A method and device for auxiliary analysis of dangerous events in closed spaces

Abstract

The present invention relates to a closed space dangerous event auxiliary analysis method and device, the method comprising: obtaining dangerous individual information corresponding to multiple historical dangerous event information; obtaining information of individuals to be analyzed, calculating the similarity between the information of the individuals to be analyzed and the dangerous individual information corresponding to the multiple historical dangerous event information, obtaining a similarity collection, in which the dangerous individual information corresponding to the multiple historical dangerous event information is arranged in order of similarity from high to low; based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection, determining whether the individual to be analyzed has a risk of a dangerous event. The present invention realizes the analysis of possible dangerous events of individuals to be analyzed through the behavioral characteristics and development trends of dangerous individuals, thereby improving the safety of closed space management.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an auxiliary analysis method and device for dangerous events in a closed space. Background Art

[0002] Although the actions and behaviors of individuals in a closed space are regulated and constrained, the behavior of each individual in the closed space still conforms to the normal behavioral characteristics and development trends. Before a dangerous event occurs, most individuals will be affected by the outside world and produce some preliminary behaviors. For example, when different mice in a closed space may perform dangerous behaviors, the dangerous behavior characteristics of different individuals are not the same, but they are within the basic development trend. For example, in closed places such as prisons and drug rehabilitation centers, different individuals will show different dangerous behaviors due to differences in thinking, living habits, cognition, etc. For example, in places where livestock such as pigs, sheep, and chickens are kept, different dangerous behaviors will occur.

[0003] Therefore, how to analyze the dangerous events that may occur to the individuals to be analyzed through the behavioral characteristics and development trends of dangerous individuals has become an urgent problem that needs to be solved. Summary of the invention

[0004] In view of this, it is necessary to provide a closed space dangerous event auxiliary analysis method and device to solve the current technical problem that it is difficult to analyze the dangerous events that may occur to the individual to be analyzed through the behavioral characteristics and development trends of the dangerous individual.

[0005] In order to achieve the above object, the present invention provides an auxiliary analysis method for dangerous events in a closed space, comprising:

[0006] Obtain dangerous individual information corresponding to multiple historical dangerous event information;

[0007] Acquire information of an individual to be analyzed, calculate similarity between the information of the individual to be analyzed and dangerous individual information corresponding to the plurality of historical dangerous event information, and obtain a similarity collection, in which the dangerous individual information corresponding to the plurality of historical dangerous event information is arranged in descending order of similarity;

[0008] Based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection, it is determined whether the individual to be analyzed has the risk of a dangerous event occurring.

[0009] Furthermore, the step of obtaining dangerous individual information corresponding to multiple pieces of historical dangerous event information includes:

[0010] The dangerous individual information corresponding to multiple pieces of historical dangerous event information is obtained from the closed space business management system, wherein the dangerous individual information corresponding to the multiple pieces of historical dangerous event information includes dangerous event category, daily event category, recording time period and dangerous individual number.

[0011] Furthermore, the dangerous individual information corresponding to the plurality of historical dangerous event information is expressed based on the following formula:

[0012] M=∑∑∑∑(A[i][j][k][l])

[0013] Among them, M represents the dangerous individual information corresponding to the multiple historical dangerous event information, i represents the dangerous event category, j represents the daily event category, k represents the recording time period, l represents the dangerous individual number, and A represents the number of times the dangerous individual l has daily event j within the recording time period k of the dangerous event i.

[0014] Furthermore, the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the plurality of historical dangerous event information is calculated based on the following formula:

[0015]

[0016] Where x represents the information of the individual to be analyzed, y represents the dangerous individual information corresponding to any piece of historical dangerous event information, d(x,y) represents the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to any piece of historical dangerous event information, x n represents the information related to daily event n in the information of the individual to be analyzed, y n Represents information related to daily event n in the dangerous individual information corresponding to any one of the historical dangerous event information.

[0017] Furthermore, the length of the recording time period is directly proportional to the accuracy of determining whether the individual to be analyzed has a risk of a dangerous event occurring.

[0018] Furthermore, the dangerous individual information corresponding to the plurality of pieces of historical dangerous event information is acquired from a closed space business management system of a plurality of closed spaces.

[0019] Further, the determining whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection includes:

[0020] Determine whether the frequency of the predicted dangerous event is greater than a preset threshold, the predicted dangerous event being the dangerous event with the highest frequency among the dangerous individual information corresponding to the first preset number of historical dangerous event information in the similarity collection;

[0021] When the frequency of the predicted dangerous event is greater than a preset threshold, determining that the individual to be analyzed has a risk of the predicted dangerous event occurring;

[0022] When the frequency of the predicted dangerous event is less than or equal to a preset threshold, it is determined that the individual to be analyzed does not have a risk of the predicted dangerous event occurring.

[0023] The present invention also provides a closed space dangerous event auxiliary analysis device, comprising:

[0024] The first acquisition module is used to acquire dangerous individual information corresponding to multiple pieces of historical dangerous event information;

[0025] A second acquisition module is used to acquire information of an individual to be analyzed, calculate the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the multiple pieces of historical dangerous event information, and obtain a similarity collection, in which the dangerous individual information corresponding to the multiple pieces of historical dangerous event information are arranged in descending order of similarity;

[0026] The determination module is used to determine whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the previously preset number of historical dangerous event information in the similarity collection.

[0027] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the closed space dangerous event auxiliary analysis method as described above is implemented.

[0028] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the closed space dangerous event auxiliary analysis method as described above is implemented.

[0029] Compared with the prior art, the beneficial effects of the present invention include: by calculating the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to multiple historical dangerous event information, determining whether the individual to be analyzed is at risk of a dangerous event based on the dangerous individual information corresponding to the historical dangerous event information with greater similarity, thereby realizing the analysis of possible dangerous events that may occur to the individual to be analyzed through the behavioral characteristics and development trends of the dangerous individual, thereby improving the safety of closed space management. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A schematic diagram of a flow chart of an embodiment of a closed space dangerous event auxiliary analysis method provided by the present invention;

[0032] Figure 2 A schematic diagram of the structure of an embodiment of an auxiliary analysis device for dangerous events in a closed space provided by the present invention;

[0033] Figure 3 A schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0035] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0036] In the description of the present invention, reference to an "embodiment" means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive of other embodiments. It is explicitly and implicitly understood by those skilled in the art that the described embodiments may be combined with other embodiments.

[0037] As a special space, individuals in closed spaces are often under strict control. Dangerous individuals in closed spaces often have some dangerous events, which affects the safety of closed space management. At present, there is no good way to judge whether dangerous events will occur in the individuals to be analyzed in closed spaces.

[0038] Based on the continuous development of informatization, the present invention collects and integrates information data in closed spaces, associates them with dangerous events that have occurred, and combines learning algorithms to establish possible associations, thereby constructing a set of multi-dimensional data models, using a huge sample library of individual and event association models to compare existing dangerous individual information with the association model sample library. The sample library has a wide coverage and can obtain multiple similarity results. Business users can make judgments and analyses based on the result data, and perform reverse reasoning based on the risk hidden danger events that have occurred, forming a multi-dimensional data analysis model, providing users with multi-dimensional references, and assisting business decision-making.

[0039] The specific embodiments are described in detail below:

[0040] The present invention provides a closed space dangerous event auxiliary analysis method, combined with Figure 1 Come and see, Figure 1 The flowchart of an embodiment of the auxiliary analysis method for dangerous events in a closed space provided by the present invention includes steps S101 to S103, wherein:

[0041] In step S101, dangerous individual information corresponding to multiple pieces of historical dangerous event information is obtained;

[0042] In step S102, the information of the individual to be analyzed is obtained, and the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the multiple historical dangerous event information is calculated to obtain a similarity collection, in which the dangerous individual information corresponding to the multiple historical dangerous event information is arranged in order of similarity from high to low;

[0043] In step S103, based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection, it is determined whether the individual to be analyzed has the risk of a dangerous event occurring.

[0044] In an embodiment of the present invention, by calculating the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to multiple historical dangerous event information, it is determined whether the individual to be analyzed is at risk of a dangerous event based on the dangerous individual information corresponding to the historical dangerous event information with greater similarity. This allows the analysis of possible dangerous events that may occur to the individual to be analyzed through the behavioral characteristics and development trends of the dangerous individual, thereby improving the safety of closed space management.

[0045] In a specific embodiment of the present invention, first, dangerous individual information corresponding to multiple historical dangerous event information can be obtained. Dangerous events can be events that affect the management of closed spaces or other individuals in the closed space. The closed space is a space in a certain area where multiple individuals are centrally managed.

[0046] After obtaining dangerous individual information corresponding to multiple historical dangerous event information, the information of the individual to be analyzed can also be obtained, and then the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to multiple historical dangerous event information is calculated to obtain a similarity collection.

[0047] Based on the dangerous individual information corresponding to the first preset number (e.g., the first 10 or the first 50) of historical dangerous event information in the similarity collection, it can be determined whether the individual to be analyzed has a risk of a dangerous event. The preset number can be set according to the accuracy required for determining whether the individual to be analyzed has a risk of a dangerous event. The larger the value of the preset number is set, the higher the accuracy of determining whether the individual to be analyzed has a risk of a dangerous event.

[0048] As a preferred embodiment, the step of obtaining dangerous individual information corresponding to multiple pieces of historical dangerous event information includes:

[0049] The dangerous individual information corresponding to multiple pieces of historical dangerous event information is obtained from the closed space business management system, wherein the dangerous individual information corresponding to the multiple pieces of historical dangerous event information includes dangerous event category, daily event category, recording time period and dangerous individual number.

[0050] In a specific embodiment of the present invention, when obtaining dangerous individual information corresponding to multiple historical dangerous event information, it can be obtained from the closed space business management system, and the dangerous individual information corresponding to multiple historical dangerous event information may include dangerous event category, daily event category, recording time period and dangerous individual number, etc. For example, there are multiple mice in the closed space, dangerous events may include fasting of mice, biting of the same kind, etc., daily events may include feeding, injection of experimental drugs, etc., the recording time period may be one week, one month, three months, etc., and the dangerous individual number is the number of each mouse in the closed space.

[0051] As a preferred embodiment, the dangerous individual information corresponding to the plurality of historical dangerous event information is expressed based on the following formula:

[0052] M=∑∑∑∑(A[i][j][k][l])

[0053] Among them, M represents the dangerous individual information corresponding to the multiple historical dangerous event information, i represents the dangerous event category, j represents the daily event category, k represents the recording time period, l represents the dangerous individual number, and A represents the number of times the dangerous individual l has daily event j within the recording time period k of the dangerous event i.

[0054] In a specific embodiment of the present invention, the above formula can be used to represent the dangerous individual information corresponding to multiple pieces of historical dangerous event information.

[0055] As a preferred embodiment, the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the multiple pieces of historical dangerous event information is calculated based on the following formula:

[0056]

[0057] Where x represents the information of the individual to be analyzed, y represents the dangerous individual information corresponding to any piece of historical dangerous event information, d(x,y) represents the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to any piece of historical dangerous event information, x n represents the information related to daily event n in the information of the individual to be analyzed, y n Represents information related to daily event n in the dangerous individual information corresponding to any one of the historical dangerous event information.

[0058] In a specific embodiment of the present invention, the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to any piece of historical dangerous event information can be calculated according to the above formula.

[0059] As a preferred embodiment, the length of the recording time period is directly proportional to the accuracy of determining whether the individual to be analyzed has a risk of a dangerous event occurring.

[0060] In a specific embodiment of the present invention, the length of the recording time period of the dangerous individual information corresponding to the historical dangerous event information can be flexibly adjusted, such as three months, six months or one year. The longer the length of the recording time period, the higher the accuracy of determining whether the individual to be analyzed is at risk of a dangerous event. For example, when recording the historical dangerous time information of multiple mice in a closed space, the length of the recording time period can be adjusted as needed, such as one month, three months, six months, one year, etc. The accuracy of determining whether the mice are at risk of a dangerous event when the recording time period is one year is higher than the accuracy of determining whether the mice are at risk of a dangerous event when the recording time period is three months.

[0061] As a preferred embodiment, the dangerous individual information corresponding to the plurality of historical dangerous event information is acquired from a closed space business management system of a plurality of closed spaces.

[0062] In a specific embodiment of the present invention, dangerous individual information corresponding to multiple pieces of historical dangerous event information can be obtained from closed space business management systems of multiple closed spaces, thereby expanding the comprehensiveness of the sample.

[0063] As a preferred embodiment, the determining whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection includes:

[0064] Determine whether the frequency of the predicted dangerous event is greater than a preset threshold, the predicted dangerous event being the dangerous event with the highest frequency among the dangerous individual information corresponding to the first preset number of historical dangerous event information in the similarity collection;

[0065] When the frequency of the predicted dangerous event is greater than a preset threshold, determining that the individual to be analyzed has a risk of the predicted dangerous event occurring;

[0066] When the frequency of the predicted dangerous event is less than or equal to a preset threshold, it is determined that the individual to be analyzed does not have a risk of the predicted dangerous event occurring.

[0067] In a specific embodiment of the present invention, after obtaining the dangerous individual information corresponding to the first preset number of historical dangerous event information in the similarity collection, the dangerous event with the highest frequency in the dangerous individual information corresponding to the first preset number of historical dangerous event information in the similarity collection can be determined first, and then it can be determined whether the frequency of the dangerous event is greater than a preset threshold. The preset threshold can be set to half or one-quarter of the preset number value. The larger the preset threshold is set, the higher the accuracy of determining whether the individual to be analyzed has the risk of a dangerous event.

[0068] If the frequency of the dangerous event is greater than the threshold, it is determined that the individual to be analyzed has the risk of the dangerous event. If the frequency of the dangerous event is less than or equal to the threshold, it is determined that the individual to be analyzed does not have the risk of the dangerous event.

[0069] The following is a specific application scenario to better illustrate the technical solution of the present invention:

[0070] The present invention establishes a set of multi-dimensional data analysis models, based on which the information of individuals and events is analyzed and processed to form a sample model library. By forming a large number of model libraries and performing similarity correlation analysis and comparison with actual individual behavior data, multiple analysis and comparison results can be provided, and then summarized from the results. The analysis results provided by the present invention will be multiple similarity values, which can extract common attributes and help business operators to make analysis and judgments. Different from the analysis of a single dimension, the present invention can provide risk ranking after accumulating the similarity. The larger the similarity value, the greater the possible risk. The higher the number and value of the same type of event being matched, the greater the impact of a certain risk event on such events. For example, if the behavioral characteristics of a certain individual to be analyzed are highly similar to multiple sample data in the past, and the personnel involved in the multiple sample data have all undergone separate management measures, then the current behavior of the individual to be analyzed meets the previous behavioral characteristics of some dangerous behaviors, and it is recommended that the management personnel may need to manage this individual to be analyzed separately to prevent and reduce the occurrence of risks.

[0071] Specifically, the specific steps of implementing the closed space dangerous event auxiliary analysis method provided by the present invention in a drug rehabilitation center are as follows:

[0072] 1. Collect statistics on various incidents involving drug addicts within a certain period of time, take the people involved in the incidents and the incidents as the basic points, and classify them in order according to the events and time to form a sequence table.

[0073] 2. The information of the drug rehabilitation personnel to be managed is also formed into a sequence list, and similarity calculation is performed with the above sequence list to obtain a similarity collection.

[0074] 3. Sort the obtained similarity collection from large to small according to the similarity value. The top 10 or top 50 can be selected.

[0075] 4. Perform attribute analysis on the top 10 or top 50 sequence sets to obtain common attributes to assist in analyzing the occurrence of a dangerous event (such as fighting or disobeying orders) during a certain period of time or after a certain event among the drug addicts to be managed.

[0076] The present invention compares the events of each dangerous individual with the sample library (dangerous event) data for similarity. The similarity is no longer based on a single data value, but a comprehensive similarity is obtained by comprehensive analysis and calculation of a series of data, thereby expanding the value range of the similarity and reducing the subjectivity of empirical judgment, so as to more objectively reflect the facts.

[0077] In actual closed space business work, report-style data is easier to obtain, the content format is more unified, and it is more conducive to calculation and analysis. The number of samples in the sample library will affect the calculation results of similarity, so the present invention requires a certain amount of relatively standardized data accumulation to make the data performance more realistic.

[0078] The number of individuals in a single closed space is limited. In actual operation, the data of dangerous individuals in multiple closed spaces can be standardized to form a larger sample library. The huge sample library can better support calculation and analysis, and all sample libraries can be analyzed and calculated centrally. According to needs, the length of the sample library can be continuously extended to provide more and more comprehensive samples.

[0079] The embodiment of the present invention also provides a closed space dangerous event auxiliary analysis device, combined with Figure 2 Come and see, Figure 2 The structure diagram of an embodiment of the enclosed space dangerous event auxiliary analysis device provided by the present invention is as follows. The enclosed space dangerous event auxiliary analysis device 200 includes:

[0080] The first acquisition module 201 is used to acquire dangerous individual information corresponding to multiple pieces of historical dangerous event information;

[0081] The second acquisition module 202 is used to acquire information of the individual to be analyzed, calculate the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the multiple historical dangerous event information, and obtain a similarity collection, in which the dangerous individual information corresponding to the multiple historical dangerous event information is arranged in descending order according to the similarity;

[0082] The determination module 203 is used to determine whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection.

[0083] The more specific implementation methods of each module of the closed space dangerous event auxiliary analysis device can be found in the description of the above-mentioned closed space dangerous event auxiliary analysis method, and have similar beneficial effects, which will not be repeated here.

[0084] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method for auxiliary analysis of dangerous events in closed spaces as described above is implemented.

[0085] Generally speaking, the computer instructions for implementing the method of the present invention can be carried by any combination of one or more computer-readable storage media. Non-transitory computer-readable storage media can include any computer-readable media except for the signal itself that is temporarily propagating.

[0086] Computer-readable storage media may be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0087] Computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages, in particular, Python suitable for neural network computing and platform frameworks based on TensorFlow, PyTorch, etc. can be used. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0088] The embodiment of the present invention further provides an electronic device, Figure 3 Come and see, Figure 3 This is a structural diagram of an embodiment of an electronic device provided by the present invention. The electronic device 300 includes a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the processor 301 executes the program, the auxiliary analysis method for dangerous events in closed spaces as described above is implemented.

[0089] As a preferred embodiment, the electronic device 300 further includes a display 303 for displaying the processor 301 executing the closed space dangerous event auxiliary analysis method as described above.

[0090] Exemplarily, the computer program may be divided into one or more modules / units, one or more modules / units are stored in the memory 302, and are executed by the processor 301 to complete the present invention. One or more modules / units may be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device 300. For example, the computer program may be divided into the first acquisition module 201, the second acquisition module 202, and the determination module 203 in the above-mentioned embodiment, and the specific functions of each module are as described above, and are not described one by one here.

[0091] The electronic device 300 may be a desktop computer, a notebook, a palm computer or a smart phone with an adjustable camera module.

[0092] Among them, the processor 301 may be an integrated circuit chip with signal processing capabilities. The above-mentioned processor 301 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present invention can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0093] The memory 302 may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc. The memory 302 is used to store programs, and the processor 301 executes the program after receiving an execution instruction. The process definition method disclosed in any of the embodiments of the present invention may be applied to the processor 301 or implemented by the processor 301.

[0094] The display 303 may be an LCD display screen or an LED display screen, for example, a display screen on a mobile phone.

[0095] Understandably, Figure 3 The structure shown is only a schematic diagram of the structure of the electronic device 300. The electronic device 300 may also include Figure 3 More or fewer components as shown. Figure 3 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0096] The computer-readable storage medium and electronic device provided according to the above embodiments of the present invention can be implemented with reference to the specific description of the method for auxiliary analysis of dangerous events in closed spaces as described above according to the present invention, and have similar beneficial effects as the method for auxiliary analysis of dangerous events in closed spaces as described above, which will not be repeated here.

[0097] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0098] The present invention discloses an auxiliary analysis method and device for dangerous events in closed spaces. By calculating the similarity between the information of an individual to be analyzed and dangerous individual information corresponding to multiple historical dangerous event information, it is determined whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the historical dangerous event information with greater similarity. This achieves the analysis of possible dangerous events that may occur to the individual to be analyzed through the behavioral characteristics and development trends of the dangerous individual, thereby improving the safety of closed space management.

[0099] The technical solution of the present invention compares the events of each dangerous individual with the sample library (dangerous event) data for similarity. The similarity is no longer based on a single data value, but a comprehensive similarity is obtained by comprehensive analysis and calculation of a series of data, thereby expanding the value range of the similarity and reducing the subjectivity of empirical judgment, so as to more objectively reflect the facts.

[0100] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A closed space dangerous event auxiliary analysis method, characterized in that: include: Obtain dangerous individual information corresponding to multiple historical dangerous event information; Acquire information of an individual to be analyzed, calculate similarity between the information of the individual to be analyzed and dangerous individual information corresponding to the plurality of historical dangerous event information, and obtain a similarity collection, in which the dangerous individual information corresponding to the plurality of historical dangerous event information is arranged in descending order of similarity; Based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection, determining whether the individual to be analyzed has a risk of a dangerous event; The determining whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection includes: Determine whether the frequency of the predicted dangerous event is greater than a preset threshold, the predicted dangerous event being the dangerous event with the highest frequency among the dangerous individual information corresponding to the first preset number of historical dangerous event information in the similarity collection; When the frequency of the predicted dangerous event is greater than a preset threshold, determining that the individual to be analyzed has a risk of the predicted dangerous event occurring; When the frequency of the predicted dangerous event is less than or equal to a preset threshold, it is determined that the individual to be analyzed does not have a risk of the predicted dangerous event occurring.

2. The closed space dangerous event auxiliary analysis method according to claim 1 is characterized in that: The step of obtaining dangerous individual information corresponding to multiple pieces of historical dangerous event information includes: The dangerous individual information corresponding to multiple pieces of historical dangerous event information is obtained from the closed space business management system, wherein the dangerous individual information corresponding to the multiple pieces of historical dangerous event information includes dangerous event category, daily event category, recording time period and dangerous individual number.

3. The closed space dangerous event auxiliary analysis method according to claim 2 is characterized in that: The similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the plurality of historical dangerous event information is calculated based on the following formula: Wherein, x represents the information of the individual to be analyzed, and y represents the dangerous individual information corresponding to any piece of historical dangerous event information. represents the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to any one of the historical dangerous event information, represents the information related to daily event n in the information of the individual to be analyzed, Represents information related to daily event n in the dangerous individual information corresponding to any one of the historical dangerous event information.

4. The closed space dangerous event auxiliary analysis method according to claim 2 or 3, characterized in that: The length of the recording time period is directly proportional to the accuracy of determining whether the individual to be analyzed has a risk of a dangerous event occurring.

5. The closed space dangerous event auxiliary analysis method according to claim 2 or 3, characterized in that: The dangerous individual information corresponding to the plurality of pieces of historical dangerous event information is acquired from the closed space business management systems of the plurality of closed spaces.

6. A closed space dangerous event auxiliary analysis device, characterized in that: include: The first acquisition module is used to acquire dangerous individual information corresponding to multiple pieces of historical dangerous event information; A second acquisition module is used to acquire information of an individual to be analyzed, calculate the similarity between the information of the individual to be analyzed and the dangerous individual information corresponding to the multiple pieces of historical dangerous event information, and obtain a similarity collection, in which the dangerous individual information corresponding to the multiple pieces of historical dangerous event information are arranged in descending order of similarity; A determination module, configured to determine whether the individual to be analyzed has a risk of a dangerous event based on dangerous individual information corresponding to a preset number of historical dangerous event information in the similarity collection; The determining whether the individual to be analyzed has a risk of a dangerous event based on the dangerous individual information corresponding to the preset number of historical dangerous event information in the similarity collection includes: Determine whether the frequency of the predicted dangerous event is greater than a preset threshold, the predicted dangerous event being the dangerous event with the highest frequency among the dangerous individual information corresponding to the first preset number of historical dangerous event information in the similarity collection; When the frequency of the predicted dangerous event is greater than a preset threshold, determining that the individual to be analyzed has a risk of the predicted dangerous event occurring; When the frequency of the predicted dangerous event is less than or equal to a preset threshold, it is determined that the individual to be analyzed does not have a risk of the predicted dangerous event occurring.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the closed space dangerous event auxiliary analysis method according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for auxiliary analysis of dangerous events in closed spaces as described in any one of claims 1 to 5 is implemented.

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