CN113706351A

CN113706351A - Block chain-based environmental control judgment method and system

Info

Publication number: CN113706351A
Application number: CN202110913221.8A
Authority: CN
Inventors: 王灿
Original assignee: Hainan Junlin Environmental Technology Co ltd
Current assignee: Hainan Junlin Environmental Technology Co ltd
Priority date: 2021-08-10
Filing date: 2021-08-10
Publication date: 2021-11-26

Abstract

The application relates to an environmental control judgment method and system based on a block chain, which comprises the steps of obtaining current environmental data to be evaluated uploaded by each preset environmental control area to be evaluated; respectively generating initial environment judgment actual weights after the environment judgment processing is finished, and screening out the initial environment judgment actual weights which do not meet the qualified weight data of the current judgment result; acquiring the irresistible environmental influence factor information of each to-be-evaluated environmental control area in the environmental data collection period, judging whether the irresistible environmental influence factor information has an association relation with unqualified environmental item data of each to-be-evaluated environmental control area, if so, filtering the unqualified environmental item data and generating a final environmental control judgment result. The invention filters the unqualified environmental project data and generates the final environmental prevention and treatment judgment result, thereby further realizing the accurate diagnosis of the environmental prevention and treatment effects in different areas.

Description

Block chain-based environmental control judgment method and system

Technical Field

The application relates to the technical field of computers, in particular to an environmental control judgment method and system based on a block chain.

Background

Blockchains are a term of art in information technology. In essence, the system is a shared database, and the data or information stored in the shared database has the characteristics of 'unforgeability', 'whole-course trace', 'traceability', 'public transparency', 'collective maintenance', and the like. Based on the characteristics, the block chain technology lays a solid 'trust' foundation, creates a reliable 'cooperation' mechanism and has wide application prospect.

With the development of the blockchain technology, blockchains are gradually applied to the field of environmental control, and for example, in the invention patent with the application number of CN202011521195.6, an unmanned aerial vehicle environmental pollution remote measurement data processing method and system based on blockchains are disclosed, which includes: step one, acquiring noise data of a construction site and storing the noise data in a block chain database; step two, when the unmanned aerial vehicle works, the noise generated by the construction site is collected in real time by using the sound intensity sensor, and whether the noise generated by the construction site causes noise pollution or not is judged by combining the information in the block chain database; step three, when noise pollution is caused, the central control module is combined with the sound intensity storage module and the time processor to obtain the noise duration to judge whether the comparison result meets the preset condition, and when the comparison result meets the preset condition, the central control module controls the alarm module to inform a construction site supervisor of the coming treatment; and step four, when the preset conditions are not met, the central control module controls the alarm module to make an environment-friendly reporting call of noise pollution.

Although the technical scheme can improve the accuracy of judging the noise pollution, the processing is timely, and the time is saved, the method cannot be well applied to the result judgment after the environmental protection, namely the method has some limitations with the scheme in the prior art, and the problem of accurate judgment of the environmental protection effect is caused.

Disclosure of Invention

Therefore, it is necessary to provide a method and a system for evaluating environmental protection based on a block chain, which can improve the accuracy of the environmental protection effect.

The technical scheme of the invention is as follows:

a blockchain-based environmental control assessment method, the method comprising:

acquiring current environmental data to be evaluated uploaded by each preset environmental control area to be evaluated; one to-be-evaluated environmental prevention and control area corresponds to one current to-be-evaluated environmental data, and each current to-be-evaluated environmental data comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data; acquiring current environment judgment standard data and current judgment result qualified weight data from a preset block chain storage module, performing environment judgment processing on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, respectively generating initial environment judgment actual weights after the environment judgment processing is completed, comparing each initial environment judgment actual weight with the current judgment result qualified weight data, and screening out initial environment judgment actual weights which do not meet the current judgment result qualified weight data; and performing unqualified analysis on the environment data collection period, the basic environment parameter data and the current environment crowd health data of the to-be-evaluated environment control area corresponding to the initial environment evaluation actual weight which does not meet the qualification weight data of the current evaluation result, respectively generating unqualified environment item data, acquiring the ineffectiveness environment influence factor information of each to-be-evaluated environment control area in the environment data collection period according to each unqualified environment item data, judging whether the ineffectiveness environment influence factor information has an incidence relation with the unqualified environment item data of each to-be-evaluated environment control area, and filtering the unqualified environment item data and generating a final environment control evaluation result if the judgment is yes.

Specifically, the method includes performing unqualified item analysis on an environmental data collection cycle, basic environmental parameter data and current environmental crowd health data of an environmental control area to be evaluated corresponding to an initial environmental evaluation actual weight which does not satisfy the qualification weight data of the current evaluation result, generating unqualified environmental item data respectively, acquiring ineffectiveness environmental influence factor information of each environmental control area to be evaluated in the environmental data collection cycle according to each unqualified environmental item data, and judging whether the ineffectiveness environmental influence factor information has an association relationship with the unqualified environmental item data of each environmental control area to be evaluated, and specifically includes:

performing unqualified analysis on the environment data collection period, the basic environment parameter data and the current environment crowd health data of the environment control area to be evaluated corresponding to the screened initial environment evaluation actual weight which does not satisfy the current evaluation result qualified weight data, respectively generating unqualified environment item data, acquiring the inefficacy environment influence factor information of each environment control area to be evaluated in the environment data collection period according to each unqualified environment item data, and generating an inefficacy generation central area point; generating a preset specific area in a radial direction based on the force-inelasticity generating central area point, and forming a force-inelasticity influence area; screening an environment control area to be evaluated in the force-ineffectiveness influence area from the force-ineffectiveness influence area according to the force-ineffectiveness influence area, acquiring unqualified environment item data corresponding to the screened environment control area to be evaluated, and recording the unqualified environment item data as environment item data to be evaluated; acquiring an inelasticity type according to the inelasticity environmental influence factor information, and judging whether the inelasticity type is matched with the environmental project data to be judged; and if the inelasticity type is judged to be matched with the environmental item data to be judged, judging that the inelasticity environmental influence factor information has an association relation with the unqualified environmental item data of each environmental control area to be evaluated, and if the inelasticity type is judged not to be matched with the environmental item data to be judged, judging that the inelasticity environmental influence factor information does not have association data with the unqualified environmental item data of each environmental control area to be evaluated.

Specifically, if it is determined that the ineffectiveness force type matches the to-be-determined environmental item data, it is determined that the ineffectiveness force environmental influence factor information has an association relationship with the unqualified environmental item data of each to-be-evaluated environmental control area, and if it is determined that the ineffectiveness force type does not match the to-be-determined environmental item data, it is determined that the ineffectiveness force environmental influence factor information does not have association data with the unqualified environmental item data of each to-be-evaluated environmental control area, which specifically includes:

respectively obtaining the type of each unqualified item in the environmental item data to be judged, and marking as an unqualified item type; respectively comparing the unqualified item types with the inequality item types, and respectively generating unqualified item influence weights; counting the actual number of the unqualified project influence weights meeting the preset standard matching degree value, and when the actual number is more than 60% of the number of the unqualified project types, determining that the inequality force type is matched with the environmental project data to be determined; and when the actual number is not more than 60% of the number of each unqualified item type, determining that the force-inequality type does not match the environmental item data to be determined.

Specifically, according to the inelasticity influence area, screening an environment control area to be evaluated in the inelasticity influence area from the inelasticity influence area, acquiring unqualified environment item data corresponding to the screened environment control area to be evaluated, and recording the unqualified environment item data as environment item data to be evaluated; then also comprises the following steps:

forming an expansion influence area after the ineffectiveness influence area is radiated outwards for a second specific distance, acquiring an environment control area to be evaluated in the expansion influence area, and recording the environment control area as a re-judgment environment area; acquiring unqualified environment item data in the re-judgment environment area, and acquiring an area influence relation between the unqualified environment item data in the re-judgment environment area and the unqualified environment item data in an environment control area to be judged in the force-irresistance influence area; and if the judging area influence relation reaches the preset actual association relation, dividing the corresponding re-judging environment area into environment item data to be judged.

Specifically, current environment judgment standard data and current judgment result qualified weight data are obtained from a preset block chain storage module, environment judgment processing is carried out on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, initial environment judgment actual weights are respectively generated after the environment judgment processing is finished, each initial environment judgment actual weight is compared with the current judgment result qualified weight data, and an initial environment judgment actual weight which does not meet the current judgment result qualified weight data is screened out; the method also comprises the following steps:

a block chain storage module is pre-established, and initial environment judgment standard data and initial judgment result qualified weight data at the current moment are acquired based on the block chain storage module; acquiring actual updating data of the initial environment judgment standard data and the initial judgment result qualified weight data in real time, and generating an updating parameter adjusting instruction based on the actual updating data; updating the initial environment judgment standard data and the initial judgment result qualified weight data based on the updating parameter adjusting instruction, and respectively generating current environment judgment standard data and current judgment result qualified weight data; and storing the current environment judgment standard data and the current judgment result qualified weight data in the block chain storage module in a Hash chain linking mode.

Specifically, an environmental control judgment system based on a blockchain, the system comprising:

the data acquisition module is used for acquiring the current environment data to be evaluated uploaded by each preset environment control area to be evaluated; one to-be-evaluated environmental prevention and control area corresponds to one current to-be-evaluated environmental data, and each current to-be-evaluated environmental data comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data;

the data screening module is used for acquiring current environment judgment standard data and current judgment result qualified weight data from a preset block chain storage module, performing environment judgment processing on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, respectively generating initial environment judgment actual weights after the environment judgment processing is completed, comparing each initial environment judgment actual weight with the current judgment result qualified weight data, and screening out initial environment judgment actual weights which do not meet the current judgment result qualified weight data;

and the result generation module is used for carrying out unqualified item analysis on the environment data collection period, the basic environment parameter data and the current environment crowd health data of the to-be-evaluated environment control area corresponding to the initial environment evaluation actual weight which does not meet the qualification weight data of the current evaluation result, respectively generating unqualified environment item data, acquiring the ineffectiveness environment influence factor information of each to-be-evaluated environment control area in the environment data collection period according to each unqualified environment item data, judging whether the ineffectiveness environment influence factor information has an association relationship with the unqualified environment item data of each to-be-evaluated environment control area, and filtering the unqualified environment item data and generating a final environment control evaluation result if the ineffectiveness environment influence factor information is judged to be the unqualified environment item data.

Specifically, the system further comprises:

the judgment result module is used for carrying out unqualified item analysis on the environment data collection period, the basic environment parameter data and the current environment crowd health data of the to-be-judged environment control area corresponding to the screened initial environment judgment actual weight which does not meet the current judgment result qualified weight data, respectively generating unqualified environment item data, acquiring the ineffectiveness environment influence factor information of each to-be-judged environment control area in the environment data collection period according to each unqualified environment item data, and generating an ineffectiveness generation central area point;

the force-inelasticity module is used for generating a preset specific region in a radial direction of a central region point based on the force-inelasticity and forming a force-inelasticity influence region;

the resistance influence module is used for screening an environment control area to be evaluated in the ineffectiveness influence area from the ineffectiveness influence area according to the ineffectiveness influence area, acquiring unqualified environment item data corresponding to the screened environment control area to be evaluated, and recording the unqualified environment item data as environment item data to be evaluated;

the environment influence module is used for acquiring an inelasticity type according to the inelasticity environment influence factor information and judging whether the inelasticity type is matched with the environment project data to be judged;

and the prevention and control area module is used for judging that the ineffectiveness environment influence factor information has an association relation with the unqualified environment item data of each environment prevention and control area to be evaluated if the ineffectiveness type is judged to be matched with the environment item data to be evaluated, and judging that the ineffectiveness environment influence factor information does not have association data with the unqualified environment item data of each environment prevention and control area to be evaluated if the ineffectiveness type is judged to be not matched with the environment item data to be evaluated.

Specifically, the system further comprises:

the environment item module is used for respectively acquiring the types of the unqualified items in the environment item data to be judged and marking as unqualified item types;

the qualified item module is used for respectively comparing the unqualified item types with the inequality resistance types and respectively generating unqualified item influence weights;

the influence weight module is used for counting the actual number of the influence weights of the unqualified items meeting the preset standard matching degree value, and when the actual number is more than 60% of the number of the types of the unqualified items, the inelasticity type is judged to be matched with the environmental item data to be judged; when the actual number is not more than 60% of the number of each unqualified item type, determining that the force-inequality type does not match the environmental item data to be determined;

the divergence distance module is used for forming an expansion influence area after the ineffectiveness influence area diverges outwards for a second specific distance, acquiring an environment control area to be evaluated in the expansion influence area and recording the environment control area as a re-judgment environment area;

the influence area module is used for obtaining the area influence relationship between the qualified environmental item data and the unqualified environmental item data of the environmental control area to be evaluated in the force-ineffectiveness influence area;

the influence relation module is used for dividing the corresponding re-judgment environment area into environment item data to be judged if the judgment area influence relation reaches the preset real association relation;

the judgment storage module is used for pre-establishing a block chain storage module and acquiring initial environment judgment standard data and initial judgment result qualified weight data at the current moment based on the block chain storage module;

the standard data module is used for acquiring actual updating data of the initial environment judgment standard data and the initial judgment result qualified weight data in real time and generating an updating parameter adjusting instruction based on the actual updating data;

the result qualified module is used for updating the initial environment judgment standard data and the initial judgment result qualified weight data by the updating parameter adjusting instruction and respectively generating current environment judgment standard data and current judgment result qualified weight data;

and the Hash chain loading module is used for storing the current environment judgment standard data and the current judgment result qualified weight data in the block chain storage module in a Hash chain loading mode.

Specifically, the computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above block chain-based environmental control assessment method when executing the computer program.

Specifically, a computer-readable storage medium stores thereon a computer program which, when executed by a processor, implements the steps of the above-described blockchain-based environmental control assessment method.

The invention has the following technical effects:

according to the block chain-based environmental control judgment method and system, the current environmental data to be evaluated uploaded by each preset environmental control area to be evaluated are acquired in sequence; one to-be-evaluated environmental prevention and control area corresponds to one current to-be-evaluated environmental data, and each current to-be-evaluated environmental data comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data; acquiring current environment judgment standard data and current judgment result qualified weight data from a preset block chain storage module, performing environment judgment processing on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, respectively generating initial environment judgment actual weights after the environment judgment processing is completed, comparing each initial environment judgment actual weight with the current judgment result qualified weight data, and screening out initial environment judgment actual weights which do not meet the current judgment result qualified weight data; the environment data collection period, the basic environment parameter data and the current environment crowd health data of the environment control area to be evaluated corresponding to the initial environment evaluation actual weight which does not satisfy the qualification weight data of the current evaluation result are analyzed in a non-qualified way, unqualified environment item data are respectively generated, the ineffectiveness environment influence factor information of each environment control area to be evaluated in the environment data collection period is obtained according to each unqualified environment item data, whether the ineffectiveness environment influence factor information has a correlation with the unqualified environment item data of each environment control area to be evaluated is judged, if yes, the unqualified environment item data are filtered and final environment control evaluation results are generated, namely, each environment control area to be evaluated is preset, and when the environment evaluation is carried out on each environment control area to be evaluated, the current environmental data to be evaluated uploaded by each environmental control area to be evaluated can be obtained in a regional mode, one environmental control area to be evaluated corresponds to one current environmental data to be evaluated, each current environmental data to be evaluated comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data, regional obtaining of the data is achieved, accuracy of environmental control evaluation and high efficiency of data processing are improved, then the current environmental evaluation standard data and the current evaluation result qualification weight data are preset and stored in a block chain storage module, non-tampering storage of the current environmental evaluation standard data and the current evaluation result qualification weight data is achieved through the block chain storage module and obtained from the block chain storage module when needed, and the environmental data collection period of each environmental control area to be evaluated is conducted on the basis of the current environmental evaluation standard data The method comprises the steps of carrying out environment judgment processing on date, basic environment parameter data and current environment crowd health data, and respectively generating initial environment judgment actual weights after the environment judgment processing is finished, wherein the initial environment judgment actual weights represent scores of current environment control effects of environment control areas to be judged, the scores are qualified only if the initial environment judgment actual weights meeting the current judgment result qualified weight data, but the initial environment judgment actual weights which do not meet the current judgment result qualified weight data are generated due to force ineffectiveness on the basis of different areas, so that the initial environment judgment actual weights which do not meet the current judgment result qualified weight data are screened out by comparing the initial environment judgment actual weights with the current judgment result qualified weight data, and the screened initial environment judgment actual weights which do not meet the current judgment result qualified weight data are subjected to environment judgment Analyzing unqualified environmental data collection periods, basic environmental parameter data and current environmental crowd health data of the environmental control areas to be evaluated correspondingly, and respectively generating unqualified environmental item data, wherein the unqualified environmental item data is data of initial environmental evaluation actual weights which cause that the current evaluation result qualification weight data is not satisfied, then acquiring ineffectiveness environmental influence factor information of each environmental control area to be evaluated in the environmental data collection periods according to each unqualified environmental item data, judging whether the ineffectiveness environmental influence factor information has a correlation with the unqualified environmental item data of each environmental control area to be evaluated, if so, indicating that the initial environmental evaluation actual weights which do not satisfy the current evaluation result qualification weight data are ineffectiveness at the moment, therefore, the judgment of disqualification is obviously inaccurate, the disqualified environmental item data are filtered, the final environmental prevention and control judgment result is generated, and the accurate diagnosis of the environmental prevention and control effects in different areas is further realized.

Drawings

FIG. 1 is a schematic flow chart illustrating a method for evaluating environmental protection based on blockchains according to an embodiment;

FIG. 2 is a block diagram of an embodiment of a system for environmental control assessment based on blockchains;

FIG. 3 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

In one embodiment, as shown in fig. 1, there is provided a method for judging environmental control based on a blockchain, the method including:

step S100: acquiring current environmental data to be evaluated uploaded by each preset environmental control area to be evaluated; one to-be-evaluated environmental prevention and control area corresponds to one current to-be-evaluated environmental data, and each current to-be-evaluated environmental data comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data;

specifically, the environmental control area to be evaluated is preset, and may be set to a town, a village or a village, for example. The environmental data collection period may be, for example, 3 months, 6 months, 1 year, or 2 years.

The basic environmental parameter data at least comprises parameters representing environmental conditions, such as radiation, water vapor pressure loss, temperature, soil humidity and the like.

Further, the current environmental population health data comprises related disease conditions caused by environmental pollution in town, a village or a village.

Step S200: acquiring current environment judgment standard data and current judgment result qualified weight data from a preset block chain storage module, performing environment judgment processing on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, respectively generating initial environment judgment actual weights after the environment judgment processing is completed, comparing each initial environment judgment actual weight with the current judgment result qualified weight data, and screening out initial environment judgment actual weights which do not meet the current judgment result qualified weight data;

specifically, the current environment judgment standard data and the current judgment result qualified weight data are preset and stored in the blockchain storage module, the blockchain storage module realizes the non-falsification storage of the current environment judgment standard data and the current judgment result qualified weight data, and the current environment judgment standard data and the current judgment result qualified weight data are acquired from the blockchain storage module when needed.

And respectively generating initial environment judgment actual weights after the environment judgment processing is finished, wherein the initial environment judgment actual weights represent the scores of the current environment control effect of the environment control area to be judged, the scores are qualified only if the initial environment judgment actual weights meet the qualified weight data of the current judgment result, but the initial environment judgment actual weights which do not meet the qualified weight data of the current judgment result due to force inelasticity can be generated on the basis of different areas.

Step S300: and performing unqualified analysis on the environment data collection period, the basic environment parameter data and the current environment crowd health data of the to-be-evaluated environment control area corresponding to the initial environment evaluation actual weight which does not meet the qualification weight data of the current evaluation result, respectively generating unqualified environment item data, acquiring the ineffectiveness environment influence factor information of each to-be-evaluated environment control area in the environment data collection period according to each unqualified environment item data, judging whether the ineffectiveness environment influence factor information has an incidence relation with the unqualified environment item data of each to-be-evaluated environment control area, and filtering the unqualified environment item data and generating a final environment control evaluation result if the judgment is yes.

Specifically, in order to realize more accurate judgment, each initial environment judgment actual weight is compared with the current judgment result qualified weight data, an initial environment judgment actual weight which does not satisfy the current judgment result qualified weight data is screened out, an environment data collection period, basic environment parameter data and current environment crowd health data of an environment control area to be judged corresponding to the screened initial environment judgment actual weight which does not satisfy the current judgment result qualified weight data are subjected to unqualified item analysis, unqualified environment item data is respectively generated, wherein the unqualified environment item data is the data of the initial environment judgment actual weight which does not satisfy the current judgment result qualified weight data, and then, the ineligible environment influence factor information of each environment control area to be judged in the environment data collection period is obtained according to each unqualified environment item data, and judging whether the ineffectiveness environmental influence factor information has an incidence relation with unqualified environmental item data of each environmental control area to be evaluated, if so, indicating that the initial environmental evaluation actual weight which does not meet the qualification weight data of the current evaluation result is caused by ineffectiveness, so that the judgment is unqualified obviously, further filtering the unqualified environmental item data and generating a final environmental control evaluation result, and further realizing accurate diagnosis of the environmental control effects of different areas.

In one embodiment, step S300: the method comprises the steps of performing unqualified analysis on an environment data collection period, basic environment parameter data and current environment crowd health data of an environment control area to be evaluated corresponding to an initial environment evaluation actual weight which does not meet the qualified weight data of the current evaluation result, respectively generating unqualified environment item data, acquiring ineffectiveness environment influence factor information of each environment control area to be evaluated in the environment data collection period according to each unqualified environment item data, and judging whether the ineffectiveness environment influence factor information has an incidence relation with the unqualified environment item data of each environment control area to be evaluated, and specifically comprises the following steps:

step S310: performing unqualified analysis on the environment data collection period, the basic environment parameter data and the current environment crowd health data of the environment control area to be evaluated corresponding to the screened initial environment evaluation actual weight which does not satisfy the current evaluation result qualified weight data, respectively generating unqualified environment item data, acquiring the inefficacy environment influence factor information of each environment control area to be evaluated in the environment data collection period according to each unqualified environment item data, and generating an inefficacy generation central area point;

specifically, the unqualified environmental project data is an index of each environmental parameter which does not meet the qualified weight data of the current judgment result, and if the projects such as radiation, water vapor pressure deficiency, temperature, soil humidity and the like do not reach the standard, the data corresponding to the partial projects are the unqualified environmental project data.

The information of the inelasticity environmental influence factors is, for example, a fire disaster occurs in a local area, water source pollution and atmospheric pollution caused by the fire disaster, and then the fire disaster is the information of the inelasticity environmental influence factors, and meanwhile, the starting place of the fire disaster is an inelasticity force generation central area point.

Step S320: generating a preset specific area in a radial direction based on the force-inelasticity generating central area point, and forming a force-inelasticity influence area;

by presetting a specific area, the regional data selection is realized, and the data processing efficiency is improved.

Step S330: screening an environment control area to be evaluated in the force-ineffectiveness influence area from the force-ineffectiveness influence area according to the force-ineffectiveness influence area, acquiring unqualified environment item data corresponding to the screened environment control area to be evaluated, and recording the unqualified environment item data as environment item data to be evaluated;

step S340: acquiring an inelasticity type according to the inelasticity environmental influence factor information, and judging whether the inelasticity type is matched with the environmental project data to be judged;

specifically, the types of inefficacy include a fire type, a flood type, and others.

And then judging whether the type of the environmental item data to be judged is matched with the type of the force-ineffectiveness, so as to judge whether the force-ineffectiveness environmental influence factor information has an incidence relation with the unqualified environmental item data of each environmental prevention and control area to be judged.

Step S350: and if the inelasticity type is judged to be matched with the environmental item data to be judged, judging that the inelasticity environmental influence factor information has an association relation with the unqualified environmental item data of each environmental control area to be evaluated, and if the inelasticity type is judged not to be matched with the environmental item data to be judged, judging that the inelasticity environmental influence factor information does not have association data with the unqualified environmental item data of each environmental control area to be evaluated.

Specifically, in this step, the environment data collection period, the basic environment parameter data and the current environment crowd health data of the environment control area to be evaluated corresponding to the initial environment evaluation actual weight value which is screened out and does not satisfy the qualification weight value data of the current evaluation result are subjected to unqualified item analysis, unqualified environment item data are respectively generated, the ineffectiveness environment influence factor information of each environment control area to be evaluated in the environment data collection period is obtained according to each unqualified environment item data, an ineffectiveness force generation central area point is generated, then a preset specific area is radially distributed based on the ineffectiveness force generation central area point, an ineffectiveness force influence area is formed, the environment control area to be evaluated in the ineffectiveness force area is screened out from the ineffectiveness force influence area according to the ineffectiveness force influence area, and acquiring unqualified environment item data corresponding to the screened to-be-evaluated environment control areas and recording the unqualified environment item data as to-be-evaluated environment item data, so that whether the type of the to-be-evaluated environment item data is matched with the type of the force irresistance is judged, and whether the force irresistance environment influence factor information and the unqualified environment item data of each to-be-evaluated environment control area have an association relation is judged.

Further, if the inelasticity type is judged to be matched with the to-be-judged environmental item data, the inelasticity environmental influence factor information is judged to have an association relation with the unqualified environmental item data of each to-be-judged environmental prevention and treatment area, and if the inelasticity type is judged to be not matched with the to-be-judged environmental item data, the inelasticity environmental influence factor information is judged to have no association data with the unqualified environmental item data of each to-be-judged environmental prevention and treatment area.

In one embodiment, step S350: if the inelasticity type is judged to be matched with the environmental item data to be judged, judging that the inelasticity environmental influence factor information has an association relation with the unqualified environmental item data of each environmental control area to be evaluated, and if the inelasticity type is judged to be not matched with the environmental item data to be judged, judging that the inelasticity environmental influence factor information does not have association data with the unqualified environmental item data of each environmental control area to be evaluated, specifically comprising the following steps:

step S351: respectively obtaining the type of each unqualified item in the environmental item data to be judged, and marking as an unqualified item type;

step S352: respectively comparing the unqualified item types with the inequality item types, and respectively generating unqualified item influence weights;

step S353: counting the actual number of the unqualified project influence weights meeting the preset standard matching degree value, and when the actual number is more than 60% of the number of the unqualified project types, determining that the inequality force type is matched with the environmental project data to be determined; and when the actual number is not more than 60% of the number of each unqualified item type, determining that the force-inequality type does not match the environmental item data to be determined.

Specifically, in this step, the types of the unqualified items in the environmental item data to be determined are obtained respectively and recorded as unqualified item types; and then comparing the unqualified item types with the inequality types respectively, and generating unqualified item influence weights respectively, wherein the unqualified item influence weights represent the influence of the inequality types on the unqualified item types, and similarly, when the unqualified item types are fire disasters, the influence on the unqualified item types is small when the unqualified item types are the dry and wet quality of the land, the numerical value of the unqualified item influence weights is small, and when the unqualified item types are haze concentration, the haze is serious due to a large amount of dust generated by the fire disasters, and the numerical value of the unqualified item influence weights is large.

Further, counting the actual number of the unqualified project influence weights meeting the preset standard matching degree value, and when the actual number is more than 60% of the number of the unqualified project types, determining that the inelasticity type is matched with the environmental project data to be determined, wherein 60% is preset, and certainly, other parameters can be set to determine whether the inelasticity type is matched with the environmental project data to be determined.

In one embodiment, step S330: screening an environment control area to be evaluated in the force-ineffectiveness influence area from the force-ineffectiveness influence area according to the force-ineffectiveness influence area, acquiring unqualified environment item data corresponding to the screened environment control area to be evaluated, and recording the unqualified environment item data as environment item data to be evaluated; then also comprises the following steps:

step S331: forming an expansion influence area after the ineffectiveness influence area is radiated outwards for a second specific distance, acquiring an environment control area to be evaluated in the expansion influence area, and recording the environment control area as a re-judgment environment area;

step S332: acquiring unqualified environment item data in the re-judgment environment area, and acquiring an area influence relation between the unqualified environment item data in the re-judgment environment area and the unqualified environment item data in an environment control area to be judged in the force-irresistance influence area;

the area influence relationship may be represented by using a specific numerical value, and the application is not particularly limited.

Step S333: and if the judging area influence relation reaches the preset actual association relation, dividing the corresponding re-judging environment area into environment item data to be judged.

Specifically, for more precise determination, by further setting a second specific distance, i.e. forming an extended influence region after the force-ineligible influence region is dispersed outward by the second specific distance, and the environmental control area to be evaluated in the expanded influence area is obtained and recorded as the re-judgment environmental area which is an area closer to the environmental control area to be evaluated in the force-ineffectiveness influence area, so that the environment area is judged to be possibly influenced by the environment control area to be judged in the force-ineffectiveness area, therefore, by acquiring the area influence relationship between the unqualified environmental item data in the re-judgment environmental area and the unqualified environmental item data in the environmental prevention and control area to be judged in the force-ineffectiveness area, and if the influence relation of the judgment area reaches the preset actual association relation, dividing the corresponding re-judgment environment area into environment item data to be judged.

In one embodiment, step S200: acquiring current environment judgment standard data and current judgment result qualified weight data from a preset block chain storage module, performing environment judgment processing on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, respectively generating initial environment judgment actual weights after the environment judgment processing is completed, comparing each initial environment judgment actual weight with the current judgment result qualified weight data, and screening out initial environment judgment actual weights which do not meet the current judgment result qualified weight data; the method also comprises the following steps:

step S201: a block chain storage module is pre-established, and initial environment judgment standard data and initial judgment result qualified weight data at the current moment are acquired based on the block chain storage module;

step S202: acquiring actual updating data of the initial environment judgment standard data and the initial judgment result qualified weight data in real time, and generating an updating parameter adjusting instruction based on the actual updating data;

step S203: updating the initial environment judgment standard data and the initial judgment result qualified weight data based on the updating parameter adjusting instruction, and respectively generating current environment judgment standard data and current judgment result qualified weight data;

step S204: and storing the current environment judgment standard data and the current judgment result qualified weight data in the block chain storage module in a Hash chain linking mode.

Specifically, in order to ensure the accuracy and the real-time performance of the current environment judgment standard data and the current judgment result qualified weight data, a block chain storage module is pre-established, and initial environment judgment standard data and initial judgment result qualified weight data at the current moment are acquired based on the block chain storage module; then, actual updating data of the initial environment judgment standard data and the initial judgment result qualified weight data are obtained in real time, and an updating parameter adjusting instruction is generated based on the actual updating data; and then, updating the initial environment judgment standard data and the initial judgment result qualified weight data based on the updating parameter adjusting instruction, and respectively generating current environment judgment standard data and current judgment result qualified weight data, so that the accuracy of the judgment data is improved, and the result of environment control is judged with high accuracy.

In conclusion, the method sequentially acquires the current environmental data to be evaluated uploaded by each preset environmental control area to be evaluated; one to-be-evaluated environmental prevention and control area corresponds to one current to-be-evaluated environmental data, and each current to-be-evaluated environmental data comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data; acquiring current environment judgment standard data and current judgment result qualified weight data from a preset block chain storage module, performing environment judgment processing on the environment data collection period, basic environment parameter data and current environment crowd health data of each to-be-judged environment control area based on the current environment judgment standard data, respectively generating initial environment judgment actual weights after the environment judgment processing is completed, comparing each initial environment judgment actual weight with the current judgment result qualified weight data, and screening out initial environment judgment actual weights which do not meet the current judgment result qualified weight data; the environment data collection period, the basic environment parameter data and the current environment crowd health data of the environment control area to be evaluated corresponding to the initial environment evaluation actual weight which does not satisfy the qualification weight data of the current evaluation result are analyzed in a non-qualified way, unqualified environment item data are respectively generated, the ineffectiveness environment influence factor information of each environment control area to be evaluated in the environment data collection period is obtained according to each unqualified environment item data, whether the ineffectiveness environment influence factor information has a correlation with the unqualified environment item data of each environment control area to be evaluated is judged, if yes, the unqualified environment item data are filtered and final environment control evaluation results are generated, namely, each environment control area to be evaluated is preset, and when the environment evaluation is carried out on each environment control area to be evaluated, the current environmental data to be evaluated uploaded by each environmental control area to be evaluated can be obtained in a regional mode, one environmental control area to be evaluated corresponds to one current environmental data to be evaluated, each current environmental data to be evaluated comprises an environmental data collection period, basic environmental parameter data and current environmental crowd health data, regional obtaining of the data is achieved, accuracy of environmental control evaluation and high efficiency of data processing are improved, then the current environmental evaluation standard data and the current evaluation result qualification weight data are preset and stored in a block chain storage module, non-tampering storage of the current environmental evaluation standard data and the current evaluation result qualification weight data is achieved through the block chain storage module and obtained from the block chain storage module when needed, and the environmental data collection period of each environmental control area to be evaluated is conducted on the basis of the current environmental evaluation standard data The method comprises the steps of carrying out environment judgment processing on date, basic environment parameter data and current environment crowd health data, and respectively generating initial environment judgment actual weights after the environment judgment processing is finished, wherein the initial environment judgment actual weights represent scores of current environment control effects of environment control areas to be judged, the scores are qualified only if the initial environment judgment actual weights meeting the current judgment result qualified weight data, but the initial environment judgment actual weights which do not meet the current judgment result qualified weight data are generated due to force ineffectiveness on the basis of different areas, so that the initial environment judgment actual weights which do not meet the current judgment result qualified weight data are screened out by comparing the initial environment judgment actual weights with the current judgment result qualified weight data, and the screened initial environment judgment actual weights which do not meet the current judgment result qualified weight data are subjected to environment judgment Analyzing unqualified environmental data collection periods, basic environmental parameter data and current environmental crowd health data of the environmental control areas to be evaluated correspondingly, and respectively generating unqualified environmental item data, wherein the unqualified environmental item data is data of initial environmental evaluation actual weights which cause that the current evaluation result qualification weight data is not satisfied, then acquiring ineffectiveness environmental influence factor information of each environmental control area to be evaluated in the environmental data collection periods according to each unqualified environmental item data, judging whether the ineffectiveness environmental influence factor information has a correlation with the unqualified environmental item data of each environmental control area to be evaluated, if so, indicating that the initial environmental evaluation actual weights which do not satisfy the current evaluation result qualification weight data are ineffectiveness at the moment, therefore, the judgment of disqualification is obviously inaccurate, the disqualified environmental item data are filtered, the final environmental prevention and control judgment result is generated, and the accurate diagnosis of the environmental prevention and control effects in different areas is further realized.

In one embodiment, as shown in fig. 2, a system for judgment of environmental control based on a blockchain, the system comprising:

In one embodiment, the system further comprises:

In one embodiment, as shown in fig. 3, a computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above-mentioned method for evaluating environmental control and prevention based on a blockchain when executing the computer program.

A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the above-described blockchain-based environmental control evaluation method.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. An environmental control judgment method based on a block chain is characterized by comprising the following steps:

2. The block chain-based environmental control evaluation method according to claim 1, wherein the method specifically includes performing ineligible analysis on an environmental data collection period, basic environmental parameter data, and current environmental population health data of an environmental control area to be evaluated, which correspond to an initial environmental evaluation actual weight that does not satisfy the current evaluation result qualification weight data, and generating respectively unqualified environmental item data, acquiring ineligible environmental influence factor information of each environmental control area to be evaluated in the environmental data collection period according to each unqualified environmental item data, and determining whether the ineligible environmental influence factor information has an association relationship with the unqualified environmental item data of each environmental control area to be evaluated, and specifically includes:

3. The method according to claim 2, wherein if it is determined that the type of inelasticity matches the environmental item data to be determined, it is determined that the information on the environment-affecting factor of inelasticity has an association relationship with the unqualified environmental item data of each environmental control area to be determined, and if it is determined that the type of inelasticity does not match the environmental item data to be determined, it is determined that the information on the environment-affecting factor of inelasticity does not have association data with the unqualified environmental item data of each environmental control area to be determined, specifically comprising:

4. The block chain-based environmental prevention and treatment evaluation method according to claim 3, wherein according to the ineffectiveness-resistant area, an environmental prevention and treatment area to be evaluated in the ineffectiveness-resistant area is screened out from the ineffectiveness-resistant area, and unqualified environmental item data corresponding to the screened environmental prevention and treatment area to be evaluated is obtained and recorded as environmental item data to be evaluated; then also comprises the following steps:

5. The method according to any one of claims 1 to 4, wherein current environmental evaluation standard data and current evaluation result qualification weight data are obtained from a preset block chain storage module, environmental evaluation processing is performed on the environmental data collection cycle, basic environmental parameter data and current environmental population health data of each environmental control area to be evaluated based on the current environmental evaluation standard data, initial environmental evaluation actual weights are respectively generated after the environmental evaluation processing is completed, each initial environmental evaluation actual weight is compared with the current evaluation result qualification weight data, and an initial environmental evaluation actual weight that does not satisfy the current evaluation result qualification weight data is screened out; the method also comprises the following steps:

6. An environmental control judgment system based on a blockchain, the system comprising:

7. The system according to claim 6, further comprising:

8. The system according to claim 6, further comprising:

9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 5 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.