A method, device and terminal for determining the hazard level of pollutants

Abstract

The present invention discloses a method, device and terminal for determining the hazard level of pollutants. The method includes: when receiving multiple detection information sent by multiple detectors from each area of ​​a subway station, an alarm is issued; the parameter values ​​of multiple determination indicators are calculated according to the multiple detection information; multiple membership functions of each determination indicator in the multiple determination indicators are loaded, and a hazard level judgment matrix is ​​constructed according to the multiple membership functions and the corresponding parameter values; the weight of each determination indicator is loaded, and the weight of each determination indicator is multiplied with the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station; the hazard level of each area of ​​the subway station is determined based on the hazard level judgment sequence of each area of ​​the subway station. Therefore, the present application can provide support for evacuation measures in different areas of the subway station according to the hazard level of each area of ​​the subway station, thereby improving the subway's emergency response capabilities and safety assurance level.

Description

Technical Field

[0001] The present invention relates to the technical field of transportation hub safety, and in particular to a method for determining the hazard level of pollutants in a region. Background Art

[0002] Metro stations are an important project in the development of today's society. With the advancement of urban modernization, they can be seen everywhere in urban window areas such as large commercial districts, airports, ports, docks, long-distance bus stations, and tourist attractions. In recent years, subway stations are in urgent need of an intelligent monitoring system for real-time monitoring to protect people's lives and property.

[0003] At present, the monitoring and command and dispatch of subway stations mainly rely on manpower and video surveillance. When users enter the subway station, the staff will conduct a full-body scan and inspection, and then check whether they are carrying pollutants and toxic agents. Then, according to the inspection results of the staff, supervision and command and dispatch are carried out to ensure the safety of the subway station. Since this method requires a large number of staff and detection equipment for inspection, it wastes time and reduces the efficiency of supervision. Summary of the invention

[0004] The embodiments of the present application provide a method, device and terminal for determining the hazard level of pollutants. In order to have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0005] In a first aspect, an embodiment of the present application provides a method for determining the hazard level of a pollutant, the method comprising:

[0006] When receiving various detection information sent by various detectors in each area of ​​the subway station, an alarm message is generated for early warning;

[0007] Calculate parameter values ​​of multiple determination indicators based on multiple detection information, wherein the multiple determination indicators include acute toxicity category, skin damage category, eye damage category, respiratory sensitization category, flammable and explosive category, pollutant concentration, passenger flow density, and passenger flow rate per unit width;

[0008] Loading the membership function of each of the multiple determination indicators at each hazard level, and constructing a hazard level judgment matrix according to the parameter value of each determination indicator and its membership function at each hazard level;

[0009] Loading the weight of each judgment indicator, and multiplying the weight of each judgment indicator by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station;

[0010] The hazard level of each area of ​​the subway station is determined based on the hazard level determination sequence of each area of ​​the subway station.

[0011] Optionally, the method further includes:

[0012] Get color display parameters for different hazard levels;

[0013] Determining, according to the color parameters of the different hazard levels, a color display parameter corresponding to the hazard level of each area of ​​the subway station;

[0014] generating a color image of each area of ​​the subway station according to the color display parameters corresponding to the hazard level of each area of ​​the subway station;

[0015] The color image of each area is sent to the corresponding client for display.

[0016] Optionally, determining the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station includes:

[0017] Identifying the maximum probability hazard level determination value of each area of ​​the subway station from the hazard level determination sequence of each area of ​​the subway station;

[0018] The hazard level corresponding to the maximum probability hazard level determination value of each area of ​​the subway station is determined as the hazard level of the area.

[0019] Optionally, a hazard level judgment matrix is ​​constructed according to the parameter value of each judgment indicator and its membership function at each hazard level, including:

[0020] According to the parameter value of each determination indicator and the membership function, the membership of each determination indicator to each hazard level is calculated, and a membership sequence of each determination indicator to each hazard level is generated;

[0021] The membership degree sequence of each judgment index is used as a row of matrix elements to generate multiple rows of matrix elements;

[0022] A hazard level judgment matrix is ​​constructed based on multiple rows of matrix elements.

[0023] Optionally, the weights of multiple determination indicators are generated according to the following steps, including:

[0024] S401 determines a plurality of determination indicators related to the hazard level;

[0025] S402: determining the relative importance ranking of each of the plurality of judgment indicators, and constructing a priority relationship matrix based on the order of importance and a scaling method;

[0026] S403 uses the square root method to calculate the initial sorting vector of the priority relationship matrix;

[0027] S404: calculating the maximum characteristic root of the initial sorting vector, and calculating the consistency ratio of the initial sorting vector according to the maximum characteristic root;

[0028] S405 determines whether the initial sorting vector is the weight of each of the multiple determination indicators based on whether the consistency ratio satisfies the consistency check;

[0029] S406: If yes, determine the initial sorting vector as the weight of each of the plurality of determination indicators.

[0030] Optionally, each vector in the initial sorting vector is determined based on whether the consistency ratio satisfies the consistency check, including:

[0031] When the consistency ratio is less than or equal to a preset threshold, it is determined that the consistency test is satisfied, and each vector in the initial sorting vector is determined as the weight of each of the multiple determination indicators;

[0032] When the consistency ratio is greater than a preset threshold, it is determined that the consistency check is not satisfied, and steps S402-S405 are continued until the consistency ratio is less than or equal to the preset threshold, and the initial sorting vector that satisfies the consistency check requirement is determined as the weight of each of the multiple determination indicators.

[0033] Optionally, multiple membership functions of each of the multiple determination indicators at each hazard level are generated according to the following steps, including:

[0034] Obtain historical data of multiple sensors within a preset period;

[0035] Obtain historical data corresponding to each determination indicator from historical data;

[0036] Determine the threshold value of each hazard level for each determination indicator based on the historical data corresponding to each determination indicator;

[0037] According to the threshold value of each judgment indicator belonging to each hazard level, multiple membership functions of each judgment indicator under each hazard level are constructed.

[0038] Optionally, the multiple determination indicators include acute toxicity category, skin damage category, eye damage category, respiratory sensitization category, flammable and explosive category, pollutant concentration, passenger flow density, and passenger flow section flow rate per unit width.

[0039] Optionally, the gas concentration in a certain area is determined by the following steps, including:

[0040] Determine the preset three-dimensional detection interval corresponding to each gas detector in the three-dimensional space of the subway;

[0041] A K-means clustering algorithm is used to perform clustering calculation on the three-dimensional detection interval to generate n interval division results of the subway three-dimensional terrain space;

[0042] The concentration of each type of gas in each of the intervals is calculated, and finally the concentration is weighted to generate the gas concentration of each interval.

[0043] In a second aspect, an embodiment of the present application provides a device for determining the hazard level of pollutants, the device comprising:

[0044] A detection information receiving module is used to generate alarm information for early warning when receiving multiple detection information sent by multiple detectors in each area of ​​the subway station;

[0045] A parameter value calculation module, used to calculate parameter values ​​of multiple determination indicators based on multiple detection information;

[0046] A hazard level judgment matrix construction module is used to load the membership function of each of the multiple judgment indicators at each hazard level, and construct a hazard level judgment matrix according to the parameter value of each judgment indicator and its membership function at each hazard level;

[0047] A hazard level judgment value generation module is used to load the weight of each judgment index, and multiply the weight of each judgment index by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station;

[0048] The hazard level determination module is used to determine the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station.

[0049] In a third aspect, an embodiment of the present application provides a terminal, which may include: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above method steps.

[0050] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0051] In an embodiment of the present application, when the pollutant hazard level determination device receives multiple detection information sent by multiple detectors from each area of ​​the subway station, it first issues an alarm, then calculates the parameter values ​​of multiple determination indicators based on the multiple detection information, then loads multiple membership functions of each of the multiple determination indicators, and constructs a hazard level determination matrix based on the multiple membership functions and the corresponding parameter values, then loads the weight of each determination indicator, and multiplies the weight of each determination indicator with the hazard level determination matrix to generate a hazard level determination sequence for each area of ​​the subway station, and finally determines the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station. Since the present application determines the hazard level of each area of ​​the subway station by loading multiple membership functions and weights of each determination indicator, and calculating the hazard level determination value in combination with the specific parameter value of each determination indicator, it can also provide support for evacuation measures in different areas of the subway station based on the hazard level of each area of ​​the subway station, thereby improving the subway's emergency response capabilities and safety assurance levels.

[0052] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0054] Figure 1 It is a flow chart of a method for determining the hazard level of a pollutant provided in an embodiment of the present application;

[0055] Figure 2 It is a structural schematic diagram of a pollutant hazard level determination device provided in an embodiment of the present application;

[0056] Figure 3 It is a structural diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them.

[0058] It should be clear that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are only examples of devices and methods consistent with some aspects of the present invention as detailed in the attached claims.

[0060] In the description of the present invention, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. In addition, in the description of the present invention, unless otherwise specified, "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0061] The present application provides a method, device, storage medium and terminal for determining the hazard level of pollutants to solve the problems existing in the above-mentioned related technical problems. In the technical solution provided by the present application, since the present application determines the hazard level of each area of ​​the subway station by loading multiple membership functions and weights of each determination index, and calculating the hazard level determination value in combination with the specific parameter value of each determination index, it can also provide support for evacuation measures in different areas of the subway station according to the hazard level of each area of ​​the subway station, thereby improving the subway's emergency response capabilities and safety assurance level. The following is a detailed description using an exemplary embodiment.

[0062] The following will be combined with the attached Figure 1 , a method for determining the hazard level of pollutants provided in an embodiment of the present application is introduced in detail. The method can be implemented by a computer program and can be run on a hazard level determination device for pollutants based on a von Neumann system. The computer program can be integrated into an application or run as an independent tool application.

[0063] See also Figure 1 , which is a flow chart of a method for determining the hazard level of pollutants provided in the present application embodiment. Figure 1 As shown, the method of the embodiment of the present application may include the following steps:

[0064] S101, when receiving various detection information sent by various detectors in each area of ​​the subway station, generating alarm information for early warning;

[0065] Among them, the detector is an electronic device deployed in the subway station to detect pollutants and collect data. The detector includes nuclear detector (Nn), biological detector (Bn), chemical detector (Cn), and video detector (Vn).

[0066] Generally, the three types of detectors, nuclear, biological and chemical, can detect the type and current concentration of suspected contaminated substances, and the video detector can identify the current passenger flow density and the flow rate of the cross-sectional passenger flow.

[0067] In a possible implementation, data is first collected and tested through various detectors installed in subway stations. When the three types of nuclear, biological and chemical detectors detect pollutants, the three types of nuclear, biological and chemical detectors send data information such as the name of the detected pollutants and the concentration of the pollutants to the monitoring platform. When the monitoring platform receives various detection information sent by various detectors in each area of ​​the subway station, it generates alarm information for early warning.

[0068] Furthermore, the alarm information may be generated in text, image and voice formats, and the warning may be sent to relevant departments via email, text message and voice prompts in the form of text, image and voice formats.

[0069] S102, calculating parameter values ​​of multiple determination indicators according to multiple detection information;

[0070] Among them, multiple judgment indicators are determined based on influencing factors that can reflect the hazard level of different areas in the subway. The logo is pre-set by R&D personnel.

[0071] In the scenario described in the present invention, in order to determine the hazard level of pollutants in each area of ​​the subway station, the factors affecting the hazard level of each pollutant are first determined. In view of the complex environment and passenger flow conditions in the subway station and the inner area of ​​the subway car, the R&D personnel selected the pollutant hazard level, pollutant concentration C, passenger flow density T, and unit width passenger flow cross-sectional flow rate P as multiple determination indicators for the hazard level of each area of ​​the subway station. The pollutant hazard level can be further divided into acute toxicity category D, skin damage category S, eye damage category E, respiratory sensitization category A, and flammable and explosive category B according to the classification standards specified in the existing GHS system. The domain U of multiple determination indicators for the hazard levels of different areas in the subway station is established as follows:

[0072] U={U D , U S , U E , U A , U B , U C , U T , Up}

[0073] It can be understood that the multiple determination indicators (or influencing factors) that affect the hazard level of each area include acute toxicity category, skin damage category, eye damage category, respiratory sensitization category, flammable and explosive category, pollutant concentration, passenger flow density, and passenger flow section flow rate per unit width.

[0074] In a possible implementation, after receiving a variety of detection information sent by a variety of detectors in each area of ​​the subway station, the parameter value of each determination indicator in the plurality of determination indicator domains U can be calculated respectively according to the various detection information.

[0075] In an embodiment of the present application, when the detector detects the gas concentration in a certain area of ​​a subway station, it first determines the preset three-dimensional detection interval corresponding to each gas detector in the three-dimensional space of the subway, and then uses the K-means clustering algorithm to perform clustering calculation on the three-dimensional detection interval to generate n interval divisions of the three-dimensional terrain space of the subway. Then, the concentration of each type of gas in each interval is calculated, and finally, the concentration is weighted and calculated to generate the gas concentration of each interval.

[0076] It should be noted that since gas and smoke detectors are usually small in size, they usually detect or characterize the gas concentration in a small space. In a large open space such as a subway station, it is impossible to arrange the detectors too densely. The first problem to be solved is how to use the concentration of a small area detected by the detector to characterize the concentration of a relatively fixed three-dimensional space area, including the determination of the three-dimensional coordinates of the three-dimensional space, and the detection error between the concentration detected by the detector and the three-dimensional area.

[0077] Specifically, when calculating the judgment index U D , U S , U E , U A , U B , U C , U T , U p When the corresponding parameter values ​​are determined, the following steps are used to determine the gas space range corresponding to each detector:

[0078] First, a gridded three-dimensional GIS spatial model of the subway station is established or obtained, and the three-dimensional spatial model includes the internal spatial structure, passages, exits and detector layout of the subway;

[0079] For each detector, the corresponding three-dimensional detection interval is constructed. Specifically, the method for determining the three-dimensional detection space is as follows:

[0080] a. Based on the pre-built CFD three-dimensional gas diffusion model, with the preset time as the constraint condition, determine that within the preset time, the difference between the gas concentration detected by each detector and the gas concentration of the outermost concentration plane in the corresponding three-dimensional detection interval calculated according to the diffusion model is within the preset range, and the gas concentration of the outermost concentration plane in the three-dimensional detection interval is greater than the minimum detection concentration of the target detector. That is, the preset time is considered to be the shortest diffusion time required for diffusion, and the three-dimensional interval corresponding to the shortest diffusion time is the range covered by the gas detector;

[0081] b. Perform the above calculation for each gas detector to obtain the three-dimensional detection interval corresponding to each gas detector;

[0082] c. Perform clustering calculation on the stereoscopic detection interval corresponding to each gas detector in the three-dimensional space of the subway, for example, using K-means clustering algorithm to cluster the stereoscopic detection interval of each gas detector to obtain n interval divisions of the three-dimensional terrain space of the subway.

[0083] d. For each interval obtained by clustering, the concentration of each type of gas is calculated by weighting the concentration detected by at least one gas detector of this type in the interval to obtain the gas concentration of the area.

[0084] S103, loading the membership function of each of the multiple determination indicators at each hazard level, and constructing a hazard level judgment matrix according to the parameter value of each determination indicator and its membership function at each hazard level;

[0085] Among them, multiple membership functions of each judgment indicator are pre-built and stored in the memory. In actual application scenarios, they can be loaded from the memory when making a hazard level judgment.

[0086] Usually, there is no absolute boundary between the hazard levels of different areas in the subway, so it is more reasonable to use membership degree to characterize the classification boundaries. Since each evaluation index is optimal when the value is small, a relatively small distribution is adopted.

[0087] In an embodiment of the present application, when generating multiple membership functions for each of the multiple judgment indicators, firstly, historical data of multiple sensors within a preset period are obtained, and then the historical data corresponding to each judgment indicator is obtained from the historical data, and then the threshold value of each judgment indicator belonging to each hazard level is determined according to the historical data corresponding to each judgment indicator, and then multiple membership functions of each judgment indicator are constructed according to the threshold value of each judgment indicator belonging to each hazard level, and finally the multiple membership functions of each judgment indicator are saved.

[0088] Specifically, historical data is collected, and according to the thresholds of each hazard level corresponding to each judgment indicator in the historical data, multiple membership functions corresponding to each judgment indicator are constructed according to the thresholds. The membership function is the mapping relationship between the judgment indicator and the hazard level set. Considering that the triangular membership function is widely used, the description is intuitive and clear, and the calculation is concise and clear, the triangular membership function is selected to establish the mapping relationship between the evaluation indicator and the hazard level set.

[0089] For example, taking passenger flow density as an example, Table 1 shows the passenger flow density corresponding to various hazard levels.

[0090] Table 1

[0091] Hazard Level Safety Safer generally More dangerous Danger Passenger flow density 0.42 0.67 1.02 1.72 3.01

[0092] The multiple membership functions corresponding to the constructed passenger flow density are:

[0093]

[0094]

[0095]

[0096]

[0097]

[0098] In a possible implementation, after calculating the parameter values ​​of multiple judgment indicators, multiple membership functions of each of the multiple judgment indicators that are pre-saved are loaded from the memory, and then the parameter values ​​of each judgment indicator are calculated one by one with the corresponding membership functions to generate a membership sequence for each judgment indicator, and the membership sequence of each judgment indicator is used as a row of matrix elements to generate multiple rows of matrix elements, and finally a hazard level judgment matrix G is constructed based on the multiple rows of matrix elements.

[0099]

[0100] For example, taking passenger flow density as an example, assuming that the data transmitted by the detector indicates that the passenger flow density is 2.1 people / square meter, a row of matrix elements (G|U T )=[0,0,0,0.70,0.30].

[0101] S104, loading the weight of each determination index, and multiplying the weight of each determination index by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station;

[0102] The weight refers to the influence of each of the eight judging indicators of the hazard level of different areas in the subway station (acute toxicity category D, skin damage category S, eye damage category E, respiratory sensitization category A, flammable and explosive category B, pollutant concentration C, passenger flow density T, and unit width passenger flow section flow rate P) on the regional hazard level. i It is easy to see that the sum of all weights is 1.

[0103]

[0104] In the embodiment of the present application, when generating the weights of the respective multiple determination indicators,

[0105] S401, first determine multiple judgment indicators related to the hazard level, S402, then determine the relative importance ranking of each of the multiple judgment indicators, and construct a priority relationship matrix based on the order of importance and the scaling method, S403 then use the square root method to calculate the initial sorting vector of the priority relationship matrix, S404 calculate the maximum eigenvalue root of the initial sorting vector, and calculate the consistency ratio of the initial sorting vector based on the maximum eigenvalue root, S405 determine whether the initial sorting vector is the weight of each of the multiple judgment indicators based on whether the consistency ratio meets the consistency test requirements; S406, if so, determine the initial sorting vector as the weight of each of the multiple judgment indicators. Technical personnel in this field can understand that the initial sorting vector is a sequence, and each parameter in the sequence corresponds to the weight of each judgment indicator.

[0106] Furthermore, when determining whether each vector in the initial sorting vector is the weight of each of multiple judgment indicators based on the consistency ratio, first, when the consistency ratio is less than or equal to the preset threshold, it is determined that the consistency check is met, and the initial sorting vector is determined as the weight of each of the multiple judgment indicators; when the consistency ratio is greater than the preset threshold, it is determined that the consistency check requirement is not met, and steps S402-S405 are continued to be executed until the consistency ratio is less than or equal to the preset threshold, and the initial sorting vector that meets the consistency check requirement is determined as the weight of each of the multiple judgment indicators.

[0107] Specifically, when generating the weights of multiple judgment indicators, firstly, according to the importance of each judgment indicator, a priority relationship matrix F=(f ij ) n*n as follows:

[0108]

[0109] In the above formula, s(i) represents the importance of the judgment index i, and s(i)<<s(j) means that the importance of the judgment index i is much less than that of the judgment index j, so the matrix can be obtained as follows:

[0110]

[0111] Solve the sorting vector based on F, and after iterative optimization until the convergence requirements are met, we can get W = (w 1 ,w 2 ,w 3 ,w 4 ,w 5 ,w 6 ,w 7 ,w 8 ) T , which is the weight corresponding to each judgment indicator.

[0112] For example, in the face of a major emergency scenario of a nuclear, biological or chemical attack, based on the relative importance of each indicator, the priority relationship matrix F can be obtained through expert scoring as follows:

[0113]

[0114] On this basis, the sorting vector is solved and the consistency check is performed. First, the initial sorting vector W is obtained by using the square root method. (0) =(0.174,0.107,0.061,0.061,0.040,0.253,0.253,0.051) T By calculating the maximum characteristic root, it is found that the consistency ratio of the initial sorting vector is 0.112>0.1, which cannot meet the consistency test, so iterative optimization is required. After one iteration, W (1) =(0.168,0.102,0.060,0.060,0.041,0.260,0.260,0.050) T By calculating the maximum eigenvalue, we find that the sorting vector consistency ratio is 0.010<0.1, which satisfies the consistency test. Therefore, W=(0.168, 0.102, 0.060, 0.060, 0.041, 0.260, 0.260, 0.050) T As the weight of multiple judgment indicators in this scenario.

[0115] In one possible implementation, after constructing the hazard level judgment matrix, firstly, the weights of the respective multiple judgment indicators saved in advance are obtained from the memory, and then the weights of the respective multiple judgment indicators are multiplied by the hazard level judgment matrix to generate multiple hazard level judgment values ​​for each area of ​​the subway station.

[0116] For example, the weights of multiple judgment indicators (acute toxicity category D, skin damage category S, eye damage category E, respiratory sensitization category A, flammable and explosive category B, pollutant concentration C, passenger flow density T, passenger flow rate per unit width P) are combined with the judgment matrix to calculate the hazard level B of different areas in the subway.

[0117]

[0118] In the above formula, B i It represents the probability that the current area belongs to the i-th hazard level. The maximum value can be used to determine the hazard level of the current area.

[0119] For example, when B=(0, 0, 0.10, 0.76, 0.14) is obtained through analysis, it can be known that the probability of belonging to the fourth level of hazard level is the largest, so it can be determined that the hazard level of the current area is level four.

[0120] S105: Determine the hazard level of each area in the subway station based on the hazard level determination sequence of each area in the subway station.

[0121] In one possible implementation, when determining the hazard level of each area of ​​a subway station, firstly, the maximum probability hazard level determination value of each area of ​​the subway station is identified from the hazard level determination sequence of each area of ​​the subway station, and then the hazard level corresponding to the maximum probability hazard level determination value of each area of ​​the subway station is determined as the hazard level of the area.

[0122] Furthermore, after determining the hazard level of each area of ​​the subway station, first obtain color display parameters of different hazard levels, then determine the color display parameters corresponding to the hazard level of each area of ​​the subway station according to the color parameters of different hazard levels, then generate a color image of each area of ​​the subway station according to the color display parameters corresponding to the hazard level of each area of ​​the subway station, and finally send the color image of each area to the corresponding client for display.

[0123] For example, the results of the hazard levels of different areas of the subway are displayed on the front end, using different colors to distinguish the hazard levels. Red represents the highest hazard level, yellow is second, blue is third, and green represents the lowest hazard level.

[0124] In an embodiment of the present application, when the pollutant hazard level determination device receives multiple detection information sent by multiple detectors from each area of ​​the subway station, it first issues an alarm, then calculates the parameter values ​​of multiple determination indicators based on the multiple detection information, then loads multiple membership functions of each of the multiple determination indicators, and constructs a hazard level determination matrix based on the multiple membership functions and the corresponding parameter values, then loads the weight of each determination indicator, and multiplies the weight of each determination indicator with the hazard level determination matrix to generate a hazard level determination sequence for each area of ​​the subway station, and finally determines the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station. Since the present application determines the hazard level of each area of ​​the subway station by loading multiple membership functions and weights of each determination indicator, and calculating the hazard level determination value in combination with the specific parameter value of each determination indicator, it can also provide support for evacuation measures in different areas of the subway station based on the hazard level of each area of ​​the subway station, thereby improving the subway's emergency response capabilities and safety assurance levels.

[0125] The following are embodiments of the device of the present invention, which can be used to implement the method embodiments of the present invention. For details not disclosed in the device embodiments of the present invention, please refer to the method embodiments of the present invention.

[0126] See also Figure 2 , which shows a schematic diagram of the structure of a pollutant hazard level determination device provided by an exemplary embodiment of the present invention. The pollutant hazard level determination device can be implemented as all or part of a terminal through software, hardware, or a combination of both. The device 1 includes a detection information receiving module 10, a parameter value calculation module 20, a hazard level judgment matrix construction module 30, a hazard level judgment value generation module 40, and a hazard level determination module 50.

[0127] The detection information receiving module 10 is used to generate alarm information for early warning when receiving various detection information sent by various detectors in each area of ​​the subway station;

[0128] A parameter value calculation module 20, used to calculate parameter values ​​of multiple determination indicators according to multiple detection information;

[0129] The hazard level judgment matrix construction module 30 is used to load the membership function of each of the multiple judgment indicators at each hazard level, and construct the hazard level judgment matrix according to the parameter value of each judgment indicator and its membership function at each hazard level;

[0130] The hazard level judgment value generating module 40 is used to load the weight of each judgment index, and multiply the weight of each judgment index by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station;

[0131] The hazard level determination module 50 is used to determine the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station.

[0132] It should be noted that the pollutant hazard level determination device provided in the above embodiment only uses the division of the above functional modules as an example when executing the pollutant hazard level determination method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the pollutant hazard level determination device provided in the above embodiment and the pollutant hazard level determination method embodiment belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0133] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0134] In an embodiment of the present application, when the pollutant hazard level determination device receives multiple detection information sent by multiple detectors from each area of ​​the subway station, it first issues an alarm, then calculates the parameter values ​​of multiple determination indicators based on the multiple detection information, then loads multiple membership functions of each of the multiple determination indicators, and constructs a hazard level determination matrix based on the multiple membership functions and the corresponding parameter values, then loads the weight of each determination indicator, and multiplies the weight of each determination indicator with the hazard level determination matrix to generate a hazard level determination sequence for each area of ​​the subway station, and finally determines the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station. Since the present application determines the hazard level of each area of ​​the subway station by loading multiple membership functions and weights of each determination indicator, and calculating the hazard level determination value in combination with the specific parameter value of each determination indicator, it can also provide support for evacuation measures in different areas of the subway station based on the hazard level of each area of ​​the subway station, thereby improving the subway's emergency response capabilities and safety assurance levels.

[0135] The present invention also provides a computer-readable medium on which program instructions are stored. When the program instructions are executed by a processor, the methods for determining the hazard level of pollutants provided by the above-mentioned various method embodiments are implemented.

[0136] The present invention also provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the methods for determining the hazard level of pollutants in the above-mentioned various method embodiments.

[0137] See also Figure 3 , which is a schematic diagram of the structure of a terminal provided in an embodiment of the present application. Figure 3 As shown, the terminal 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0138] The communication bus 1002 is used to realize the connection and communication between these components.

[0139] The user interface 1003 may include a display screen (Display) and a camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.

[0140] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0141] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts of the entire electronic device 1000, and executes various functions and processes data of the electronic device 1000 by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0142] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM), and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally also be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a pollutant hazard level determination application program.

[0143] exist Figure 3 In the terminal 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 1001 can be used to call the pollutant hazard level determination application stored in the memory 1005, and specifically perform the following operations:

[0144] When receiving various detection information sent by various detectors in each area of ​​the subway station, an alarm message is generated for early warning;

[0145] Calculate parameter values ​​of multiple determination indicators based on multiple detection information;

[0146] Loading the membership function of each of the multiple determination indicators at each hazard level, and constructing a hazard level judgment matrix according to the parameter value of each determination indicator and its membership function at each hazard level;

[0147] Loading the weight of each judgment indicator, and multiplying the weight of each judgment indicator by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station;

[0148] The hazard level of each area of ​​the subway station is determined based on the hazard level determination sequence of each area of ​​the subway station.

[0149] In one embodiment, the processor 1001 further performs the following operations:

[0150] Get color display parameters for different hazard levels;

[0151] Determining, according to the color parameters of the different hazard levels, a color display parameter corresponding to the hazard level of each area of ​​the subway station;

[0152] generating a color image of each area of ​​the subway station according to the color display parameters corresponding to the hazard level of each area of ​​the subway station;

[0153] The color image of each area is sent to the corresponding client for display.

[0154] In one embodiment, when the processor 1001 determines the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station, the processor 1001 specifically performs the following operations:

[0155] Identifying the maximum probability hazard level determination value of each area of ​​the subway station from the hazard level determination sequence of each area of ​​the subway station;

[0156] The hazard level corresponding to the maximum probability hazard level determination value of each area of ​​the subway station is determined as the hazard level of the area.

[0157] In one embodiment, when the processor 1001 constructs a hazard level judgment matrix according to the parameter value of each judgment indicator and its membership function at each hazard level, the processor 1001 specifically performs the following operations:

[0158] Calculating the parameter value of each determination index with its corresponding membership function one by one to generate a membership sequence of each determination index;

[0159] The membership degree sequence of each judgment index is used as a row of matrix elements to generate multiple rows of matrix elements;

[0160] A hazard level judgment matrix is ​​constructed based on multiple rows of matrix elements.

[0161] In an embodiment of the present application, when the pollutant hazard level determination device receives multiple detection information sent by multiple detectors from each area of ​​the subway station, it first issues an alarm, then calculates the parameter values ​​of multiple determination indicators based on the multiple detection information, then loads multiple membership functions of each of the multiple determination indicators, and constructs a hazard level determination matrix based on the multiple membership functions and the corresponding parameter values, then loads the weight of each determination indicator, and multiplies the weight of each determination indicator with the hazard level determination matrix to generate a hazard level determination sequence for each area of ​​the subway station, and finally determines the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station. Since the present application determines the hazard level of each area of ​​the subway station by loading multiple membership functions and weights of each determination indicator, and calculating the hazard level determination value in combination with the specific parameter value of each determination indicator, it can also provide support for evacuation measures in different areas of the subway station based on the hazard level of each area of ​​the subway station, thereby improving the subway's emergency response capabilities and safety assurance levels.

[0162] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program for determining the hazard level of pollutants can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0163] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A method for determining the hazard level of pollutants, characterized in that: The method comprises: When receiving various detection information sent by various detectors in each area of ​​the subway station, an alarm message is generated for early warning; Calculating parameter values ​​of multiple determination indicators based on the multiple detection information, wherein the multiple determination indicators include acute toxicity category, skin damage category, eye damage category, respiratory sensitization category, flammable and explosive category, pollutant concentration, passenger flow density, and passenger flow rate per unit width; the multiple determination indicators are determined based on influencing factors that can reflect the hazard levels of different areas of the subway; Loading the membership function of each of the multiple determination indicators at each hazard level, and constructing a hazard level judgment matrix according to the parameter value of each determination indicator and its membership function at each hazard level; Loading the weight of each judgment indicator, and multiplying the weight of each judgment indicator by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station; The hazard level of each area of ​​the subway station is determined based on the hazard level determination sequence of each area of ​​the subway station.

2. The method according to claim 1, characterized in that The method further comprises: Get color display parameters for different hazard levels; Determining, from the color display parameters of the different hazard levels, a color display parameter corresponding to the hazard level of each area of ​​the subway station; generating a color image of each area of ​​the subway station according to the color display parameters corresponding to the hazard level of each area of ​​the subway station; The color image of each area is sent to the corresponding client for display.

3. The method according to claim 1, characterized in that The determining the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station includes: Identifying the maximum probability hazard level determination value of each area of ​​the subway station from the hazard level determination sequence of each area of ​​the subway station; The hazard level corresponding to the maximum probability hazard level determination value of each area of ​​the subway station is determined as the hazard level of the area.

4. The method according to claim 1, characterized in that: The step of constructing a hazard level judgment matrix according to the parameter value of each judgment indicator and its membership function at each hazard level includes: According to the parameter value of each determination indicator and the membership function, the membership of each determination indicator to each hazard level is calculated, and a membership sequence of each determination indicator to each hazard level is generated; Taking the membership degree sequence of each determination index as a row of matrix elements, generating multiple rows of matrix elements; A hazard level judgment matrix is ​​constructed based on the multiple rows of matrix elements.

5. The method according to claim 1, characterized in that The weights of multiple judgment indicators are generated according to the following steps, including: S401 determining a plurality of determination indicators related to the hazard level; S402: Determine the relative importance ranking of each of the plurality of determination indicators, and construct a priority relationship matrix based on the order of importance and a scaling method; S403 uses the square root method to calculate the initial sorting vector of the priority relationship matrix; S404: calculating the maximum characteristic root of the initial sorting vector, and calculating the consistency ratio of the initial sorting vector according to the maximum characteristic root; S405 determining whether the initial sorting vector is the weight of each of the multiple determination indicators based on whether the consistency ratio satisfies the consistency check; S406: If yes, determine the initial sorting vector as the weights of each of the multiple determination indicators.

6. The method according to claim 5, characterized in that The determining whether the initial sorting vector is the weight of each of the multiple determination indicators based on whether the consistency ratio satisfies the consistency check includes: When the consistency ratio is less than or equal to a preset threshold, it is determined that the consistency check is satisfied, and the weights of the multiple determination indicators are determined in the initial sorting vector; When the consistency ratio is greater than a preset threshold, it is determined that the consistency check is not satisfied, and steps S402-S405 are continued until the consistency ratio is less than or equal to the preset threshold, and the initial sorting vector that satisfies the consistency check requirement is determined as the weight of each of the multiple determination indicators.

7. The method according to claim 1, characterized in that The following steps are followed to generate multiple membership functions of each of the multiple judgment indicators at each hazard level, including: Acquiring historical data of the multiple detectors within a preset period; Acquire historical data corresponding to each determination indicator from the historical data; Determine, based on the historical data corresponding to each of the determination indicators, the threshold value of each of the determination indicators belonging to each hazard level; According to the threshold value of each determination indicator belonging to each hazard level, a plurality of membership functions of each determination indicator under each hazard level are constructed.

8. The method according to claim 1, characterized in that The following steps are used to determine the gas concentration in an area, including: Determine the preset three-dimensional detection interval corresponding to each gas detector in the three-dimensional space of the subway; Using a K-means clustering algorithm to perform clustering calculation on the three-dimensional detection interval to generate n interval division results of the subway three-dimensional terrain space; The concentration of each type of gas in each of the intervals is calculated, and finally the concentration is weighted to generate the gas concentration of each interval.

9. A device for determining the hazard level of pollutants, characterized in that: The device comprises: A detection information receiving module is used to generate alarm information for early warning when receiving multiple detection information sent by multiple detectors in each area of ​​the subway station; a parameter value calculation module, used to calculate parameter values ​​of multiple determination indicators according to the multiple detection information, wherein the multiple determination indicators include acute toxicity category, skin damage category, eye damage category, respiratory sensitization category, flammable and explosive category, pollutant concentration, passenger flow density, and passenger flow cross-sectional flow rate per unit width; the multiple determination indicators are determined based on influencing factors that can reflect the hazard level of different areas of the subway; A hazard level judgment matrix construction module is used to load the membership function of each of the multiple judgment indicators at each hazard level, and construct a hazard level judgment matrix according to the parameter value of each judgment indicator and its membership function at each hazard level; A hazard level judgment value generation module is used to load the weight of each judgment index, and multiply the weight of each judgment index by the hazard level judgment matrix to generate a hazard level judgment sequence for each area of ​​the subway station; The hazard level determination module is used to determine the hazard level of each area of ​​the subway station based on the hazard level determination sequence of each area of ​​the subway station.

10. A terminal, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps as described in any one of claims 1-8.

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