CN115409375A - Security accident monitoring method, device, equipment and readable storage medium - Google Patents
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Abstract
The application provides a safety accident monitoring method, a safety accident monitoring device, a safety accident monitoring equipment and a readable storage medium, wherein first target data uploaded to a server by a target enterprise can be obtained, and each data parameter in the first target data can be analyzed according to the grade coefficient of each work task to obtain the analysis result of each data parameter; determining a production safety risk coefficient of a target enterprise according to the analysis result of each data parameter; judging whether the target enterprise meets preset early warning conditions or not according to the production safety risk coefficient of the target enterprise; and if so, sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise. According to the method and the device, potential safety accidents can be found and early warning signals can be sent out in time by analyzing the data of the relevant production safety of the target enterprise, the occurrence of the safety accidents can be restrained, the economic benefits of the target enterprise can be protected, and unnecessary loss can be reduced.
Description
Technical Field
The present application relates to the field of security management technologies, and in particular, to a method, an apparatus, a device, and a readable storage medium for monitoring a security incident.
Background
With the development of science and technology, the productivity of a plurality of enterprises is gradually improved, and after the production level of the enterprises is increased, the requirements of the enterprises on the production safety of the enterprises are gradually improved.
In the production process, in order to further complete the production potential safety hazard investigation work of enterprises and prevent production safety accidents, a plurality of enterprises pay more attention to production safety gradually, and establish a safety production standardized management system, a safety risk management and control system, a potential safety hazard investigation and treatment system, an emergency management system and an accident management system gradually. However, at present, the production safety management systems of many enterprises are not mature, and potential safety hazards of the enterprises cannot be found in time to avoid safety accidents. Therefore, the actual production safety condition of the enterprise needs to be monitored in real time, so that the enterprise can be helped to find potential safety hazards and occurrence of safety production accidents in time, and the enterprise can be helped to deal with the potential safety hazards and occurrence of safety production accidents in time.
Disclosure of Invention
In view of the above, the present application provides a method, an apparatus, a device and a readable storage medium for monitoring a security incident, which are used to solve at least one of the above technical drawbacks of security incident monitoring in the prior art.
A security incident monitoring method comprising:
acquiring first target data uploaded to a server by a target enterprise, wherein the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task;
analyzing each data parameter in the first target data according to the grade coefficient of each work task to obtain an analysis result of each data parameter;
determining the production safety risk coefficient of the target enterprise according to the analysis result of each data parameter;
judging whether the target enterprise meets preset early warning conditions or not according to the production safety risk coefficient of the target enterprise;
and if the target enterprise meets the preset early warning condition, sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise.
Preferably, the determining the production safety risk coefficient of the target enterprise according to the analysis result of each data parameter includes:
according to the analysis result of each data parameter, scoring the work task to which each data parameter belongs to obtain the scoring result of the set work task corresponding to each production safety index;
carrying out weighted calculation on the scoring result of each work task corresponding to each production safety index to obtain the scoring result of each production safety index;
and according to the grading result of each production safety index, carrying out weighted calculation on the risk coefficient of each production safety index of the target enterprise to obtain the production safety risk coefficient of the target enterprise.
Preferably, the method further comprises:
acquiring first monitoring data of monitoring equipment of the target enterprise in real time, wherein the first monitoring data comprises monitoring data of actual production conditions of the target enterprise;
determining whether the first monitoring data comprises safety accident data related to the target enterprise;
and if the first monitoring data comprise safety accident data related to the target enterprise, determining that a safety accident occurs in the target enterprise, acquiring map data of the geographical position of the target enterprise, and analyzing the first monitoring data to obtain an accident analysis result of the target enterprise, wherein the accident analysis result of the target enterprise comprises an accident type and an accident spread range of the target enterprise.
Preferably, the method further comprises:
determining a risk coefficient of the target enterprise according to the accident analysis result of the target enterprise;
and sending an early warning signal corresponding to the danger coefficient of the target enterprise to the target enterprise, a rescue unit where the target enterprise is located and a related supervision department where the target enterprise belongs according to the danger coefficient of the target enterprise, the accident analysis result of the target enterprise and the map data of the geographic position of the target enterprise.
Preferably, the determining whether the first monitoring data includes incident data related to the target enterprise includes:
if the temperature, humidity or pressure value of the target enterprise exceeds a corresponding safety threshold value, the first monitoring data is determined to comprise safety accident data related to the target enterprise;
and/or the presence of a gas in the atmosphere,
if the first monitoring data comprises the alarm signal data of the target enterprise, determining that the first monitoring data comprises safety accident data related to the target enterprise.
Preferably, the analyzing the first monitoring data to obtain the accident analysis result of the target enterprise includes:
analyzing the first monitoring data to determine the accident type of the target enterprise;
and determining the accident spread range of the target enterprise according to the accident type of the target enterprise, and taking the accident type and the accident spread range of the target enterprise as an accident analysis result of the target enterprise.
Preferably, the determining, according to the production safety risk coefficient of the target enterprise, whether the target enterprise meets a preset early warning condition includes:
judging whether the production safety risk coefficient of the target enterprise reaches a risk coefficient corresponding to a risk early warning signal at the lowest risk level in a preset risk early warning signal relation table or not according to the production safety risk coefficient of the target enterprise and the preset risk early warning signal relation table;
and if so, determining that the target enterprise meets preset early warning conditions.
A security incident monitoring device comprising:
the system comprises a first data acquisition unit, a second data acquisition unit and a processing unit, wherein the first data acquisition unit is used for acquiring first target data uploaded to a server by a target enterprise, the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task;
the analysis unit is used for analyzing each data parameter in the first target data according to the grade coefficient of each work task to obtain an analysis result of each data parameter;
the first safety factor determining unit is used for determining a production safety risk coefficient of the target enterprise according to the analysis result of each data parameter;
the first judgment unit is used for judging whether the target enterprise meets preset early warning conditions or not according to the production safety risk coefficient of the target enterprise;
and the first early warning unit is used for sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise when the execution result of the first judging unit determines that the target enterprise meets the preset early warning condition.
A security incident monitoring device comprising:
one or more processors, and a memory;
the memory has stored therein computer readable instructions which, when executed by the one or more processors, carry out the steps of the security incident monitoring method of any of the preceding introductions.
A readable storage medium having computer readable instructions stored therein, which, when executed by one or more processors, cause the one or more processors to implement the steps of a security incident monitoring method as described in any of the preceding introductions.
According to the technical scheme, the method provided by the embodiment of the application can acquire first target data uploaded to a server by a target enterprise, wherein the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task; each work task is provided with different grade coefficients, and the condition of each work task can be known by analyzing the data parameters corresponding to each work task, so that each data parameter in the first target data can be analyzed according to the grade coefficient of each work task, and the analysis result of each data parameter can be obtained; after the analysis result of each data parameter is obtained, the production safety risk coefficient of the target enterprise can be further determined according to the analysis result of each data parameter; the different levels of production safety risk coefficients reflect different levels of production safety conditions of the target enterprise. In the practical application process, when the production safety risk coefficient of the target enterprise reaches a certain level, an early warning signal needs to be sent out. Therefore, after the production safety risk coefficient of the target enterprise is obtained, whether the target enterprise meets the preset early warning condition or not can be judged according to the production safety risk coefficient of the target enterprise; and if the target enterprise meets the preset early warning condition, sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise.
The method provided by the embodiment of the application can find potential safety accidents and send out early warning signals in time by analyzing the data of the relevant production safety of the target enterprise, is beneficial to restraining the safety accidents, is beneficial to protecting the economic benefits of the target enterprise, and reduces unnecessary loss.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the description below are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without inventive labor.
Fig. 1 is a flowchart illustrating a method for monitoring a security incident according to an embodiment of the present disclosure;
FIG. 2 is a schematic structural diagram of a security incident monitoring device according to an example of the present application;
fig. 3 is a block diagram of a hardware structure of a security accident monitoring apparatus according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
In view of the fact that most of the current security incident monitoring schemes are difficult to adapt to complicated and variable service types, the applicant researches a security incident monitoring scheme. According to the method and the device, potential safety accidents can be found and early warning signals can be sent out in time by analyzing the data of the relevant production safety of the target enterprise, the occurrence of the safety accidents can be restrained, the economic benefits of the target enterprise can be protected, and unnecessary loss can be reduced.
The methods provided by the embodiments of the present application are operational with numerous general purpose or special purpose computing device environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multi-processor apparatus, distributed computing environments that include any of the above devices or equipment, and the like.
The embodiment of the application provides a production safety monitoring method, which can be applied to various monitoring systems, and also can be applied to various computer terminals or intelligent terminals, and the execution main body of the method can be a processor or a server of the computer terminal or the intelligent terminal.
The following describes a flow of a security incident monitoring method according to an embodiment of the present application with reference to fig. 1, where the flow may include the following steps:
step S101, first target data uploaded to a server by a target enterprise is obtained, the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task.
Specifically, in the actual application process, the enterprise generally uploads some data related to the enterprise to the server for backup storage at regular intervals. So that the production operations of the enterprise can be analyzed based on the backed up saved data. The backup data stored by the enterprise in the server can feed back relevant conditions of the enterprise. The backup data uploaded to the server by the enterprise may include data of various information.
For example, the data uploaded to the server by the enterprise may include data related to production safety of the enterprise, business data related to sales of the enterprise, data related to tax declaration of the enterprise, and the like.
Therefore, if the production safety condition of the enterprise is required to be known, the backup data stored in the server by the enterprise can be acquired to analyze the production safety condition of the enterprise. Wherein the first target data may include a plurality of pieces of data. The first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task. For example, the first target data may include data related to production safety of the target enterprise, data related to sales business of the target enterprise, data related to tax declaration of the target enterprise, and the like.
Step S102, analyzing each data parameter in the first target data according to the grade coefficient of each work task to obtain an analysis result of each data parameter.
Specifically, in the actual application process, the industries of the target enterprises are different, the work tasks to be completed are also different, and the importance degree of each work task is different due to different contents of each work task, so that different work tasks correspond to different level coefficients, and the level coefficients of the work tasks represent the importance degree of the work tasks. The higher the ranking factor of a work task, the more important it is to characterize the work task.
For example, work tasks may be divided into critical tasks and non-critical tasks by importance.
The critical task may characterize the task that the enterprise must perform to complete production safety management work, such as equipping a fire suppression facility.
The non-critical task can represent the work task to be a task which can be selectively completed by the enterprise to do production safety management work, for example, to develop production safety lectures.
The work tasks corresponding to the production safety indexes of the target enterprise are different.
Therefore, by analyzing each of the work tasks, the situation of the respective data parameters in the first target data can be known. Therefore, each data parameter in the first target data can be analyzed according to the grade coefficient of each work task to obtain an analysis result of each data parameter, so that the analysis result can be used for analyzing the production safety condition of the target enterprise.
And S103, determining the production safety risk coefficient of the target enterprise according to the analysis result of each data parameter.
Specifically, as can be seen from the above description, the method provided in the embodiment of the present application may determine an analysis result of each data parameter by analyzing each data parameter in the first target data.
Because each data parameter corresponds to one work task, each production safety index correspondingly comprises at least one work task.
Therefore, after the analysis result of each data parameter is obtained, the production safety risk coefficient of the target enterprise can be determined according to the analysis result of each data parameter. So that whether the production safety condition of the target enterprise needs to be pre-warned can be determined through the production safety risk coefficient of the target enterprise.
And step S104, judging whether the target enterprise meets preset early warning conditions or not according to the production safety risk coefficient of the target enterprise.
Specifically, in the practical application process, different production safety risk coefficients indicate that the enterprise has different levels of risks. The early warning signals corresponding to different levels of danger are different.
For example, it may be set that the higher the production safety risk factor, the higher the level of its corresponding warning signal.
The early warning method is characterized in that different levels of early warning signals are set for different production safety risk coefficients, in the practical application process, early warning is carried out on not all levels of production safety risk coefficients, generally speaking, when the production safety risk coefficients of an enterprise reach preset early warning conditions, it is shown that safety accidents may be caused by the production safety conditions of the current enterprise, and early warning is needed. To remind the enterprise to make an amendment or rescue.
Therefore, after the production safety risk coefficient of the target enterprise is determined, whether the target enterprise meets the preset early warning condition or not can be judged according to the production safety risk coefficient of the target enterprise. If the target enterprise meets the preset early warning condition, step S105 may be executed.
And step S105, sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise.
Specifically, as can be seen from the above description, the method provided in this embodiment of the present application may determine whether the target enterprise meets a preset early warning condition according to the production safety risk coefficient of the target enterprise, and if it is determined that the target enterprise meets the preset early warning condition, it indicates that a safety accident may be caused by the production safety condition of the current enterprise, and an early warning signal corresponding to the production safety risk coefficient of the target enterprise may be sent to the target enterprise if an early warning needs to be performed.
According to the technical scheme, the method provided by the embodiment of the application can find potential safety accidents and send early warning signals in time by analyzing the data of the related production safety of the target enterprise, so that the method is beneficial to restraining the safety accidents, protecting the economic benefits of the target enterprise and reducing unnecessary loss.
As can be seen from the above description, the method provided in this embodiment of the present application may determine the production safety risk coefficient of the target enterprise according to the analysis result of each of the data parameters, and then introduces the process, where the process may include the following steps:
step S201, scoring the work task to which each data parameter belongs according to the analysis result of each data parameter, and obtaining a scoring result of the work task corresponding to each set production safety index.
Specifically, as can be seen from the above description, the method provided in the embodiment of the present application may determine an analysis result of each data parameter, where each data parameter corresponds to one work task, each work task corresponds to one production safety index, and each production safety index includes at least one work task. In order to better understand the completion of the work task corresponding to each production safety index of the target enterprise and to better characterize the completion of the work task corresponding to each data parameter, the work task to which each data parameter belongs may be scored according to the analysis result of each data parameter, so as to obtain the scoring result of the set work task corresponding to each production safety index.
The assignment method for the completed job task and the assignment method for the uncompleted job task are different.
And acquiring the grade result of the set work task corresponding to each production safety index, so that the grade result of each production safety index can be determined according to the grade result of the work task corresponding to each production safety index.
Step S202, the scoring result of each work task corresponding to each production safety index is subjected to weighted calculation to obtain the scoring result of each production safety index.
Specifically, it can be known from the above description that the method provided in the embodiment of the present application can obtain the scoring result of the work task corresponding to each set production safety index.
As can be seen from the above description, each production safety index includes at least one work task, and if the completion condition of the work task required to be completed by each production safety index needs to be determined, the scoring result of each production safety index can be obtained by performing weighted calculation on the scoring result of each work task corresponding to each production safety index.
Step S203, carrying out weighted calculation on the risk coefficient of each production safety index of the target enterprise according to the grading result of each production safety index to obtain the production safety risk coefficient of the target enterprise.
Specifically, it can be known from the above description that the method provided in the embodiment of the present application may determine the scoring result of each production safety index, where the scoring result of the production safety index represents the completion condition of the work task corresponding to the production safety index.
Therefore, after the scoring result of each production safety index is determined, the risk coefficient of each production safety index of the target enterprise can be weighted and calculated according to the scoring result of each production safety index, so as to obtain the production safety risk coefficient of the target enterprise.
As can be seen from the above-mentioned introduced technical solutions, the method provided in the embodiment of the present application may determine the production safety risk coefficient of the target enterprise according to the analysis result of each data parameter, so that whether the production safety condition of the target enterprise needs to be pre-warned may be determined according to the production safety risk coefficient of the target enterprise.
In an actual application process, when an enterprise has a security incident, the method provided in the embodiment of the present application may further monitor the security incident occurring in real time at the target enterprise, and the process is introduced next, and may include the following steps:
step S301, obtaining first monitoring data of the monitoring device of the target enterprise in real time, where the first monitoring data includes monitoring data of an actual production situation of the target enterprise.
In particular, in the practical application process, in order to ensure the safety of an enterprise, some monitoring devices are generally installed when the enterprise is managed on a daily basis. The monitoring equipment can collect and store the daily operation related data of the enterprise in real time. Therefore, the method provided by the embodiment of the application may further obtain the first monitoring data of the monitoring device of the target enterprise in real time, where the first monitoring data may include the monitoring data of the actual production situation of the target enterprise.
The timeliness of the data of the monitoring equipment is good, and when the target enterprise has a safety accident, the safety accident of the target enterprise can be found in time by analyzing the first monitoring data of the monitoring equipment of the target enterprise.
For example, by monitoring camera equipment or related sensors, such as: the temperature control alarm and the hazardous article leakage alarm can monitor the production field of an enterprise in real time, and when data of the production field of the enterprise reaches the safety threshold values of the temperature control alarm, the hazardous article leakage alarm and other equipment, the sensor linkage control system can send out early warning signals.
In the practical application process, when an enterprise has safety accidents such as fire, dangerous article leakage and explosion, poisoning and suffocation possibly can be caused, production environment parameters of the enterprise can possibly reach early warning conditions, and whether the enterprise has the safety accidents or not can be found by analyzing the production environment parameters of the enterprise.
Step S302, judging whether the first monitoring data comprises safety accident data related to the target enterprise.
Specifically, as can be seen from the above description, by analyzing the first monitoring data of the monitoring device of the target enterprise, the security incident that has occurred can be found in time. Accordingly, after obtaining the first monitoring data, it may be determined whether the first monitoring data includes incident data associated with the target enterprise. If the first monitoring data is determined to comprise safety accident data related to the target enterprise, the target enterprise is indicated to have a safety accident, the safety accident needs to be processed in time, and the target enterprise may need to be rescued.
Step S303, determining that a safety accident occurs to the target enterprise, acquiring map data of the geographical position of the target enterprise, and analyzing the first monitoring data to obtain an accident analysis result of the target enterprise, wherein the accident analysis result of the target enterprise comprises an accident type and an accident spread range of the target enterprise.
Specifically, as can be seen from the above description, the method provided in the embodiment of the present application may determine whether the first monitoring data includes incident data related to the target enterprise, and if it is determined that the first monitoring data includes incident data related to the target enterprise, it is determined that the target enterprise has an incident, and the incident needs to be handled in time, and the target enterprise may need to be rescued.
But the losses and spread that may arise from different accidents are different.
For example, the geographic extent of injury and spread resulting from fire accidents, chemical spill accidents, and explosion accidents are all different.
Therefore, after it is determined that a security accident occurs to the target enterprise, the map data of the geographic location of the target enterprise may be obtained, and the first monitoring data is analyzed to obtain an accident analysis result of the target enterprise, where the accident analysis result of the target enterprise may include an accident type and an accident spread range of the target enterprise.
When the target enterprise is determined to have a safety accident, determining the accident type and the accident spread range of the target enterprise can be helpful for timely rescue work.
For example, in the case of a liquid,
if the safety accident of the target enterprise is a fire accident involving dangerous chemicals, the range with the radius of 50 meters may be the range covered by the fire accident of the target enterprise, with the center of the geographical position where the fire accident of the target enterprise is located as the center of the circle.
If the safety accident of the target enterprise is a fire accident involving dangerous chemicals, the range with the radius of 25 meters may be the range covered by the fire accident of the target enterprise, with the center of the geographical position where the fire accident of the target enterprise is located as the center of the circle.
If the safety accident of the target enterprise is an explosion accident involving dangerous chemicals, the first range of the spread is the range of the spread of the safety accident of the target enterprise by taking the center of the geographical position where the fire accident of the target enterprise is located as the center of a circle.
Wherein the first range may be calculated with reference to a preset explosion accident influence range calculation formula:
wherein,
wherein,
R 1 a radius that may represent the range of influence caused by an explosive;
W TNT may represent TNT equivalent in kilograms;
eta can represent the explosion efficiency of the flammable vapor cloud, wherein the explosion efficiency of the flammable vapor cloud is influenced by factors such as wind direction under the explosion situation, the situation of barriers around an explosion point, the temperature and pressure conditions during explosion, the activity of explosive substances, the shape and the size of the vapor cloud and the like, the variability is large, and the value range can be [0.1 percent and 10 percent ];
w may represent the amount of explosive leakage in kilograms in a vapor cloud of an explosive range;
H h can represent the high calorific value of the explosive with the unit of kJ/kg;
H TNT the explosive heat value of TNT can be expressed in kJ/kg.
If the safety accident of the target enterprise is an explosion accident involving dangerous chemicals, the geographical position center of the fire accident of the target enterprise is taken as the center of a circle, and the spread second range is the spread range of the safety accident of the target enterprise.
Wherein the second range may be calculated with reference to a preset chemical leakage incident impact range:
wherein,
c (x, y, z) may represent the mass concentration of the leak at the coordinate (x, y, z) point in kg/m 3 Where x may represent a downwind distance, y may represent a cross-sectional wind distance, and z may represent a vertical distance from the ground;
Q m may represent the leak rate of the leak source in kg/s;
u may represent the mean wind speed for the leak height;
σ y may be expressed as a diffusion parameter of the leak in the transverse wind direction;
σ z may be expressed as a diffusion parameter of the leak downwind;
h may represent the effective height of the source of the leak.
According to the technical scheme, the method provided by the embodiment of the application can judge whether the target enterprise has a safety accident by acquiring the first monitoring data of the monitoring equipment of the target enterprise in real time and analyzing the first monitoring data, and after the target enterprise is determined to have the safety accident, the type and the range of the accident of the target enterprise can be further determined by analyzing the first monitoring data, so that the rescue work can be timely carried out.
As can be seen from the above description, after determining that a security accident occurs to the target enterprise, the method provided in the embodiment of the present application may determine the type and the coverage range of the accident that occurs to the target enterprise, and in an actual application process, after determining the type and the coverage range of the accident that occurs to the target enterprise, the method provided in the embodiment of the present application may further include determining a risk coefficient of the target enterprise, and performing an early warning according to the risk coefficient of the target enterprise, and then introduces the process, which may include the following steps:
step S401, determining the risk coefficient of the target enterprise according to the accident analysis result of the target enterprise.
Specifically, as can be seen from the above description, the method provided in the embodiment of the present application may determine the accident analysis result of the target enterprise.
The accident analysis result of the target enterprise may include the accident type and the accident spread range of the target enterprise.
The danger coefficients corresponding to different accident types and different accident spread ranges are different.
Accordingly, after determining the incident analysis results for the target business, the risk factor for the target business may be determined based on the incident analysis results for the target business.
For example, the risk coefficient of the current security incident of the target enterprise may be determined according to the incident type and the incident coverage of the target enterprise.
Step S402, sending an early warning signal corresponding to the danger coefficient of the target enterprise to the target enterprise, a rescue unit at the location of the target enterprise and a related supervision department to which the target enterprise belongs according to the danger coefficient of the target enterprise, the accident analysis result of the target enterprise and the map data of the geographic position of the target enterprise.
Specifically, it can be known from the above description that the method provided in the embodiment of the present application can determine the risk coefficient of the target enterprise according to the accident analysis result of the target enterprise, and the early warning signals corresponding to the risk coefficients of different levels are different, and the required rescue efforts are also different.
Therefore, after the risk coefficient of the target enterprise is determined, according to the risk coefficient of the target enterprise, the accident analysis result of the target enterprise, and the map data of the geographic location of the target enterprise, an early warning signal corresponding to the risk coefficient of the target enterprise may be sent to the target enterprise, a rescue unit where the target enterprise is located, and a relevant supervision department to which the target enterprise belongs.
According to the technical scheme, the method provided by the embodiment of the application can send the early warning signal corresponding to the danger coefficient of the target enterprise to the target enterprise, the rescue unit where the target enterprise is located and the related supervision department where the target enterprise belongs according to the danger coefficient of the target enterprise, the accident analysis result of the target enterprise and the map data of the geographic position of the target enterprise, so that the rescue work can be timely performed, and the economic loss is reduced.
As can be seen from the above description, the method provided in the embodiment of the present application may determine whether the first monitoring data includes the incident data related to the target enterprise, and then introduces several implementation manners for determining whether the first monitoring data includes the incident data related to the target enterprise, which specifically include the following steps:
in the first kind of the method, the first,
if it is determined that the temperature, humidity or pressure value of the target enterprise displayed in the first monitoring data exceeds a corresponding safety threshold, determining that the first monitoring data comprises safety accident data related to the target enterprise;
second, if it is determined that the first monitoring data includes the alarm signal data of the target enterprise, it is determined that the first monitoring data includes safety accident data related to the target enterprise.
In a third aspect of the present invention,
and if it is determined that the temperature, humidity or pressure value of the target enterprise, which is displayed in the first monitoring data, exceeds the corresponding safety threshold value, and the first monitoring data comprises the alarm signal data of the target enterprise, determining that the first monitoring data comprises safety accident data related to the target enterprise.
According to the technical scheme, the method provided by the embodiment of the application can judge whether the temperature, humidity or pressure value of the target enterprise displayed in the first monitoring data exceeds the corresponding safety threshold value, and judge whether the first monitoring data comprises safety accident data related to the target enterprise by including the alarm signal data of the target enterprise in the first monitoring data, so that whether the target enterprise has a safety accident can be determined, and early warning and rescue work can be timely performed.
As can be seen from the above-described technical solutions, the method provided in the embodiment of the present application may analyze the first monitoring data to obtain an accident analysis result of the target enterprise, and then introduce the process, where the process may include the following steps:
step S501, analyzing the first monitoring data and determining the accident type of the target enterprise.
Specifically, as can be seen from the above description, the method provided in the embodiment of the present application may obtain the first monitoring data, where the first monitoring data may include an actual operation condition of the target enterprise, and if a security incident occurs in the target enterprise, the first monitoring data may include data of a security incident related to the target enterprise.
By analyzing the first monitoring data, the related situation of the safety accident of the target enterprise can be known. And the first monitoring data may include the type of security incident occurred and the possible spread of the target enterprise.
Thus, after obtaining the first monitoring data, the first monitoring data may be analyzed to determine the type of incident of the target business.
Step S502, determining the accident spread range of the target enterprise according to the accident type of the target enterprise, and taking the accident type and the accident spread range of the target enterprise as the accident analysis result of the target enterprise.
Specifically, as can be seen from the above description, the method provided in the embodiment of the present application may determine the accident type of the target enterprise by analyzing the first monitoring data, where the coverage of different types of accidents is different, and therefore, after determining the accident type of the target enterprise, the coverage of the accident of the target enterprise may be determined according to the accident type of the target enterprise, and the accident type and the coverage of the accident of the target enterprise are used as the accident analysis result of the target enterprise.
According to the technical scheme, the method provided by the embodiment of the application can be used for analyzing the first monitoring data and determining the accident type of the target enterprise. After the accident type of the target enterprise is determined, the accident spread range of the target enterprise can be determined according to the accident type of the target enterprise, and the accident type and the accident spread range of the target enterprise are used as the accident analysis result of the target enterprise. So that a risk coefficient for the target business may be determined based on the incident analysis results for the target business.
As can be seen from the above description, the method provided in this embodiment of the present application may determine whether the target enterprise meets the preset early warning condition according to the production safety risk coefficient of the target enterprise, and then introduce the process, where the process may include the following steps:
step S601, judging whether the production safety risk coefficient of the target enterprise reaches the risk coefficient corresponding to the risk early warning signal of the lowest risk level in the preset risk early warning signal relation table or not according to the production safety risk coefficient of the target enterprise and the preset risk early warning signal relation table.
Specifically, as can be seen from the above description, the method provided by the embodiment of the present application may determine the production safety risk coefficient of the target enterprise, where different production safety risk coefficients correspond to different risk early warning signals.
Therefore, after the production safety risk coefficient of the target enterprise is determined, whether the production safety risk coefficient of the target enterprise reaches the risk coefficient corresponding to the risk early warning signal at the lowest risk level in the preset risk early warning signal relation table or not can be judged according to the production safety risk coefficient of the target enterprise and the preset risk early warning signal relation table.
If the production safety risk coefficient of the target enterprise reaches the risk coefficient corresponding to the risk early warning signal with the lowest risk level in the preset risk early warning signal relation table, it indicates that a safety accident occurring in the target enterprise may bring about a large influence and needs to be early warned, and therefore it can be determined that the target enterprise meets the preset early warning condition.
The preset early warning condition can be set to early warning if the production safety risk coefficient of the target enterprise reaches the risk coefficient corresponding to the risk early warning signal with the lowest risk level in the preset risk early warning signal relation table.
According to the technical scheme, whether the production safety risk coefficient of the target enterprise reaches the risk coefficient corresponding to the risk early warning signal with the lowest risk level in the preset risk early warning signal relation table or not can be judged according to the production safety risk coefficient of the target enterprise and the preset risk early warning signal relation table, so that rescue work can be timely carried out.
Further optionally, the method provided in this embodiment of the application may further set a modification permission of the first target data and the first monitoring data, so as to limit the first target data and the first monitoring data from being tampered with.
For example, the configuration may be implemented by applying a blockchain technique, and the first target data saved to the server by the target enterprise and the first monitoring data cannot be modified once being saved, so that the work tracing can be performed after a security accident occurs.
The following describes the security accident monitoring apparatus provided in the embodiment of the present application, and the security accident monitoring apparatus described below and the security accident monitoring method described above may be referred to in correspondence with each other.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a safety accident monitoring device disclosed in the embodiment of the present application.
As shown in fig. 2, the safety accident monitoring apparatus may include:
the system comprises a first data acquisition unit 101, a second data acquisition unit, a first processing unit and a second processing unit, wherein the first data acquisition unit is used for acquiring first target data uploaded to a server by a target enterprise, the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task;
the analysis unit 102 is configured to analyze each data parameter in the first target data according to a level coefficient of each work task to obtain an analysis result of each data parameter;
the first safety factor determining unit 103 is configured to determine a production safety risk coefficient of the target enterprise according to an analysis result of each data parameter;
a first judging unit 104, configured to judge whether the target enterprise meets a preset early warning condition according to the production safety risk coefficient of the target enterprise;
and the first early warning unit 105 is configured to send an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise when the execution result of the first determining unit determines that the target enterprise meets a preset early warning condition.
As can be seen from the above-described technical solutions, the apparatus provided in the embodiment of the present application may utilize the first data obtaining unit 101 to obtain first target data uploaded to the server by a target enterprise, where the first target data includes a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task; each work task is provided with different grade coefficients, and the condition of each work task can be known by analyzing the data parameters corresponding to each work task, so that each data parameter in the first target data can be analyzed by the analysis unit 102 according to the grade coefficient of each work task, and the analysis result of each data parameter can be obtained; after the analysis result of each data parameter is obtained, a first safety factor determining unit 103 may be further used to determine a production safety risk coefficient of the target enterprise according to the analysis result of each data parameter; the different levels of production safety risk coefficients reflect different levels of production safety conditions of the target enterprise. In the practical application process, when the production safety risk coefficient of the target enterprise reaches a certain level, an early warning signal needs to be sent out. Therefore, after obtaining the production safety risk coefficient of the target enterprise, the first determining unit 104 may be used to determine whether the target enterprise meets a preset early warning condition according to the production safety risk coefficient of the target enterprise; if the target enterprise meets the preset early warning condition, an early warning signal corresponding to the production safety risk coefficient of the target enterprise may be sent to the target enterprise by using the first early warning unit 105.
The device that this application embodiment provided can discover latent incident and in time send out early warning signal through the relevant production safety's of analysis target enterprise data, helps restraining the emergence of incident, helps protecting target enterprise's economic benefits, reduces the unnecessary loss.
Further optionally, the first safety factor determining unit 103 may include:
the first coefficient determining subunit is configured to score the work task to which each data parameter belongs according to the analysis result of each data parameter, and obtain a score result of the work task corresponding to each set production safety index;
the second coefficient determining subunit is configured to perform weighted calculation on the scoring result of each work task corresponding to each production safety index to obtain the scoring result of each production safety index;
and the third coefficient determining subunit is used for performing weighted calculation on the risk coefficient of each production safety index of the target enterprise according to the grading result of each production safety index to obtain the production safety risk coefficient of the target enterprise.
Further optionally, the apparatus may further include:
the monitoring data acquisition unit is used for acquiring first monitoring data of monitoring equipment of the target enterprise in real time, wherein the first monitoring data comprises monitoring data of the actual production condition of the target enterprise;
a second judging unit, configured to judge whether the first monitoring data includes safety accident data related to the target enterprise;
and the accident analysis unit is used for determining that a safety accident occurs to the target enterprise when the execution result of the second judgment unit is that the first monitoring data includes safety accident data related to the target enterprise, acquiring map data of the geographical position of the target enterprise, and analyzing the first monitoring data to obtain an accident analysis result of the target enterprise, wherein the accident analysis result of the target enterprise includes an accident type and an accident spread range of the target enterprise.
Further optionally, the apparatus may further include:
the second safety factor determining unit is used for determining a danger coefficient of the target enterprise according to the accident analysis result of the target enterprise;
and the second early warning unit is used for sending early warning signals corresponding to the danger coefficient of the target enterprise to the target enterprise, a rescue unit where the target enterprise is located and a related supervision department where the target enterprise belongs according to the danger coefficient of the target enterprise, the accident analysis result of the target enterprise and the map data of the geographic position where the target enterprise is located.
Further optionally, the execution process of the second judging unit may include:
if the temperature, humidity or pressure value of the target enterprise exceeds the corresponding safety threshold value, the first monitoring data is determined to comprise safety accident data related to the target enterprise;
and/or the presence of a gas in the gas,
if the first monitoring data comprises the alarm signal data of the target enterprise, determining that the first monitoring data comprises safety accident data related to the target enterprise.
Further optionally, the accident analysis unit may include:
the accident type determining unit is used for analyzing the first monitoring data and determining the accident type of the target enterprise;
and the accident spread range unit is used for determining the accident spread range of the target enterprise according to the accident type of the target enterprise and taking the accident type and the accident spread range of the target enterprise as the accident analysis result of the target enterprise.
Further optionally, the first determining unit 104 may include:
the first judgment subunit is configured to judge, according to the production safety risk coefficient of the target enterprise and a preset risk early warning signal relation table, whether the production safety risk coefficient of the target enterprise reaches a risk coefficient corresponding to a risk early warning signal at a lowest risk level in the preset risk early warning signal relation table;
and the determining unit is used for determining that the target enterprise meets the preset early warning condition when the execution result of the first judging subunit is yes.
Further optionally, the apparatus may further include:
and the permission setting unit is used for setting the modification permission of the first target data and the first monitoring data so as to limit the first target data and the first monitoring data from being tampered.
The specific processing flow of each unit included in the safety accident monitoring apparatus may refer to the related description of the safety accident monitoring method, and is not described herein again.
The safety accident monitoring device provided by the embodiment of the application can be applied to safety accident monitoring equipment, such as a terminal: mobile phones, computers, etc. Optionally, fig. 3 shows a block diagram of a hardware structure of the safety accident monitoring device, and referring to fig. 3, the hardware structure of the safety accident monitoring device may include: at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4.
In the embodiment of the present application, the number of the processor 1, the communication interface 2, the memory 3, and the communication bus 4 is at least one, and the processor 1, the communication interface 2, and the memory 3 complete mutual communication through the communication bus 4.
The processor 1 may be a central processing unit CPU, or an Application Specific Integrated Circuit ASIC (Application Specific Integrated Circuit), or one or more Integrated circuits configured to implement the embodiments of the present Application, etc.;
the memory 3 may include a high-speed RAM memory, and may further include a non-volatile memory (non-volatile memory) or the like, such as at least one disk memory;
wherein the memory stores a program and the processor can call the program stored in the memory, the program for: and realizing each processing flow in the terminal safety accident monitoring scheme.
Embodiments of the present application further provide a readable storage medium, where the storage medium may store a program adapted to be executed by a processor, where the program is configured to: and realizing each processing flow of the terminal in the safety accident monitoring scheme.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. The various embodiments may be combined with each other. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of security incident monitoring, comprising:
acquiring first target data uploaded to a server by a target enterprise, wherein the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task;
analyzing each data parameter in the first target data according to the grade coefficient of each work task to obtain an analysis result of each data parameter;
determining the production safety risk coefficient of the target enterprise according to the analysis result of each data parameter;
judging whether the target enterprise meets a preset early warning condition or not according to the production safety risk coefficient of the target enterprise;
and if the target enterprise meets the preset early warning condition, sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise.
2. The method of claim 1, wherein determining the target enterprise's production safety risk factor based on the analysis of each of the data parameters comprises:
according to the analysis result of each data parameter, scoring the work task to which each data parameter belongs to obtain the scoring result of the set work task corresponding to each production safety index;
carrying out weighted calculation on the scoring result of each work task corresponding to each production safety index to obtain the scoring result of each production safety index;
and according to the grading result of each production safety index, carrying out weighted calculation on the risk coefficient of each production safety index of the target enterprise to obtain the production safety risk coefficient of the target enterprise.
3. The method of claim 1, further comprising:
acquiring first monitoring data of monitoring equipment of the target enterprise in real time, wherein the first monitoring data comprises monitoring data of actual production conditions of the target enterprise;
determining whether the first monitoring data comprises safety accident data related to the target enterprise;
if the first monitoring data comprise safety accident data related to the target enterprise, determining that a safety accident occurs to the target enterprise, acquiring map data of the geographical position of the target enterprise, and analyzing the first monitoring data to obtain an accident analysis result of the target enterprise, wherein the accident analysis result of the target enterprise comprises an accident type and an accident spread range of the target enterprise.
4. The method of claim 3, further comprising:
determining a risk coefficient of the target enterprise according to the accident analysis result of the target enterprise;
and sending an early warning signal corresponding to the danger coefficient of the target enterprise to the target enterprise, a rescue unit where the target enterprise is located and a related supervision department where the target enterprise belongs according to the danger coefficient of the target enterprise, the accident analysis result of the target enterprise and the map data of the geographic position of the target enterprise.
5. The method of claim 3, wherein determining whether the first monitoring data includes incident data associated with the target enterprise comprises:
if the temperature, humidity or pressure value of the target enterprise exceeds the corresponding safety threshold value, the first monitoring data is determined to comprise safety accident data related to the target enterprise;
and/or the presence of a gas in the gas,
and if the first monitoring data comprises the alarm signal data of the target enterprise, determining that the first monitoring data comprises safety accident data related to the target enterprise.
6. The method of claim 3, wherein analyzing the first monitoring data to obtain the accident analysis result of the target enterprise comprises:
analyzing the first monitoring data to determine the accident type of the target enterprise;
and determining the accident spread range of the target enterprise according to the accident type of the target enterprise, and taking the accident type and the accident spread range of the target enterprise as an accident analysis result of the target enterprise.
7. The method according to any one of claims 1 to 6, wherein the determining whether the target enterprise meets a preset early warning condition according to the production safety risk coefficient of the target enterprise comprises:
judging whether the production safety risk coefficient of the target enterprise reaches a risk coefficient corresponding to a risk early warning signal at the lowest risk level in a preset risk early warning signal relation table or not according to the production safety risk coefficient of the target enterprise and the preset risk early warning signal relation table;
and if so, determining that the target enterprise meets preset early warning conditions.
8. A security incident monitoring device, comprising:
the system comprises a first data acquisition unit, a second data acquisition unit and a processing unit, wherein the first data acquisition unit is used for acquiring first target data uploaded to a server by a target enterprise, the first target data comprises a plurality of data parameters, each data parameter is a parameter of a work task corresponding to each set production safety index, and each production safety index corresponds to at least one work task;
the analysis unit is used for analyzing each data parameter in the first target data according to the grade coefficient of each work task to obtain an analysis result of each data parameter;
the first safety factor determining unit is used for determining a production safety risk coefficient of the target enterprise according to the analysis result of each data parameter;
the first judgment unit is used for judging whether the target enterprise meets a preset early warning condition or not according to the production safety risk coefficient of the target enterprise;
and the first early warning unit is used for sending an early warning signal corresponding to the production safety risk coefficient of the target enterprise to the target enterprise when the execution result of the first judging unit determines that the target enterprise meets the preset early warning condition.
9. A safety accident monitoring apparatus, comprising:
one or more processors, and a memory;
the memory has stored therein computer readable instructions which, when executed by the one or more processors, carry out the steps of the security incident monitoring method of any one of claims 1 to 7.
10. A readable storage medium, characterized by: the readable storage medium has stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to carry out the steps of the security incident monitoring method of any of claims 1 to 7.
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| CN116562627A (en) * | 2023-05-19 | 2023-08-08 | 中国电信股份有限公司湖州分公司 | Security risk management method, system, equipment, medium and product |
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| CN116562627A (en) * | 2023-05-19 | 2023-08-08 | 中国电信股份有限公司湖州分公司 | Security risk management method, system, equipment, medium and product |
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