CN113376327B - Environmental monitoring information management method and system based on big data - Google Patents
Environmental monitoring information management method and system based on big data Download PDFInfo
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Abstract
The application relates to an environmental monitoring information management method and system based on big data, which comprises the steps of acquiring the actual environmental grade information of each preset environmental monitoring standard area based on the big data, and setting the environmental monitoring standard area corresponding to the better actual environmental grade as a recommendable environmental control area; acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, and performing cluster analysis according to the recommendable environment parameter data set; and screening out an environment area to be managed matched with the same cluster associated environment characteristic data from a preset environment area database to be managed based on the same cluster associated environment characteristic data, and generating an optimal environment area monitoring report based on the same cluster optimal environment area and a recommendable environment parameter data set of the recommendable environment control area. The invention realizes the efficient, rapid and ordered management of the environment monitoring information and the high utilization rate.
Description
Technical Field
The present application relates to the field of environmental monitoring technologies, and in particular, to a method and a system for managing environmental monitoring information based on big data.
Background
Environmental monitoring refers to the activities of environmental monitoring mechanisms to monitor and measure environmental quality conditions. The environmental monitoring is to monitor and measure the index reflecting the environmental quality to determine the environmental pollution condition and the environmental quality. The environment monitoring mainly comprises the monitoring of physical indexes, the monitoring of chemical indexes and the monitoring of an ecosystem.
At present, with the development of big data, the combination of big data and environmental monitoring has appeared, for example, a water source environment monitoring device based on big data disclosed in the invention patent with publication number CN213068814U, a water source environment monitoring device based on big data comprises a floating device and a monitoring device body, the upper side wall surface of the floating device is fixedly connected with the monitoring device body, the floating device comprises a mounting frame, the inner side wall surface of the mounting frame is provided with a rotating groove, the inner side wall surface of the rotating groove is rotatably connected with a connecting structure, a filter screen is connected between the supporting rods, the lower end of the inner side back surface of the filter screen is fixedly connected with a stabilizing piece, one end of the device for arranging a floating pile is a movable component.
Obviously can see out, accessible connection structure carries out the adjustment of floating zone among the above-mentioned technical scheme so that monitoring devices is more stable in the course of the work, and the bracing piece is still installed to the stake lower extreme that floats simultaneously, and its inside filter screen that can connect is used for avoiding the floater to block monitoring mouth, and causes the problem that the monitoring result has the mistake. However, currently, most of the environmental monitoring data are collected, but the environmental monitoring data are not effectively utilized, which results in a problem of low utilization rate of the environmental monitoring data.
Disclosure of Invention
Accordingly, it is desirable to provide a method and a system for managing environment monitoring information based on big data, which can improve the utilization rate of the environment monitoring data.
The technical scheme of the invention is as follows:
a big data-based environmental monitoring information management method comprises the following steps:
acquiring actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area; acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating associated environment characteristic data of the same cluster after the cluster analysis; and screening out an environment area to be managed matched with the associated environment characteristic data of the same cluster from a preset environment area database to be managed based on the associated environment characteristic data of the same cluster, recording the environment area to be optimized as an optimal environment area of the same cluster, and generating an optimal environment area monitoring report based on the optimal environment area of the same cluster and a recommended environment parameter data set of a recommended environment control area.
Specifically, actual environment grade information of each preset environment monitoring standard area is obtained based on big data, a better actual environment grade is screened out from each actual environment grade information according to a specific proportion, and the environment monitoring standard area corresponding to the better actual environment grade is set as a recommendable environment control area; the method specifically comprises the following steps:
acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data, and generating an image environment data grade; acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data, and generating a parameter environmental data grade; comparing the image environment data grade with the parameter environment data grade, and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range; if the image environment data grade and the parameter environment data grade are judged not to be within a preset standard error range, generating an actual parameter adjustment weight; adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight, and generating actual environment grade information; and arranging the actual environment grade information according to the grade sequence, screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the ranks, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region.
Specifically, based on the same cluster associated environment characteristic data, screening out an environment area to be managed matched with the same cluster associated environment characteristic data from a preset environment area database to be managed, recording the environment area to be optimized as a same cluster optimal environment area, and generating an optimal environment area monitoring report based on the same cluster optimal environment area and a recommended environment parameter data set of a recommended environment control area; the method specifically comprises the following steps:
comparing the same cluster associated environment characteristic data with the environmental areas to be managed in a preset environmental area database to be managed one by one based on the same cluster associated environment characteristic data, and respectively generating environment data matching values; performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result; generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result; performing redundant feature filtering on the actual matching group data set, generating an environmental area to be managed matched with the same-cluster associated environmental feature data after the redundant feature filtering is completed, and marking the environmental area to be optimized as a same-cluster better environmental area; and extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of preferred environment areas and the recommendable environment control areas, and generating a preferred environment area monitoring report based on the same parameter characteristics.
Specifically, redundant feature filtering is performed on the actual matching group data set, an environment area to be managed matched with the same cluster associated environment feature data is generated after redundant feature filtering is completed, and the environment area to be optimized is recorded as a same cluster better environment area, which specifically includes:
acquiring current environment judgment standard data, and performing judgment standard parameter filtering on the same cluster associated environment characteristic data based on the current environment judgment standard data; generating real associated environment characteristic data after the evaluation standard parameters are filtered; performing redundant population filtering on the actual matched population data set based on the real associated environment feature data; and after the filtering of redundant groups is finished, generating an environmental area to be managed which is matched with the associated environmental characteristic data of the same cluster, and marking the environmental area to be optimized as an optimal environmental area of the same cluster.
Specifically, based on the same cluster associated environment feature data, screening out an environment area to be managed matched with the same cluster associated environment feature data from a preset environment area database to be managed, recording the environment area to be optimized as a same cluster preferred environment area, and generating a preferred environment area monitoring report based on the same cluster preferred environment area and a recommended environment parameter data set of a recommended environment control area, and then further comprising:
generating a report display interface according to the superior environment area monitoring report; splitting the monitoring report of the better environment region according to the data capacity of the data, generating a plurality of better data of the split environment region, and simultaneously acquiring the actual display area of the better data of each split environment region; acquiring the current terminal display area of the report display interface; and displaying according to a preset display proportion according to the actual display area and the current terminal display area.
Specifically, the environmental monitoring information management system based on big data comprises:
the proportion screening module is used for acquiring actual environment grade information of each preset environment monitoring standard region based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region;
the environment parameter module is used for acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating clustered associated environment characteristic data after the cluster analysis;
and the associated environment module is used for screening out an environment area to be managed matched with the associated environment characteristic data of the same cluster from a preset environment area database to be managed based on the associated environment characteristic data of the same cluster, recording the environment area to be optimized as an optimal environment area of the same cluster, and generating an optimal environment area monitoring report based on the optimal environment area of the same cluster and a recommended environment parameter data set of a recommended environment control area.
Specifically, the system further comprises:
the image acquisition module is used for acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data and generating an image environment data grade;
the module acquisition module is used for acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data and generating a parameter environmental data grade;
the data grade module is used for comparing the image environment data grade with the parameter environment data grade and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range or not;
the parameter environment module is used for generating an actual parameter adjustment weight if the image environment data grade and the parameter environment data grade are judged not to be in a preset standard error range;
the actual environment module is used for adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight and generating actual environment grade information;
and the recommended environment module is used for arranging the actual environment grade information according to the grade sequence, screening out a better actual environment grade from the actual environment grade information according to the proportion of top ten of the rank, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommended environment control region.
Specifically, the system further comprises:
the environment area module is used for comparing the same cluster associated environment characteristic data with environment areas to be managed in a preset environment area database to be managed one by one based on the same cluster associated environment characteristic data and respectively generating environment data matching values;
the convolution operation module is used for performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result;
the traversal convolution module is used for generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result;
the group data module is used for filtering redundant features of the actually matched group data set, generating an environment area to be managed matched with the associated environment feature data of the same cluster after the redundant features are filtered, and recording the environment area to be optimized as a better environment area of the same cluster;
the optimal environment module is used for extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of optimal environment areas and the recommendable environment control areas and generating an optimal environment area monitoring report based on the same parameter characteristics;
the standard data module is used for acquiring current environment judgment standard data and filtering judgment standard parameters of the same cluster associated environment characteristic data based on the current environment judgment standard data;
the parameter filtering module is used for generating real associated environment characteristic data after the judgment standard parameter filtering is finished;
a real correlation module for performing redundant population filtering on the actual matched population data set based on the real correlation environment feature data;
the group filtering module is used for generating an environment area to be managed matched with the same cluster associated environment characteristic data after the redundant group filtering is finished, and recording the environment area to be optimized as a same cluster better environment area;
the monitoring report module is used for generating a report display interface according to the monitoring report of the better environment area;
the optimal display module is used for splitting the optimal environment region monitoring report according to the data capacity of the data, generating a plurality of optimal split environment region data and acquiring the actual display area of the optimal split environment region data;
the terminal display module is used for acquiring the current terminal display area of the report display interface;
and the current terminal module is used for displaying according to the actual display area and the current terminal display area according to a preset display proportion.
Specifically, the computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the environment monitoring information management method based on big data 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 big-data based environmental monitoring information management method.
The invention has the following technical effects:
according to the environment monitoring information management method and system based on the big data, the actual environment grade information of each preset environment monitoring standard area is obtained sequentially based on the big data, a better actual environment grade is screened out from each actual environment grade information according to a specific proportion, and the environment monitoring standard area corresponding to the better actual environment grade is set as a recommendable environment control area; acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating associated environment characteristic data of the same cluster after the cluster analysis; the method comprises the steps of screening out environment areas to be managed matched with environment characteristic data to be managed from a preset environment area database to be managed based on the environment characteristic data to be clustered, recording the environment areas to be optimized as optimal environment areas to be clustered, generating optimal environment area monitoring reports based on the optimal environment areas to be clustered and recommended environment parameter data sets of control areas of the optimal environment areas and the recommended environment, screening the areas with optimal environment levels after the environment data of all the areas are monitored, namely screening the areas with the environmental data acquired based on big data, clustering and screening the environment areas to be managed matched with the environment characteristic data to be managed from the preset environment area database to be managed by utilizing the environment characteristic data to be clustered, matching the characteristics of one area to other areas with the same optimal environment, recommending the optimal environment areas to the other areas with the same optimal environment through the characteristics of one area, generating the optimal environment parameter data sets matched with the environment characteristic data to be managed from the environment area database to be managed by utilizing the environment characteristic data to be clustered, and further realizing efficient management of the environment information, and further realizing the efficient management of the environmental monitoring of the environmental data.
Drawings
FIG. 1 is a schematic flow chart illustrating a big data-based environmental monitoring information management method according to an embodiment;
FIG. 2 is a block diagram of a big data based environment monitoring information management system in one embodiment;
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 and not restrictive on the broad application.
In one embodiment, as shown in fig. 1, there is provided a big data based environmental monitoring information management method, including:
step S100: acquiring actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area;
specifically, in this step, each of the environment monitoring standard regions is preset, and the actual environment level information represents a quality level of an environment of each of the environment monitoring standard regions. Before acquiring the actual environmental grade information of each preset environmental monitoring standard area, acquiring basic environmental data of each environmental monitoring standard area, and evaluating the basic environmental data to further acquire the actual environmental grade information of the environmental monitoring standard area. The basic environment data may include surface environment information, such as image information, and may also include intrinsic environment information, such as specific environment parameter information.
In addition, in this embodiment, the obtaining based on big data means that the hardware device with big data technology is arranged, for example, data can be collected in real time and the collected data can be transmitted to the big data cloud end in real time, and of course, the adopted hardware devices are arranged in the environment monitoring standard area in a scattered manner, so that all-around data collection is realized, and then the actual environment grade information of each environment monitoring standard area is accurately obtained.
In addition, in order to ensure the effectiveness and the high efficiency of data, a better actual environment grade is screened out from each actual environment grade information according to a specific proportion, wherein according to the specific proportion, useless data can be filtered out according to a preset screening rule, and then the actual environment grade information meeting the requirements is selected out. Specifically, the specific proportion is preset, for example, the specific proportion can be screened if the preset grade meets the specific grade, so that the screened superior actual environment grade is effective, higher in grade and meaningful for reference.
And then, setting the environment monitoring standard region corresponding to the better actual environment level as a recommendable environment control region.
Step S200: acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating associated environment characteristic data of the same cluster after the cluster analysis;
specifically, in this step, after the recommendable environment control region is obtained, in order to study and manage parameter data of the recommendable environment control region and further know the reason why the environment of the recommendable environment control region is better, a recommendable environment parameter data set of the recommendable environment control region is obtained, and cluster analysis is performed according to the recommendable environment parameter data set, so that the environment feature data associated with the same cluster is generated after the cluster analysis.
The cluster analysis is an unsupervised learning method, and does not need any label, but deduces a cluster label based on the structure of data. Namely, by acquiring the associated environment characteristic data of the same cluster, the classification according to the associated characteristics is realized to form each cluster, and the associated environment characteristic data of the same cluster represents the associated relationship and the self characteristics of the recommendable environment parameter data set of the recommendable environment control area and other data.
Step S300: and screening out an environment area to be managed matched with the associated environment characteristic data of the same cluster from a preset environment area database to be managed based on the associated environment characteristic data of the same cluster, recording the environment area to be optimized as an optimal environment area of the same cluster, and generating an optimal environment area monitoring report based on the optimal environment area of the same cluster and a recommended environment parameter data set of a control area of the recommended environment.
Specifically, in this step, a plurality of environment areas to be managed are stored in the environment area database to be managed in advance, and it can be understood that the data in the environment area database to be managed are all data to be processed and analyzed. Therefore, in this embodiment, based on the same cluster associated environment characteristic data, the same cluster associated environment characteristic data is utilized to screen out an environment area to be managed, which is matched with the same cluster associated environment characteristic data, from a preset environment area database to be managed, so that an area to be managed is matched with other areas of the same preferred environment through the characteristics of one area, and a preferred environment area monitoring report is generated through the same cluster preferred environment area and the recommendable environment parameter data set of the recommendable environment control area, so that the environmental data of the preferred environment area is analyzed, and further, through the form of the report, the advantages of the environment of the preferred area and the advantages of environment management are known more clearly, and thus, management of other environment areas is facilitated for managers, and further, efficient, rapid, ordered and high-utilization management of the environment monitoring information is realized.
In one embodiment, step S100: acquiring actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area; the method specifically comprises the following steps:
step S110: acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data, and generating an image environment data grade;
step S120: acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data, and generating a parameter environmental data grade;
step S130: comparing the image environment data grade with the parameter environment data grade, and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range;
step S140: if the image environment data grade and the parameter environment data grade are judged not to be in a preset standard error range, generating an actual parameter adjustment weight;
step S150: adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight, and generating actual environment grade information;
step S160: and arranging the actual environment grade information according to the grade sequence, screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the ranks, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region.
Specifically, in this step, in order to obtain the actual environmental level information of each environmental monitoring standard region accurately, therefore, through multi-angle comparison in this step, that is, at first, obtain the image monitoring environment data based on each preset environmental monitoring standard region through obtaining the big data image acquisition module that is based on presetting, and according to image monitoring environment data compares with preset standard environmental image data, and generates image environmental data grade, wherein, big data image acquisition module is the device that is used for monitoring environmental data who sets up in environmental monitoring standard region, and big data image acquisition module is through gathering the environmental image data in the region, and simultaneously after gathering image data, immediately upload to big data cloud end, and then conveniently carry out data analysis at big data cloud end.
In addition, the image environment data grade is generated by comparing the image environment data with preset standard environment image data, and the image environment data grade is obtained for one angle.
On the other angle, through the environmental parameter monitoring data based on each preset environmental monitoring standard region is obtained by the big data parameter collection module, and according to the environmental parameter monitoring data is compared with the preset standard parameter environmental data, and a parameter environmental data grade is generated. And then, comparing the data with preset standard parameter environment data and generating a parameter environment data grade. The environmental parameter monitoring data comprise an air index, a pollution index, haze concentration and the like.
Further, comparing the image environment data grade with the parameter environment data grade, and determining whether the image environment data grade and the parameter environment data grade are within a preset standard error range, when determining that the image environment data grade and the parameter environment data grade are not within the preset standard error range, it indicates that there is a deviation between the image environment data grade and the parameter environment data grade, so that, in order to implement data correction processing, the image environment data grade and the parameter environment data grade are adjusted according to the actual parameter adjustment weight, and actual environment grade information is generated.
And then, arranging the actual environment grade information according to the high-low order of the grade, and screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the grade, wherein the top ten of the grade is a specific proportion, so that the better environment is obtained through sorting, and the data processing precision is improved.
In one embodiment, step S300: screening out an environment area to be managed matched with the same cluster associated environment characteristic data from a preset environment area database to be managed based on the same cluster associated environment characteristic data, recording the environment area to be optimized as a same cluster preferred environment area, and generating a preferred environment area monitoring report according to the same cluster preferred environment area and a recommended environment parameter data set of a control area of the recommended environment; the method specifically comprises the following steps:
step S310: comparing the same cluster associated environment characteristic data with the environmental areas to be managed in a preset environmental area database to be managed one by one based on the same cluster associated environment characteristic data, and respectively generating environment data matching values;
step S320: performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result;
step S330: generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result;
step S340: performing redundant feature filtering on the actual matching group data set, generating an environmental area to be managed matched with the same-cluster associated environmental feature data after the redundant feature filtering is completed, and marking the environmental area to be optimized as a same-cluster better environmental area;
step S350: and extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of preferred environment areas and the recommendable environment control areas, and generating a preferred environment area monitoring report based on the same parameter characteristics.
Specifically, in this step, in order to achieve accurate acquisition of a detection report and accurate generation of an environment area to be managed that matches the same cluster-associated environment feature data, the environment area to be managed is accurately generated, and therefore, a more accurate monitoring of the environment area to be managed that matches the same cluster-associated environment feature data is achieved by comparing the same cluster-associated environment feature data with the environment area to be managed in a preset environment area database one by one based on the same cluster-associated environment feature data, generating environment data matching values respectively, then performing convolution operation on the environment data matching values, generating a target environment convolution feature of the environment data matching values, performing traversal convolution operation on the environment data matching values based on the target environment convolution feature, obtaining a current traversal convolution result, then generating an actual matching group data set that matches the same cluster-associated environment feature data based on the current traversal convolution result, and filtering an interference factor, and therefore, performing redundant feature filtering on the actual matching group data set, generating an environment area to be managed that matches the same cluster-associated environment feature data after redundant feature filtering is completed, and recording the environment area to be optimized as the same cluster-associated environment area to be managed.
In one embodiment, step S340: redundant feature filtering is carried out on the actual matching group data set, an environment area to be managed matched with the same cluster associated environment feature data is generated after redundant feature filtering is completed, and the environment area to be optimized is recorded as a same cluster better environment area, and the method specifically comprises the following steps:
step S341: acquiring current environment judgment standard data, and performing judgment standard parameter filtering on the same cluster associated environment characteristic data based on the current environment judgment standard data;
step S342: generating real associated environment characteristic data after the evaluation standard parameters are filtered;
step S343: performing redundant population filtering on the actual matched population data set based on the real associated environment feature data;
step S344: and after the redundant group filtering is finished, generating an environment area to be managed matched with the environment characteristic data associated with the same cluster, and recording the environment area to be optimized as a better environment area of the same cluster.
Specifically, in this step, in order to ensure real-time effectiveness of the data, it is necessary to first obtain current environment judgment standard data, where the current environment judgment standard data is a currently updated standard related to environment judgment, such as an updated national standard, an updated quotation mark, or another standard capable of measuring environment quality. In this step, the judgment standard parameter filtering is performed on the same cluster associated environment feature data based on the current environment judgment standard data, so that the filtering from the source is realized, then the real associated environment feature data is generated after the judgment standard parameter filtering is completed, the redundant cluster filtering is performed on the actually matched cluster data set based on the real associated environment feature data, and finally, the environment area to be managed matched with the same cluster associated environment feature data is generated after the redundant cluster filtering is completed, so that the accurate and effective acquisition of the same cluster better environment area is realized.
In one embodiment, step S300: screening out an environment area to be managed matched with the same cluster associated environment characteristic data from a preset environment area database to be managed based on the same cluster associated environment characteristic data, recording the environment area to be optimized as a same cluster optimal environment area, generating an optimal environment area monitoring report from a recommended environment parameter data set of a control area based on the same cluster optimal environment area and the recommended environment, and then further comprising:
step S410: generating a report display interface according to the superior environment area monitoring report;
step S420: splitting the monitoring report of the better environment region according to the data capacity of the data, generating a plurality of better data of the split environment region, and simultaneously acquiring the actual display area of the better data of each split environment region;
step S430: acquiring the current terminal display area of the report display interface;
step S440: and displaying according to the actual display area and the current terminal display area according to a preset display proportion.
Specifically, in this step, first, in order to improve user experience and improve interest and effectiveness of browsing of a report by a user, the monitoring report of the optimal environment region is sequentially split according to data capacity of data, a plurality of better data of the split environment region are generated, an actual display area of the better data of each split environment region is obtained, a current terminal display area of the report display interface is obtained, and the optimal environment region monitoring report is displayed according to a preset display proportion according to the actual display area and the current terminal display area, so that the optimal environment region monitoring report is displayed in regions with different sizes according to capacity, and accordingly, a high-efficiency display effect is achieved, and user experience of a report viewer is improved.
In summary, the present invention sequentially obtains the actual environment grade information of each preset environment monitoring standard region based on big data, and screens out a better actual environment grade from each actual environment grade information according to a specific ratio, and sets the environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region; acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating clustered associated environment characteristic data after the cluster analysis; the method comprises the steps of screening out environment areas to be managed matched with environment characteristic data to be managed from a preset environment area database to be managed based on the environment characteristic data to be clustered, recording the environment areas to be optimized as optimal environment areas to be clustered, generating optimal environment area monitoring reports based on the optimal environment areas to be clustered and recommended environment parameter data sets of control areas of the optimal environment areas and the recommended environment, screening the areas with optimal environment levels after the environment data of all the areas are monitored, namely screening the areas with the environmental data acquired based on big data, clustering and screening the environment areas to be managed matched with the environment characteristic data to be managed from the preset environment area database to be managed by utilizing the environment characteristic data to be clustered, matching the characteristics of one area to other areas with the same optimal environment, recommending the optimal environment areas to the other areas with the same optimal environment through the characteristics of one area, generating the optimal environment parameter data sets matched with the environment characteristic data to be managed from the environment area database to be managed by utilizing the environment characteristic data to be clustered, and further realizing efficient management of the environment information, and further realizing the efficient management of the environmental monitoring of the environmental data.
In one embodiment, as shown in fig. 2, a big data based environmental monitoring information management system includes:
the proportion screening module is used for obtaining actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area;
the environment parameter module is used for acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating clustered associated environment characteristic data after the cluster analysis;
and the associated environment module is used for screening out an environment area to be managed matched with the associated environment characteristic data of the same cluster from a preset environment area database to be managed based on the associated environment characteristic data of the same cluster, recording the environment area to be optimized as an optimal environment area of the same cluster, and generating an optimal environment area monitoring report based on the optimal environment area of the same cluster and a recommended environment parameter data set of a recommended environment control area.
In one embodiment, the system further comprises:
the image acquisition module is used for acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data and generating an image environment data grade;
the module acquisition module is used for acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data and generating a parameter environmental data grade;
the data grade module is used for comparing the image environment data grade with the parameter environment data grade and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range or not;
the parameter environment module is used for generating an actual parameter adjustment weight if the image environment data grade and the parameter environment data grade are judged not to be in a preset standard error range;
the actual environment module is used for adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight and generating actual environment grade information;
and the recommendation environment module is used for arranging the actual environment grade information according to the high-low sequence of the grades, screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the ranks, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region.
In one embodiment, the system further comprises:
the environment area module is used for comparing the same cluster associated environment characteristic data with environment areas to be managed in a preset environment area database to be managed one by one based on the same cluster associated environment characteristic data and respectively generating environment data matching values;
the convolution operation module is used for performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result;
the traversal convolution module is used for generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result;
the group data module is used for filtering redundant features of the actually matched group data set, generating an environment area to be managed matched with the associated environment feature data of the same cluster after the redundant features are filtered, and recording the environment area to be optimized as a better environment area of the same cluster;
the optimal environment module is used for extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of optimal environment areas and the recommendable environment control areas and generating an optimal environment area monitoring report based on the same parameter characteristics;
the standard data module is used for acquiring current environment judgment standard data and filtering judgment standard parameters of the same cluster associated environment characteristic data based on the current environment judgment standard data;
the parameter filtering module is used for generating real associated environment characteristic data after the judgment standard parameter filtering is finished;
a real association module for performing redundant population filtering on the actual matched population data set based on the real associated environment feature data;
the group filtering module is used for generating an environment area to be managed matched with the same cluster associated environment characteristic data after the redundant group filtering is finished, and recording the environment area to be optimized as a same cluster better environment area;
the monitoring report module is used for generating a report display interface according to the monitoring report of the better environment area;
the optimal display module is used for splitting the optimal environment region monitoring report according to the data capacity of the data, generating a plurality of optimal split environment region data and acquiring the actual display area of the optimal split environment region data;
the terminal display module is used for acquiring the current terminal display area of the report display interface;
and the current terminal module is used for displaying according to the actual display area and the current terminal display area according to a preset display proportion.
In one embodiment, as shown in fig. 3, a computer device includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method for managing environment monitoring information based on big data when executing the computer program.
In one embodiment, the processor performs the steps of: acquiring actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area; acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating clustered associated environment characteristic data after the cluster analysis; screening out an environmental area to be managed matched with the associated environmental feature data of the same cluster from a preset environmental area database to be managed based on the associated environmental feature data of the same cluster, recording the environmental area to be optimized as an optimal environmental area of the same cluster, and generating an optimal environmental area monitoring report based on the optimal environmental area of the same cluster and a recommended environmental parameter data set of a controllable area of the recommended environment; acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data, and generating an image environment data grade; acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data, and generating a parameter environmental data grade; comparing the image environment data grade with the parameter environment data grade, and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range; if the image environment data grade and the parameter environment data grade are judged not to be in a preset standard error range, generating an actual parameter adjustment weight; adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight, and generating actual environment grade information; arranging the actual environment grade information according to the grade sequence, screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the ranks, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region; comparing the same cluster associated environment characteristic data with environment areas to be managed in a preset environment area database to be managed one by one based on the same cluster associated environment characteristic data, and respectively generating environment data matching values; performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result; generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result; performing redundant feature filtering on the actual matching group data set, generating an environment area to be managed matched with the same cluster associated environment feature data after the redundant feature filtering is completed, and recording the environment area to be optimized as a same cluster optimal environment area; and extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of preferred environment areas and the recommendable environment control areas, and generating a preferred environment area monitoring report based on the same parameter characteristics.
A computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the above-mentioned big-data-based environmental monitoring information management 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 (Rambus) direct RAM (RDRAM), direct memory 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, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.
Claims (8)
1. A big data-based environmental monitoring information management method is characterized by comprising the following steps:
acquiring actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area; acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating associated environment characteristic data of the same cluster after the cluster analysis; screening out an environmental area to be managed matched with the same cluster associated environmental characteristic data from a preset environmental area database to be managed based on the same cluster associated environmental characteristic data, recording the environmental area to be managed as a same cluster preferred environmental area, and generating a preferred environmental area monitoring report by using a recommended environmental parameter data set of a control area based on the same cluster preferred environmental area and the recommended environment;
acquiring actual environment grade information of each preset environment monitoring standard area based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard area corresponding to the better actual environment grade as a recommendable environment control area; the method specifically comprises the following steps:
acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data, and generating an image environment data grade; acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data, and generating a parameter environmental data grade; comparing the image environment data grade with the parameter environment data grade, and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range; if the image environment data grade and the parameter environment data grade are judged not to be in a preset standard error range, generating an actual parameter adjustment weight; adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight, and generating actual environment grade information; and arranging the actual environment grade information according to the grade sequence, screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the ranks, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region.
2. The environment monitoring information management method based on big data according to claim 1, wherein an environment area to be managed matched with the environment feature data associated with the same cluster is screened out from a preset environment area database to be managed based on the environment feature data associated with the same cluster, the environment area to be managed is marked as a preferred environment area of the same cluster, and a preferred environment area monitoring report is generated based on the preferred environment area of the same cluster and a recommended environment parameter data set of a control area of the recommended environment; the method specifically comprises the following steps:
comparing the same cluster associated environment characteristic data with environment areas to be managed in a preset environment area database to be managed one by one based on the same cluster associated environment characteristic data, and respectively generating environment data matching values; performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result; generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result; performing redundant feature filtering on the actual matching group data set, generating an environment area to be managed matched with the same cluster associated environment feature data after the redundant feature filtering is completed, and recording the environment area to be managed as a same cluster preferred environment area; and extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of preferred environment areas and the recommendable environment control areas, and generating a preferred environment area monitoring report based on the same parameter characteristics.
3. The environmental monitoring information management method based on big data according to claim 2, wherein redundant feature filtering is performed on the actually matched group data set, and after the redundant feature filtering is completed, an environmental area to be managed that is matched with the environmental feature data associated with the same cluster is generated, and the environmental area to be managed is recorded as a better environmental area of the same cluster, which specifically includes:
acquiring current environment judgment standard data, and performing judgment standard parameter filtering on the same cluster associated environment characteristic data based on the current environment judgment standard data; generating real associated environment characteristic data after the evaluation standard parameters are filtered; performing redundant population filtering on the actual matched population data set based on the real associated environment feature data; and after the redundant groups are filtered, generating an environment area to be managed matched with the associated environment characteristic data of the same cluster, and recording the environment area to be managed as a better environment area of the same cluster.
4. The big data based environmental monitoring information management method according to any one of claims 1 to 3, wherein an environmental area to be managed matched with the environmental feature data associated with the same cluster is screened out from a preset environmental area database to be managed based on the environmental feature data associated with the same cluster, the environmental area to be managed is marked as a better environmental area of the same cluster, and a better environmental area monitoring report is generated based on the better environmental area of the same cluster and a recommended environmental parameter data set of a control area of the recommended environment, and then further comprising:
generating a report display interface according to the superior environment area monitoring report; splitting the monitoring report of the better environment region according to the data capacity of the data, generating a plurality of better data of the split environment region, and simultaneously acquiring the actual display area of the better data of each split environment region; acquiring the current terminal display area of the report display interface; and displaying according to the actual display area and the current terminal display area according to a preset display proportion.
5. An environment monitoring information management system based on big data, characterized in that the system comprises:
the proportion screening module is used for acquiring actual environment grade information of each preset environment monitoring standard region based on big data, screening out a better actual environment grade from each actual environment grade information according to a specific proportion, and setting the environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region;
the environment parameter module is used for acquiring a recommendable environment parameter data set of the recommendable environment control region according to the recommendable environment control region, performing cluster analysis according to the recommendable environment parameter data set, and generating clustered associated environment characteristic data after the cluster analysis;
the system comprises a cluster-based association environment characteristic data acquisition module, a cluster-based association environment parameter data acquisition module and a cluster-based association environment parameter monitoring module, wherein the cluster-based association environment characteristic data acquisition module is used for acquiring cluster-based association environment characteristic data of a plurality of clusters, acquiring a cluster-based association environment parameter data set of a plurality of clusters, and acquiring a cluster-based association environment parameter data set of a plurality of clusters;
the image acquisition module is used for acquiring image monitoring environment data of each preset environment monitoring standard area based on a preset big data image acquisition module, comparing the image monitoring environment data with preset standard environment image data and generating an image environment data grade;
the module acquisition module is used for acquiring environmental parameter monitoring data of each preset environmental monitoring standard area based on a preset big data parameter acquisition module, comparing the environmental parameter monitoring data with preset standard parameter environmental data and generating a parameter environmental data grade;
the data grade module is used for comparing the image environment data grade with the parameter environment data grade and judging whether the image environment data grade and the parameter environment data grade are within a preset standard error range or not;
the parameter environment module is used for generating an actual parameter adjustment weight if the image environment data grade and the parameter environment data grade are judged not to be in a preset standard error range;
the actual environment module is used for adjusting the image environment data grade and the parameter environment data grade according to the actual parameter adjusting weight and generating actual environment grade information;
and the recommendation environment module is used for arranging the actual environment grade information according to the high-low sequence of the grades, screening out a better actual environment grade from the actual environment grade information according to the proportion of the top ten of the ranks, and setting an environment monitoring standard region corresponding to the better actual environment grade as a recommendable environment control region.
6. The big data based environmental monitoring information management system according to claim 5, further comprising:
the environment area module is used for comparing the same cluster associated environment characteristic data with environment areas to be managed in a preset environment area database to be managed one by one based on the same cluster associated environment characteristic data and respectively generating environment data matching values;
the convolution operation module is used for performing convolution operation on the environment data matching value, generating a target environment convolution characteristic of the environment data matching value, and performing traversal convolution operation on the environment data matching value based on the target environment convolution characteristic to obtain a current traversal convolution result;
the traversal convolution module is used for generating an actual matching group data set matched with the same cluster associated environment characteristic data according to the current traversal convolution result;
the group data module is used for filtering redundant features of the actually matched group data set, generating an environment area to be managed matched with the associated environment feature data of the same cluster after the redundant features are filtered, and recording the environment area to be managed as a better environment area of the same cluster;
the optimal environment module is used for extracting the same parameter characteristics in the recommendable environment parameter data sets of the same cluster of optimal environment areas and the recommendable environment control areas and generating an optimal environment area monitoring report based on the same parameter characteristics;
the standard data module is used for acquiring current environment judgment standard data and filtering judgment standard parameters of the same cluster associated environment characteristic data based on the current environment judgment standard data;
the parameter filtering module is used for generating real associated environment characteristic data after the evaluation standard parameter filtering is finished;
a real correlation module for performing redundant population filtering on the actual matched population data set based on the real correlation environment feature data;
the group filtering module is used for generating an environmental area to be managed matched with the same cluster associated environmental characteristic data after the redundant group filtering is finished, and marking the environmental area to be managed as a same cluster better environmental area;
the monitoring report module is used for generating a report display interface according to the monitoring report of the better environment area;
the optimal display module is used for splitting the optimal environment region monitoring report according to the data capacity of the data, generating a plurality of optimal split environment region data and acquiring the actual display area of the optimal split environment region data;
the terminal display module is used for acquiring the current terminal display area of the report display interface;
and the current terminal module is used for displaying according to the actual display area and the current terminal display area according to a preset display proportion.
7. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program performs the steps of the method according to any of claims 1 to 4.
8. 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 according to any one of claims 1 to 4.
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