Intelligent door and window control system and method with remote monitoring function

Abstract

The present invention relates to the field of regional equipment control technology, and specifically discloses an intelligent door and window control system and method with remote monitoring function, the method comprising creating a control circuit according to the emergency door position and emergency door parameters, determining the edge control node and its instruction mapping relationship based on the control circuit; the instruction mapping relationship is the mapping of trigger signal-control instruction; the camera system built into the production area collects monitoring video, identifies the monitoring video, locates abnormal personnel, and determines the abnormal level. The present invention obtains monitoring video through an existing monitoring system, identifies the monitoring video, determines the emergency door that needs to be controlled, and on this basis, pre-activates the relevant emergency door according to historical data, and can respond quickly when control is needed, and the control process has high real-time performance and high integration.

Description

Technical Field

[0001] The present invention relates to the technical field of regional equipment control, and in particular to an intelligent door and window control system and method with a remote monitoring function. Background Art

[0002] Emergency door control systems are generally used in regional management scenarios. Sometimes the emergency doors need to be controlled according to external conditions, and sometimes they need to be controlled according to the internal environment of the scene. In existing intelligent workshops, these have become infrastructure. Even if there is no intelligent control process, there will be manual remote control methods, that is, the master control end sends instructions to control each emergency door.

[0003] Most of the existing emergency door control systems do not have advance control. One intelligent method is to execute the closing procedure when a sensor detects someone passing by. However, some emergency doors have a preprocessing process in the closing process, such as safety doors, and the real-time closing performance is difficult to grasp. How to optimize the real-time performance of the emergency door control process is a technical problem that the technical solution of the present invention aims to solve. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent door and window control system and method with remote monitoring function to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A smart door and window control method with remote monitoring function, the method comprising:

[0007] A control circuit is created according to the emergency door position and emergency door parameters, and an edge control node and its instruction mapping relationship are determined based on the control circuit; the instruction mapping relationship is a mapping of a trigger signal to a control instruction;

[0008] The camera system built into the production area collects surveillance video, identifies the surveillance video, locates abnormal personnel, and determines the abnormality level;

[0009] An edge control node is selected according to the positioning result, a control instruction is determined according to the instruction mapping relationship, and the control instruction is sent to the controller of the emergency door through the edge control node.

[0010] As a further solution of the present invention: the step of creating a control circuit according to the emergency door position and emergency door parameters, and determining the edge control node and its instruction mapping relationship based on the control circuit includes:

[0011] Check the building registration information and obtain the location of the emergency door;

[0012] Establish a connection channel with the controller of each emergency door, query the control record, and obtain the emergency door opening position within an opening and closing cycle according to the control record; the emergency door opening position is indexed by time ratio;

[0013] Calculating a control difficulty coefficient according to the emergency door opening position within one opening and closing cycle; the control difficulty coefficient is determined by a derivative characteristic of the emergency door opening position;

[0014] The calculation process of the control difficulty coefficient is: D = αf′(x)+βf″(x);

[0015] In the formula, α and β are weight coefficients, and f(x) is the emergency door opening position calculated based on time proportion statistics;

[0016] Clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating control routes according to the clustering results;

[0017] An edge control node and its instruction mapping relationship are determined based on the control line.

[0018] As a further solution of the present invention: the step of clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating control lines according to the clustering results comprises:

[0019] Selecting a preset number of data centers based on the control difficulty coefficient;

[0020] Traversing emergency door locations according to the data center and clustering the emergency door locations;

[0021] Build a bus based on the data center, build a branch line based on the clustering results, and get the control line;

[0022] Among them, the objective function of clustering is:

[0023]

[0024] Where n is the total number of emergency door locations, k is the total number of data centers, and x i is the coordinate of the i-th emergency door position, μ 1j is the coordinate of the data center; i is the control difficulty coefficient of the i-th emergency door, μ 2j is the control difficulty coefficient of the data center; x i -μ 1j is the distance between two coordinate spaces; ‖Δ‖ 2 is the L2 norm of Δ.

[0025] As a further solution of the present invention: the step of determining the edge control node and its instruction mapping relationship based on the control line includes:

[0026] Based on the statistical branch lines of the data center, query the control parameters of the emergency door controller at each branch line terminal; the control parameters are the data structure of the control instructions of the emergency door controller;

[0027] The control parameters are spliced ​​according to the preset connection sequence, the total control code is determined, and an edge control node based on the total control code is set at the data center;

[0028] Obtain and count the historical total control codes at the edge control node to obtain a total code table; the total code table contains a total control code item and an input number item;

[0029] The total code table is traversed, logical operations are performed on the control total code in turn, data items are merged according to the results of the logical operations, and data items are intercepted according to a preset number threshold to obtain a revised total code table; the revised total code table contains a total code range item and an input number item.

[0030] As a further solution of the present invention: the steps of collecting monitoring video by a camera system built into the production area, identifying the monitoring video, locating abnormal personnel, and determining the abnormality level include:

[0031] The camera system built into the production area collects surveillance video, performs face recognition on the surveillance video, and determines the identity of the person and his current location in real time;

[0032] querying the historical location according to the identity of the person, comparing the current location with the historical location, and determining the degree of abnormality according to the comparison result;

[0033] When the abnormality reaches the preset abnormality threshold, the abnormality level is queried based on the identity of the person.

[0034] As a further solution of the present invention: the step of selecting an edge control node according to the positioning result, determining a control instruction according to the instruction mapping relationship, and sending the control instruction to the controller of the emergency door through the edge control node includes:

[0035] Read the current position, select the target emergency door within the preset distance range with the current position as the center, and determine the required state of the target emergency door;

[0036] Determine a demand control parameter according to the demand state, and determine a demand code according to the demand control parameter;

[0037] Query the edge control node corresponding to the target emergency door, and match the total code in the revised total code table according to the required code;

[0038] The matched total code is sent based on the queried edge control node; wherein, during the sending process, the required code in the total code is sent directly, and the non-required code in the total code is sent after inserting the execution pause tag, and the execution pause tag is used to pause the control instruction sending process of the controller.

[0039] The technical solution of the present invention also provides an intelligent door and window control system with a remote monitoring function, the system comprising:

[0040] A preprocessing module, used to create a control circuit according to the emergency door position and emergency door parameters, and determine the edge control node and its instruction mapping relationship based on the control circuit; the instruction mapping relationship is a mapping of trigger signal-control instruction;

[0041] A video recognition module is used to collect surveillance videos from a camera system built into the production area, identify the surveillance videos, locate abnormal personnel, and determine the abnormality level;

[0042] The instruction sending module is used to select an edge control node according to the positioning result, determine the control instruction according to the instruction mapping relationship, and send the control instruction to the controller of the emergency door through the edge control node.

[0043] As a further solution of the present invention: the preprocessing module comprises:

[0044] A location acquisition unit, used to query building record information and obtain the location of the emergency door;

[0045] A record query unit, used to establish a connection channel with the controller of each emergency door, query the control record, and obtain the emergency door opening position within an opening and closing cycle according to the control record; the emergency door opening position is indexed by time ratio;

[0046] A difficulty coefficient calculation unit, used to calculate a control difficulty coefficient according to the emergency door opening position within one opening and closing cycle; the control difficulty coefficient is determined by a derivative characteristic of the emergency door opening position;

[0047] The calculation process of the control difficulty coefficient is: D = αf′(x)+βf″(x);

[0048] In the formula, α and β are weight coefficients, and f(x) is the emergency door opening position calculated based on time proportion statistics;

[0049] An emergency door clustering unit, used for clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating a control line according to the clustering results;

[0050] A mapping creation unit is used to determine the edge control node and its instruction mapping relationship based on the control line.

[0051] As a further solution of the present invention: the emergency door clustering unit includes:

[0052] A center selection subunit, used to select a preset number of data centers based on a control difficulty coefficient;

[0053] an execution subunit, configured to traverse the emergency door positions according to the data center and cluster the emergency door positions;

[0054] The line construction subunit is used to construct a bus according to the data center, construct a branch line according to the clustering result, and obtain a control line;

[0055] Among them, the objective function of clustering is:

[0056]

[0057] Where n is the total number of emergency door locations, k is the total number of data centers, and x i is the coordinate of the i-th emergency door position, μ 1j is the coordinate of the data center; i is the control difficulty coefficient of the i-th emergency door, μ 2j is the control difficulty coefficient of the data center; x i -μ 1j is the distance between two coordinate spaces; ‖Δ‖ 2 is the L2 norm of Δ.

[0058] As a further solution of the present invention: the mapping creation unit includes:

[0059] A query subunit is used to query the control parameters of the emergency door controller at each branch terminal based on the statistical branch of the data center; the control parameters are the data structure of the control instructions of the emergency door controller;

[0060] The node setting subunit is used to splice the control parameters according to the preset connection sequence, determine the total control code, and set the edge control node based on the total control code at the data center;

[0061] The total code table generating subunit is used to obtain and count the historical control total codes at the edge control node to obtain a total code table; the total code table contains a control total code item and an input number item;

[0062] The operator unit is used to traverse the total code table, perform logical operations on the control total code in turn, merge data items according to the logical operation results, and intercept data items according to a preset number threshold to obtain a modified total code table; the modified total code table contains a total code range item and an input number item.

[0063] Compared with the prior art, the beneficial effects of the present invention are: the present invention obtains monitoring video through the existing monitoring system, identifies the monitoring video, and determines the emergency door that needs to be controlled. On this basis, the relevant emergency door is pre-activated according to historical data. When control is needed, it can respond quickly, and the control process has high real-time and integration. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0065] Figure 1 The figure is a flowchart of an intelligent door and window control method with remote monitoring function.

[0066] Figure 2 It is a flowchart of step S100.

[0067] Figure 3 This is a flowchart of step S200.

[0068] Figure 4 It is a flowchart of step S300.

[0069] Figure 5 This is a structural block diagram of the intelligent door and window control system with remote monitoring function. DETAILED DESCRIPTION

[0070] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0071] Figure 1 The flowchart of the intelligent door and window control method with remote monitoring function is as follows. In an embodiment of the present invention, an intelligent door and window control method with remote monitoring function includes:

[0072] Step S100: creating a control circuit according to the emergency door position and emergency door parameters, and determining the edge control node and its instruction mapping relationship based on the control circuit; the instruction mapping relationship is a mapping of a trigger signal to a control instruction;

[0073] Step S200: The camera system built into the production area collects monitoring video, identifies the monitoring video, locates abnormal personnel, and determines the abnormality level;

[0074] Step S300: select an edge control node according to the positioning result, determine a control instruction according to the instruction mapping relationship, and send the control instruction to the controller of the emergency door through the edge control node.

[0075] Before explaining the steps, the application scenario of the technical solution of the present invention is limited. The application scenario of the technical solution of the present invention is a scenario with a safety door and a demand for intelligent closing, such as a chemical site with exhaust gas leakage. When an emergency occurs, the emergency door needs to be closed urgently. The emergency door is a benchmark facility in this scenario and is generally connected to an external controller so that it can be automatically opened and closed under digital instructions.

[0076] In one example of the technical solution of the present invention, a control line is created through the position of the emergency door, and the master control end sends instructions to the controllers of each emergency door through the control line. In this process, emergency doors at similar positions can be classified into one category. At this time, with the help of one bus, instructions can be sent to multiple controllers to synchronously adjust multiple emergency doors. This is consistent with the actual situation because when dealing with special situations, it is rare to close only one emergency door.

[0077] After determining the control line and edge control node (one edge control node corresponds to one type of emergency door), use the monitoring system to obtain real-time video and identify the video. This step can use existing video intelligent recognition technology or introduce a manual recognition process. Generally, in order to ensure the real-time performance of the emergency door control process (manual recognition has high flexibility, but considering fatigue factors, the real-time performance is poor), video intelligent recognition technology is mainly used, and its accuracy is at least that of face recognition. In the application scenario of this application, the number of managed personnel is limited, and there are few face feature databases. Both face recognition accuracy and speed can be guaranteed at a relatively low cost.

[0078] By analyzing the surveillance video, we can locate the position of abnormal personnel and the abnormality level. According to the position of the abnormal personnel, the target emergency door is selected, and then the corresponding edge control node is queried. The total code is sent through the edge control node to control the state of the emergency door. The simplest control instruction includes two states, which correspond to the opening or closing of the emergency door.

[0079] In fact, under the existing technical background, it is not difficult to control the area of ​​the emergency door to be opened or closed. Compared with the opening and closing instructions, it is just to reference an additional encapsulation function that represents the position.

[0080] It is worth mentioning that, as a preferred embodiment of the technical solution of the present invention, the monitoring video can be further analyzed to identify the actual opening state of the emergency door through the monitoring video. The control instruction issuance process based on the edge control node is verified by the actual opening state. If there is any discrepancy, an error message is generated.

[0081] Figure 2 This is a flowchart of step S100, wherein the step of creating a control circuit according to the emergency door position and emergency door parameters, and determining the edge control node and its instruction mapping relationship based on the control circuit includes:

[0082] Step S101: query the building registration information to obtain the location of the emergency door;

[0083] The location of the emergency door is determined during the building construction process and can be directly read from the building filing information.

[0084] Step S102: establishing a connection channel with the controllers of each emergency door, querying the control record, and obtaining the emergency door opening position within an opening and closing cycle according to the control record; the emergency door opening position is indexed by the time ratio;

[0085] The control process of the emergency door is completed by the controller, which drives the motor to complete the closing and opening of the emergency door. A complete opening or closing process is regarded as an opening and closing cycle. The starting point of the cycle is taken as the zero time point. The opening position of the emergency door at different times is counted, and the motion parameters of the emergency door opening and closing process can be obtained as the target of subsequent control instructions.

[0086] Step S103: calculating a control difficulty coefficient according to the emergency door opening position within one opening and closing cycle; the control difficulty coefficient is determined by a derivative characteristic of the emergency door opening position;

[0087] By analyzing the emergency door opening position within an opening and closing cycle, the control difficulty coefficient can be calculated. Because the motor power is fixed, different motors have different opening and closing speeds and opening and closing accelerations, which can be calculated from the emergency door opening position (derivation);

[0088] The calculation process of the control difficulty coefficient is: D = αf′(x)+βf″(x);

[0089] Where α and β are weight coefficients, and f(x) is the emergency door opening position calculated based on time proportion statistics.

[0090] Step S104: clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating control routes according to the clustering results;

[0091] The distance to the emergency door position is calculated, and the emergency doors are clustered according to the two parameters of distance and control difficulty coefficient. The main line and branch line can be determined based on the clustering results, which are collectively referred to as control lines.

[0092] Step S105: determining edge control nodes and their instruction mapping relationships based on the control circuit;

[0093] The edge control nodes are determined in the control circuit, and the number of the edge control nodes is generally the same as the number of cluster types; on this basis, an instruction mapping relationship can be established, which is the mapping relationship between the data at the edge control node and the control instructions of each controller. In general, the control instructions of each controller are counted in a preset order, which is the data at the edge control node.

[0094] As a preferred embodiment of the technical solution of the present invention, the step of clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating control lines according to the clustering results includes:

[0095] Selecting a preset number of data centers based on the control difficulty coefficient;

[0096] Traversing emergency door locations according to the data center and clustering the emergency door locations;

[0097] Build a bus based on the data center, build a branch line based on the clustering results, and get the control line;

[0098] Among them, the objective function of clustering is:

[0099]

[0100] Where n is the total number of emergency door locations, k is the total number of data centers, and x i is the coordinate of the i-th emergency door position, μ 1j is the coordinate of the data center; i is the control difficulty coefficient of the i-th emergency door, μ 2j is the control difficulty coefficient of the data center; x i -μ 1j is the distance between two coordinate spaces; ‖Δ‖ 2 is the L2 norm of Δ.

[0101] The above content describes the clustering process in detail. First, the data center is selected according to the control difficulty coefficient. The higher the control difficulty coefficient, the greater the power of the emergency door opening and closing motor. By selecting the data center according to the control difficulty coefficient, high-power motors can be divided into different categories as much as possible and controlled by the bus at the same time; then, based on the data center, each emergency door can be clustered; finally, the data center is connected to obtain the bus, and a branch line is established on the bus to connect to each emergency door.

[0102] As a preferred embodiment of the technical solution of the present invention, the step of determining the edge control node and its instruction mapping relationship based on the control line includes:

[0103] Based on the statistical branch lines of the data center, query the control parameters of the emergency door controller at each branch line terminal; the control parameters are the data structure of the control instructions of the emergency door controller;

[0104] The control parameters are spliced ​​according to the preset connection sequence, the total control code is determined, and an edge control node based on the total control code is set at the data center;

[0105] Obtain and count the historical total control codes at the edge control node to obtain a total code table; the total code table contains a total control code item and an input number item;

[0106] The total code table is traversed, logical operations are performed on the control total code in turn, data items are merged according to the results of the logical operations, and data items are intercepted according to a preset number threshold to obtain a revised total code table; the revised total code table contains a total code range item and an input number item.

[0107] The above content limits the generation process of edge control nodes and instruction mapping relationships. The principle is to use the input end of the data center as the edge control node, query the data structure of the control instructions of each emergency door corresponding to the edge control node, and count multiple data structures according to a preset order to obtain a total control code. Each part of the total control code has a unique corresponding emergency door.

[0108] On this basis, the historical total control code and its input times at the edge control node are counted. The more times the code is input, the more synchronous control situations of the corresponding emergency doors are. This can be understood as "a single move affects the whole body". Its practical significance is that the same batch of emergency doors often need to be closed in coordination.

[0109] The total code tables are extracted and compared in pairs. If there are only some differences between the two historical control total codes, they can be merged into one range. Correspondingly, the input times also need to be accumulated.

[0110] Finally, data items whose input times reach a preset times threshold are selected to obtain a revised total code table.

[0111] Figure 3 The flowchart of step S200 is as follows: the steps of collecting surveillance video by a camera system built into the production area, identifying the surveillance video, locating abnormal personnel, and determining the abnormality level include:

[0112] Step S201: The camera system built into the production area collects surveillance video, performs face recognition on the surveillance video, and determines the identity of the person and his current location in real time;

[0113] Step S202: query the historical location according to the identity of the person, compare the current location with the historical location, and determine the abnormality according to the comparison result;

[0114] Step S203: When the abnormality reaches a preset abnormality threshold, the abnormality level is queried according to the identity of the person.

[0115] The above content makes specific limitations on the video recognition process. The principle is to perform face recognition on the surveillance video to determine the identity of the person. The historical location of the person can be queried based on the identity of the person. By comparing the historical location with the current location, it can be determined whether the person appears in a location that does not often appear. The degree of abnormality is determined based on the number of times the location appears. The fewer the number of times, the higher the degree of abnormality.

[0116] Furthermore, when the abnormality is high enough, the registered information of the person's identity is queried to determine the abnormality level; for example, in general, a young male is more dangerous than an elderly male and has a higher abnormality level.

[0117] Figure 4 The flowchart of step S300 is as follows: the step of selecting an edge control node according to the positioning result, determining a control instruction according to the instruction mapping relationship, and sending the control instruction to the controller of the emergency door through the edge control node includes:

[0118] Step S301: reading the current position, taking the current position as the center, selecting a target emergency door within a preset distance range, and determining the required state of the target emergency door;

[0119] Step S302: determining a demand control parameter according to the demand state, and determining a demand code according to the demand control parameter;

[0120] Step S303: query the edge control node corresponding to the target emergency door, and match the total code in the revised total code table according to the required code;

[0121] Step S304: Send the matched total code based on the queried edge control node; wherein, during the sending process, the required code in the total code is sent directly, and the non-required code in the total code is sent after inserting the execution pause tag, and the execution pause tag is used to pause the control instruction sending process of the controller.

[0122] The above content provides a specific description of the actual control process. First, the current position of the abnormal person is read, and the distance range is determined according to the abnormal level. The emergency door to be closed and the closing amplitude are selected within the distance range, which is called the target emergency door. The closing amplitude is called the demand control parameter; the demand control parameter is implemented by the motor under the control instruction. The control instruction is the demand code in the above content. The demand code refers to the control instruction of an emergency door. The total code table is traversed according to the demand code to determine the matched total code. The matched total code refers to the set of control instructions of all emergency doors corresponding to an edge control node.

[0123] Furthermore, the emergency door that needs to be controlled is actually the emergency door corresponding to the demand code, and the other emergency doors corresponding to the general code are only the emergency doors that may be adjusted. The function of the general code is to put the emergency doors that may be adjusted in a pre-activated state so that they can respond more quickly when receiving a control command.

[0124] To sum up, the working principle of the technical solution of the present invention is actually to identify the surveillance video and determine the emergency door that needs to be controlled. On this basis, the relevant emergency door is pre-activated according to historical data, so that it can respond quickly when control is needed.

[0125] Figure 5 The structure diagram of the intelligent door and window control system with remote monitoring function is shown in FIG. 1 . In an embodiment of the present invention, an intelligent door and window control system with remote monitoring function is provided. The system 10 includes:

[0126] A preprocessing module 11 is used to create a control circuit according to the emergency door position and emergency door parameters, and determine the edge control node and its instruction mapping relationship based on the control circuit; the instruction mapping relationship is a mapping of a trigger signal to a control instruction;

[0127] The video recognition module 12 is used to collect monitoring videos from a camera system built into the production area, identify the monitoring videos, locate abnormal personnel, and determine the abnormality level;

[0128] The instruction sending module 13 is used to select an edge control node according to the positioning result, determine a control instruction according to the instruction mapping relationship, and send the control instruction to the controller of the emergency door through the edge control node.

[0129] Furthermore, the preprocessing module 11 includes:

[0130] A location acquisition unit, used to query building record information and obtain the location of the emergency door;

[0131] A record query unit, used to establish a connection channel with the controller of each emergency door, query the control record, and obtain the emergency door opening position within an opening and closing cycle according to the control record; the emergency door opening position is indexed by time ratio;

[0132] A difficulty coefficient calculation unit, used to calculate a control difficulty coefficient according to the emergency door opening position within one opening and closing cycle; the control difficulty coefficient is determined by a derivative characteristic of the emergency door opening position;

[0133] The calculation process of the control difficulty coefficient is: D = αf′(x)+βf″(x);

[0134] In the formula, α and β are weight coefficients, and f(x) is the emergency door opening position calculated based on time proportion statistics;

[0135] An emergency door clustering unit, used for clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating a control line according to the clustering results;

[0136] A mapping creation unit is used to determine the edge control node and its instruction mapping relationship based on the control line.

[0137] Specifically, the emergency door clustering unit includes:

[0138] A center selection subunit, used to select a preset number of data centers based on a control difficulty coefficient;

[0139] an execution subunit, configured to traverse the emergency door positions according to the data center and cluster the emergency door positions;

[0140] The line construction subunit is used to construct a bus according to the data center, construct a branch line according to the clustering result, and obtain a control line;

[0141] Among them, the objective function of clustering is:

[0142]

[0143] Where n is the total number of emergency door locations, k is the total number of data centers, and x i is the coordinate of the i-th emergency door position, μ 1j is the coordinate of the data center; i is the control difficulty coefficient of the i-th emergency door, μ 2j is the control difficulty coefficient of the data center; x i -μ 1j is the distance between two coordinate spaces; ‖Δ‖ 2 is the L2 norm of Δ.

[0144] Furthermore, the mapping creation unit includes:

[0145] A query subunit is used to query the control parameters of the emergency door controller at each branch terminal based on the statistical branch of the data center; the control parameters are the data structure of the control instructions of the emergency door controller;

[0146] The node setting subunit is used to splice the control parameters according to the preset connection sequence, determine the total control code, and set the edge control node based on the total control code at the data center;

[0147] The total code table generating subunit is used to obtain and count the historical control total codes at the edge control node to obtain a total code table; the total code table contains a control total code item and an input number item;

[0148] The operator unit is used to traverse the total code table, perform logical operations on the control total code in turn, merge data items according to the logical operation results, and intercept data items according to a preset number threshold to obtain a modified total code table; the modified total code table contains a total code range item and an input number item.

[0149] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent door and window control method with remote monitoring function, characterized in that: The method comprises: A control circuit is created according to the emergency door position and emergency door parameters, and an edge control node and its instruction mapping relationship are determined based on the control circuit; the instruction mapping relationship is a mapping of a trigger signal to a control instruction; The camera system built into the production area collects surveillance video, identifies the surveillance video, locates abnormal personnel, and determines the abnormality level; Select an edge control node according to the positioning result, determine the control command according to the command mapping relationship, and send the control command to the controller of the emergency door through the edge control node; The step of creating a control circuit according to the emergency door position and the emergency door parameters, and determining the edge control node and its instruction mapping relationship based on the control circuit comprises: Check the building registration information and obtain the location of the emergency door; Establish a connection channel with the controller of each emergency door, query the control record, and obtain the emergency door opening position within an opening and closing cycle according to the control record; the emergency door opening position is indexed by time ratio; Calculating a control difficulty coefficient according to the emergency door opening position within one opening and closing cycle; the control difficulty coefficient is determined by a derivative characteristic of the emergency door opening position; Clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating control routes according to the clustering results; Determine the edge control node and its instruction mapping relationship based on the control line; The calculation process of the control difficulty coefficient is as follows: ; In the formula, and is the weight coefficient, is the emergency door opening position calculated based on the time ratio; The step of clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients and creating control lines according to the clustering results comprises: Selecting a preset number of data centers based on the control difficulty coefficient; Traversing emergency door locations according to the data center and clustering the emergency door locations; Build a bus based on the data center, build a branch line based on the clustering results, and get the control line; Among them, the objective function of clustering is: ； Where n is the total number of emergency door locations, k is the total number of data centers, is the coordinate of the i-th emergency door position, are the coordinates of the data center; is the control difficulty coefficient of the i-th emergency door, is the control difficulty coefficient of the data center; is the distance between two coordinate spaces; for The L2 norm of .

2. The intelligent door and window control method with remote monitoring function according to claim 1 is characterized in that: The step of determining the edge control node and its instruction mapping relationship based on the control line includes: Based on the statistical branch lines of the data center, query the control parameters of the emergency door controller at each branch line terminal; the control parameters are the data structure of the control instructions of the emergency door controller; The control parameters are spliced ​​according to the preset connection sequence, the total control code is determined, and an edge control node based on the total control code is set at the data center; Obtain and count the historical total control codes at the edge control node to obtain a total code table; the total code table contains a total control code item and an input number item; The total code table is traversed, logical operations are performed on the control total code in turn, data items are merged according to the results of the logical operations, and data items are intercepted according to a preset number threshold to obtain a revised total code table; the revised total code table contains a total code range item and an input number item.

3. The intelligent door and window control method with remote monitoring function according to claim 2 is characterized in that: The steps of collecting surveillance video by a camera system built into the production area, identifying the surveillance video, locating abnormal personnel, and determining the abnormality level include: A camera system built into the production area collects surveillance video and locates the worker in the surveillance video; Obtain the personnel outline of the staff, intercept the area corresponding to the personnel outline in the image at different times, and obtain the histogram of the area in different dimensions; Calculate the mean and standard deviation of the histograms of different dimensions, compare the mean and standard deviation with the preset color value conditions, and when the mean and standard deviation do not meet the color value conditions, mark the current staff member as an abnormal person, and record the number of images with the mark; Read the video acquisition frequency, calculate the total number of images within the preset time, and determine the abnormality level based on the ratio between the number of images and the total number of images; the larger the ratio, the higher the abnormality level.

4. The intelligent door and window control method with remote monitoring function according to claim 3 is characterized in that: The steps of selecting an edge control node according to the positioning result, determining a control instruction according to the instruction mapping relationship, and sending the control instruction to the controller of the emergency door through the edge control node include: Obtain the location of the abnormal person, take the location as the center, select the target emergency door within the preset distance range, and determine the required state of the target emergency door; Determine a demand control parameter according to the demand state, and determine a demand code according to the demand control parameter; Query the edge control node corresponding to the target emergency door, and match the total code in the revised total code table according to the required code; The matched total code is sent based on the queried edge control node; wherein, during the sending process, the required code in the total code is sent directly, and the non-required code in the total code is sent after inserting the execution pause tag, and the execution pause tag is used to pause the control instruction sending process of the controller.

5. An intelligent door and window control system with remote monitoring function, characterized in that: The system comprises: A preprocessing module, used to create a control circuit according to the emergency door position and emergency door parameters, and determine the edge control node and its instruction mapping relationship based on the control circuit; the instruction mapping relationship is a mapping of a trigger signal to a control instruction; A video recognition module is used to collect surveillance videos from a camera system built into the production area, identify the surveillance videos, locate abnormal personnel, and determine the abnormality level; An instruction sending module is used to select an edge control node according to the positioning result, determine a control instruction according to the instruction mapping relationship, and send the control instruction to the controller of the emergency door through the edge control node; The preprocessing module comprises: A location acquisition unit, used to query building record information and obtain the location of the emergency door; A record query unit, used to establish a connection channel with the controller of each emergency door, query the control record, and obtain the emergency door opening position within an opening and closing cycle according to the control record; the emergency door opening position is indexed by time ratio; A difficulty coefficient calculation unit, used to calculate a control difficulty coefficient according to the emergency door opening position within one opening and closing cycle; the control difficulty coefficient is determined by a derivative characteristic of the emergency door opening position; The calculation process of the control difficulty coefficient is: ; In the formula, and is the weight coefficient, is the emergency door opening position calculated based on the time ratio; An emergency door clustering unit, used for clustering the emergency door positions according to the emergency door positions and the control difficulty coefficients, and creating a control line according to the clustering results; A mapping creation unit, used to determine the edge control node and its instruction mapping relationship based on the control line; The emergency door clustering unit comprises: A center selection subunit, used to select a preset number of data centers based on a control difficulty coefficient; an execution subunit, configured to traverse the emergency door positions according to the data center and cluster the emergency door positions; The line construction subunit is used to construct a bus according to the data center, construct a branch line according to the clustering result, and obtain a control line; Among them, the objective function of clustering is: ； Where n is the total number of emergency door locations, k is the total number of data centers, is the coordinate of the i-th emergency door position, are the coordinates of the data center; is the control difficulty coefficient of the i-th emergency door, is the control difficulty coefficient of the data center; is the distance between two coordinate spaces; for The L2 norm of .

6. The intelligent door and window control system with remote monitoring function according to claim 5 is characterized in that: The mapping creation unit comprises: A query subunit is used to query the control parameters of the emergency door controller at each branch terminal based on the statistical branch of the data center; the control parameters are the data structure of the control instructions of the emergency door controller; The node setting subunit is used to splice the control parameters according to the preset connection sequence, determine the total control code, and set the edge control node based on the total control code at the data center; The total code table generating subunit is used to obtain and count the historical control total codes at the edge control node to obtain a total code table; the total code table contains a control total code item and an input number item; The operator unit is used to traverse the total code table, perform logical operations on the control total code in turn, merge data items according to the logical operation results, and intercept data items according to a preset number threshold to obtain a modified total code table; the modified total code table contains a total code range item and an input number item.

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