) and the control part installed outside the door, it is easy for people to open the lock outdoors. The access control system during this period was still in its early and immature stage, so the access control system at that time was usually called an electronic lock and was not widely used.

[0003] In recent years, with the development of proximity card technology and biometric technology, the access control system has made a leap forward and entered a mature stage. There have been systems using various technologies, such as proximity card access control systems, fingerprint access control systems, iris access control systems, facial recognition access control systems, and random keypad access control systems. The access control system has developed into a smart access control system, which has its own strengths in terms of security, convenience, and manageability. The application areas of smart access control systems are becoming increasingly wide.

[0004] At present, there is still room for improvement in the management of smart access control. For example, smart access control generally has multiple entry and exit channels. If they are opened at the same time, the traffic efficiency can be improved, but the labor cost and management difficulty will increase. If only part of them or even only one is opened, although the labor cost and management difficulty will decrease, the traffic efficiency may be affected. The key to solving these problems lies in the inability to effectively predict the number of people flow corresponding to the future time segments in the building controlled by the smart access control. Summary of the invention

[0005] In order to solve technical problems in related fields, the present invention provides a dynamic control system for smart building access control. It adopts a crowd prediction model to intelligently predict the single crowd number corresponding to the current time segment of the smart access control based on the duration length, multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and multiple control data corresponding to the smart access control, and outputs it as the predicted crowd number corresponding to the current time segment. Based on multiple targeted screened basic data, an artificial intelligence model is used to intelligently predict the predicted crowd number corresponding to the current time segment in the building controlled by the smart access control. A dynamic control mechanism is also introduced to dynamically control the number of entry and exit channels opened of the smart access control based on the received predicted crowd number corresponding to the current time segment. The current time segment starts at the current moment and the duration is equal to the preset time length, thereby improving the intelligence level of smart access control management.

[0006] According to the present invention, a smart building access control system is provided, the system comprising: A dynamic control mechanism, used to dynamically control the number of access channels opened by the smart access control based on the predicted number of people flow corresponding to the received current time segment, wherein the current time segment starts at the current time and lasts for a duration equal to a preset time length; A multi-layer learning mechanism, used for outputting the Hoffet neural network after multiple learning as a crowd flow prediction model, wherein the Hoffet neural network is learned multiple times to obtain the Hoffet neural network after multiple learning; The information input mechanism is used to obtain the number of multiple flows of people corresponding to multiple historical time segments before the current time segment of the smart access control, and to obtain the number of single flows of people corresponding to the same time segment of the smart access control on the day before the current day; Data analysis agency, used to obtain the number of companies, permanent office workers and number of floors in buildings controlled by smart access control and output multiple copies of control data corresponding to smart access control; The target conversion device is respectively connected to the dynamic control mechanism, the multi-layer learning mechanism, the information input mechanism and the data analysis mechanism, and is used to adopt the crowd prediction model based on the duration length, the multiple crowd flow numbers corresponding to the multiple historical time segments before the current time segment of the smart access control, the single crowd flow number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control to intelligently predict the single crowd flow number corresponding to the smart access control in the current time segment and output it as the predicted crowd flow number corresponding to the current time segment; Among them, the crowd prediction model is used to intelligently predict the single crowd number corresponding to the smart access control in the current time segment based on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control, and output it as the predicted crowd number corresponding to the current time segment, including: performing numerical normalization processing on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control, and then synchronously inputting them into the crowd prediction model; Among them, obtaining the multiple numbers of pedestrian flows corresponding to multiple historical time segments before the current time segment of the smart access control and obtaining the single number of pedestrian flows corresponding to the same time segment of the day before the current day include: the same time segment of the day before the current day and the current time segment occupy the same time position in their respective days.

[0007] It can be seen that the present invention has at least the following three important inventive concepts: Invention point A: A crowd prediction model is used to intelligently predict the single crowd number corresponding to the current time segment of the smart access control based on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the day before the current day, and the multiple control data corresponding to the smart access control, and output it as the predicted crowd number corresponding to the current time segment, so as to intelligently predict the predicted crowd number corresponding to the current time segment of the building controlled by the smart access control based on multiple targeted filtered basic data using an artificial intelligence model; Invention point B: A dynamic control mechanism is introduced to dynamically control the number of access channels opened by the smart access control based on the predicted number of people flow corresponding to the received current time segment, wherein the current time segment starts at the current time and lasts for a duration equal to a preset time length, thereby improving the intelligence level of smart access control management; Invention point C: A multi-layer learning mechanism is introduced to output the Hoffitt neural network after multiple learning as a crowd flow prediction model, wherein the Hoffitt neural network is learned multiple times to obtain the Hoffitt neural network after multiple learning, thereby completing the customized design of the crowd flow prediction model. 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 Schematic diagram of the internal structure of a smart building access control system according to the first embodiment of the present invention.

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

[0010] Figure 3 Schematic diagram of the internal structure of a smart building 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 building access control system of the present invention with reference to the accompanying drawings.

[0012] Figure 1 This is a schematic diagram of the internal structure of a smart building access control system according to a first embodiment of the present invention, wherein the system comprises: A dynamic control mechanism, used to dynamically control the number of access channels opened by the smart access control based on the predicted number of people flow corresponding to the received current time segment, wherein the current time segment starts at the current time and lasts for a duration equal to a preset time length; Specifically, the dynamic control mechanism is used to dynamically control the number of access channels opened by the smart access control based on the predicted number of people flow corresponding to the received current time segment, the current time segment starting from the current moment and the duration length equal to the preset time length, including: the SOC control chip can be selected to implement the dynamic control mechanism, which is used to dynamically control the number of access channels opened by the smart access control based on the predicted number of people flow corresponding to the received current time segment, the current time segment starting from the current moment and the duration length equal to the preset time length; A multi-layer learning mechanism, used for outputting the Hoffet neural network after multiple learning as a crowd flow prediction model, wherein the Hoffet neural network is learned multiple times to obtain the Hoffet neural network after multiple learning; The information input mechanism is used to obtain the number of multiple flows of people corresponding to multiple historical time segments before the current time segment of the smart access control, and to obtain the number of single flows of people corresponding to the same time segment of the smart access control on the day before the current day; Data analysis agency, used to obtain the number of companies, permanent office workers and number of floors in buildings controlled by smart access control and output multiple copies of control data corresponding to smart access control; The target conversion device is respectively connected to the dynamic control mechanism, the multi-layer learning mechanism, the information input mechanism and the data analysis mechanism, and is used to adopt the crowd prediction model based on the duration length, the multiple crowd flow numbers corresponding to the multiple historical time segments before the current time segment of the smart access control, the single crowd flow number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control to intelligently predict the single crowd flow number corresponding to the smart access control in the current time segment and output it as the predicted crowd flow number corresponding to the current time segment; Among them, the crowd prediction model is used to intelligently predict the single crowd number corresponding to the smart access control in the current time segment based on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control, and output it as the predicted crowd number corresponding to the current time segment, including: performing numerical normalization processing on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control, and then synchronously inputting them into the crowd prediction model; Among them, obtaining the number of multiple flows corresponding to multiple historical time segments before the current time segment of the smart access control and obtaining the number of single flows corresponding to the same time segment of the smart access control the day before the current day includes: the same time segment of the day before the current day and the current time segment occupy the same time position in their respective days; Among them, the crowd prediction model is used to intelligently predict the single crowd flow number corresponding to the smart access control in the current time segment based on the duration length, multiple crowd flow numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd flow number corresponding to the same time segment of the smart access control the day before the current day, and multiple control data corresponding to the smart access control, and output it as the predicted crowd flow number corresponding to the current time segment, which also includes: running the crowd prediction model to obtain the single crowd flow number corresponding to the smart access control in the current time segment output by the crowd prediction model.

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

[0014] and Figure 1 different, Figure 2 The smart building access control dynamic control system can also include the following components: A wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, respectively, and is used to receive the respective configuration information of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner, so as to realize the real-time configuration of the current working mode of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism; Wherein, the wireless transceiver is respectively connected with the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and is used to receive the respective configuration information of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in time sharing, so as to realize the real-time configuration of the current working mode of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively. The wireless transceiver is respectively connected with the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism through a wireless communication link; The wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through a time division duplex communication link, and the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism have different IP address data; And wherein, the wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through a wireless communication link, including: the wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through a time division duplex communication link; And wherein, the wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through a wireless communication link, including: the wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through a frequency division duplex communication link.

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

[0016] and Figure 1 different, Figure 3 The smart building access control dynamic control system can also include the following components: An HDMI transmission device, connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, respectively, for providing data input operation and data output operation for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner; Wherein, the HDMI transmission device is respectively connected with the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and is used to provide data input operation and data output operation for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in time sharing, including: the HDMI transmission device includes a plurality of HDMI transmission interfaces, which are respectively connected with the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and are used to provide data input operation and data output operation for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in time sharing; The HDMI transmission device includes a plurality of HDMI transmission interfaces, which are respectively connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and are used to provide data input operation and data output operation for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner, including: the internal structures of the plurality of HDMI transmission interfaces are the same; And wherein, the HDMI transmission device includes multiple HDMI transmission interfaces, which are used to connect to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively, and are used to provide data input operations and data output operations for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner, including: the multiple HDMI transmission interfaces use the same pulse generating circuit.

[0017] In addition, in the smart building access control dynamic control system, the duration length, the multiple numbers of people flows corresponding to the multiple historical time segments before the current time segment of the smart access control, the single number of people flows corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control are numerically normalized and then synchronously input into the crowd prediction model, including: the duration length, the multiple numbers of people flows corresponding to the multiple historical time segments before the current time segment of the smart access control, the single number of people flows corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control are numerically converted into octal values ​​and then synchronously input into the crowd prediction model.

[0018] The smart building access control system of the present invention is used to address the technical problem in the prior art that the smart access control cannot effectively predict the future number of people flow, resulting in the difficulty in determining the number of entry and exit channels to be opened in the future. By adopting a people flow prediction model to intelligently predict the number of single people flow corresponding to the smart access control in the current time segment and output it as the predicted number of people flow corresponding to the current time segment, the number of entry and exit channels opened of the smart access control is dynamically controlled based on the received predicted number of people flow corresponding to the current time segment. The current time segment takes the current moment as the starting point and the duration length is equal to the preset time length, thereby solving the above technical problem.

[0019] Although the present invention has been described with reference to the structures disclosed herein, it is not limited to the details shown, and this application is intended to cover such modifications or changes as fall within the scope of the following claims.

Claims

1. A smart building access control system, characterized in that: The system comprises: A dynamic control mechanism, used to dynamically control the number of access channels opened by the smart access control based on the predicted number of people flow corresponding to the received current time segment, wherein the current time segment starts at the current time and lasts for a duration equal to a preset time length; A multi-layer learning mechanism, used for outputting the Hoffet neural network after multiple learning as a crowd flow prediction model, wherein the Hoffet neural network is learned multiple times to obtain the Hoffet neural network after multiple learning; The information input mechanism is used to obtain the number of multiple flows of people corresponding to multiple historical time segments before the current time segment of the smart access control, and to obtain the number of single flows of people corresponding to the same time segment of the smart access control on the day before the current day; Data analysis agency, used to obtain the number of companies, permanent office workers and number of floors in buildings controlled by smart access control and output multiple copies of control data corresponding to smart access control; The target conversion device is respectively connected to the dynamic control mechanism, the multi-layer learning mechanism, the information input mechanism and the data analysis mechanism, and is used to adopt the crowd prediction model based on the duration length, the multiple crowd flow numbers corresponding to the multiple historical time segments before the current time segment of the smart access control, the single crowd flow number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control to intelligently predict the single crowd flow number corresponding to the smart access control in the current time segment and output it as the predicted crowd flow number corresponding to the current time segment; Among them, the crowd prediction model is used to intelligently predict the single crowd number corresponding to the smart access control in the current time segment based on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control, and output it as the predicted crowd number corresponding to the current time segment, including: performing numerical normalization processing on the duration length, the multiple crowd numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd number corresponding to the same time segment of the smart access control the day before the current day, and the multiple control data corresponding to the smart access control, and then synchronously inputting them into the crowd prediction model; Among them, obtaining the multiple numbers of pedestrian flows corresponding to multiple historical time segments before the current time segment of the smart access control and obtaining the single number of pedestrian flows corresponding to the same time segment of the day before the current day include: the same time segment of the day before the current day and the current time segment occupy the same time position in their respective days.

2. The smart building access control system according to claim 1, characterized in that: The crowd prediction model is used to intelligently predict the single crowd flow number corresponding to the smart access control in the current time segment based on the duration length, multiple crowd flow numbers corresponding to multiple historical time segments before the current time segment of the smart access control, the single crowd flow number corresponding to the same time segment of the smart access control the day before the current day, and multiple control data corresponding to the smart access control, and output it as the predicted crowd flow number corresponding to the current time segment, which also includes: running the crowd prediction model to obtain the single crowd flow number corresponding to the smart access control in the current time segment output by the crowd prediction model.

3. The smart building access control system according to claim 2, characterized in that: The system further comprises: A wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, respectively, and is used to receive the respective configuration information of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner, so as to realize the real-time configuration of the current working mode of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism; Among them, the wireless transceiver device is respectively connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and is used to receive the configuration information of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in time sharing, so as to realize the real-time configuration of the current working mode of the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism. The wireless transceiver device is respectively connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism through a wireless communication link.

4. The smart building access control system according to claim 3, characterized in that: The wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through a time division duplex communication link, including: the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism have different IP address data.

5. The smart building access control system according to claim 4, characterized in that: The wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through wireless communication links, including: the wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through time division duplex communication links.

6. The smart building access control system according to claim 4, characterized in that: The wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through wireless communication links, including: the wireless transceiver device is connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively through frequency division duplex communication links.

7. The smart building access control system according to claim 2, characterized in that: The system further comprises: An HDMI transmission device, connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, respectively, for providing data input operation and data output operation for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner; Among them, the HDMI transmission device is respectively connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and is used to provide data input operations and data output operations for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner. The HDMI transmission device includes multiple HDMI transmission interfaces, which are respectively connected to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism, and are used to provide data input operations and data output operations for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner.

8. The smart building access control system according to claim 7, characterized in that: The HDMI transmission device includes multiple HDMI transmission interfaces, which are used to connect to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively, and are used to provide data input operations and data output operations for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner, including: the internal structures of the multiple HDMI transmission interfaces are the same.

9. The smart building access control system according to claim 7, characterized in that: The HDMI transmission device includes multiple HDMI transmission interfaces, which are used to connect to the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism respectively, and are used to provide data input operations and data output operations for the target conversion device, the dynamic control mechanism, the multi-layer learning mechanism, the information entry mechanism and the data analysis mechanism in a time-sharing manner, including: the multiple HDMI transmission interfaces use the same pulse generating circuit.

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