CN116737824B - Block chain-based data sharing method and system - Google Patents
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Abstract
The invention discloses a data sharing method based on a block chain, which comprises the following steps: step one: establishing a scheme sharing cloud platform and a database, establishing an AI matching algorithm, deploying a pest control subsystem and a pest natural enemy popularization subsystem, and step two: deploying a pest control subsystem in a plantation, detecting pest encountering conditions of plantation crops, and step three: an administrator formulates a pest control scheme according to the condition of the pests in the plantation, puts natural enemies attractants according to the types of the natural enemies, detects the propagation condition of the natural enemies of the pests and the change of the scale of the number of the pests, and step four: the AI matching algorithm refers to the control scheme established by a large number of administrators, trains and learns a plantation pest control scheme model, and then nurseryman utilizes AI to complete the plantation pest control.
Description
Technical Field
The invention relates to the technical field of blockchains, in particular to a blockchain-based data sharing method and a blockchain-based data sharing system.
Background
By using the blockchain technology, data sharing and information intercommunication can be well realized, along with the rapid development of the Internet of things technology and the 5G technology, the popularization of the big data processing technology and the rapid iteration of algorithms are realized, and at present, the existing blockchain data sharing system on the market can share data and information at high speed and in large quantity, but the practicality and accuracy of various data shared in the system are realized, so that the problem that a user can solve by using the shared data can not cause new problems any more, can not cause non-virtuous circle, and needs to be perfected and improved. Therefore, the design can use the block chain technology as the main material, ensure the accuracy and high reliability of the shared data in the system, use the AI technology as the auxiliary material, ensure the user to refer to the data shared by the system to solve the problem, can not cause new problems, and can not cause the data sharing method and system of non-virtuous circle to be necessary.
Disclosure of Invention
The present invention is directed to a method and a system for sharing data based on blockchain, so as to solve the above-mentioned problems in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a blockchain-based data sharing method, the method comprising the steps of:
step one: establishing a scheme sharing cloud platform and a database, establishing an AI matching algorithm, and deploying a pest control subsystem and a pest natural enemy popularization subsystem;
Step two: deploying a pest control subsystem in a plantation, and detecting pest encountering situations of plantation crops;
Step three: an administrator formulates a pest control scheme according to the situation of the pests in the plantation, puts natural enemies attractants according to the types of the natural enemies, and detects the propagation situation of the natural enemies of the pests and the change of the scale of the number of the pests;
Step four: the AI matching algorithm is trained to learn a plantation pest control scheme model by referring to control schemes established by a large number of administrators, and then nurseryman completes plantation pest control by using AI.
According to the technical scheme, the establishment scheme shares a cloud platform and a database, creates an AI matching algorithm, deploys a pest control subsystem and a pest natural enemy popularization subsystem, and comprises the following steps:
After the scheme sharing cloud platform is developed, the scheme sharing cloud platform is deployed to the cloud;
accessing a database, and establishing in the database:
"Pest species data table", "Pest actual model gallery", "Pest natural enemy attractant data table", "Pest natural enemy species data table", "Pest natural enemy actual model gallery", "Pest model gallery";
creating an AI matching algorithm;
and accessing the pest control subsystem and the pest natural enemy popularization subsystem to the scheme sharing cloud platform.
According to the technical scheme, the data sharing method and system based on the blockchain are characterized in that: the pest control subsystem is deployed in a plantation, and the step of detecting pest encounter situations of plantation crops comprises the following steps:
Deploying pest control subsystems in various plantation areas;
The subsystem shares cloud platform interaction data with a scheme by using an HTTP protocol;
The subsystem uses a pest detection module, accesses a camera to take T as a period, and periodically shoots pest images on plantation crops;
Uploading pest images to a scheme sharing cloud platform;
the cloud platform stores the pest image data into a pest actual model gallery;
the manager logs in the scheme to share the cloud platform to define types and names for each type of pests in the model gallery;
The administrator then takes a large number of pest images;
judging the quantity scale of the pests in the plantation and judging the influence of the pests on the crops.
According to the technical scheme, the data sharing method and system based on the blockchain are characterized in that: the administrator sets pest control scheme according to the condition of the plant garden pests, puts natural enemies of the pests into the plant garden, puts natural enemies attractants according to the types of the natural enemies, and detects the propagation condition of the natural enemies of the pests and the change of the number scale of the pests, and the method comprises the following steps:
An administrator logs in to the scheme sharing cloud platform;
Investigation revealed the specific case of the plantation encountering pests, and analysis showed that: the information of pest number scale, pest existence type, crop influence, pest population propagation number growth curve;
the analysis of the growth curve is based on plantation pest images regularly shot by the camera;
according to the number of pests in each image area and the change of the number of pests on one image in a period of time;
estimating a pest population propagation quantity increase curve;
The administrator makes pest control scheme according to the above information, mainly comprising:
Introducing a natural enemy of the insect according to the insect species K, and introducing natural enemies of the insect with the quantity Q according to the insect quantity Q and an insect population propagation quantity growth curve w;
In addition, after the natural enemies of the pests are introduced into the plantation, the situation that the natural enemies of the pests are gradually expanded from the plantation to the outside and finally the natural enemies of the pests are far away from the plantation can be considered;
The manager is based on the type K of natural enemies of the pests;
and (3) throwing an attractant H which can attract natural enemies of pests to reproduce in the plantation.
According to the technical scheme, the steps of putting natural enemy attractants according to the natural enemy types and detecting the propagation condition of the natural enemy of the insect and the change of the number scale of the insect comprise the following steps:
After an administrator makes a pest control scheme;
throwing natural enemies of the pests with the quantity of Q and the type of K into a plantation;
putting natural enemy attractants H of pests in various places of the plantation;
The pest natural enemy popularization subsystem regularly shoots the pest natural enemy quantity scale Q and the pest quantity scale Q of each area of the plantation through the camera;
the manager attracts the natural enemies according to the quantity scale of the natural enemies and the attraction degree of the attractants;
Analyzing a population quantity propagation curve W of natural enemies of the pests;
Under the influence of a natural enemy propagation curve W of pests, analyzing a pest population quantity change curve W1;
if the slope of the curve w1 is substantially zero, and the number of the corresponding population of the curve is within 14 days after the substantially zero;
no pest exists on the images shot by all cameras in all areas;
The administrator gradually puts in the attractant in the direction away from the plantation, and gradually moves the natural enemy population of the pests out of the plantation.
According to the above technical scheme, the AI matching algorithm trains and learns a plantation pest control scheme model by referring to control schemes formulated by a large number of administrators, and then nurseryman completes the plantation pest control step by AI, comprising:
In the initial stage of system deployment, an administrator is required to serve a plantation;
the administrator counts various parameters of pests and natural enemies in the garden;
Estimating curves W, W1 and W, and preparing a pest control scheme;
when the system is deployed in multiple places and achieves a certain result, an administrator creates a series of pest control schemes:
because the administrator formulates the scheme, the operation is completed on the scheme sharing cloud platform;
The cloud platform stores all scheme information data into a cloud database;
a database stores control schemes for deploying the system in multiple places, and all scheme information is shared on a cloud platform;
The cloud platform invokes an AI matching algorithm to train and learn, and gradually trains a pest model diagram, a pest natural enemy model diagram and a pest natural enemy attractant model according to a scheme;
AI repeatedly trains and learns, constantly optimizes the model;
The final administrator selects the best prevention solution model and stores it in the model library.
According to the above technical scheme, the nurseryman steps for controlling the plantation pests by using the AI include:
The cloud platform invokes AI to train an optimized pest control scheme model;
The system is deployed in other plantations in other areas, and all schemes are shared;
Plantation nurseryman accesses the system on APP;
AI calls cameras deployed in the plantation, and counts the number of pests, the types of the pests and the population propagation curve w of the pests in the plantation;
The number scale is divided into: 1. class 2,3, 4, 5 grades;
a curve w estimated according to the classification and AI;
A proper introduction amount of natural enemies of the pests with the quantity Q and a proper preparation of the attractant amount H are recommended for nurseryman;
nurseryman introducing natural enemies and attractants of pests according to a pest control scheme formulated by AI;
After the AI judges that the pests are cleaned, guiding nurseryman to gradually lead out natural enemies of the pests;
the scheme and the process AI continue to train and learn, and continue to optimize the model.
According to the above technical scheme, the pest control subsystem includes:
the pest detection module is used for detecting the types and the quantity scales of pests in each area in the plantation;
The pest identification module is used for extracting a pest model from the shot pest image and sending the pest model to the scheme sharing cloud platform;
And the crop detection module is used for detecting the influence of pests on crops.
According to the technical scheme, the pest natural enemy popularization subsystem comprises:
The attractant analysis module is used for searching a place suitable for putting the attractant in the garden;
The natural enemy throwing module is used for reporting to the scheme sharing cloud platform, and the types and population quantity scales of the natural enemies of the pests are thrown in the garden;
the pest natural enemy detection module is used for detecting the population propagation condition of the natural enemy of the thrown pest on the day enemy's rear area, the scale change curve of the pest population quantity and the influence change of the pest damage quantity of crops.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, an established scheme is set to share a cloud platform and a database, an AI matching algorithm is created, a pest control subsystem and a pest natural enemy popularization subsystem are deployed, the pest control subsystem is deployed in a plantation, the situation that a crop in the plantation encounters a pest is detected, an administrator sets a pest control scheme according to the situation of the pest in the plantation, the natural enemy is put in the plantation, a natural enemy attractant is put in according to the type of the natural enemy, the propagation situation of the pest and the change of the scale of the number of the pest are detected, the AI matching algorithm references to the control scheme set by a large number of administrators, and a plantation pest control scheme model is trained and learned, and then nurseryman utilizes AI to complete the pest control of the plantation, so that the user benefit can be well ensured while the conventional system shares a data scheme, the problem is solved by the system, a new problem can not appear any more, and a non-benign cycle can not be entered.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flowchart of a block chain based data sharing method according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a block chain-based data sharing method and system according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: fig. 1 is a flowchart of a blockchain-based data sharing method and system according to an embodiment of the present invention, where the embodiment may be applied to a plantation scene such as an orchard garden, and the method may be performed by the blockchain-based data sharing method and system according to the embodiment, as shown in fig. 1, and the method specifically includes the following steps:
step one: establishing a scheme sharing cloud platform and a database, establishing an AI matching algorithm, and deploying a pest control subsystem and a pest natural enemy popularization subsystem;
In the embodiment of the invention, after the scheme sharing cloud platform is developed, the scheme sharing cloud platform is deployed to the cloud end and is accessed into a database, and the database is built: the method comprises the steps of creating an AI matching algorithm, and accessing a pest control subsystem and a pest natural enemy popularization subsystem to a scheme sharing cloud platform.
Step two: deploying a pest control subsystem in a plantation, and detecting pest encountering situations of plantation crops;
In the embodiment of the invention, pest control subsystems are deployed in various places of plantations, the subsystems interact data with a scheme sharing cloud platform by using an HTTP protocol, the subsystems periodically shoot pest images on the plantations by using a pest detection module, an access camera takes T as a period, the pest images are uploaded to the scheme sharing cloud platform, the cloud platform stores pest image data into a pest actual model gallery, an administrator logs in the scheme sharing cloud platform as the definition type and name of each type of pest in the model gallery, and the administrator judges the quantity and scale of the plantations and judges the influence of the pests on the crops according to the shot quantity of pest images.
Step three: an administrator formulates a pest control scheme according to the situation of the pests in the plantation, puts natural enemies attractants according to the types of the natural enemies, and detects the propagation situation of the natural enemies of the pests and the change of the scale of the number of the pests;
S31: in the embodiment of the invention, an administrator logs in to the scheme sharing cloud platform, surveys and clearly shows the specific situation of the plant encountering pests, and analyzes: the method comprises the steps of estimating a pest population propagation quantity growth curve according to the pest quantity of a plantation which is regularly shot by a camera and the quantity of the pests in each image area and the change of the quantity of the pests on one image in a period of time, and formulating a pest control scheme by an administrator according to the information, wherein the pest population propagation quantity growth curve is estimated by analyzing the pest quantity scale, the pest existence type, the crop influence and the pest population propagation quantity growth curve, and the pest control scheme mainly comprises the following steps: introducing a natural enemy of the insect according to the insect species K, introducing a natural enemy of the insect with the quantity Q according to the insect quantity Q and a propagation quantity increasing curve w of the insect population, and in addition, considering that the natural enemy of the insect is gradually expanded from the plantation to the outside after being introduced into the plantation, finally leading the natural enemy of the insect to be far away from the plantation, and putting an attractant H which can attract the natural enemy of the insect to propagate in the plantation into the plantation according to the species K of the natural enemy of the insect by an administrator;
S32: after an administrator formulates a pest control scheme, putting natural enemies of the number Q and the type K into a plantation, putting natural enemies of the pests into the plantation everywhere, shooting the natural enemies of the pests in each area of the plantation in a regular mode through a camera by using a natural enemies popularization subsystem, analyzing a natural enemies population quantity propagation curve W according to the natural enemies quantity scale and the attraction degree of the attractants to the natural enemies by the administrator, analyzing a natural enemies population quantity change curve W1 under the influence of the natural enemies propagation curve W, and if the slope of the curve W1 is basically zero and the population quantity is basically zero, then, on images shot by all cameras of all areas, gradually putting the attractants in the direction away from the plantation, gradually removing the natural enemies of the pests out of the plantation.
Step four: the AI matching algorithm refers to a control scheme established by a large number of administrators, trains and learns a plantation pest control scheme model, and then nurseryman utilizes AI to complete plantation pest control;
S41: in the embodiment of the invention, an administrator is required to serve a plantation in the initial deployment stage of the system, the administrator counts various parameters of pests and various parameters of natural enemies of the pests in the plantation, the curves W, W1 and W are estimated, pest control schemes are made, when the system is deployed in multiple places and a certain achievement is obtained, when the administrator makes a series of pest control schemes, the administrator makes schemes, operations are completed on a scheme sharing cloud platform, the cloud platform stores all scheme information data into a cloud database, one database stores control schemes for deploying the system in multiple places, all scheme information are shared on the cloud platform, the cloud platform invokes an AI matching algorithm to train and learn, a pest model diagram, a natural enemy pest model diagram and an AI natural enemy attractant model are trained and learned repeatedly according to gradually train, and finally, the administrator selects the best prevention scheme model and stores the best prevention scheme model into a model library;
S42: after the cloud platform invokes the AI to train the optimized pest control scheme model, other plantations in other areas are deployed with the system, all schemes are shared, the plantations nurseryman access the system on the APP, the AI invokes the cameras deployed in the plantations, and the number of pests, the types of pests and the pest population propagation curve w in the plantations are counted, and the system is divided into the following steps according to the number scale: 1. class 2, class 3, class 4 and class 5 are classified according to the classification and curve w estimated by AI, a proper introduction quantity of natural enemies of pests with the quantity Q and a proper introduction quantity of attractant H are recommended for nurseryman, the natural enemies of the pests and the attractant are introduced according to a pest control scheme formulated by AI by nurseryman, after the AI judges that the pests are cleaned, the natural enemies of the pests are led out gradually by guiding nurseryman, the scheme and the process AI continue training and learning, and the model is optimized continuously; compared with the existing data sharing method system in the market, the system has the advantages that before data sharing, the acquired successful cases are re-shared to the system through market research and deployment of the system on the market, the data acquired by the system are ensured to be accurate and reliable information, the correct data are trained and learned through a self-created AI matching algorithm, the trained achievements are shared to the system by the AI through repeated optimization, and finally, the information is widely shared by the AI.
Embodiment two: fig. 2 is a schematic block diagram of a block chain based data sharing method and system according to a second embodiment of the present invention, as shown in fig. 2, where the system includes:
A database for storing all data generated by the system, wherein the database is established: the pest species data table, the pest actual model drawing library, the pest natural enemy attractant data table, the pest natural enemy species data table, the pest natural enemy actual model drawing library and the pest model drawing library are used for storing various data in a classified manner;
The AI matching algorithm is used for training and learning a pest control scheme model, analyzing and estimating a pest population propagation curve and a pest natural enemy population propagation curve, and providing a control scheme for the plantation nurseryman;
The scheme sharing cloud platform is used for an administrator to count and estimate various data, formulate a scheme and issue the scheme to the pest control subsystem and the pest natural enemy popularization subsystem, transfer and transfer the various data, and schedule all modules and subsystems in the system to complete the overall operation of the system;
The pest control subsystem is used for being deployed in a plantation and detecting the population quantity of pests, the types of the pests and the influence condition of the pests on crops in the plantation;
The pest natural enemy popularization subsystem is used for guiding the plantation nurseryman to throw in the pest natural enemy, throwing in the pest natural enemy attractant, detecting the leading-in day enemy's rear area, leading nurseryman to gradually lead out the pest natural enemy, wherein the population number of the pest and the pest natural enemy changes;
In some embodiments of the present invention, a pest control subsystem includes:
the pest detection module is used for detecting the types and the quantity scales of pests in each area in the plantation;
The pest identification module is used for extracting a pest model from the shot pest image and sending the pest model to the scheme sharing cloud platform;
The crop detection module is used for detecting the influence of pests on crops;
in some embodiments of the invention, a pest natural enemy popularization subsystem includes:
The attractant analysis module is used for searching a place suitable for putting the attractant in the garden;
The natural enemy throwing module is used for reporting to the scheme sharing cloud platform, and the types and population quantity scales of the natural enemies of the pests are thrown in the garden;
the pest natural enemy detection module is used for detecting the population propagation condition of the natural enemy of the thrown pest on the day enemy's rear area, the scale change curve of the pest population quantity and the influence change of the pest damage quantity of crops.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The data sharing method based on the block chain is characterized by comprising the following steps of: the method comprises the following steps:
step one: establishing a scheme sharing cloud platform and a database, establishing an AI matching algorithm, and deploying a pest control subsystem and a pest natural enemy popularization subsystem;
Step two: deploying a pest control subsystem in a plantation, and detecting pest encountering situations of plantation crops;
Step three: an administrator formulates a pest control scheme according to the situation of the pests in the plantation, puts natural enemies attractants according to the types of the natural enemies, and detects the propagation situation of the natural enemies of the pests and the change of the scale of the number of the pests;
step four: the AI matching algorithm refers to a control scheme established by a large number of administrators, trains and learns a plantation pest control scheme model, and then nurseryman utilizes AI to complete plantation pest control;
the AI matching algorithm trains and learns a plantation pest control scheme model by referring to control schemes established by a large number of administrators, and then nurseryman completes the plantation pest control step by AI, comprising:
In the initial stage of system deployment, an administrator is required to serve a plantation;
the administrator counts various parameters of pests and natural enemies in the garden;
Estimating curves W, W1 and W to prepare a pest control scheme, wherein W is a pest population propagation curve, W1 is a pest population quantity change curve, and W is a pest natural enemy population quantity propagation curve;
when the system is deployed in multiple places and achieves a certain result, an administrator creates a series of pest control schemes:
because the administrator formulates the scheme, the operation is completed on the scheme sharing cloud platform;
The cloud platform stores all scheme information data into a cloud database;
a database stores control schemes for deploying the system in multiple places, and all scheme information is shared on a cloud platform;
The cloud platform invokes an AI matching algorithm to train and learn, and gradually trains a pest model diagram, a pest natural enemy model diagram and a pest natural enemy attractant model according to a scheme;
AI repeatedly trains and learns, constantly optimizes the model;
finally, the administrator selects the best control scheme model and stores the best control scheme model into a model library;
the nurseryman steps for controlling the plant garden pests by utilizing AI comprise the following steps:
The cloud platform invokes AI to train an optimized pest control scheme model;
The system is deployed in other plantations in other areas, and all schemes are shared;
Plantation nurseryman accesses the system on APP;
AI calls cameras deployed in the plantation, and counts the number of pests, the types of the pests and the population propagation curve w of the pests in the plantation;
The number scale is divided into: 1. class 2,3, 4, 5 grades;
a curve w estimated according to the classification and AI;
A proper introduction amount of natural enemies of the pests with the quantity Q and a proper preparation of the attractant amount H are recommended for nurseryman;
nurseryman introducing natural enemies and attractants of pests according to a pest control scheme formulated by AI;
After the AI judges that the pests are cleaned, guiding nurseryman to gradually lead out natural enemies of the pests;
the scheme and the process AI continue to train and learn, and continue to optimize the model.
2. The blockchain-based data sharing method of claim 1, wherein: the establishment scheme shares a cloud platform and a database, creates an AI matching algorithm, deploys a pest control subsystem and a pest natural enemy popularization subsystem, and comprises the following steps:
After the scheme sharing cloud platform is developed, the scheme sharing cloud platform is deployed to the cloud;
accessing a database, and establishing in the database:
"Pest species data table", "Pest actual model gallery", "Pest natural enemy attractant data table", "Pest natural enemy species data table", "Pest natural enemy actual model gallery", "Pest model gallery";
creating an AI matching algorithm;
and accessing the pest control subsystem and the pest natural enemy popularization subsystem to the scheme sharing cloud platform.
3. The blockchain-based data sharing method of claim 1, wherein: the pest control subsystem is deployed in a plantation, and the step of detecting pest encounter situations of plantation crops comprises the following steps:
Deploying pest control subsystems in various plantation areas;
The subsystem shares cloud platform interaction data with a scheme by using an HTTP protocol;
The subsystem uses a pest detection module, accesses a camera to take T as a period, and periodically shoots pest images on plantation crops;
Uploading pest images to a scheme sharing cloud platform;
the cloud platform stores the pest image data into a pest actual model gallery;
the manager logs in the scheme to share the cloud platform to define types and names for each type of pests in the model gallery;
and then, the manager judges the quantity and scale of the pests in the plantation according to the shot large number of pest images, and judges the influence of the pests on the crops.
4. The blockchain-based data sharing method of claim 1, wherein: the administrator sets pest control scheme according to the condition of the plant garden pests, puts natural enemies of the pests into the plant garden, puts natural enemies attractants according to the types of the natural enemies, and detects the propagation condition of the natural enemies of the pests and the change of the number scale of the pests, and the method comprises the following steps:
An administrator logs in to the scheme sharing cloud platform;
Investigation revealed the specific case of the plantation encountering pests, and analysis showed that: the information of pest number scale, pest existence type, crop influence, pest population propagation number growth curve;
the analysis of the growth curve is based on plantation pest images regularly shot by the camera;
the system converts the shot pest images into gray histograms so as to filter the interference of other scenery color pixel points on pest outline figure pixel points;
The system recalls the pest outline model graph stored in the database, and compares the gray level histogram with the outline model graph for analysis;
Analyzing how many pest contour patterns are on the gray level histogram, so as to judge the pest quantity on one image;
according to the number of pests in each image area and the change of the number of pests on one image in a period of time;
estimating a pest population propagation quantity increase curve;
The administrator makes pest control scheme according to the above information, mainly comprising:
introducing a natural enemy of the insect according to the insect species K, and introducing natural enemies of the insect with the number Q according to the insect number Q and the insect population propagation curve w;
In addition, after the natural enemies of the pests are introduced into the plantation, the situation that the natural enemies of the pests are gradually expanded from the plantation to the outside and finally the natural enemies of the pests are far away from the plantation can be considered;
The manager is based on the type K of natural enemies of the pests;
and (3) throwing an attractant H which can attract natural enemies of pests to reproduce in the plantation.
5. The blockchain-based data sharing method of claim 4, wherein: according to natural enemy species, putting in natural enemy attractants, and detecting the propagation condition of the natural enemy of the insect and the change of the number scale of the insect, wherein the method comprises the following steps:
After an administrator makes a pest control scheme;
throwing natural enemies of the pests with the quantity of Q and the type of K into a plantation;
putting natural enemy attractants H of pests in various places of the plantation;
The pest natural enemy popularization subsystem regularly shoots the pest natural enemy quantity scale Q and the pest quantity scale Q of each area of the plantation through the camera;
the manager attracts the natural enemies according to the quantity scale of the natural enemies and the attraction degree of the attractants;
Analyzing a population quantity propagation curve W of natural enemies of the pests;
under the influence of a natural enemy population quantity propagation curve W of pests, analyzing a pest population quantity change curve W1;
if the slope of the curve w1 is substantially zero, and the number of the corresponding population of the curve is within 14 days after the substantially zero;
no pest exists on the images shot by all cameras in all areas;
The administrator gradually puts in the attractant in the direction away from the plantation, and gradually moves the natural enemy population of the pests out of the plantation.
6. The data sharing system based on the block chain is characterized in that: the system comprises:
A database for storing all data generated by the system, wherein the database is established: the pest species data table, the pest actual model drawing library, the pest natural enemy attractant data table, the pest natural enemy species data table, the pest natural enemy actual model drawing library and the pest model drawing library are used for storing various data in a classified manner;
The AI matching algorithm is used for training and learning a pest control scheme model, analyzing and estimating a pest population propagation curve and a pest natural enemy population propagation curve, and providing a control scheme for the plantation nurseryman;
The scheme sharing cloud platform is used for an administrator to count and estimate various data, formulate a scheme and issue the scheme to the pest control subsystem and the pest natural enemy popularization subsystem, transfer and transfer the various data, and schedule all modules and subsystems in the system to complete the overall operation of the system;
The pest control subsystem is used for being deployed in a plantation and detecting the population quantity of pests, the types of the pests and the influence condition of the pests on crops in the plantation;
The pest natural enemy popularization subsystem is used for guiding the plantation nurseryman to throw in the pest natural enemy, throwing in the pest natural enemy attractant, detecting the population quantity change of the pest and the pest natural enemy on the leading-in day enemy's rear area and guiding the nurseryman to gradually lead out the pest natural enemy.
7. The blockchain-based data sharing system of claim 6, wherein: the pest control subsystem includes:
the pest detection module is used for detecting the types and the quantity scales of pests in each area in the plantation;
The pest identification module is used for extracting a pest model from the shot pest image and sending the pest model to the scheme sharing cloud platform;
And the crop detection module is used for detecting the influence of pests on crops.
8. The blockchain-based data sharing system of claim 6, wherein: the pest natural enemy popularization subsystem comprises:
The attractant analysis module is used for searching a place suitable for putting the attractant in the garden;
The natural enemy throwing module is used for reporting to the scheme sharing cloud platform, and the types and population quantity scales of the natural enemies of the pests are thrown in the garden;
the pest natural enemy detection module is used for detecting the population propagation condition of the natural enemy of the thrown pest on the day enemy's rear area, the scale change curve of the pest population quantity and the influence change of the pest damage quantity of crops.
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