CN112149939A - Enterprise pollution risk monitoring system and prevention and control analysis method - Google Patents
Enterprise pollution risk monitoring system and prevention and control analysis method Download PDFInfo
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Abstract
The application provides an enterprise pollution risk monitoring system and a prevention and control analysis method, wherein the system is applied to city management and comprises the following components: the information acquisition module is used for acquiring basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network; inquiring the first storage through the information processing module to obtain an enterprise risk value corresponding to the basic information of the target enterprise; if the enterprise risk value is larger than the set value, determining the target enterprise as a high-risk polluted enterprise; and querying the second memory according to the surrounding environment information of the high-risk polluted enterprise through a risk assessment module to obtain the pollution risk of the high-risk polluted enterprise. According to the technical scheme, the pollution risk of the target enterprise is judged by adopting the system according to the target enterprise related to pollution in the city and the surrounding environment information of the target enterprise, and the risk is visually provided for the city manager through the output module, so that the city manager can conveniently monitor the target enterprise.
Description
Technical Field
The application relates to the technical field of big data, in particular to an enterprise pollution risk monitoring system and a prevention and control analysis method.
Background
By the end of 2017, the China has 41963 dust explosion-related enterprises in common. Dust explosion has five elements: ignition source, dust concentration, oxygen (air), closed space and combustible material. Once dust explodes, the harm is serious, the dust explosion has strong destructive power, secondary explosion is easy to generate, and toxic gas is generated. In 2010, the starch dust of the Qinhuangdai island, exploded to cause 21 deaths and 47 injuries; in 2012, in the european sea area of wenzhou city, aluminum dust in wenzhou city explodes to cause 13 deaths and 15 injuries; in 2014, Jiangsu province, caused 97 deaths due to aluminum dust explosion (after another accident report period, 49 deaths due to ineffective treatment); in 2015, artificial boards in the inner Mongolian river city explode to cause 6 deaths and 3 injuries.
At present, dust explosion-related enterprises are difficult to supervise, and the problems of non-standard dust removal systems, serious dust accumulation on operation sites, high dust explosion risks and the like generally exist.
Disclosure of Invention
The application provides an enterprise pollution risk monitoring system and a prevention and control capability analysis method, which are used for improving monitoring on enterprise pollution.
In a first aspect, the present application provides an enterprise pollution risk monitoring system, which is applied to city management, and includes: the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module is used for acquiring basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network; after the basic information of a target enterprise is collected, a first storage is inquired through an information processing module to obtain an enterprise risk value corresponding to the basic information of the target enterprise, and the first storage stores corresponding relations between the basic information of different enterprises and the enterprise risk value; if the enterprise risk value is larger than a set value, determining the target enterprise as a high-risk polluted enterprise; then, a second memory is inquired through a risk evaluation module of the system according to the surrounding environment information of the high-risk polluted enterprise, and the pollution risk of the high-risk polluted enterprise is obtained; the second storage stores corresponding relations between the surrounding environment information and pollution risks of different enterprises; and after the pollution risk is determined, outputting the basic information of the high-risk polluted enterprise, the peripheral environment information of the high-risk polluted enterprise and the pollution risk of the high-risk polluted enterprise through an output module of the system. According to the technical scheme, the pollution risk of the target enterprise is judged by adopting the system according to the target enterprise related to pollution in the city and the surrounding environment information of the target enterprise, and the risk is visually provided for the city manager through the output module, so that the city manager can conveniently monitor the target enterprise.
In a specific possible implementation, the information collection module is specifically configured to filter the basic information of the target enterprise based on the set data type to obtain the basic information of the target enterprise. Thereby obtaining basic information about the pollution of the target enterprise.
In a specific possible implementation manner, the system further comprises an information sorting module, and the information sorting module is used for storing the information collected by the information collecting module in the first storage, and eliminating repeated information in the basic information of the target enterprise when the information is stored. The data can be conveniently arranged in the later period.
In a specific implementation, the corresponding relationship between the basic information of the different enterprises and the enterprise risk value is specifically to obtain the intrinsic risk information and the management correction term of the enterprise production conditions of the different enterprises according to the basic information of the different enterprises, and determine the enterprise risk value according to the obtained intrinsic risk information and the management correction term of the enterprise production conditions. And acquiring the risk value of the enterprise through the inherent risk information and the management correction term of the production condition of the enterprise.
In a specific possible embodiment, the enterprise risk value is R, where R1 a, R1 is intrinsic risk information of the enterprise production conditions, and a is a regulatory amendment.
In a specific possible embodiment, the intrinsic risk information of the occurrence condition of the enterprise includes: the likelihood of risk occurrence and the severity of the accident impact; the information processing module is specifically configured to obtain inherent risk information of the enterprise occurrence condition according to the possibility of risk occurrence and the severity of the accident influence.
In a specific possible embodiment, the intrinsic risk information of the enterprise production condition is R1, and R1 ═ P × S, where P is the possibility of enterprise risk occurrence and S is the severity of accident impact.
In a specific embodiment, the likelihood of the enterprise risk occurrence includes: the type of dust removal system and the type of dust of an enterprise;
the information processing module is specifically used for calculating the score of the dust removal system type of the enterprise according to the dust removal system type of the enterprise and the score corresponding to the set dust removal system type; calculating the value of the dust type of the enterprise according to the dust type of the enterprise and the set value corresponding to the dust type; a risk probability of occurrence P-P1-P2 for the business; wherein P1 is the score of the dust removal system type of the enterprise, and P2 is the score of the dust type of the enterprise.
In a specific possible embodiment, the management revision term includes: safety standardization level and accident history;
the information processing module is specifically used for calculating the score of the safety standardization level of the enterprise according to the safety standardization level of the enterprise and the score corresponding to the set safety standardization level; calculating the score of the accident history of the enterprise according to the accident history of the enterprise and the set score corresponding to the accident history; the management correction term a is a1+ a2, where a1 is the score of the safety standardization level of the enterprise and a2 is the score of the accident history of the enterprise.
In a particular possible embodiment, the ambient environment information includes sensitive data objects within a safe distance of the target enterprise.
In a specific possible embodiment, the sensitive data objects include different objects of population density, building density, traffic conditions, and the like.
In a specific implementation scheme, the information processing module is further configured to determine whether the high-risk polluted enterprise has a potential safety hazard according to the acquired basic information of the high-risk polluted enterprise and a set safety standard;
the output module is also used for outputting prompt information of whether the high-risk pollution enterprises have potential safety hazards.
In a specific possible implementation, the output module is a common display device such as a mobile terminal, a display screen, and the like. The city manager can watch conveniently.
In a second aspect, a method for preventing and controlling enterprise pollution risk is provided, the method comprising the following steps:
acquiring basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network;
inquiring a first storage to obtain an enterprise risk value corresponding to the basic information of the target enterprise, wherein the first storage stores the corresponding relation between the basic information of different enterprises and the enterprise risk value; if the enterprise risk value is larger than a set value, determining the target enterprise as a high-risk polluted enterprise;
inquiring a second memory according to the peripheral environment information of the high-risk polluted enterprise to obtain the pollution risk of the high-risk polluted enterprise; the second storage stores corresponding relations between the surrounding environment information and pollution risks of different enterprises;
and outputting the basic information of the high-risk polluted enterprises, the surrounding environment information of the high-risk polluted enterprises and the pollution risks of the high-risk polluted enterprises.
According to the technical scheme, the pollution risk of the target enterprise is judged by adopting the system according to the target enterprise related to pollution in the city and the surrounding environment information of the target enterprise, and the risk is visually provided for the city manager through the output module, so that the city manager can conveniently monitor the target enterprise.
In a specific implementation, the obtaining of the basic information of the target enterprise and the ambient environment information of the target enterprise through the communication network specifically includes:
and screening the basic information of the target enterprise based on the set data type to acquire the basic information of the target enterprise.
In a specific possible embodiment, the method further comprises: and storing the information acquired by the information acquisition module in the first memory, and eliminating repeated information in the basic information of the target enterprise during storage.
In a specific implementation, the correspondence between the basic information of different enterprises and the enterprise risk values is specifically:
and according to the basic information of the different enterprises, acquiring the inherent risk information and the management correction term of the enterprise production conditions of the different enterprises, and determining the enterprise risk value according to the acquired inherent risk information and the management correction term of the enterprise production conditions.
In a specific possible embodiment, the enterprise risk value is R, where R1 a, R1 is intrinsic risk information of the enterprise production conditions, and a is a regulatory amendment.
In a specific possible embodiment, the intrinsic risk information of the occurrence condition of the enterprise includes: the likelihood of risk occurrence and the severity of the accident impact;
the method further comprises acquiring inherent risk information of the enterprise occurrence condition according to the possibility of the risk occurrence and the severity of the accident influence.
In a specific possible embodiment, the intrinsic risk information of the enterprise production condition is R1, and R1 ═ P × S, where P is the possibility of enterprise risk occurrence and S is the severity of accident impact.
In a specific embodiment, the likelihood of the enterprise risk occurrence includes: the type of dust removal system and the type of dust of an enterprise;
the method further comprises the following steps: calculating the score of the dust removal system type of the enterprise according to the dust removal system type of the enterprise and the set score corresponding to the dust removal system type; calculating the value of the dust type of the enterprise according to the dust type of the enterprise and the set value corresponding to the dust type; a risk probability of occurrence P-P1-P2 for the business; wherein P1 is the score of the dust removal system type of the enterprise, and P2 is the score of the dust type of the enterprise.
In a specific possible embodiment, the management revision term includes: safety standardization level and accident history;
the method further comprises the following steps: calculating the score of the safety standardization level of the enterprise according to the safety standardization level of the enterprise and the score corresponding to the set safety standardization level; calculating the score of the accident history of the enterprise according to the accident history of the enterprise and the set score corresponding to the accident history; the management correction term a is a1+ a2, where a1 is the score of the safety standardization level of the enterprise and a2 is the score of the accident history of the enterprise.
In a particular possible embodiment, the ambient environment information includes sensitive data objects within a safe distance of the target enterprise.
In a specific possible embodiment, the method further comprises: judging whether the high-risk polluted enterprises have potential safety hazards or not according to the acquired basic information of the high-risk polluted enterprises and the set safety standard;
and outputting prompt information of whether the high-risk pollution enterprises have potential safety hazards.
In a third aspect, an embodiment of the present application provides a monitoring device, where the monitoring device includes a processor, and is configured to implement the method described in the second aspect. The monitoring device may also include a memory for storing instructions and data. The memory is coupled to the processor, and the processor, when executing the program instructions stored in the memory, may implement the method described in the second aspect above. The monitoring device may further include a communication interface for the device to communicate with other devices, such as a transceiver, a circuit, a bus, a module, or other types of communication interfaces, and the other devices may be network devices or terminal devices.
In one particular implementation, the monitoring device includes: a memory for storing program instructions;
a processor for calling instructions stored in the memory to cause the apparatus to perform the second aspect of the embodiments of the present application and any one of the possible designed methods of the second aspect.
In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, which includes instructions that, when executed on a computer, cause the computer to perform the method of the second aspect and any one of the possible designs of the second aspect.
In a fifth aspect, an embodiment of the present application further provides a chip system, where the chip system includes a processor and may further include a memory, and is configured to implement the method according to any one of the possible designs of the second aspect and the second aspect. The chip system may be formed by a chip, and may also include a chip and other discrete devices.
In a sixth aspect, this application further provides a computer program product including instructions that, when executed on a computer, implement the method of any one of the possible designs of the second aspect and the second aspect.
Drawings
Fig. 1 is a schematic diagram of an enterprise pollution risk monitoring system architecture provided in the present application;
FIG. 2 is a flowchart of identifying a high-risk polluting enterprise according to an embodiment of the present disclosure;
fig. 3 is a set score corresponding to the risk occurrence probability provided by the embodiment of the present application;
FIG. 4 is a set score corresponding to the severity of the impact of the incident provided by an embodiment of the present application;
fig. 5 is a set score corresponding to the normalization of security management provided in the embodiment of the present application;
fig. 6 is a processing result of daily special treatment self-inspection data of an enterprise of a target enterprise, which is indicated by an output module of the system provided in the embodiment of the present application;
fig. 7 is a processing result of daily special treatment self-inspection data of an enterprise of a target enterprise, which is indicated by an output module of the system provided in the embodiment of the present application;
fig. 8 is a flowchart of a prevention and control capability analysis method provided in an embodiment of the present application;
fig. 9 is a schematic structural diagram of a monitoring device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clear, the present application will be further described in detail with reference to the accompanying drawings. The particular methods of operation in the method embodiments may also be applied to apparatus embodiments or system embodiments. In the description of the present application, the term "plurality" means two or more unless otherwise specified.
In order to facilitate understanding of the enterprise pollution risk monitoring system provided in the embodiments of the present application, the following terms are first introduced:
geospatial techniques: all techniques for acquiring, managing, analyzing, visualizing and disseminating data and information;
urban big data: dynamic and static data generated by subjects such as governments, enterprises and public institutions, individuals, various urban facilities and equipment and the like closely related to the four major functions of the city are called city big data;
business intelligence: business Intelligence, abbreviation: BI, also known as business intelligence or business intelligence, refers to the use of modern data warehouse technology, online analytical processing technology, data mining and data presentation technology to perform data analysis to achieve business value.
Machine learning: machine learning is the science of artificial intelligence, and the main research object in the field is artificial intelligence, particularly how to improve the performance of a specific algorithm in empirical learning.
Explosion-related of dust: it means that combustible dust particles suspended in a closed or confined space or in an outdoor environment are rapidly combusted, and dust explosion is possible if the dispersion concentration of the combustible particles in the closed environment is high enough to be confined in the atmosphere or other suitable gaseous medium such as molecular oxygen.
First, an application scenario of the enterprise pollution risk monitoring system provided by the embodiment of the present application is described, and the enterprise pollution risk monitoring system provided by the embodiment of the present application is applied to city management, and is used for monitoring the influence of enterprise pollution on a city, so as to provide an evaluation for monitoring an enterprise. The enterprise pollution risk monitoring system provided by the embodiment of the present application is described in detail below with reference to specific embodiments.
As shown in fig. 1, an embodiment of the present application provides an enterprise pollution risk monitoring system, which is applied in city management. The system acquires the information of enterprises and the surrounding based on the urban big data and monitors the enterprises.
With continuing reference to fig. 1, an enterprise pollution risk detection system provided by an embodiment of the present application includes: the information acquisition module 200 acquires basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network. When obtaining the basic information of the target enterprise, the information collecting module 200 obtains the basic information data of the target enterprise through the city functional department, such as: statistical bureau, environmental protection bureau and the like. The information acquisition module 200 acquires original service data of each government functional department related to the dust-related explosion service through a communication network, specifically including dust-related explosion enterprise data of departments such as a statistical bureau and an environmental protection bureau. The information provided by the statistical bureau, the environmental protection bureau, and the like includes various information of the target enterprise, but the information does not necessarily relate to the pollution risk of the target enterprise, such as the output value of the target enterprise, the benefit of the target enterprise, and the like. There is a need to screen data provided by the urban functional sector. During the specific screening, the information collection module 200 screens the basic information of the target enterprise based on the set data type to obtain the basic information of the target enterprise. The set data type can be set manually according to needs, such as the dust type and the enterprise name of the target enterprise, which relate to the target enterprise and the pollution-related information. The acquired basic information of the target enterprise comprises the enterprise name, the dust type, the number of people involved in the operation, the geographical position and the like of the target enterprise.
When the information acquisition module 200 acquires information of a target enterprise from the urban functional departments, recorded data may be duplicated in different urban functional departments, so in this embodiment of the present application, the system further includes an information sorting module 100, where the information sorting module 100 is configured to store information acquired by the information acquisition module 200 in a first memory, and to remove duplicated information in basic information of the target enterprise when storing the information. When information of a target enterprise is acquired through different government departments, the information is cleaned and managed through the information sorting module 100, repeated data and the like are removed, and the information is classified and sorted to form a data set which can be used finally. Such as population density information, dust type information relating to pollution.
The information collection module 200 is further applied to unifying the basic information of the managed target enterprise into an original library to form various library tables, such as a grid management database, an enterprise management database, an industry supervision database, a hidden danger troubleshooting database, an internet of things monitoring database, a safety accident database, an emergency rescue database, an administrative law enforcement database, and the like. The library table is stored in a first memory.
The information collection module 200 may collect the surrounding environment information of the target enterprise, which includes different information such as population information, housing information, and traffic information of the target enterprise, in addition to the basic information of the target enterprise.
The basic information of the target enterprise and the surrounding environment information of the target enterprise, which are acquired by the information acquisition module 200, are used for judging the pollution condition of the target enterprise, and determining the influence caused by pollution through the surrounding environment information after judgment. When the pollution condition of the target enterprise is specifically judged, the system further comprises an information processing module 300, the information processing module 300 queries a first storage to obtain an enterprise risk value corresponding to the basic information of the target enterprise, and the first storage stores corresponding relations between the basic information of different enterprises and the enterprise risk value; and if the enterprise risk value is larger than the set value, determining the target enterprise as a high-risk polluted enterprise.
When the information processing module 300 determines that the target enterprise is a high-risk polluted enterprise, as shown in fig. 2, the information processing module 300 identifies the high-risk polluted enterprise from the perspective of the possibility P of risk occurrence (dust type, dust removal system type), the severity S of accident influence (the number of people involved in dust operation, the maximum dust production per shift, safe distance), the degree of standardization a of safety management (accident history, safety standardization).
In the specific identification, the information processing module 300 is specifically configured to obtain the intrinsic risk information and the management correction term of the enterprise production condition of the target enterprise according to the basic information of the target enterprise, and obtain the enterprise risk value according to the obtained intrinsic risk information and the management correction term of the enterprise production condition. The intrinsic risk information and the management correction term, which are based on the enterprise production conditions in particular, can be calculated in different ways, such as in a specific embodiment, the enterprise risk value is R, where R1 a, R1 is the intrinsic risk information of the enterprise production conditions, and a is the management correction term.
The inherent risk information R1 of the enterprise occurrence condition includes: the probability of risk occurrence P and the severity of the accident impact S; the information processing module 300 acquires the inherent risk information R1 of the occurrence condition of the business from the possibility P of occurrence of the risk and the severity S of the impact of the accident. When the information processing module 300 specifically acquires the intrinsic risk information of the enterprise occurrence condition, R1 may be represented by P × S, where P is the possibility of occurrence of an enterprise risk and S is the severity of an accident. Wherein, the possibility P of enterprise risk occurrence includes: the type of dust removal system of the enterprise and the type of dust. The information processing module 300 calculates the score P1 of the dust removal system type of the enterprise according to the dust removal system type of the enterprise and the score corresponding to the set dust removal system type; calculating a score P2 of the dust type of the enterprise according to the dust type of the enterprise and the score corresponding to the set dust type; thereafter, the information processing module 300 processes the business according to the risk probability P of occurrence of the business P1P 2; wherein P1 is the score of the dust removal system type of the enterprise, and P2 is the score of the dust type of the enterprise. As shown in fig. 3, the information processing module 300 stores scores corresponding to the set dust removal system types, such as 3 points for dry dust removal and 1 part for wet dust removal, and the information processing module 300 determines the score of P1 according to the acquired dust removal system type of the target enterprise. The information processing module 300 also stores a score corresponding to the set dust type, and the information processing module 300 determines the score of P2 from the acquired dust type of the target company. If a target enterprise P1 is 3 and P2 is 5, the risk occurrence probability is P3 × 5 — 15.
As shown in fig. 4, the severity S of the accident effect includes: the maximum number of simultaneous operation people for powder, the maximum dust yield per shift and the safety distance. During specific processing, the information processing module 300 determines a score S1 of the maximum powder-related simultaneous operator number of the target enterprise according to the maximum powder-related simultaneous operator number of the target enterprise and a score corresponding to the set maximum powder-related simultaneous operator number, determines a score S2 of the target enterprise corresponding to the maximum dust yield per shift according to the maximum dust yield per shift of the target enterprise and a score corresponding to the set maximum dust yield in U.S. edition, and determines a score S3 of the safety distance of the target enterprise according to the safety distance of the target enterprise and a score corresponding to the set safety distance. After determining S1, S2, and S3, the information processing module 300 may determine the severity of the accident impact of the target business according to S1+ S2+ S3. As shown in fig. 4, S1 is 3, S2 is 2, S3 is 1, and S is 3+2+1 is 6.
As shown in fig. 5, the management correction term includes: a level of safety standardization and a history of accidents. During specific processing, the information processing module 300 calculates the score of the safety standardization level of the enterprise according to the safety standardization level of the enterprise and the score corresponding to the set safety standardization level; calculating the score of the accident history of the enterprise according to the accident history of the enterprise and the set score corresponding to the accident history; the management correction term a is a1+ a2, where a1 is the score of the safety standardization level of the enterprise and a2 is the score of the accident history of the enterprise. As shown in fig. 5, if the safety standardization level of the target enterprise is 1.05, the accident history is 0.05, the management revision term a is a1+ a2 is 1.05+0.05 is 1.1.
After the intrinsic risk information R1 and the management correction term a of the enterprise production condition are determined, the enterprise risk value is R1 a, and in the above example, for reference, when P is 15, S is 6, and a is 1.1, the corresponding R1 is P15S 6 a 1.1 is 99, thereby obtaining the enterprise risk value of the target enterprise, the information processing module 300 compares the enterprise risk value of the target enterprise with the set value, and when the enterprise risk value R is greater than the set value, it determines that the enterprise is a high-risk polluted enterprise, i.e., a risk enterprise.
The basic information of the target enterprise collected by the information collection module 200 further includes enterprise daily special treatment self-checking data such as hidden danger, improvement, overdue non-improvement, improvement rate and the like of the target enterprise special treatment self-checking in the past year, and the information processing module 300 evaluates the acquired enterprise daily special treatment self-checking data and the set improvement standard, analyzes the rule of the hidden danger data and the time rate of hidden danger improvement, and assists in evaluating whether the enterprise daily special treatment is in place or not. In addition, the information processing module 300 is further configured to determine whether the high-risk polluted enterprise has a potential safety hazard according to the acquired basic information of the high-risk polluted enterprise and a set safety standard, the system includes an output module 500, and the output module 500 is configured to output prompt information whether the high-risk polluted enterprise has the potential safety hazard. As shown in fig. 6, fig. 6 shows the processing result of the output module 500 of the system for daily professional remediation and self-inspection data of the target enterprise according to the information processing module 300. In fig. 6, 50 enterprises are queried, wherein 10 unapproved enterprises are 15 with potential safety hazard, 2 unapproved enterprises are overdue, and the information processing module 300 is shown to count the potential modification rate to 97% according to the data. Referring to fig. 7 together, fig. 7 shows different data information, such as a location 1 of enterprise rectification, a location 1 of overdue rectification, and the like.
When the target enterprise is determined to be the inauguration enterprise, the risk of the inauguration enterprise needs to be judged. Therefore, the system provided in the embodiment of the present application further includes a risk assessment module 400, where the risk assessment module 400 queries the second storage according to the surrounding environment information of the high-risk polluted enterprise to obtain the pollution risk of the high-risk polluted enterprise; and the second storage stores corresponding relations between the surrounding environment information and the pollution risks of different enterprises.
In the specific judgment, when the information processing module 300 determines that the target enterprise is a high-risk polluted enterprise, the risk assessment module 400 queries the second memory according to the surrounding environment information of the high-risk polluted enterprise to obtain the pollution risk of the high-risk polluted enterprise; and the second storage stores corresponding relations between the surrounding environment information and the pollution risks of different enterprises. The surrounding environment information comprises sensitive data targets in the safety distance of the high-risk polluted enterprises, and the high-risk polluted enterprises with insufficient safety distance are identified; and analyzing the risk of possible accidents. Wherein the sensitive data objects include: the risk assessment module 400 performs secondary derivative disaster prediction analysis on data such as regular soil data, population density, building information, corporate data and the like, by combining with figures of people and enterprises in a spread range and data such as river data, traffic accidents, urban pipe networks and the like. If the safety distance range of the high-risk pollution enterprise has the targets of kindergarten, school, hospital and the like, the risk caused by incapability of the high-risk pollution enterprise is caused according to the targets. The output module 500 of the system can output the basic information of the high-risk polluted enterprise, the surrounding environment information of the high-risk polluted enterprise and the pollution risk of the high-risk polluted enterprise, so that the existing risk can be visually observed. The output module 500 may be a common display device such as a mobile terminal and a display screen, for example, an LED screen, a PC, a notebook, a PAD, a smart phone, and the like.
Through the system, the historical special inspection and law enforcement conditions of governments in the past are collected, and the enterprise risk, the enterprise self management and control and the enterprise economic condition are combined to evaluate whether the historical safety supervision of the governments is in place or not on one hand, and to assist in decision-making of future supervision plans and law enforcement (limited period rectification, production halt rectification and shutdown) on the other hand. At present, technologies and methods for risk monitoring and prevention and control capability analysis of dust explosion-related enterprises in cities are not available, and products for risk monitoring and prevention and control analysis of the dust explosion-related enterprises in cities based on geographic information, city big data (house information, road information, population information and rescue information) and advanced analysis (commercial intelligence, machine learning and the like) technologies are not available.
The embodiment of the application also provides an enterprise pollution risk prevention and control analysis method, which adopts any one of the enterprise pollution risk monitoring systems, and comprises the following steps:
acquiring basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network;
inquiring a first storage to obtain an enterprise risk value corresponding to the basic information of the target enterprise, wherein the first storage stores the corresponding relation between the basic information of different enterprises and the enterprise risk value; if the enterprise risk value is larger than a set value, determining the target enterprise as a high-risk polluted enterprise;
inquiring a second memory according to the peripheral environment information of the high-risk polluted enterprise to obtain the pollution risk of the high-risk polluted enterprise; the second storage stores corresponding relations between the surrounding environment information and pollution risks of different enterprises;
and outputting the basic information of the high-risk polluted enterprises, the surrounding environment information of the high-risk polluted enterprises and the pollution risks of the high-risk polluted enterprises.
In order to facilitate understanding of the prevention and control analysis method provided in the embodiments of the present application, the following description is made with reference to fig. 8.
Step 1: automatically identifying high-risk dust explosion-related enterprises;
specifically, the target enterprise is judged according to the risk occurrence probability of the target enterprise, the severity of the accident influence and the normative degree of the safety management, wherein the risk occurrence probability, the severity of the accident influence and the normative degree of the safety management can be specifically referred to the above expression in the system.
Step 2: and (4) analyzing the dangerousness and the control force, and assisting positive and negative supervision decisions.
Specifically, after the enterprise is judged to be a high-risk dust explosion-related enterprise, auxiliary government safety supervision decisions are provided according to enterprise basic information of the enterprise, the previous enterprise self safety control conditions, safety distance analysis, accident risk analysis and the previous government detection law enforcement conditions.
During specific analysis, the information acquisition module 200 can acquire enterprise daily special treatment self-checking data such as hidden danger, improvement, overdue non-improvement, improvement rate and the like of target enterprise special treatment self-checking in the past year of the target enterprise, the information processing module 300 evaluates the acquired enterprise daily special treatment self-checking data and the set improvement standard, analyzes the hidden danger data rule and the hidden danger improvement timeliness, and assists in evaluating whether the enterprise daily special treatment is in place. And the information processing module 300 judges whether the high-risk polluted enterprise has potential safety hazard according to the acquired basic information of the high-risk polluted enterprise and the set safety standard, and then outputs prompt information of whether the high-risk polluted enterprise has potential safety hazard through the output module 500.
After the target enterprise is determined to be the inauguration enterprise, the risk assessment module 400 determines the pollution risk of the target enterprise according to the acquired surrounding environment information of the target enterprise. When the information processing module 300 determines that the target enterprise is a risk enterprise, the risk assessment module 400 obtains the surrounding environment information of the target enterprise according to the local information in the basic information of the target enterprise, wherein the surrounding environment information includes a sensitive data target within the security distance of the target enterprise, and identifies the target enterprise with insufficient security distance; and analyzing the risk of possible accidents. Wherein the sensitive data office table comprises: the risk assessment module 400 performs secondary derivative disaster prediction analysis on data such as regular soil data, population density, building information, corporate data and the like, by combining with figures of people and enterprises in a spread range and data such as river data, traffic accidents, urban pipe networks and the like. When the target such as a kindergarten, a school, a hospital and the like exists in the safe distance range of the target enterprise, the target enterprise is subjected to risks caused by incapability according to the target. The output module 500 may output the basic information of the target enterprise, the surrounding environment information of the target enterprise, and the pollution risk of the target enterprise, so that the existing risk can be visually observed. The output module 500 may be a common display device such as a mobile terminal and a display screen, for example, an LED screen, a PC, a notebook, a PAD, a smart phone, and the like.
Through the system, the historical special inspection and law enforcement conditions of governments in the past are collected, and the enterprise risk, the enterprise self management and control and the enterprise economic condition are combined to evaluate whether the historical safety supervision of the governments is in place or not on one hand, and to assist in decision-making of future supervision plans and law enforcement (limited period rectification, production halt rectification and shutdown) on the other hand. At present, technologies and methods for risk monitoring and prevention and control capability analysis of dust explosion-related enterprises in cities are not available, and products for risk monitoring and prevention and control analysis of the dust explosion-related enterprises in cities based on geographic information, city big data (house information, road information, population information and rescue information) and advanced analysis (commercial intelligence, machine learning and the like) technologies are not available.
In an example, as shown in fig. 9, the monitoring apparatus 1000 is used to implement the function of the terminal device in the above method, and the monitoring apparatus 1000 may be a terminal device, or an apparatus in a terminal device. The monitoring device 1000 comprises at least one processor 1001 for implementing the functions of the device in the above method. For example, the processor 1001 may be configured to query a first database to obtain an enterprise risk value corresponding to the basic information of the target enterprise, where the first database stores corresponding relationships between the basic information and the enterprise risk values of different enterprises; and if the enterprise risk value is greater than the set value, determining the target enterprise as a high-risk polluted enterprise, specifically referring to the detailed description of the method, which is not described here.
In some embodiments, the monitoring device 1000 may also include at least one memory 1002 for storing program instructions and/or data. The memory 1002 is coupled to the processor 1001. The coupling in the embodiments of the present application is a spaced coupling or communication connection between devices, units or modules, and may be in an electrical, mechanical or other form, and is used for information interaction between the devices, units or modules. As another implementation, the memory 1002 may also be located outside of the monitoring device 1000. The processor 1001 may cooperate with the memory 1002. The processor 1001 may execute program instructions stored in the memory 1002. At least one of the at least one memory may be included in the processor.
In some embodiments, monitoring apparatus 1000 may also include a communication interface 1003 for communicating with other devices over a transmission medium, such that the apparatus used in monitoring apparatus 1000 may communicate with other devices. Illustratively, the communication interface 1003 may be a transceiver, circuit, bus, module, or other type of communication interface, which may be a network device or other terminal device, etc. The processor 1001 transmits and receives data using the communication interface 1003, and is used to implement the method in the above-described embodiment. Illustratively, the communication interface 1003 may be used to obtain basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network.
In an example, the monitoring apparatus 1000 is used to implement the functions of the modules in the method, and the monitoring apparatus 1000 may be a network device, or an apparatus in a network device. The monitoring device 1000 includes at least one processor 1001 for implementing the functions of the modules in the above-described method. For example, the processor 1001 may be configured to query a first database to obtain an enterprise risk value corresponding to the basic information of the target enterprise, where the first database stores corresponding relationships between the basic information and the enterprise risk values of different enterprises; and if the enterprise risk value is greater than the set value, determining the target enterprise as a high-risk polluted enterprise, specifically referring to the detailed description of the method, which is not described here.
In some embodiments, the monitoring device 1000 may also include at least one memory 1002 for storing program instructions and/or data. The memory 1002 is coupled to the processor 1001. The coupling in the embodiments of the present application is a spaced coupling or communication connection between devices, units or modules, and may be in an electrical, mechanical or other form, and is used for information interaction between the devices, units or modules. As another implementation, the memory 1002 may also be located outside of the monitoring device 1000. The processor 1001 may cooperate with the memory 1002. The processor 1001 may execute program instructions stored in the memory 1002. At least one of the at least one memory may be included in the processor.
In some embodiments, monitoring apparatus 1000 may also include a communication interface 1003 for communicating with other devices over a transmission medium, such that the apparatus used in monitoring apparatus 1000 may communicate with other devices. Illustratively, the communication interface 1003 may be a transceiver, circuit, bus, module, or other type of communication interface, which may be a network device or other terminal device, etc. The processor 1001 transmits and receives data using the communication interface 1003, and is used to implement the method in the above-described embodiment. Illustratively, communication interface 1003 may transmit a subchannel indication, a resource pool indication, or the like.
The embodiment of the present application does not limit the connection medium among the communication interface 1003, the processor 1001, and the memory 1002. For example, in fig. 9, the memory 1002, the processor 1001, and the communication interface 1003 may be connected by a bus, and the bus may be divided into an address bus, a data bus, a control bus, and the like.
In the embodiments of the present application, the processor may be a general-purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in a processor.
In the embodiment of the present application, the memory may be a nonvolatile memory, such as a Hard Disk Drive (HDD) or a solid-state drive (SSD), and may also be a volatile memory, for example, a random-access memory (RAM). The memory is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory in the embodiments of the present application may also be circuitry or any other device capable of performing a storage function for storing program instructions and/or data.
The method provided by the embodiment of the present application may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, a network appliance, a user device, or other programmable apparatus. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a Digital Video Disk (DVD)), or a semiconductor medium (e.g., an SSD), among others.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (22)
1. An enterprise pollution risk monitoring system, comprising:
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module is used for acquiring basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network;
the information processing module is used for inquiring a first storage to obtain an enterprise risk value corresponding to the basic information of the target enterprise, and the first storage stores the corresponding relation between the basic information of different enterprises and the enterprise risk value; if the enterprise risk value is larger than a set value, determining the target enterprise as a high-risk polluted enterprise;
the risk evaluation module is used for inquiring the second memory according to the peripheral environment information of the high-risk polluted enterprise to obtain the pollution risk of the high-risk polluted enterprise; the second storage stores corresponding relations between the surrounding environment information and pollution risks of different enterprises;
and the output module is used for outputting the basic information of the high-risk polluted enterprise, the surrounding environment information of the high-risk polluted enterprise and the pollution risk of the high-risk polluted enterprise.
2. The system of claim 1, wherein the information collection module is specifically configured to filter basic information of a target enterprise based on a set data type to obtain the basic information of the target enterprise.
3. The system according to claim 2, further comprising an information sorting module, wherein the information sorting module is configured to store the information collected by the information collecting module in the first storage, and when storing, eliminate duplicate information in the basic information of the target enterprise.
4. The system according to claim 1, wherein the correspondence between the basic information of the different enterprises and the enterprise risk values is specifically configured to obtain intrinsic risk information and management correction terms of enterprise production conditions of the different enterprises according to the basic information of the different enterprises, and determine the enterprise risk values according to the obtained intrinsic risk information and management correction terms of the enterprise production conditions.
5. The system of claim 4, wherein the enterprise risk value is R, wherein R1A, R1 is intrinsic risk information for the enterprise production conditions, and A is a regulatory amendment.
6. The system of claim 4 or 5, wherein the intrinsic risk information of the enterprise occurrence condition comprises: the likelihood of risk occurrence and the severity of the accident impact;
the information processing module is specifically configured to obtain inherent risk information of the enterprise occurrence condition according to the possibility of risk occurrence and the severity of the accident influence.
7. The system of claim 6, wherein the intrinsic risk information of the enterprise production conditions is R1, and R1 is P S, wherein P is the probability of enterprise risk occurrence and S is the severity of accident impact.
8. The system of claim 6 or 7, wherein the likelihood of an enterprise risk occurrence comprises: the type of dust removal system and the type of dust of an enterprise;
the information processing module is specifically used for calculating the score of the dust removal system type of the enterprise according to the dust removal system type of the enterprise and the score corresponding to the set dust removal system type; calculating the value of the dust type of the enterprise according to the dust type of the enterprise and the set value corresponding to the dust type; a risk probability of occurrence P-P1-P2 for the business; wherein P1 is the score of the dust removal system type of the enterprise, and P2 is the score of the dust type of the enterprise.
9. A system according to any of claims 4 to 8, wherein the management correction term comprises: safety standardization level and accident history;
the information processing module is specifically used for calculating the score of the safety standardization level of the enterprise according to the safety standardization level of the enterprise and the score corresponding to the set safety standardization level; calculating the score of the accident history of the enterprise according to the accident history of the enterprise and the set score corresponding to the accident history; the management correction term a is a1+ a2, where a1 is the score of the safety standardization level of the enterprise and a2 is the score of the accident history of the enterprise.
10. The system of any one of claims 1 to 9, wherein the ambient environment information comprises sensitive data objects within a target enterprise security distance.
11. The system according to any one of claims 1 to 10, wherein the information processing module is further configured to determine whether a potential safety hazard exists in the high-risk polluted enterprise according to the acquired basic information of the high-risk polluted enterprise and a set safety standard;
the output module is also used for outputting prompt information of whether the high-risk pollution enterprises have potential safety hazards.
12. An enterprise pollution risk prevention and control analysis method is characterized by comprising the following steps:
acquiring basic information of a target enterprise and surrounding environment information of the target enterprise through a communication network;
inquiring a first storage to obtain an enterprise risk value corresponding to the basic information of the target enterprise, wherein the first storage stores the corresponding relation between the basic information of different enterprises and the enterprise risk value; if the enterprise risk value is larger than a set value, determining the target enterprise as a high-risk polluted enterprise;
inquiring a second memory according to the peripheral environment information of the high-risk polluted enterprise to obtain the pollution risk of the high-risk polluted enterprise; the second storage stores corresponding relations between the surrounding environment information and pollution risks of different enterprises;
and outputting the basic information of the high-risk polluted enterprises, the surrounding environment information of the high-risk polluted enterprises and the pollution risks of the high-risk polluted enterprises.
13. The method according to claim 12, wherein the acquiring the basic information of the target enterprise and the ambient environment information of the target enterprise through the communication network includes:
and screening the basic information of the target enterprise through the communication network based on the set data type to acquire the basic information of the target enterprise.
14. The method of claim 13, further comprising:
and storing the information acquired by the information acquisition module in the first memory, and eliminating repeated information in the basic information of the target enterprise during storage.
15. The method according to claim 13, wherein the correspondence between the basic information of different enterprises and the enterprise risk values is specifically:
and according to the basic information of the different enterprises, acquiring the inherent risk information and the management correction term of the enterprise production conditions of the different enterprises, and determining the enterprise risk value according to the acquired inherent risk information and the management correction term of the enterprise production conditions.
16. The method of claim 15, wherein the business risk value is R, wherein R1 a, R1 is intrinsic risk information of the business' production conditions, and a is a regulatory amendment.
17. The method of claim 14 or 15, wherein the intrinsic risk information of the conditions of occurrence of the enterprise comprises: the likelihood of risk occurrence and the severity of the accident impact;
the method further comprises acquiring inherent risk information of the enterprise occurrence condition according to the possibility of the risk occurrence and the severity of the accident influence.
18. The method of claim 17, wherein the intrinsic risk information of the enterprise production conditions is R1, and R1 is P S, where P is the probability of enterprise risk occurrence and S is the severity of accident impact.
19. The method of claim 16 or 17, wherein the likelihood of an enterprise risk occurrence comprises: the type of dust removal system and the type of dust of an enterprise;
the method further comprises the following steps: calculating the score of the dust removal system type of the enterprise according to the dust removal system type of the enterprise and the set score corresponding to the dust removal system type; calculating the value of the dust type of the enterprise according to the dust type of the enterprise and the set value corresponding to the dust type; a risk probability of occurrence P-P1-P2 for the business; wherein P1 is the score of the dust removal system type of the enterprise, and P2 is the score of the dust type of the enterprise.
20. A method according to any of claims 15 to 19, wherein managing correction terms comprises: safety standardization level and accident history;
the method further comprises the following steps: calculating the score of the safety standardization level of the enterprise according to the safety standardization level of the enterprise and the score corresponding to the set safety standardization level; calculating the score of the accident history of the enterprise according to the accident history of the enterprise and the set score corresponding to the accident history; the management correction term a is a1+ a2, where a1 is the score of the safety standardization level of the enterprise and a2 is the score of the accident history of the enterprise.
21. The method of any one of claims 12 to 20, wherein the ambient environment information comprises sensitive data objects within a target enterprise security distance.
22. The method of any one of claims 12 to 21, further comprising: judging whether the high-risk polluted enterprises have potential safety hazards or not according to the acquired basic information of the high-risk polluted enterprises and the set safety standard;
and outputting prompt information of whether the high-risk pollution enterprises have potential safety hazards.
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