KR20180054352A - Outdoor Farm Weather Risk Management Methode - Google Patents

Abstract

The present invention relates to a method for managing open land agricultural cultivation using agricultural weather information, which uses an agricultural cultivation management system for open land cultivation (100) comprising: a database (110) including a weather information database (111) which accumulates and stores real time weather information received from a weather information server through a communication interface (120) via a communication network (N), and a crop information database (112) which stores crop information with respect to crops to be cultivated; and a crop condition prediction module (130) which predicts prediction details by analyzing real time weather information and accumulated weather information received from the database (110), and delivers the prediction details to a user terminal (150) through the communication interface (120). The method comprises: a step of collecting data (S1); a step of analyzing the data (S2); a step of selecting varieties to be cultivated (S3); a step of predicting seeding time (S4); a step of forecasting damages by blight and harmful insects (S5); and a step of selecting agricultural pesticides and predicting time to spray the agricultural pesticides.

Description

{Outdoor Farm Weather Risk Management Methode}

The present invention relates to a non-agricultural farm management management method using agricultural weather information, and more particularly, to a non-agricultural farm management management method using agricultural weather information, which comprises a weather information server (10) A database 110 including a database 111 and a crop information database 112 for storing crop information about cultivated crops; and a database 110 including cumulative weather information received from the database 110, A crop condition prediction module (130) for analyzing information to predict a prediction and delivering the prediction to the user terminal (150) through the communication interface (120); A method for cultivating and managing a non-crop farmland using agricultural weather information using an agricultural cultivation management management system (100) for growing non-crop cultivated land,

(S1) for collecting the real-time weather information, the accumulated weather information, and the crop information, and analyzing the real-time weather information, the accumulated weather information, and the crop information collected in the data collection step (S1) (S3) of selecting a cultivar suitable for the prediction based on the analysis data analyzed in the data analysis step (S2) and delivering the selected cultivar to the user terminal (150) A seeding time predicting step S4 for predicting a seeding time of the cultivar selected as the prediction item in the cultivar selection step S3 and transmitting it to the user terminal 150, (S5) for predicting a pest or a pest according to the predicted pest based on analysis data analyzed in step (S2) and transmitting the predicted pest or pest to the user terminal (150) A pesticide selecting and spraying timing predicting step (S6) for selecting suitable pesticides and predicting the spraying and delivering them to the user terminal (150) when the occurrence of a pest or a pest is predicted in the pest predicting step (S5); The present invention relates to a method for managing agricultural cultivation management using agricultural weather information.

Agriculture is the industry that produces the most basic food and foodstuffs for the survival of mankind. It is a representative primary industry that provided the foundation for mankind to settle in one place and develop civilization.

This agriculture requires a lot of manpower. In our country, the aging and small-sized families are rapidly advancing into the modern society, and the proportion of the population engaged in agriculture is also decreasing, and the average age of agriculture is gradually aging, It is becoming a problem.

On the other hand, since agriculture produces organic organisms, it depends heavily on natural conditions such as land and climate. In recent years, there have been many methods of cultivating crops while controlling the cultivation environment artificially in facilities such as greenhouses . In addition, ICT (Information & Communication Technology) fusion technology is applied to farming methods to optimize crop cultivation environment in the farmhouse. In response to the weakening of food resources, ICT To increase the competitiveness of agriculture.

As a conventional invention for realizing such precision agriculture, a farmhouse that manages a facility such as a plastic house or a glass greenhouse conventionally has proposed a system and method for controlling a horticultural facility (Korean Patent Registration No. 10-1465082) "Have been proposed.

However, most of these existing inventions are operated as a facility capable of controlling the temperature / humidity / light quantity so as to suitably maintain the growth environment of the crops in the facilities such as the greenhouse, , Beans, potatoes, etc.) are not applicable when considering the characteristics of cultivation through non-cultivation instead of cultivation.

On the other hand, in the case of such non-cultivated crops, various factors such as the growth and development as well as the occurrence of pests and diseases are greatly affected by the weather conditions, compared to the case of cultivating the plants. Accordingly, it is possible to not only receive such a weather phenomenon in real time quickly and accurately, but also to accurately forecast weather conditions by analyzing big data such as weather information for a predetermined period of time in the cultivating area, According to the situation forecast, a method of predicting and providing proper seeding, prevention of sickness, harvesting time, etc. is required.

Korean Patent No. 10-1465082

DISCLOSURE OF THE INVENTION The present invention solves the above-mentioned problems of the prior art, and it is an object of the present invention to provide a method and apparatus for not only receiving and measuring important weather information in a real time, but also accumulating and managing it as Big Data, , Agroforestry using comprehensive agricultural weather information such as sowing time of selected cultivated cultivar, prediction of sickness and pest, prediction of pesticide selection for spraying of pesticide for prevention of disease and pest and spraying time of selected cultivated cultivar And to provide cultivation management management methods.

On the other hand, in the course of cultivation of a series of cultivation, the cultivation history of the cultivated crops is stored and managed as systematic data according to the decision of the user, so that the agricultural weather can be applied as another data for cultivation management, And to provide a method for cultivating and managing the farmhouse using information.

In order to achieve the above object, the present invention provides a non-farm farm management management method using agricultural weather information, which comprises: accumulating real-time weather information received from a weather information server (10) via a communication network (120) And a crop information database 112 for storing crop information on cultivated crops; and a database 110 for storing cumulative information received from the database 110, A crop state prediction module (130) for analyzing weather information and real time weather information to predict a forecast and delivering the forecast to the user terminal (150) through the communication interface (120); A method for cultivating and managing a non-crop farmland using agricultural weather information using an agricultural cultivation management management system (100) for growing non-crop cultivated land,

(S1) for collecting the real-time weather information, the accumulated weather information, and the crop information, and analyzing the real-time weather information, the accumulated weather information, and the crop information collected in the data collection step (S1) (S3) of selecting a cultivar suitable for the prediction based on the analysis data analyzed in the data analysis step (S2) and delivering the selected cultivar to the user terminal (150) A seeding time predicting step S4 for predicting a seeding time of the cultivar selected as the prediction item in the cultivar selection step S3 and transmitting it to the user terminal 150, (S5) for predicting a pest or a pest according to the predicted pest based on analysis data analyzed in step (S2) and transmitting the predicted pest or pest to the user terminal (150) A pesticide selecting and spraying timing predicting step (S6) for selecting suitable pesticides and predicting the spraying and delivering them to the user terminal (150) when the occurrence of a pest or a pest is predicted in the pest predicting step (S5); And a control unit.

In addition, a harvesting time predicting step (S7) for predicting a crop harvesting time based on the analysis data analyzed in the data analysis step (S2) and delivering it to the user terminal (150); And further comprising:

The data collection step S1 includes a real time data collection step S1a for continuously collecting the information in real time while the cultivar type selection step S3 to the harvest time prediction step S7 are performed; Wherein the data analysis step (S2) comprises: a real-time data analysis step (S7) of continuously analyzing the information in real time while the cultivar type selection step (S3) to the harvest time prediction step (S7) (S2a); And further comprising:

In addition, the selection step S3, the seeding time predicting step S4, the disease and pest prediction step S5, the pesticide selection and spraying time predicting step S6, and the harvesting time predicting step S7, S3a, S4a, S6a, and S7a for accepting the decision of the user after each of the steps S3a, S4a, S6a, and S7a is performed.

The cultivation history of the cultivated crop including the decision of the user received in the respective decision steps S3a, S4a, S6a and S7a is transmitted to the cultivation operation database 113 through the agricultural history information management module 140, A farm history management step S8 for storing and managing the farm history information; And further comprising:

In accordance with the present invention, it is possible to receive and measure particularly important weather information in the non-growing stage in real time, and to utilize it as Big Data while cumulating and managing it, and selecting suitable cultivation varieties, Provides methods for cultivation management management of agro-agriculture using comprehensive agricultural weather information such as sowing time of sowing, forecast of sickness and insect damage, selection of pesticide for prevention of disease and insect damage, It is possible to make it possible.

On the other hand, in the course of cultivation of a series of cultivation, the cultivation history of the cultivated crops is stored and managed as systematic data according to the decision of the user, so that the agricultural weather can be applied as another data for cultivation management, It is possible to provide a method of cultivating management management of a non-farm household using information.

Fig. 1 is a block diagram of an overall construction block diagram of an agricultural cultivation management management system for cultivating a non-cultivated land according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for managing cultivation management of a non-farm household using agricultural weather information according to an embodiment of the present invention.
3 is a graph for explaining an announcement of a disaster alert according to a plagiarism prediction model of a non-farm farm management management method using agricultural weather information according to an embodiment of the present invention.
4 is a graph for explaining the disaster prevention notification operation according to a plagiarism prediction model of a non-farm farm management management method using agricultural weather information according to an embodiment of the present invention.
5 is a block diagram of the measurement module of the agricultural cultivation management management system for the non-cultivated farm in which the non-farm farming management management method using the agricultural weather information according to an embodiment of the present invention is performed.

Hereinafter, a method for cultivating and managing a non-farm household using agricultural weather information according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. First, it should be noted that, in the drawings, the same components or parts are denoted by the same reference numerals whenever possible. In describing the present invention, a detailed description of known functions and configurations incorporated herein will be omitted so as to avoid obscuring the subject matter of the present invention.

First, a brief description will be given of an agricultural cultivation management management system for a non-agricultural cultivation in which a non-agricultural cultivation management management method using agricultural weather information according to an embodiment of the present invention is performed. As shown in FIG. 1, the agriculture cultivation management management system 100 for cultivating a non-cultivated land includes a weather information accumulating and accumulating real-time weather information received from the weather information server 10 through the communication network 120 via the communication interface 120, A data base 110 including an information database 111 and a crop information database 112 for storing crop information on cultivated crops; And a crop state prediction module (130) for analyzing the information, predicting the prediction, and transmitting the prediction to the user terminal (150) through the communication interface (120).

First, the database 110 will be described. 1, the database 110 includes a weather information database 111 for accumulating and storing real-time weather information received from the weather information server 10 through the communication network 120 via the communication interface 120 And a crop information database 112 for storing crop information on cultivated crops. In this case, the real-time weather information received from the weather information server 10 may include at least one of a current temperature, a maximum temperature and a minimum temperature of the plantation site, temperature information including a daylight difference, a time / day / month / annual rainfall rate, Information including at least one of < / RTI > In addition, the short-term / medium-term / long-term weather forecast provided from the weather information server 10 includes danger weather forecast information that can affect cultivation such as typhoon, hail, frost, strong wind, . The weather information is accumulated and stored in the weather information database 111 and utilized by the crop condition prediction module 130 as Big-Data for determining various predictions.

As shown in FIG. 1, the weather information database 111 receives weather information for each installation location from the measurement module 200 from the communication interface 120 so that accurate weather conditions of actual cultivated land can be measured and delivered It is desirable to store more. 1, the measurement module 200 is installed in the actual cultivated land and is installed in the actual cultivating area, and the temperature, the underground temperature, the vertical temperature, the humidity, the underground humidity, the wind speed, the wind direction, the luminous intensity, the soil EC (electrical conductivity) And a sensor unit 210 for measuring weather information for each installation location including at least one of rainfall, rainfall, and precipitation and transmitting the measured weather information to the communication interface 120. In this case, the sensor unit 210 can detect at least one of the temperature, the ground temperature, the vertical temperature, the humidity, the ground humidity, the wind speed, the wind direction, the luminous intensity, the soil EC (electrical conductivity) And a wireless transmitting / receiving unit 213 for transmitting weather information for each installation location measured by the sensor unit 211 to the communication interface 120. The wireless transmission / . Meanwhile, the sensor unit 210 may include a power supply unit 212 required for driving as shown in FIG. In this case, the power supply unit 212 is detachably installed in consideration of the characteristics of the sensor unit 210 in which a plurality of power supply units 212 are installed, In a solar cell.

As shown in FIG. 1, the measurement module 200 may include a sensor unit 210, such as shown in FIGS. 1 and 2, so that the state of a crop cultivated on the cultivated land can be grasped and stored. And a camera module 230 installed in the camera module 230, respectively.

On the other hand, the crop information database 112 is configured to have a function of storing crop information on cultivated crops. In this case, the crop information includes information on the growth characteristics according to the weather conditions such as the seeding time, the temperature and the amount of sunshine, and the amount of rainfall for each of the cultivated crops, the characteristics of the disease or pest according to the weather conditions, It is preferable to be configured to include various information necessary for the cultivation of the crop.

Next, the crop condition prediction module 130 will be described. As shown in FIG. 1, the crop state prediction module 130 analyzes the cumulative weather information and the real-time weather information received from the database 110, And to transmit the prediction to the user terminal 150 via the communication interface 120. The user terminal 150 may be connected to the communication terminal 100 via the communication interface 120. [

1, the crop condition prediction module 130 includes an analysis module 131 for analyzing cumulative weather information and real-time weather information received from the database 110, As shown in FIG. 1, the crop condition prediction module 130 selects a suitable cultivar type through the Big-Data analyzed by the analysis module 131, Further comprising a prediction module (132) for predicting one or more predictions of a time, a disease and a pest prediction, a selection of a pesticide for prevention of a disease and a pest, a spray timing guide, and a harvest time forecast of the cultivated cultivar . 1, the crop state prediction module 130 transmits the prediction predicted by the prediction module 132 to the user terminal 150 through the communication interface 120, And a decision module 133 for receiving the decision of the user. That is, according to a big-data analysis method widely used recently, it is configured to predict and determine the items required for cultivation of the crop in each growth stage, to deliver the information to the user, and to guide the user.

The user terminal 150 may include at least one of a mobile terminal, a tablet, a notebook computer, and a personal computer. In this case, the user terminal 150 is preferably configured to be able to exchange information with the communication interface 120 via the communication network N, as shown in FIG.

Next, a method of cultivating and managing a non-farm household using agricultural weather information according to an embodiment of the present invention will be described. A method for cultivating and managing a non-agricultural land use management system using agricultural weather information according to the present invention is a method for cultivating agricultural land management using agricultural weather information using the agricultural cultivation management system (100) , A data analysis step (S2), a cultivar selection step (S3), a seeding time predicting step (S4), a disease and pest prediction step (S5), and a pesticide selection and spraying time predicting step (S6) .

First, the data collection step S1 will be described. The data collection step S1 collects the real-time weather information, the accumulated weather information, and the crop information, and stores the collected information in the database 110. [ In this case, as shown in FIG. 2, the data collection step S1 is a step of collecting the real time data (real time data) continuously collecting the information in real time while the cultivar type selection step (S3) And a collecting step (S1a). 1, the crop condition predicting module 130 includes a seed supplier server 20 that transmits seed prices and supply and demand conditions for each cultivar type through the communication interface 120, A pesticide supplier server 30 for transmitting the characteristics, price, and supply / demand status of pesticides, an agricultural machine supplier server 40 for conveying the type and unit price of agricultural machinery, availability and supply / demand status of agricultural machinery, agricultural products It is preferable to further connect to at least one of the seller servers 50, and the data collecting step S1 preferably collects such additional information together.

Next, the data analysis step S2 will be described. The data analysis step S2 is a step of analyzing the real-time weather information, the accumulated weather information, and the crop information collected in the data collection step S1, as shown in FIG. In this case, the data analysis step S2 is preferably performed by a big-data analysis method. The data analyzing step S2 may include a step S3 of selecting cultivated cultivars or a step S7 of predicting the harvest time, as shown in FIG. 2, in order to analyze data continuously fluctuating during the cultivation process in real time. And a real-time data analysis step (S2a) for continuously analyzing the information in real time during the execution of the real-time data analysis step (S2a).

Next, the cultivation type selection step (S3) will be described. As shown in FIG. 2, the cultivar type selection step S3 is a step of selecting a cultivar suitable for the prediction based on the analysis data analyzed in the data analysis step S2 and delivering it to the user terminal 150 .

Next, the seeding time predicting step S4 will be described. As shown in FIG. 2, the seeding time predicting step S4 predicts the seeding time of the cultivar selected as the prediction item in the cultivar selection step S3, and transmits the predicted seeding time to the user terminal 150. FIG.

Next, the disease and pest forecasting step S5 will be described. As shown in FIG. 2, the disease and pest forecasting step S5 predicts a pest or a pest based on the analysis data analyzed in the data analysis step S2 and transmits the predicted pest or pest to the user terminal 150 . The above-described disease and pest forecasting step (S5) will be described in more detail through an embodiment for predicting and preventing potato blight if the potato is a cultivated crop.

Potato blight occurs in areas with high humidity between 4 and 29 ° C. Hot, dry weather prevents the spread of the disease. Contagious potatoes and tomatoes are rotting within two weeks, and this plague is the leading disease of potato famine in Ireland in 1845-60. As shown in FIG. 3, when there is a disease in which the characteristics are known through analysis of Big Data (in the case of potato blight, it is highly dependent on temperature and humidity, and particularly when humidity is high) And the cumulative value of the time is determined to be equal to or greater than a predetermined reference value. When it is determined that the cumulative value of the time exceeds the predetermined reference value, 150 to the user.

Meanwhile, as shown in FIG. 4, when the relative humidity is 90% or more for a predetermined period of time, it is observed and analyzed in real time and cumulatively, and when it is determined that the accumulation value of the time exceeds the predetermined reference, And transmits the information to the user through the user terminal 150. [0064]

Next, the pesticide selection and spraying timing predicting step (S6) will be described. As shown in FIG. 2, the pesticide selection and spraying time predicting step S6 may be performed by selecting appropriate pesticides and predicting the spraying time when the occurrence of the pest or insect pests is predicted in the pest and pest forecasting step S5, 150, respectively. In this case, it is preferable to transmit relevant information such as the pesticide suitable for disaster prevention, its disaster management medication time and dosage.

Meanwhile, as shown in FIG. 2, the method of managing the cultivation management of a non-farm household using agricultural weather information according to an embodiment of the present invention to guide an appropriate harvesting time is based on analysis data analyzed in the data analysis step (S2) A harvesting time predicting step (S7) for predicting the harvest time of the crop and transmitting the predicted harvesting time to the user terminal (150); And further comprising: In this case, the crop condition predicting module 130 is further connected to the agricultural product seller server 50 through the communication interface 120 and the communication network N as shown in FIG. 1, It is preferable to determine the most advantageous harvesting time and shipment amount according to the harvesting time by further taking into consideration the market demand and the demand of the agricultural products delivered from the agricultural merchant seller server 50 in the process of performing the harvesting.

Meanwhile, as described above, when the user makes a decision on the prediction items provided to the user for each step and conducts the cultivation according to the decision, it is preferable to systematically organize and store and manage the same. In order to do this, the seedling selection step S3, the seeding time predicting step S4, the disease and pest forecasting step S5, the pesticide selection and spraying time predicting step S6, and the harvesting time predicting step S7, S3a, S4a, S6a, and S7a, respectively, to accept the decision of the user after each of the steps S4a, S4b, and S4c are performed.

The cultivation history of the cultivated crop including the decision of the user received in the respective decision steps S3a, S4a, S6a and S7a is transmitted to the cultivation operation database 113 through the agricultural history information management module 140, (S8) for storing and managing the agricultural history management step (S8).

In the foregoing, optimal embodiments have been disclosed in the drawings and specification. Although specific terms have been employed herein, they are used for purposes of illustration only and are not intended to limit the scope of the invention as defined in the claims or the claims. Therefore, those skilled in the art will appreciate that various modifications and equivalent embodiments are possible without departing from the scope of the present invention. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

N: Network
10: weather information server 20: seed supplier server
30: Pesticide supplier server 40: Farm machinery supplier server
50: agricultural product seller server 60: terrain data server
100: Agricultural cultivation management management system for agriculture
110: Database
111: weather information database 112: crop information database
113: Cultivation operation database
115: main database
120: Communication interface
130: Crop condition prediction module
131: analysis module 132: prediction module
133: Decision module
140: Agricultural history information management module
150: User terminal
200: Measurement module
210: sensor unit 220: installation position detection module
230: Camera module

Claims (5)

A weather information database 111 for accumulating and storing the real-time weather information received from the weather information server 10 via the communication network 120 via the communication network 120 and the crop information data 111 for storing the crop information on the cultivated crop A database 110 including a base 112;
A crop state prediction module (hereinafter referred to as " crop state prediction module ") that analyzes the cumulative weather information and the real-time weather information received from the database 110 to predict a forecast and transmits the forecast to the user terminal 150 via the communication interface 120 130); A method for cultivating and managing a non-crop farmland using agricultural weather information using an agricultural cultivation management management system (100) for growing non-crop cultivated land,
A data collection step (S1) of collecting the real-time weather information, the accumulated weather information, and the crop information;
A data analyzing step (S2) of analyzing the real-time weather information, the accumulated weather information and the crop information collected in the data collecting step (S1);
Selecting a cultivar type suitable for the prediction based on the analysis data analyzed in the data analysis step (S2) and transmitting the selected cultivar type to the user terminal (150);
A seeding time predicting step (S4) of predicting the seeding time of the cultivar selected as the prediction item in the cultivar type selection step (S3) and transmitting it to the user terminal (150);
A disease and pest forecasting step (S5) for predicting a pest or a pest based on the analysis data analyzed in the data analysis step (S2) and delivering the pest or the pest to the user terminal (150);
A step S6 of selecting and spraying pesticides for selecting suitable pesticides and delivering the pesticide to the user terminal 150 when the occurrence of a disease or a pest is predicted in the pest and pest prediction step S5; Wherein the method comprises the steps of:
The method according to claim 1,
A harvesting time predicting step (S7) of predicting a crop harvesting time based on the analyzed data analyzed in the data analysis step (S2) and delivering it to the user terminal (150); The method according to any one of claims 1 to 5,
The method according to claim 2,
The data collection step (S1) includes a real time data collection step (S1a) for continuously collecting the information in real time while the cultivar type selection step (S3) to the harvesting time prediction step (S7) are performed; Further comprising:
The data analysis step (S2) includes a real time data analysis step (S2a) for continuously analyzing the information in real time while the cultivar type selection step (S3) to the harvest time predicting step (S7) is performed; The method according to any one of claims 1 to 5,
The method according to any one of claims 2 to 5,
The seedling selection step S3, the seeding time predicting step S4, the disease and pest forecasting step S5, the pesticide selection and spraying time predicting step S6, and the harvesting time predicting step S7 are Wherein the decision step (S3a, S4a, S6a, S7a) for accepting the decision of the user is further performed after the execution of the decision making process.
The method according to claim 4,
The cultivation history of the cultivated crop including the decision of the user delivered in each of the decision steps S3a, S4a, S6a and S7a is stored in the cultivation operation database 113 via the agricultural history information management module 140 A farm history management step (S8) for managing the farm history; The method according to any one of claims 1 to 5,

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