Digital access management method and system

Abstract

The invention relates to the technical field of warehouse management, and particularly discloses a digital access management method and system, and the method comprises the steps: obtaining air data containing time information based on an air detection point, simulating the air data of other positions according to the air data, and obtaining an air data matrix containing the time information; the wind speed is obtained regularly based on the wind speed detection points, data of all the point locations in the air data matrix are recognized according to the wind speed, and the risk value of all the point locations is determined; determining a risk level of each entrance and exit according to the risk value, and executing a management process according to the risk level; the air data in the machine room are obtained according to the air detection equipment, the risk degree of each position in the machine room is determined according to the air data, then the management requirement of each entrance and exit is determined, different management standards are set for different work contents, and convenience and safety are balanced.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to a digital access management method and system. Background Art

[0002] There may be some harmful gases in the computer room environment, such as hydrogen, hydrogen sulfide, sulfur dioxide, ozone and volatile organic compounds (VOCs). These gases mainly come from batteries, air conditioning refrigerant leakage, decoration materials or electronic equipment operation process. These harmful gases can cause certain harm to the human body. Therefore, people entering the computer room need to take some security measures. However, in the existing production environment, many staff members do not take security measures for convenience, which obviously poses a great safety hazard. How to provide a staff entry and exit management solution applied to the computer room to improve the safety of the staff is the technical problem that the technical solution of the present invention wants to solve. Summary of the Invention

[0003] The purpose of the present invention is to provide a digital access management method and system to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A digital access management method and system, the method comprising:

[0006] Obtain the distribution information of hazardous equipment and determine the air detection points and wind speed detection points based on the distribution information of hazardous equipment;

[0007] Acquire air data containing time information based on the air detection point, simulate air data at other locations based on the air data, and obtain an air data matrix containing time information; the row and column positions of the air data matrix correspond one-to-one to the respective positions in the storage space of the hazardous device;

[0008] Regularly obtain wind speed based on wind speed detection points, identify data of each point in the air data matrix according to the wind speed, and determine the risk value of each point;

[0009] The risk level at each entrance and exit is determined according to the risk value, and a management process is executed according to the risk level.

[0010] As a further solution of the present invention, the steps of obtaining the distribution information of hazardous equipment and determining the air detection points and wind speed detection points according to the distribution information of hazardous equipment include:

[0011] Obtaining a building model of the storage space of the hazard device;

[0012] Querying installation information of dangerous equipment and filling a dangerous equipment model in a building model according to the installation information; the stored information includes the type of dangerous equipment, storage location and storage capacity;

[0013] Determine the importance of each point in the building model containing the hazardous equipment model;

[0014] Selecting air detection points based on the importance;

[0015] The air detection points are clustered, the building model is partitioned based on the clustering results, and a wind speed detection point is set at the center of each area.

[0016] As a further solution of the present invention: the process of determining the importance is:

[0017] Obtain the distance between the point and each hazard device model, determine the basic value based on the hazard device type of the hazard device model, and determine the importance based on the accumulated basic value of the distance. The calculation process is as follows:

[0018] In the formula, I(x,y) represents the importance of the point (x,y), B i is the basic value of the ith hazard device model, N represents the total number of hazard device models, d i (x, y) represents the distance between the center point of the i-th hazard device model and the point (x, y), d0 represents the preset distance base value; α is the preset coefficient;

[0019] The process of selecting air detection points based on the importance is as follows:

[0020] The selection value of each point is calculated based on the importance; the selection value is proportional to the importance of the point and inversely proportional to the number of selected air detection points within a preset range.

[0021] As a further solution of the present invention, the steps of acquiring air data containing time information based on air detection points, simulating air data at other locations based on the air data, and obtaining an air data matrix containing time information include:

[0022] Acquire air data based on air detection points and insert time tags when acquiring air data;

[0023] Inserting a grid into the building model using a grid tool, and generating a matrix corresponding to the building model based on the grid as a matrix template; wherein the cell size of the grid is a preset value, and an adjustment port is opened;

[0024] At a certain moment, query the latest air data of each air detection point at that moment, query the row and column position corresponding to the air detection point in the matrix template, insert the latest air data into the row and column position to obtain the transfer matrix;

[0025] The data in the transit matrix is ​​expanded to obtain the air data matrix, and the moment is used as the time label of the air data matrix.

[0026] As a further solution of the present invention, the steps of regularly obtaining wind speed based on wind speed detection points, identifying data of each point in the air data matrix according to the wind speed, and determining the risk value of each point include:

[0027] Obtain wind speed based on wind speed detection points regularly;

[0028] Determining additional data for each point in the air data matrix to other points based on the wind speed;

[0029] For any point, the additional data of other points at that point are counted, and the risk value is determined based on the additional data counted and the original data of the point.

[0030] As a further solution of the present invention, the step of determining the risk level of each entrance and exit according to the risk value and executing the management process according to the risk level includes:

[0031] For any entrance and exit, obtain the traffic area and traffic frequency pointed to by the entrance and exit; the traffic probability is determined by the historical traffic records within a preset time range;

[0032] Count the risk values ​​in the traffic area, accumulate the calculated risk values ​​according to the traffic frequency, and obtain the total risk value at the entrance and exit;

[0033] The risk level is determined based on the threshold reached by the total risk value; the corresponding relationship between the threshold and the risk level is pre-set;

[0034] The amount of management resources is determined according to the risk level; the management resources are used to adjust the data collection accuracy of the collection equipment at the entrance and exit, the identification subject of the data processing equipment, and the data recognition accuracy of the identification subject.

[0035] The technical solution of the present invention also provides a digital access management system, the system comprising:

[0036] The detection point determination module is used to obtain the distribution information of hazardous equipment and determine the air detection points and wind speed detection points based on the distribution information of hazardous equipment;

[0037] An air data acquisition module is configured to acquire air data containing time information based on air detection points, simulate air data at other locations based on the air data, and obtain an air data matrix containing time information; the row and column positions of the air data matrix correspond one-to-one to the respective positions in the hazardous device storage space;

[0038] A point risk assessment module is used to periodically obtain wind speed based on wind speed detection points, identify the data of each point in the air data matrix according to the wind speed, and determine the risk value of each point;

[0039] The entrance and exit management control module is used to determine the risk level of each entrance and exit according to the risk value and execute the management process according to the risk level.

[0040] As a further solution of the present invention: the detection point determination module includes:

[0041] A building model acquisition unit, used to acquire a building model of a storage space of a hazardous device;

[0042] A model filling unit is used to query the installation information of the dangerous equipment and fill the dangerous equipment model in the building model according to the installation information; the storage information includes the type of dangerous equipment, storage location and storage capacity;

[0043] An importance determination unit, used to determine the importance of each point in a building model containing a hazardous equipment model;

[0044] an air detection point selection unit, configured to select an air detection point based on the importance;

[0045] The wind speed detection point setting unit is used to cluster the air detection points, partition the building model based on the clustering results, and set a wind speed detection point at the center of each area.

[0046] As a further solution of the present invention: the process of determining the importance is:

[0047] Obtain the distance between the point and each hazard device model, determine the basic value based on the hazard device type of the hazard device model, and determine the importance based on the accumulated basic value of the distance. The calculation process is as follows:

[0048] In the formula, I(x,y) represents the importance of the point (x,y), B i is the basic value of the ith hazard device model, N represents the total number of hazard device models, d i (x, y) represents the distance between the center point of the i-th hazard device model and the point (x, y), d0 represents the preset distance base value; α is the preset coefficient;

[0049] The process of selecting air detection points based on the importance is as follows:

[0050] The selection value of each point is calculated based on the importance; the selection value is proportional to the importance of the point and inversely proportional to the number of selected air detection points within a preset range.

[0051] As a further solution of the present invention: the air data acquisition module includes:

[0052] A data acquisition unit, configured to acquire air data based on air detection points and insert a time tag when acquiring the air data;

[0053] A template generation unit, configured to insert a grid into the building model using a grid tool, and generate a matrix corresponding to the building model based on the grid as a matrix template; wherein the cell size of the grid is a preset value and an adjustment port is open;

[0054] The transfer matrix generation unit is used to query the latest air data of each air detection point at a certain moment, query the row and column positions corresponding to the air detection points in the matrix template, insert the latest air data into the row and column positions, and obtain the transfer matrix;

[0055] The data expansion unit is used to expand the data in the transit matrix to obtain the air data matrix, and use the moment as the time tag of the air data matrix.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention obtains air data in the computer room based on air detection equipment, determines the risk level of each location in the computer room based on the air data, and then determines the management requirements of each entrance and exit, sets different management standards for different work contents, and balances convenience and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention.

[0059] Figure 1 The overall flow chart of the digital access management method is shown.

[0060] Figure 2 Shows the structural diagram of the digital access management system. DETAILED DESCRIPTION

[0061] 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 with reference to 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.

[0062] Figure 1 The following is a general flow chart of a digital access management method and system. In an embodiment of the present invention, a digital access management method includes:

[0063] Step S100: Obtaining distribution information of hazardous equipment, and determining air detection points and wind speed detection points based on the hazardous equipment distribution information;

[0064] The technical solution of the present invention is applied to computer rooms containing hazardous equipment. The danger of these hazardous equipment mainly lies in the gases they produce, such as some batteries, laser printers, copiers and some UPS equipment. In addition, some cables will also produce some hazardous gases when short-circuited, and some equipment will produce volatile organic compounds. These gases have a great impact on the staff in the computer room and need to be detected. In actual application, the distribution information of the hazardous equipment is obtained. The distribution information is which hazardous equipment is installed at which location. According to the distribution information of the hazardous equipment, the air detection points and wind speed detection points are determined. The air detection points are used to detect the air data in the computer room, and the wind speed detection points are used to detect the wind speed in the computer room. The goal of setting up air detection points is to keep costs as low as possible while achieving good data acquisition results. The simplest way to set up air detection points is to determine the risk (which gases are produced and the speed at which these gases act) and the possibility of gas production based on the type of hazardous equipment, and determine whether to set up air detection points based on the risk and the possibility of leakage. After the air detection points are set up, the wind speed detection points are determined based on the equipment results of the air detection points. The number of wind speed detection points is much smaller than the number of air detection points. In extreme cases, only one wind speed detection point is set up to obtain the wind speed of the entire computer room. Many computer rooms have ventilation equipment and ventilation channels, and the wind speed in the computer room is almost in a very stable state.

[0065] Step S200: Acquire air data containing time information based on the air detection point, simulate air data at other locations based on the air data, and obtain an air data matrix containing time information; the row and column positions of the air data matrix correspond one-to-one to the respective positions in the hazardous device storage space;

[0066] Air detection equipment is installed at the air detection point. The air detection equipment includes detection equipment based on physical principles and detection equipment based on chemical principles. After the air detection equipment is installed, the air data at the location can be obtained. The acquisition time is inserted into the obtained air data as the time information of the air data; based on the data at the air detection point, the air data in the entire computer room can be simulated, which is represented by an air data matrix. The simulation process is based on the data at all air detection points at the same time, and the air data matrix obtained by simulation is also the air data matrix at that time; the number of rows and columns in the air data matrix are both preset values. The more rows and columns, the more points need to be simulated, and the higher the density of the obtained air data matrix. The row and column positions of the air data matrix correspond one-to-one to each position in the storage space of the hazardous device.

[0067] It is worth mentioning that there are many types of air data that need to be acquired by the technical solution of the present invention. Many existing devices can realize the acquisition function, but for the data statistics stage, statistics need to be performed by type. For multiple types of air data, multiple independent statistics can be performed. Therefore, the embodiment of the technical solution of the present invention only takes one type as an example.

[0068] Step S300: regularly obtaining wind speed based on wind speed detection points, identifying data of each point in the air data matrix according to the wind speed, and determining the risk value of each point;

[0069] Wind speed detection points are used to detect wind speed. Generally, wind speed is in a very stable state because the airflow direction in a machine room is almost predetermined. Wind speed is obtained based on the wind speed detection points at regular intervals, and the timing interval can be very long. The data of each point in the air data matrix is ​​identified in combination with the obtained wind speed to determine the risk value of each point.

[0070] Step S400: determining the risk level of each entrance and exit according to the risk value, and executing a management process according to the risk level;

[0071] After the risk value of each point is determined, each entrance and exit is analyzed. For any entrance and exit, the risk value of the area around it or related to it is obtained to determine the risk level of the entrance and exit. The management process is executed according to the risk level. The management process mainly monitors whether the people entering are wearing protective equipment. The higher the risk level, the stricter the monitoring process.

[0072] Regarding step S100, the steps of obtaining the distribution information of hazardous devices and determining the air detection points and wind speed detection points according to the hazardous device distribution information include:

[0073] Obtaining a building model of the storage space of the hazard device;

[0074] Querying installation information of dangerous equipment and filling a dangerous equipment model in a building model according to the installation information; the stored information includes the type of dangerous equipment, storage location and storage capacity;

[0075] Determine the importance of each point in the building model containing the hazardous equipment model;

[0076] Selecting air detection points based on the importance;

[0077] The air detection points are clustered, the building model is partitioned based on the clustering results, and a wind speed detection point is set at the center of each area.

[0078] In an example of the technical solution of the present invention, the process of determining the air detection points and the wind speed detection points is specifically defined, and a building model of the hazardous equipment storage space is obtained. The hazardous equipment storage space is the computer room mentioned in the present invention. The installation information of the hazardous equipment is queried, and the hazardous equipment model is filled in the building model according to the installation information; the installation information includes the type of hazardous equipment, the installation location and the equipment size. This process generally only involves a data reading process. The hazardous equipment model (such as a cylinder with a cross-section of different polygons) is queried according to the type of hazardous equipment, the number of hazardous equipment models is determined according to the storage capacity, and the corresponding number of hazardous equipment models are inserted into the building model according to the storage location.

[0079] For a building model containing a hazardous equipment model, the importance of each point is determined, and points with an importance greater than a preset importance threshold are selected as air detection points. Then, the selected air detection points are clustered, and the influencing parameter of the clustering process is distance. That is, the air detection points are clustered based on their locations, and the building model is partitioned based on the clustering results, with a wind speed detection point set at the center of each area. The clustering algorithm uses a clustering algorithm with an unlimited number of classes, such as the DBSCAN algorithm and the Mean Shift algorithm.

[0080] Furthermore, the importance is determined as follows:

[0081] Obtain the distance between the point and each hazard device model, determine the basic value according to the hazard device type of the hazard device model, and determine the importance based on the accumulated basic value of the distance. The calculation process is as follows.

[0082] In the formula, I(x,y) represents the importance of the point (x,y), B i is the basic value of the ith hazard device model, N represents the total number of hazard device models, d i (x, y) represents the distance between the center point of the i-th hazard device model and the point (x, y), d0 represents the preset distance base value; α is the preset coefficient;

[0083] The calculation principle of importance is to calculate the influence of each hazardous device model at a certain point that needs to be calculated. The influence degree is Item, d0 is used to ensure that the denominator has a minimum value to prevent the impact from being too large. The impact is proportional to the base value. Generally, the greater the risk of the hazardous equipment type, the larger the base value; the impact is inversely proportional to the distance.

[0084] The process of selecting air detection points based on the importance is as follows:

[0085] The selection value of each point is calculated based on the importance; the selection value is proportional to the importance of the point and inversely proportional to the number of selected air detection points within a preset range.

[0086] Regarding the selection process of air detection points, the conventional logic is that the greater the importance, the larger the selection value, and the easier it is to be selected. Based on this logic, a parameter, the number of selected air detection points within the preset range, is introduced to prevent the selection of air detection points from being too concentrated.

[0087] Regarding step S200, the steps of acquiring air data containing time information based on the air detection point, simulating air data at other locations based on the air data, and obtaining an air data matrix containing time information include:

[0088] Acquire air data based on air detection points and insert time tags when acquiring air data;

[0089] Inserting a grid into the building model using a grid tool, and generating a matrix corresponding to the building model based on the grid as a matrix template; wherein the cell size of the grid is a preset value, and an adjustment port is opened;

[0090] At a certain moment, query the latest air data of each air detection point at that moment, query the row and column position corresponding to the air detection point in the matrix template, insert the latest air data into the row and column position to obtain the transfer matrix;

[0091] The data in the transit matrix is ​​expanded to obtain the air data matrix, and the moment is used as the time label of the air data matrix.

[0092] The above content explains the generation process of the air data matrix. Air data containing the acquisition time is obtained based on the air detection points. Then, a grid is inserted into the building model. The grid determines the number of points that need to be simulated. The cell size of the grid is set by the staff. There is also a built-in adjustment port in the grid tool to receive the adjustment information of the staff; a matrix template is created based on the grid. The creation process is very simple. Each grid node is numbered to determine its row and column. A matrix template is created based on the number of rows and columns of the grid nodes. For any moment, the latest air data of each air detection point at that moment is queried. The air detection point is included in the computer room. The row and column positions corresponding to the air detection point are queried in the matrix template, and the data of the air detection point at that moment is inserted into the position. After the data of all air detection points are inserted into the matrix template, a transit matrix is ​​obtained. The data in the transit matrix is ​​expanded to obtain the air data matrix, and the moment is used as the time label of the air data matrix.

[0093] Regarding step S300, the steps of regularly obtaining wind speed based on wind speed detection points, identifying data of each point in the air data matrix according to the wind speed, and determining the risk value of each point include:

[0094] Obtain wind speed based on wind speed detection points regularly;

[0095] Determining additional data for each point in the air data matrix to other points based on the wind speed;

[0096] For any point, the additional data of other points at that point are counted, and the risk value is determined based on the additional data counted and the original data of the point.

[0097] A sensor for detecting wind speed is installed at the wind speed detection point. The wind speed includes wind direction and speed. The wind speed is obtained at regular intervals. The additional data of each point corresponding to the air detection point to other points in the air data matrix is ​​determined based on the wind speed. For any point (not corresponding to the air detection point), the additional data of other points (points corresponding to the air detection point) at this point are counted, and the risk value is determined based on the additional data counted.

[0098] The calculation process of the additional data is:

[0099] For any point that does not correspond to an air detection point, calculate the mapped wind speed of all wind speed detection points at that point, calculate the combined wind speed of all mapped wind speeds, construct a query area in the opposite direction of the combined wind speed, query the air data of the air detection points in the query area in sequence, calculate the additional value based on the air data and the distance between the air detection point and the current point, and accumulate all the additional values ​​as additional data;

[0100] The mapped wind speed has the same direction as the wind speed at the wind speed detection point, and the modulus is the wind speed modulus divided by the distance between the wind speed detection point and the current point. The query area is a fan-shaped area with a preset angle range of the ray centered in the opposite direction of the combined wind speed.

[0101] The above scheme provides an expansion scheme for air data. It combines wind speed to simulate data for points that are not air detection points and determines some additional data. In the above scheme, it is considered that the additional data is only affected by the air detection point where the wind speed points to the point. In addition, based on the additional data, some correction coefficients can be introduced to make it between the minimum and maximum values ​​of all air data.

[0102] In fact, there are many data expansion schemes. If wind speed is not introduced, for any point, the air data at the nearest air detection point can be directly used as the data at that point. At this time, some points may be adjacent points, but they belong to two air detection points, and their data will have certain differences and the differences are large. Therefore, in this scheme, introducing a smoothing operation can also obtain a more appropriate air data matrix.

[0103] Regarding step S400, the steps of determining the risk level of each entrance and exit according to the risk value and executing the management process according to the risk level include:

[0104] For any entrance and exit, obtain the traffic area and traffic frequency pointed to by the entrance and exit; the traffic probability is determined by the historical traffic records within a preset time range;

[0105] Count the risk values ​​in the traffic area, accumulate the calculated risk values ​​according to the traffic frequency, and obtain the total risk value at the entrance and exit;

[0106] The risk level is determined based on the threshold reached by the total risk value; the corresponding relationship between the threshold and the risk level is pre-set;

[0107] Determine the amount of management resources based on the level of risk.

[0108] After the risk value of each point is determined, each entrance and exit is analyzed in turn. For any entrance and exit, the traffic area and traffic frequency pointed to by the entrance and exit are obtained. Any area that is connected to the entrance and exit can be used as the traffic area of ​​the entrance and exit. Regarding the traffic frequency, historical traffic records are obtained within a preset time range. The historical traffic records are the number of people appearing in the traffic area. The ratio of the number of people in each passing area to the total number of people appearing in all traffic areas is calculated (not the ratio to the number of people entering the computer room at the entrance and exit. One person appears in two traffic areas, and the total is two). This ratio is used as the traffic frequency. The traffic frequency reflects the possibility of staff reaching different traffic areas when entering the computer room from the entrance and exit. In addition, the traffic area is a sub-area of ​​the computer room and is a pre-divided area.

[0109] Then, the risk values ​​within the passage area are calculated (the total risk values ​​or the mean risk values ​​can be calculated), and the calculated risk values ​​of each passage area are accumulated according to the passage frequency. The passage frequency is equivalent to a weight in the range of zero to one. After the accumulation is completed, the obtained value is called the total risk value, which is used as a value to describe the risk level of the entrance and exit.

[0110] The staff pre-sets the correspondence between the threshold and the risk level, determines the risk level based on the threshold reached by the total risk value, and determines the amount of management resources based on the risk level. The management resources are used to adjust the data collection accuracy of the collection equipment at the entrance and exit, the identification subject of the data processing equipment, and the data recognition accuracy of the identification subject. The higher the risk level, the more dangerous it is, the higher the amount of management resources, the higher the data collection accuracy, and the higher the data recognition accuracy. In addition, the identification subject is the type of protective equipment. The higher the risk level, the more types of identification subjects there are.

[0111] Figure 2 FIG1 shows a structural diagram of a digital access management system. In a preferred embodiment of the technical solution of the present invention, a digital access management system is also provided. The system 10 includes:

[0112] The detection point determination module 11 is used to obtain the distribution information of the hazardous equipment and determine the air detection points and wind speed detection points according to the distribution information of the hazardous equipment;

[0113] An air data acquisition module 12 is configured to acquire air data containing time information based on air detection points, simulate air data at other locations based on the air data, and obtain an air data matrix containing time information; the row and column positions of the air data matrix correspond one-to-one to the respective positions in the hazardous device storage space;

[0114] The point risk assessment module 13 is used to periodically obtain wind speed based on the wind speed detection point, identify the data of each point in the air data matrix according to the wind speed, and determine the risk value of each point;

[0115] The entrance and exit management control module 14 is used to determine the risk level of each entrance and exit according to the risk value and execute a management process according to the risk level.

[0116] Furthermore, the detection point determination module 11 includes:

[0117] A building model acquisition unit, used to acquire a building model of a storage space of a hazardous device;

[0118] A model filling unit is used to query the installation information of the dangerous equipment and fill the dangerous equipment model in the building model according to the installation information; the storage information includes the type of dangerous equipment, storage location and storage capacity;

[0119] An importance determination unit, used to determine the importance of each point in a building model containing a hazardous equipment model;

[0120] an air detection point selection unit, configured to select an air detection point based on the importance;

[0121] The wind speed detection point setting unit is used to cluster the air detection points, partition the building model based on the clustering results, and set a wind speed detection point at the center of each area.

[0122] Specifically, the process of determining the importance is as follows:

[0123] Obtain the distance between the point and each hazard device model, determine the basic value based on the hazard device type of the hazard device model, and determine the importance based on the accumulated basic value of the distance. The calculation process is as follows:

[0124] In the formula, I(x,y) represents the importance of the point (x,y), B i is the basic value of the ith hazard device model, N represents the total number of hazard device models, d i (x, y) represents the distance between the center point of the i-th hazard device model and the point (x, y), d0 represents the preset distance base value; α is the preset coefficient;

[0125] The process of selecting air detection points based on the importance is as follows:

[0126] The selection value of each point is calculated based on the importance; the selection value is proportional to the importance of the point and inversely proportional to the number of selected air detection points within a preset range.

[0127] Furthermore, the air data acquisition module 12 includes:

[0128] A data acquisition unit, configured to acquire air data based on air detection points and insert a time tag when acquiring the air data;

[0129] A template generation unit, configured to insert a grid into the building model using a grid tool, and generate a matrix corresponding to the building model based on the grid as a matrix template; wherein the cell size of the grid is a preset value and an adjustment port is open;

[0130] The transfer matrix generation unit is used to query the latest air data of each air detection point at a certain moment, query the row and column positions corresponding to the air detection points in the matrix template, insert the latest air data into the row and column positions, and obtain the transfer matrix;

[0131] The data expansion unit is used to expand the data in the transit matrix to obtain the air data matrix, and use the moment as the time tag of the air data matrix.

[0132] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A digital access management method, characterized in that: The method comprises: Obtain the distribution information of hazardous equipment and determine the air detection points and wind speed detection points based on the distribution information of hazardous equipment; Acquire air data containing time information based on the air detection point, simulate air data at other locations based on the air data, and obtain an air data matrix containing time information; the row and column positions of the air data matrix correspond one-to-one to the respective positions in the hazardous device storage space; Regularly obtain wind speed based on wind speed detection points, identify data of each point in the air data matrix according to the wind speed, and determine the risk value of each point; The risk level at each entrance and exit is determined according to the risk value, and a management process is executed according to the risk level.

2. The digital access management method according to claim 1, characterized in that: The steps of obtaining the distribution information of hazardous equipment and determining the air detection points and wind speed detection points according to the distribution information of hazardous equipment include: Obtaining a building model of the storage space of the hazard device; Querying installation information of dangerous equipment and filling a dangerous equipment model in a building model according to the installation information; the stored information includes the type of dangerous equipment, storage location and storage capacity; Determine the importance of each point in the building model containing the hazardous equipment model; Selecting air detection points based on the importance; The air detection points are clustered, the building model is partitioned based on the clustering results, and a wind speed detection point is set at the center of each area.

3. The digital access management method according to claim 2, characterized in that: The process of determining the importance is as follows: Obtain the distance between the point and each hazard device model, determine the basic value based on the hazard device type of the hazard device model, and determine the importance based on the accumulated basic value of the distance. The calculation process is as follows: In the formula, I(x,y) represents the importance of the point (x,y), B i is the basic value of the ith hazard device model, N represents the total number of hazard device models, d i (x, y) represents the distance between the center point of the i-th hazard device model and the point (x, y), d0 represents the preset distance base value; α is the preset coefficient; The process of selecting air detection points based on the importance is as follows: The selection value of each point is calculated based on the importance; the selection value is proportional to the importance of the point and inversely proportional to the number of selected air detection points within a preset range.

4. The digital access management method according to claim 3, characterized in that: The steps of acquiring air data containing time information based on the air detection point, simulating air data at other locations based on the air data, and obtaining an air data matrix containing time information include: Acquire air data based on air detection points and insert time tags when acquiring air data; Inserting a grid into the building model using a grid tool, and generating a matrix corresponding to the building model based on the grid as a matrix template; wherein the cell size of the grid is a preset value, and an adjustment port is opened; At a certain moment, query the latest air data of each air detection point at that moment, query the row and column position corresponding to the air detection point in the matrix template, insert the latest air data into the row and column position to obtain the transfer matrix; The data in the transit matrix is ​​expanded to obtain the air data matrix, and the moment is used as the time label of the air data matrix.

5. The digital access management method according to claim 1, characterized in that: The steps of regularly acquiring wind speed based on wind speed detection points, identifying data of each point in the air data matrix according to the wind speed, and determining the risk value of each point include: Obtain wind speed based on wind speed detection points regularly; Determining additional data for each point in the air data matrix to other points based on the wind speed; For any point, the additional data of other points at that point are counted, and the risk value is determined based on the additional data counted and the original data of the point.

6. The digital access management method according to claim 5, characterized in that: The steps of determining the risk level of each entrance and exit according to the risk value and executing the management process according to the risk level include: For any entrance and exit, obtain the traffic area and traffic frequency pointed to by the entrance and exit; the traffic probability is determined by the historical traffic records within a preset time range; Count the risk values ​​in the traffic area, accumulate the calculated risk values ​​according to the traffic frequency, and obtain the total risk value at the entrance and exit; The risk level is determined based on the threshold reached by the total risk value; the corresponding relationship between the threshold and the risk level is pre-set; The amount of management resources is determined according to the risk level; the management resources are used to adjust the data collection accuracy of the collection equipment at the entrance and exit, the identification subject of the data processing equipment, and the data recognition accuracy of the identification subject.

7. A digital access management system, characterized in that: The system comprises: The detection point determination module is used to obtain the distribution information of hazardous equipment and determine the air detection points and wind speed detection points based on the distribution information of hazardous equipment; An air data acquisition module is configured to acquire air data containing time information based on air detection points, simulate air data at other locations based on the air data, and obtain an air data matrix containing time information; the row and column positions of the air data matrix correspond one-to-one to the respective positions in the hazardous device storage space; A point risk assessment module is used to periodically obtain wind speed based on wind speed detection points, identify the data of each point in the air data matrix according to the wind speed, and determine the risk value of each point; The entrance and exit management control module is used to determine the risk level of each entrance and exit according to the risk value and execute the management process according to the risk level.

8. The digital access management system according to claim 7, characterized in that: The detection point determination module includes: A building model acquisition unit, used to acquire a building model of a storage space of a hazardous device; A model filling unit is used to query the installation information of the dangerous equipment and fill the dangerous equipment model in the building model according to the installation information; the storage information includes the type of dangerous equipment, storage location and storage capacity; An importance determination unit, used to determine the importance of each point in a building model containing a hazardous equipment model; an air detection point selection unit, configured to select an air detection point based on the importance; The wind speed detection point setting unit is used to cluster the air detection points, partition the building model based on the clustering results, and set a wind speed detection point at the center of each area.

9. The digital access management system according to claim 8, characterized in that: The process of determining the importance is as follows: Obtain the distance between the point and each hazard device model, determine the basic value based on the hazard device type of the hazard device model, and determine the importance based on the accumulated basic value of the distance. The calculation process is as follows: In the formula, I(x,y) represents the importance of the point (x,y), B i is the basic value of the ith hazard device model, N represents the total number of hazard device models, d i (x, y) represents the distance between the center point of the i-th hazard device model and the point (x, y), d0 represents the preset distance base value; α is the preset coefficient; The process of selecting air detection points based on the importance is as follows: The selection value of each point is calculated based on the importance; the selection value is proportional to the importance of the point and inversely proportional to the number of selected air detection points within a preset range.

10. The digital access management system according to claim 7, characterized in that: The air data acquisition module includes: A data acquisition unit, configured to acquire air data based on air detection points and insert a time tag when acquiring the air data; A template generation unit, configured to insert a grid into the building model using a grid tool, and generate a matrix corresponding to the building model based on the grid as a matrix template; wherein the cell size of the grid is a preset value and an adjustment port is open; The transfer matrix generation unit is used to query the latest air data of each air detection point at a certain moment, query the row and column positions corresponding to the air detection points in the matrix template, insert the latest air data into the row and column positions, and obtain the transfer matrix; The data expansion unit is used to expand the data in the transit matrix to obtain the air data matrix, and use the moment as the time tag of the air data matrix.

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