CN114037318A - Agricultural big data analysis platform and method - Google Patents
Agricultural big data analysis platform and method Download PDFInfo
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- CN114037318A CN114037318A CN202111366097.4A CN202111366097A CN114037318A CN 114037318 A CN114037318 A CN 114037318A CN 202111366097 A CN202111366097 A CN 202111366097A CN 114037318 A CN114037318 A CN 114037318A
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Abstract
The invention is suitable for the technical field of data platforms, and provides an agricultural big data analysis platform and a method, wherein the platform comprises: the basic layer is used for acquiring basic agricultural data; the data layer is used for storing basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information; the agricultural service system comprises an application layer, a data base layer and a data base layer, wherein the application layer is used for developing an agricultural service system according to basic agricultural data and visual agricultural information so that the agricultural service system can be updated according to data provided by the application layer, and the agricultural service system comprises an agricultural remote sensing system, an agricultural product quality tracing system and a rural comprehensive information service system; and the decision layer is used for providing reference decision information for the management department according to the historical agricultural abnormal information. Through building an agricultural big data analysis platform, scattered agricultural data are accessed and integrated in a centralized mode, agricultural data are prevented from being split, analysis processing can be carried out on basic agricultural data to obtain visual agricultural information, and related personnel can understand deeply conveniently.
Description
Technical Field
The invention relates to the technical field of data platforms, in particular to an agricultural big data analysis platform and method.
Background
At present, massive agricultural data are difficult to communicate in the agricultural production process, and cannot be effectively applied to the processes of agricultural plan making, agricultural product planting and selling, designated decision making of agricultural management departments and the like, agricultural data are mutually split due to the fact that an agricultural data analysis platform is imperfect, effective fusion is lacking among the data, the data cannot clearly describe services and cannot be understood by service personnel, data assets are difficult to carry out unified centralized management, and massive agricultural data are not effectively utilized.
Therefore, it is desirable to provide an agricultural big data analysis platform and method, which aim to solve the above problems.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an agricultural big data analysis platform and method to solve the problems in the background technology.
The invention provides an agricultural big data analysis platform on one hand, which comprises:
the basic layer is used for obtaining basic agricultural data and classifying the basic agricultural data, and the basic layer comprises: the system comprises a basic agricultural data acquisition module, a data processing module and a data processing module, wherein the basic agricultural data acquisition module is used for acquiring basic agricultural data and comprises a plurality of acquisition terminals; the basic agricultural data classification module is used for automatically classifying the basic agricultural data acquired by different acquisition terminals, and the basic agricultural data comprises cost basic agricultural data, growth basic agricultural data, climate basic agricultural data, demand basic agricultural data and production basic agricultural data;
the data layer is used for storing basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information;
the agricultural service system comprises an application layer, a data support layer and a data processing layer, wherein the application layer is used for developing the agricultural service system according to basic agricultural data and visual agricultural information and providing data support for the agricultural service system so that the agricultural service system can be updated according to data provided by the application layer, and the agricultural service system comprises an agricultural remote sensing system, an agricultural product quality tracing system, a rural comprehensive information service system, an agricultural environmental pollution treatment system and an agricultural product market monitoring and early warning system; and
and the decision layer is used for providing reference decision information for the management department according to the historical agricultural abnormal information.
Further, the data layer includes:
the storage module is used for storing the basic agricultural data in a classified manner;
the data processing module is used for analyzing and processing basic agricultural data to obtain visual agricultural information and comprises various data processing units, and each data processing unit is used for processing specific basic agricultural data and generating visual agricultural information.
Further, the data processing unit includes:
the data transmission subunit is used for acquiring basic agricultural data from the storage module and sending the basic agricultural data to the data processing subunit;
the data processing subunit is used for analyzing and processing basic agricultural data according to a data processing formula to obtain visual agricultural data, the data processing subunit is internally provided with a data processing formula, and the data processing formula can be edited and changed; and
and the information additional subunit is used for generating additional information according to the visual agricultural data, the additional information is used for reflecting the specific significance of the visual agricultural data, and the additional information and the corresponding visual agricultural data are summarized to generate the visual agricultural information.
Further, the application layer includes:
the agricultural remote sensing system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural remote sensing system from the data layer;
the agricultural product quality tracing system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural product quality tracing system from the data layer;
the rural comprehensive information service system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the rural comprehensive information service system from the data layer;
the agricultural environmental pollution treatment system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural environmental pollution treatment system from the data layer; and
and the agricultural product market monitoring and early warning system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural product market monitoring and early warning system from the data layer.
Further, the decision layer comprises:
the historical agricultural abnormal information base is used for storing historical agricultural abnormal information and storing corresponding historical effective decision information;
the agricultural data abnormity judging module is used for judging whether the basic agricultural data is abnormal or not, and when the basic agricultural data is abnormal, the abnormal basic agricultural data is marked as abnormal basic data;
the abnormal data matching module is used for matching the abnormal basic data with the historical agricultural abnormal information, outputting the historical agricultural abnormal information with the highest matching value and outputting corresponding historical effective decision information; and
and the decision information generating module is used for marking the historical effective decision information as reference decision information, and the reference decision information is used for providing reference for a management department.
Further, the agricultural data abnormity determining module comprises:
the agricultural data abnormity judging unit is used for judging abnormity of the acquired basic agricultural data, the agricultural data abnormity judging unit comprises a normal range value of each basic agricultural data, and when the basic agricultural data is not in the corresponding normal range value, the basic agricultural data is judged to be abnormal; and
and the abnormal basic data output unit is used for marking the abnormal basic agricultural data as abnormal basic data.
Further, the anomaly data matching module comprises:
the abnormal basic data integration module is used for integrating the abnormal basic data in a preset time period to form abnormal basic information;
an information matching module, configured to match the abnormal basic information with historical agricultural abnormal information, obtain a first numerical value of abnormal basic data in the abnormal basic information, obtain a second numerical value of abnormal historical data in the historical agricultural abnormal information, obtain a third numerical value of the abnormal basic data and the abnormal historical data that belong to the same type of data and have the same abnormal reason, calculate a matching value, where the matching value is (the third numerical value/the first numerical value) × (the third numerical value/the second numerical value), the abnormal reasons refer to that the basic agricultural data are lower than a normal range value or higher than the normal range value, the first numerical value refers to the specific quantity of the abnormal basic data, the second numerical value refers to the specific quantity of the abnormal historical data, and the third numerical value refers to the specific quantity of the abnormal basic data and the abnormal historical data which belong to the same kind of data and have the same abnormal reasons; and
and the decision information output module is used for obtaining historical agricultural abnormal information with the highest matching value with the abnormal basic information and outputting historical effective decision information corresponding to the historical agricultural abnormal information.
Furthermore, the data layer further comprises a data exchange module, and the data exchange module is used for realizing the exchange and sharing of the data in the storage module and the external data.
Further, the platform also comprises an expert service module, the expert service module is used for managing agricultural expert teams, and a live broadcast unit, an online course unit, an expert hotline and an expert question and answer unit are arranged in the expert service module.
In another aspect of the invention, an agricultural big data analysis method is provided, which comprises the following steps:
acquiring basic agricultural data and classifying the basic agricultural data;
storing the basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information;
developing an agricultural service system according to basic agricultural data and visual agricultural information, and providing data support for the agricultural service system so that the agricultural service system can be updated according to data provided by an application layer;
and providing reference decision information for management departments according to the historical agricultural abnormal information.
Compared with the prior art, the invention has the beneficial effects that:
through setting up the big data analysis platform of agricultural, the agricultural data that will disperse is concentrated to be inserted and is integrated, avoids agricultural data to split each other, can carry out analysis processes to basic agricultural data and obtain audio-visual agricultural information, and relevant personnel of being convenient for go on deep understanding, can also be according to basic agricultural data and audio-visual agricultural information development agricultural service system, and the decision-making layer can provide reference decision-making information for the management department according to historical agricultural abnormal information in addition for agricultural data is by the utilization of maximize.
Drawings
Fig. 1 is a schematic structural diagram of an agricultural big data analysis platform.
Fig. 2 is a schematic structural diagram of a base layer in an agricultural big data analysis platform.
Fig. 3 is a schematic structural diagram of a data layer in an agricultural big data analysis platform.
Fig. 4 is a schematic structural diagram of a data processing unit in an agricultural big data analysis platform.
Fig. 5 is a schematic structural diagram of an application layer in an agricultural big data analysis platform.
Fig. 6 is a schematic structural diagram of a decision layer in an agricultural big data analysis platform.
Fig. 7 is a schematic structural diagram of an agricultural data anomaly determination module in an agricultural big data analysis platform.
Fig. 8 is a schematic structural diagram of an abnormal data matching module in an agricultural big data analysis platform.
FIG. 9 is a flow chart of a method for analyzing agricultural big data.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
As shown in fig. 1, an embodiment of the present invention provides an agricultural big data analysis platform, where the platform includes:
the basic layer 100 is used for acquiring basic agricultural data and classifying the basic agricultural data;
the data layer 200 is used for storing basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information;
the application layer 300 is used for developing an agricultural service system according to basic agricultural data and visual agricultural information, providing data support for the agricultural service system, and enabling the agricultural service system to be updated according to data provided by the application layer 300, wherein the agricultural service system comprises an agricultural remote sensing system, an agricultural product quality tracing system, a rural comprehensive information service system, an agricultural environmental pollution treatment system and an agricultural product market monitoring and early warning system; and
and the decision layer 400 is used for providing reference decision information for the management department according to the historical agricultural abnormal information.
It should be noted that, at present, mass data generated in the agricultural production process are difficult to be communicated, and cannot be effectively applied to the processes of agricultural planning, agricultural product planting and selling, designated decision making of agricultural management departments and the like, agricultural data are split each other due to the fact that an agricultural data analysis platform is imperfect, effective fusion between data is lacked, the data cannot clearly describe services, and are difficult to be understood by service personnel, data assets are difficult to be uniformly and centrally managed, and mass agricultural data are not effectively utilized.
In the embodiment of the invention, by building an agricultural big data analysis platform, scattered agricultural data are accessed, integrated and analyzed and processed in a centralized manner, the agricultural big data analysis platform comprises a basic layer 100, a data layer 200, an application layer 300 and a decision layer 400, the basic layer 100 is used for collecting basic agricultural data, the basic agricultural data comprises cost basic agricultural data, growth basic agricultural data, climate basic agricultural data, demand basic agricultural data, production basic agricultural data and the like, the basic layer 100 can provide basic data support for other layers, agricultural data collection networks are established in different types according to actual conditions and aiming at various industries related to agriculture and various resources related to agriculture, efficient real-time data transmission network channels are established, and virtualization, automation, analysis and processing of the platform are realized by utilizing technologies such as cloud computing and cloud storage, Parallel operation, data security and energy management are carried out, and agile response of the platform to business services is guaranteed; the data layer 200 is used for storing basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information, it can be understood that the basic agricultural data is difficult to visually feel the back significance of the basic agricultural data without processing, the data layer 200 adopts mainstream database technology to build an agricultural big data resource base, the basic agricultural data can be processed based on analysis methods such as correlation analysis, visual analysis, knowledge mining, data fusion and the like, and the visual agricultural information can be further obtained, and agricultural product price trends, comprehensive cultivated land quantity, farmland quality, crop varieties, cultivation techniques, industrial structures, agricultural material allocation, agricultural product yield and the like can be seen through the visual agricultural information, so that government management capacity, enterprise service level, farmer production capacity and agricultural product sales capacity can be improved.
In the embodiment of the invention, an agricultural service system can be developed according to basic agricultural data and visual agricultural information, an application layer 300 provides data support for the agricultural service system, the agricultural service system comprises an agricultural remote sensing system, an agricultural product quality tracing system, a rural comprehensive information service system, an agricultural environmental pollution treatment system, an agricultural product market monitoring and early warning system and the like, the various systems are already used in actual agricultural production and are not repeated, and an agricultural big data analysis platform is used for providing latest data for the agricultural service systems, so that the agricultural service system can better and more accurately perform service; it can be understood that abnormal data exists in the basic agricultural data, the abnormal data can bring loss to agricultural related personnel, in order to reduce the loss, a management department needs to make a decision in time, and the decision layer 400 can provide reference decision information for the management department according to historical agricultural abnormal information.
As shown in fig. 2, as a preferred embodiment of the present invention, the base layer 100 includes:
the agricultural data acquisition system comprises a basic agricultural data acquisition module 101, a data acquisition module and a data processing module, wherein the basic agricultural data acquisition module 101 is used for acquiring basic agricultural data, and the basic agricultural data acquisition module 101 comprises a plurality of acquisition terminals; and
the basic agricultural data classification module 102 is configured to automatically classify basic agricultural data acquired by different acquisition terminals, where the basic agricultural data includes cost basic agricultural data, growth basic agricultural data, climate basic agricultural data, demand basic agricultural data, and production basic agricultural data.
In the embodiment of the invention, the basic agricultural data acquisition module 101 comprises a plurality of acquisition terminals, each acquisition terminal is used for acquiring specific basic agricultural data, thus, basic agricultural data are conveniently classified, the basic agricultural data comprise cost basic agricultural data, growth basic agricultural data, climate basic agricultural data, demand basic agricultural data, production basic agricultural data and the like, the cost basic agricultural data are used for reflecting the cost of agricultural products, the growth basic agricultural data are used for reflecting the growth situation of the agricultural products, the climate basic agricultural data are used for reflecting weather and climate, the demand basic agricultural data are used for reflecting the market demand condition of the agricultural products, the production basic agricultural data are used for reflecting the yield of the agricultural products, it can be understood that some data can be directly obtained through the acquisition terminal, and some data needs to be uploaded by a worker.
As shown in fig. 3 and 4, as a preferred embodiment of the present invention, the data layer 200 includes:
the storage module 201 is used for storing basic agricultural data in a classified manner; and
the data processing module 202 is used for analyzing and processing basic agricultural data to obtain visual agricultural information, and the data processing module 202 comprises a plurality of data processing units, wherein each data processing unit is used for processing specific basic agricultural data and generating visual agricultural information.
In the embodiment of the present invention, it can be understood that the basic agricultural data are various in variety, and the processing and analyzing methods for different or different combinations of basic agricultural data are different, so that the data processing module 202 includes a plurality of data processing units, each of which is used for processing specific basic agricultural data and generating intuitive agricultural information; the data processing unit includes: the data transmission subunit 2021 is used for acquiring the basic agricultural data from the storage module and sending the basic agricultural data to the data processing subunit 2022; the data processing subunit 2022 is configured to analyze and process the basic agricultural data according to a data processing formula to obtain intuitive agricultural data, where the data processing subunit 2022 has a data processing formula built therein, and the data processing formula can be edited and modified; and an information adding subunit 2023, configured to generate additional information according to the intuitive agricultural data, where the additional information is used to reflect the specific meaning of the intuitive agricultural data, and the additional information and the corresponding intuitive agricultural data are summarized to generate intuitive agricultural information, where the additional information is, for example, that the crop is growing normally, the crop is mature early, the crop is mature late, and the like.
As shown in fig. 5, as a preferred embodiment of the present invention, the application layer 300 includes:
the agricultural remote sensing system supporting unit 301 is used for acquiring basic agricultural data and visual agricultural information required by the agricultural remote sensing system from the data layer 200;
the agricultural product quality tracing system supporting unit 302 is used for acquiring basic agricultural data and visual agricultural information required by the agricultural product quality tracing system from the data layer 200;
the rural comprehensive information service system supporting unit 303 is used for acquiring basic agricultural data and visual agricultural information required by the rural comprehensive information service system from the data layer 200;
the agricultural environmental pollution treatment system support unit 304 is used for acquiring basic agricultural data and visual agricultural information required by the agricultural environmental pollution treatment system from the data layer 200; and
and the agricultural product market monitoring and early warning system supporting unit 305 is used for acquiring basic agricultural data and visual agricultural information required by the agricultural product market monitoring and early warning system from the data layer 200.
In the embodiment of the invention, after the agricultural service system acquires the corresponding basic agricultural data and the visual agricultural information from the data layer 200, the agricultural service system can update in time according to the basic agricultural data and the visual agricultural information, so that help can be better provided for agricultural production.
As shown in fig. 6, 7 and 8, as a preferred embodiment of the present invention, the decision layer 400 includes:
a historical agricultural anomaly information base 401, which is used for storing historical agricultural anomaly information and storing corresponding historical effective decision information;
the agricultural data anomaly determination module 402 is used for determining whether the basic agricultural data is abnormal or not, and when the basic agricultural data is abnormal, marking the abnormal basic agricultural data as abnormal basic data;
the abnormal data matching module 403 is configured to match the abnormal basic data with historical agricultural abnormal information, output historical agricultural abnormal information with the highest matching value, and output corresponding historical effective decision information; and
a decision information generating module 404, configured to mark the historical valid decision information as reference decision information, where the reference decision information is used to provide reference for a management department.
In the embodiment of the invention, a historical agricultural abnormal information base 401 is arranged in a decision layer 400, historical agricultural abnormal information and corresponding historical effective decision information are stored in the historical agricultural abnormal information base 401, the historical agricultural abnormal information and the corresponding historical effective decision information are uploaded by workers, an agricultural data abnormal judgment module 402 comprises an agricultural data abnormal judgment unit 4021 and an abnormal basic data output unit 4022, wherein the agricultural data abnormal judgment unit 4021 is used for performing abnormal judgment on the acquired basic agricultural data, the agricultural data abnormal judgment unit 4021 comprises a normal range value of each basic agricultural data, and when the basic agricultural data is not in the corresponding normal range value, the basic agricultural data is judged to be abnormal; the abnormal basic data output unit 4022 is configured to mark the abnormal basic agricultural data as abnormal basic data.
In this embodiment of the present invention, the abnormal data matching module 403 includes an abnormal basic data integrating module 4031, an information matching module 4032 and a decision information output module 4033, where the abnormal basic data integrating module 4031 is configured to integrate abnormal basic data in a predetermined time period to form abnormal basic information; the information matching module 4032 is configured to match the abnormal basic information with the historical agricultural abnormal information to obtain a first numerical value of the abnormal basic data in the abnormal basic information, obtain a second numerical value of the abnormal historical data in the historical agricultural abnormal information, obtain a third numerical value of the abnormal basic data and the abnormal historical data that belong to the same data and have the same abnormal reason, calculate a matching value, where the matching value is (third numerical value/first numerical value) (third numerical value/second numerical value), the first numerical value is a specific number of the abnormal basic data, the second numerical value is a specific number of the abnormal historical data, and the third numerical value is a specific number of the abnormal basic data and the abnormal historical data that belong to the same data and have the same abnormal reason, the abnormal reason refers to that the basic agricultural data is lower than a normal range value or higher than the normal range value; the decision information output module 4033 is used for obtaining historical agricultural abnormal information with the highest matching value with the abnormal basic information and outputting historical effective decision information corresponding to the historical agricultural abnormal information. For example, the abnormal basic information includes agricultural data a, agricultural data B and agricultural data C in a predetermined time period, for convenience of understanding and calculation, where the abnormal data are all lower than the normal range value, the first quantity value is 3, the historical agricultural abnormal information base includes first historical agricultural abnormal information, second historical agricultural abnormal information and third historical agricultural abnormal information, the first historical agricultural abnormal information includes agricultural data a, agricultural data B and agricultural data D, the second quantity value is 3, and the third quantity value is 2; the second historical agricultural abnormal information comprises agricultural data E, agricultural data B and agricultural data D, the second numerical value is 3, and the third numerical value is 1; the first historical agricultural abnormal information comprises agricultural data A, agricultural data B, agricultural data C and agricultural data E, the second numerical value is 4, the third numerical value is 3, and the matching values of the first historical agricultural abnormal information, the second historical agricultural abnormal information and the third historical agricultural abnormal and abnormal basic information are respectively as follows: 44%, 11% and 75%, determining the historical effective decision information corresponding to the third historical agricultural abnormal information as reference decision information.
As a preferred embodiment of the present invention, the data layer 200 further includes a data exchange module, and the data exchange module is configured to implement exchange and sharing between data in the storage module and external data.
In the embodiment of the invention, the platform also comprises an expert service module, the expert service module is used for managing an agricultural expert team, a live broadcast unit, an online course unit, an expert hotline and an expert question and answer unit are arranged in the expert service module, the expert service module is the middle and hard strength of industrial production management and data grasping and analysis, the platform combs industrial scientific research and management expert teams according to a single-product whole industrial chain, and professional, authoritative and accurate technical support services are provided for the problem of an practitioner from production to management in the whole industrial chain by adopting an online and offline combination mode.
As shown in fig. 9, an embodiment of the present invention further provides an agricultural big data analysis method, including the following steps:
s100, acquiring basic agricultural data and classifying the basic agricultural data;
s200, storing basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information;
s300, developing an agricultural service system according to basic agricultural data and visual agricultural information, and providing data support for the agricultural service system so that the agricultural service system can be updated according to data provided by an application layer;
and S400, providing reference decision information for management departments according to the historical agricultural abnormal information.
The method provided by the embodiment of the invention can be realized based on the agricultural big data analysis platform.
In the embodiment of the invention, the basic agricultural data comprises cost basic agricultural data, growth basic agricultural data, climate basic agricultural data, demand basic agricultural data, production basic agricultural data and the like, according to actual conditions, agricultural data acquisition networks are constructed in different categories aiming at various industries related to agriculture and various resources related to agriculture, a high-efficiency real-time data transmission network channel is established, the technologies such as cloud computing and cloud storage are utilized to realize virtualization, automation, parallel operation, data safety and energy management of a platform, and the agile response of the platform to business services is ensured; in addition, the method needs to analyze basic agricultural data to obtain visual agricultural information, and can understand that the basic agricultural data is difficult to visually feel the back significance of the basic agricultural data without processing, an agricultural big data resource base is built by adopting a mainstream database technology, the basic agricultural data can be processed based on analysis methods such as correlation analysis, visual analysis, knowledge mining, data fusion and the like, the most visual agricultural information is further obtained, the price trend of agricultural products, the quantity of comprehensive cultivated land, the farmland quality, the crop variety, the cultivation technology, the industrial structure, the agricultural fund configuration, the agricultural product yield and the like can be seen through the visual agricultural information, and the method is favorable for improving government management capacity, enterprise service level, farmer production capacity and agricultural sales capacity.
In the embodiment of the invention, an agricultural service system can be developed according to basic agricultural data and visual agricultural information, the agricultural service system comprises an agricultural remote sensing system, an agricultural product quality tracing system, a rural comprehensive information service system, an agricultural environmental pollution treatment system, an agricultural product market monitoring and early warning system and the like, and the various systems are used in actual agricultural production and are not described again; it can be understood that abnormal data can exist in the basic agricultural data, the abnormal data can bring loss to agricultural related personnel, in order to reduce the loss, a management department needs to make a decision in time, and the method can provide reference decision information for the management department according to historical agricultural abnormal information.
The present invention has been described in detail with reference to the preferred embodiments thereof, and it should be understood that the invention is not limited thereto, but is intended to cover modifications, equivalents, and improvements within the spirit and scope of the present invention.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
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 a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. 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).
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. An agricultural big data analysis platform, the platform comprising:
the basic layer is used for obtaining basic agricultural data and classifying the basic agricultural data, and the basic layer comprises: the system comprises a basic agricultural data acquisition module, a data processing module and a data processing module, wherein the basic agricultural data acquisition module is used for acquiring basic agricultural data and comprises a plurality of acquisition terminals; the basic agricultural data classification module is used for automatically classifying the basic agricultural data acquired by different acquisition terminals, and the basic agricultural data comprises cost basic agricultural data, growth basic agricultural data, climate basic agricultural data, demand basic agricultural data and production basic agricultural data;
the data layer is used for storing basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information;
the agricultural service system comprises an application layer, a data support layer and a data processing layer, wherein the application layer is used for developing the agricultural service system according to basic agricultural data and visual agricultural information and providing data support for the agricultural service system so that the agricultural service system can be updated according to data provided by the application layer, and the agricultural service system comprises an agricultural remote sensing system, an agricultural product quality tracing system, a rural comprehensive information service system, an agricultural environmental pollution treatment system and an agricultural product market monitoring and early warning system; and
and the decision layer is used for providing reference decision information for the management department according to the historical agricultural abnormal information.
2. The agricultural big data analysis platform according to claim 1, wherein the data layer comprises:
the storage module is used for storing the basic agricultural data in a classified manner;
the data processing module is used for analyzing and processing basic agricultural data to obtain visual agricultural information and comprises various data processing units, and each data processing unit is used for processing specific basic agricultural data and generating visual agricultural information.
3. The agricultural big data analysis platform according to claim 2, wherein the data processing unit comprises:
the data transmission subunit is used for acquiring basic agricultural data from the storage module and sending the basic agricultural data to the data processing subunit;
the data processing subunit is used for analyzing and processing basic agricultural data according to a data processing formula to obtain visual agricultural data, the data processing subunit is internally provided with a data processing formula, and the data processing formula can be edited and changed; and
and the information additional subunit is used for generating additional information according to the visual agricultural data, the additional information is used for reflecting the specific significance of the visual agricultural data, and the additional information and the corresponding visual agricultural data are summarized to generate the visual agricultural information.
4. The agricultural big data analysis platform according to claim 1, wherein the application layer comprises:
the agricultural remote sensing system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural remote sensing system from the data layer;
the agricultural product quality tracing system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural product quality tracing system from the data layer;
the rural comprehensive information service system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the rural comprehensive information service system from the data layer;
the agricultural environmental pollution treatment system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural environmental pollution treatment system from the data layer; and
and the agricultural product market monitoring and early warning system supporting unit is used for acquiring basic agricultural data and visual agricultural information required by the agricultural product market monitoring and early warning system from the data layer.
5. The agricultural big data analysis platform according to claim 1, wherein the decision layer comprises:
the historical agricultural abnormal information base is used for storing historical agricultural abnormal information and storing corresponding historical effective decision information;
the agricultural data abnormity judging module is used for judging whether the basic agricultural data is abnormal or not, and when the basic agricultural data is abnormal, the abnormal basic agricultural data is marked as abnormal basic data;
the abnormal data matching module is used for matching the abnormal basic data with the historical agricultural abnormal information, outputting the historical agricultural abnormal information with the highest matching value and outputting corresponding historical effective decision information; and
and the decision information generating module is used for marking the historical effective decision information as reference decision information, and the reference decision information is used for providing reference for a management department.
6. The agricultural big data analysis platform according to claim 5, wherein the agricultural data abnormality determination module comprises:
the agricultural data abnormity judging unit is used for judging abnormity of the acquired basic agricultural data, the agricultural data abnormity judging unit comprises a normal range value of each basic agricultural data, and when the basic agricultural data is not in the corresponding normal range value, the basic agricultural data is judged to be abnormal; and
and the abnormal basic data output unit is used for marking the abnormal basic agricultural data as abnormal basic data.
7. The agricultural big data analysis platform of claim 6, wherein the abnormal data matching module comprises:
the abnormal basic data integration module is used for integrating the abnormal basic data in a preset time period to form abnormal basic information;
an information matching module, configured to match the abnormal basic information with historical agricultural abnormal information, obtain a first numerical value of abnormal basic data in the abnormal basic information, obtain a second numerical value of abnormal historical data in the historical agricultural abnormal information, obtain a third numerical value of the abnormal basic data and the abnormal historical data that belong to the same type of data and have the same abnormal reason, calculate a matching value, where the matching value is (the third numerical value/the first numerical value) × (the third numerical value/the second numerical value), the abnormal reasons refer to that the basic agricultural data are lower than a normal range value or higher than the normal range value, the first numerical value refers to the specific quantity of the abnormal basic data, the second numerical value refers to the specific quantity of the abnormal historical data, and the third numerical value refers to the specific quantity of the abnormal basic data and the abnormal historical data which belong to the same kind of data and have the same abnormal reasons; and
and the decision information output module is used for obtaining historical agricultural abnormal information with the highest matching value with the abnormal basic information and outputting historical effective decision information corresponding to the historical agricultural abnormal information.
8. The agricultural big data analysis platform according to claim 2, wherein the data layer further comprises a data exchange module, and the data exchange module is used for realizing exchange and sharing of data in the storage module and data outside.
9. The agricultural big data analysis platform according to claim 1, further comprising an expert service module, wherein the expert service module is used for managing agricultural expert teams, and a live broadcast unit, an online course unit, an expert hotline and an expert question and answer unit are arranged in the expert service module.
10. An agricultural big data analysis method, which is characterized by comprising the following steps:
acquiring basic agricultural data and classifying the basic agricultural data;
storing the basic agricultural data and analyzing the basic agricultural data to obtain visual agricultural information;
developing an agricultural service system according to basic agricultural data and visual agricultural information, and providing data support for the agricultural service system so that the agricultural service system can be updated according to data provided by an application layer;
and providing reference decision information for management departments according to the historical agricultural abnormal information.
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