KR102189418B1 - Natural Extract and Mixed Spray System of Smart Farm - Google Patents

Abstract

The present invention relates to a natural extract and a mixed spraying device of a smart farm, and a decision tree that improves eco-friendliness while enabling a more rational and comprehensive analysis of environmental factors controlling factors using a decision tree technique. Provides a natural extract that can be used optimized for the used smart farm and a mixed spray device for it.

Description

Natural Extract and Mixed Spray System of Smart Farm {Natural Extract and Mixed Spray System of Smart Farm}

The present invention relates to a natural extract and mixing spray device of smart farm. In more detail, a natural extract that can be used optimized for a smart farm using a decision tree that enables a more rational and comprehensive analysis and response of environmental factor regulators using the decision tree technique while enhancing eco-friendliness. And it is to provide a mixing spray device for this.

As social interest in health increases, the demand for fruits and vegetables is increasing rapidly. Accordingly, it is almost essential to use pesticides when cultivating crops for a stable supply of fruits and vegetables. In addition, from the standpoint of farmers and agricultural companies whose annual income is determined by the yield of crops without damage from pests and pests, an attempt to cultivate crops without the use of pesticides can lead to a significant risk in that farming per year can be wrong It becomes (Risk).

However, pesticides used in this way remain in the produced agricultural products, raising serious concerns about the safety of food, and seriously threaten the health of growers due to the toxicity of synthetic chemicals, and cause environmental pollution and ecosystem disturbances. It is causing problems.

Accordingly, organic farming is rapidly spreading worldwide as well as domestic farmers due to concerns about the safety of agricultural products and sustainable agriculture through environmental preservation, and research on the production of eco-friendly agricultural products has been conducted. ), vegetables and cultivated crops. In particular, at the present time when demand for safe agricultural products is increasing and regulations related to agricultural environment are being strengthened internationally, the future farming methods are bound to gradually change toward eco-friendly farming methods such as organic farming.

In this respect, there have been attempts to cultivate crops by reducing the use of pesticides by using natural pesticides that can replace chemical pesticides.

However, as described above, when the use of pesticides is excluded 100%, it is difficult to effectively control fruit trees, especially those vulnerable to diseases and pests, and when applied to fruit trees, such as grapes, conventional organic methods are Compared to the agricultural method using pesticides, there is a problem that a significant difference is not shown in terms of the quality of fruit such as sugar content, or the quality is rather deteriorated.

Furthermore, with the aim of improving the nutrition, growth, and quality of agricultural crops as a substitute for pesticides, technologies that have actively applied them to fruit trees among crops using enzymes such as natural fruits and medicinal plants have been found to date. It was difficult to see.

Accordingly, it is possible to grow agricultural crops such as fruits without pests without using any pesticides, and development of eco-friendly organic nutrients and related farming techniques that can increase the sugar content of grapes to the maximum compared to the prior art among fruit trees Is required.

In addition, agriculture through smart farms combined with ICT technology is in the spotlight. Therefore, it is necessary to develop a technology that can produce eco-friendly agricultural products while using such a smart farm.

In addition to the production of eco-friendly agricultural products, the quality of crop growth, yield, taste, etc. is affected by the effects of temperature, humidity, solar radiation, water supply, and carbon dioxide for crops generally grown in farm houses. Therefore, a device that keeps temperature, humidity, insolation, etc. constant under an environment such as a farm house is used, but there is a disadvantage that the manager must directly operate it in the field.

Therefore, in order to cope with this, various innovations in agriculture are being attempted. By incorporating information and communication technology into agricultural production, processing, distribution, and consumption, it is possible to automatically manage the growing environment of crops remotely and increase production efficiency Smart farms are currently attracting attention.

However, in the case of the conventional house automatic control system, if the information on the preset temperature or humidity and the result of comparing the value detected by the sensor are different, the actuator corresponding to the sensor is controlled so that the crop cultivation environment inside the greenhouse is Try to maintain a certain level. However, if the automatic control system controls the actuator to run, for example, the automatic control system controls the execution of the temperature enhancing adjustment actuator, but the window mounted on the ceiling of the house is open, the temperature enhancing adjustment actuator is executed. Although it raises the temperature inside the house, there is a problem that collision between actuators may occur because the temperature inside the house decreases due to an open window mounted on the ceiling of the house.

Therefore, there is a need for a control method in the form of providing an algorithm that can comprehensively analyze and consider environmental factors that may affect each other and make decisions as determined by actual farmers. In particular, there is a need to develop a method to increase the competitiveness of a smart farm by periodically learning the results of the growth environment and the degree of development of the crops to further advance the above-described algorithm.

Furthermore, there is a need for a way to apply a smart farm to an eco-friendly organic farming method by grafting eco-friendly farming methods to promote the development of living organisms without intervening artificial compounds or artificial means.

In relation to the prior art, prior art 1 (KR 10-2012-0076584 A) has disclosed a technology for executing an actuator by determining whether an actuator mounted inside a house is executed simultaneously with another actuator. However, it has not reached the stage of determining the driving direction of the smart farm in consideration of comprehensive environmental factors.

Prior Art 2 (KR 10-2012-0076584 A) operates the system so that simultaneous execution between multiple actuators is not possible, so the operation time is long, which may result in wasted resources. Even if it is operated simultaneously, it is irrelevant or must be operated simultaneously by artificially. There is a drawback that cannot be used in this case.

In addition, the prior art has certain limitations in that the means to which the eco-friendly farming method of smart farm can be applied cannot be applied.

KR 10-2012-0076584 A KR 10-2012-0076584 A

It is an object of the present invention to comprehensively analyze each environmental factor based on the value measured by each sensor to enable eco-friendly agriculture to be applied in a smart farm using a decision tree capable of maintaining an optimal growth environment, and It is to provide a mixing spray device that allows the natural extract to be applied effectively.

In addition, the natural extract and mixing spray device is applied to the optimal environmental conditions of the crop through the decision tree in the smart farm, so that the eco-friendly agricultural products can have a higher productivity.

In order to achieve the above object, the natural extract and mixing spray device of the smart farm according to an embodiment of the present invention is installed inside the smart farm, the first nozzle connected to the first tank containing the first liquid; It includes a second nozzle connected to a second tank containing a second liquid phase, and the first nozzle and the first nozzle have a jet discharged through the first nozzle and a jet discharged through the second nozzle in the air. It is installed so that the spraying direction of the first nozzle and the spraying direction of the second nozzle are obtuse angles so that they can be mixed, and the first liquid phase contains natural extract, and the second liquid phase contains liquid potassium silicate. .

The smart farm is a control unit; An environmental sensor including an air temperature sensor, a geothermal temperature sensor, a humidity sensor, an insolation measurement sensor, and a CO ₂ sensor installed inside or outside the first agricultural facility house; And an environmental control means including a window opening and closing means, a lighting control means, a heating means, a CO ₂ supply means, a light shielding means, a natural extract providing means, and a humidity control means in the agricultural facility house.

The smart farm may further include a data receiver, and the data receiver may receive environmental information from an external database.

The smart farm further includes a data receiver, and receives information measured through an environmental sensor installed inside or outside the second agricultural facility house, and a result of comparing the predicted environmental information and the second environmental information is the decision-making step. It may be cumulatively reflected in.

The natural extract and mixing spray device of the smart farm may be controlled by receiving a signal from the controller.

The extract may be a hot water extract.

The crop may be any one of tomato and paprika, and the hot water extract may be a mixture of non-sprout and ramie extract.

On the other hand, the control method of a smart farm using a decision tree according to an embodiment of the present invention is an air temperature sensor, a geothermal temperature sensor, a humidity sensor, and insolation installed inside or outside the first crop facility house according to a predetermined time interval. A first environmental information sensing step of transmitting environmental information collected from an environmental sensor including a measurement sensor and a CO ₂ sensor to a control unit; Crop facilities expected when the environmental control module operates the environmental control means including window opening and closing means, lighting control means, heating means, CO ₂ supply means, light shielding means, natural extract supply means and humidity control means in the agricultural facility house An environmental prediction step of predicting predicted environmental information in the house; A decision-making step in which a decision-making module receives environmental information from the environmental control module, matches it with ideal environmental information of a crop, and makes a decision on a control operation according to a predetermined criterion; A control step of controlling the environment control means by receiving control information from the decision making module by a control unit; It may include a second environmental information sensing step of transmitting the environmental information collected from the environmental sensor to the control unit according to a predetermined time interval after the control step.

The decision making step uses a decision tree model, and a result of comparing the predicted environment information and the second environment information value may be cumulatively reflected in the decision making step.

In the method for controlling a smart farm using the decision tree, the environmental information may further include environmental information received from an external database.

In the control method of the smart farm using the decision tree, the ideal environment information may be based on indoor and outdoor environmental information values of the second agricultural facility house previously determined.

In the control method of a smart farm using the decision tree, a value obtained by evaluating a crop produced in the second agricultural facility house and a value obtained by evaluating a crop produced in the first farm facility house are received through a terminal. The crop evaluation input step and the decision module should be improved in the first crop facility house by comparing the environmental information of the second crop facility house and the first crop facility house during the growing period of the crop based on the input crop evaluation value. It may further include an analysis step of analyzing environmental information to be performed.

In the method for controlling a smart farm using the decision tree, the decision module may reflect information obtained in the analysis step to the decision tree model.

In the control method of a smart farm using the decision tree, the natural extract providing means is that the natural extract is sprayed through the spraying device installed at predetermined intervals in the first crop facility house, and the natural extract is extracted with hot water. It can be.

In the control method of a smart farm using a decision tree, the crop may be any one of tomato and paprika, and the hot water extract may be a mixture of non-sprout extract and ramie extract.

Hereinafter, the present invention will be described in more detail.

The natural extract and mixing spray device of the smart farm according to an embodiment of the present invention is installed inside the smart farm, the first nozzle connected to the first tank containing the first liquid; It includes a second nozzle connected to a second tank containing a second liquid phase, and the first nozzle and the first nozzle have a jet discharged through the first nozzle and a jet discharged through the second nozzle in the air. It is installed so that the spraying direction of the first nozzle and the spraying direction of the second nozzle are obtuse angles so that they can be mixed, and the first liquid phase contains natural extract, and the second liquid phase contains liquid potassium silicate. .

The spray direction of the first nozzle refers to a linear direction that is fired to the spray object by the nozzle. This can be expressed as an imaginary straight line of 1r or 2r when described with reference to FIG. 2.

The first liquid phase and the second liquid phase may be mixed and sprayed in the air while the spraying direction of the first nozzle and the spraying direction of the second nozzle form an obtuse angle.

The specific method for the spraying method is defined as including all means that can be used by a person having ordinary knowledge in the relevant field, such as a method of using a pump or a method of using pressure or falling energy.

As described later, if the liquid potassium silicate and the natural product extract are not mixed and sprayed onto the land, the natural extract cannot be effectively absorbed by the crop because the surface of the land is hardened by the liquid potassium silicate. In addition, when the liquid potassium silicate and the natural extract are mixed in a mixing container, the activity of the natural extract is lost due to the physical properties and high basicity of the liquid potassium silicate, and when the mixture is left for a certain period of time or longer, floating matters are generated. The problem of loss of activity occurs.

Therefore, there is a need for a method in which the liquid potassium silicate and the natural extract are mixed and sprayed immediately before the mixing spraying. Therefore, the natural extract and the liquid potassium silicate may be separately stored in peacetime using the first tank and the second tank, and then mixed and sprayed in a certain concentration range and amount by receiving a signal from the control unit. In particular, the natural extract and mixing spray device has the advantage that it can be applied to an automated process in an environment where it is impossible for a person to perform a mixing process before spraying, such as a smart farm.

Not only does it exhibit antibacterial activity against plant pathogens using a natural extract in which the extracts of the bisquat tree and ramie extract are mixed, but also improves the soil quality to promote the growth of tomatoes and paprika and make the color of tomatoes and paprika appear excellent. .

Preferably, the first liquid natural extract may be a mixture of 10 to 30 parts by weight of ramie plant and 40 to 80 parts by weight of plum tree extract based on 100 parts by weight of the extract of birch tree. In the case of the above range, not only the antibacterial activity against pathogens of plants is high, but also the growth activity of tomatoes and paprika can be increased by improving soil quality.

The tree is 8-15m in size and 50-120cm in diameter, and its age is unknown, but it is estimated to be about 300 to 500 years old. Bismuth trees hate barren and dry places very much and have strong sound resistance, but their growth is very slow. Female and male trees are different, and flowers bloom in April, and the fruit ripens in the following autumn, and looks like almonds.

Ramie grass is native to Southeast Asia and has been cultivated for a long time for the purpose of making fabrics by obtaining the bast fibers of the stems (靭皮纖維). In Egypt it was already used as mummy cloth along with flax 7,000 years ago. It was introduced in Europe in the 18th century, and it was cultivated in Korea from the Goryeo Dynasty. Until the introduction of cotton, it was the most important textile crop in East Asia including Korea, China, and Japan. The Chinese character of ramie grass is called jeoma (苧麻).

More preferably, the second liquid phase may be mixed in an amount of 0.0001 to 0.001 parts by weight based on 100 parts by weight of the first liquid phase. That is, the natural extract is a hot water extract, and the liquid potassium silicate may be mixed in an amount of 0.0001 to 0.001 parts by weight based on 100 parts by weight of the hot water extract. In the case of the above range, it is possible to cultivate tomatoes and paprika having excellent colors with the effect of increasing the growth activity of tomatoes and paprika by improving the soil quality.

If the liquid potassium silicate is contained in an amount of less than 0.0001, the effect of improving soil quality does not appear, and if it is included in 0.001 parts by weight, the land becomes too hard, which interferes with plant growth, and may exceed the proper pH, so it is not recommended for periodic use. It can be a problem.

The smart farm is a control unit; An environmental sensor including an air temperature sensor, a geothermal temperature sensor, a humidity sensor, an insolation measurement sensor, and a CO ₂ sensor installed inside or outside the first agricultural facility house; And an environmental control means including a window opening and closing means, a lighting control means, a heating means, a CO ₂ supply means, a light shielding means, a natural extract providing means, and a humidity control means in the agricultural facility house.

The smart farm may further include a data receiver, and the data receiver may receive environmental information from an external database.

The smart farm further includes a data receiver, and receives information measured through an environmental sensor installed inside or outside the second agricultural facility house, and a result of comparing the predicted environmental information and the second environmental information is the decision-making step. It may be cumulatively reflected in.

The natural extract and mixing spray device of the smart farm may be controlled by receiving a signal from the controller.

The extract may be a hot water extract.

The crop may be any one of tomato and paprika, and the hot water extract may be a mixture of non-sprout and ramie extract.

The control method of a smart farm using a decision tree according to an embodiment of the present invention is an air temperature sensor, a geothermal temperature sensor, a humidity sensor, and an insolation measurement sensor installed inside or outside the first crop facility house according to a predetermined time interval. , A first environmental information sensing step of transferring environmental information collected from an environmental sensor including a CO ₂ sensor to a control unit; Crop facilities expected when the environmental control module operates the environmental control means including window opening and closing means, lighting control means, heating means, CO ₂ supply means, light shielding means, natural extract supply means and humidity control means in the agricultural facility house An environmental prediction step of predicting predicted environmental information in the house; A decision-making step in which a decision-making module receives environmental information from the environmental control module, matches it with ideal environmental information of a crop, and makes a decision on a control operation according to a predetermined criterion; A control step of controlling the environment control means by receiving control information from the decision making module by a control unit; It may include a second environmental information sensing step of transmitting the environmental information collected from the environmental sensor to the control unit according to a predetermined time interval after the control step.

The decision tree or decision tree in the present invention refers to decision tree learning, and uses a decision tree as a prediction model that connects an observation value and a target value for an item. It is defined as meaning belonging to the predictive modeling method used in learning.

The smart farm referred to in the present invention refers to a farm that enables proper maintenance of the growing environment of crops remotely and automatically by grafting ICT to a facility for growing crops.

The agricultural facility house in the present invention includes the dictionary meaning, and is defined as including an installation having a structure having a wall and a roof for cultivating crops.

The air temperature sensor referred to in the present invention refers to a sensor installed to measure the air temperature inside or outside the agricultural facility house, and includes all sensors that can be used by those with ordinary knowledge in the field.

The geothermal temperature sensor referred to in the present invention refers to a sensor installed to measure the temperature in water during land or underwater cultivation, and includes all sensors that can be used by those with ordinary knowledge in the field.

The humidity sensor referred to in the present invention is defined as including all devices capable of measuring the humidity inside or outside the agricultural facility house.

In the present invention, the solar radiation measurement sensor is defined as including all devices capable of measuring solar radiant energy transmitted to the inside or outside of a farm facility house.

The CO ₂ sensor in the present invention is defined as including all devices capable of measuring carbon dioxide contained in the air inside or outside the agricultural facility house.

The environmental sensor referred to in the present invention refers to one or more alternatively including an air temperature sensor, a geothermal temperature sensor, a humidity sensor, an insolation measurement sensor, and a CO ₂ sensor, and is not limited to the above-described sensor.

The means for opening and closing the window in the agricultural facility house in the present invention is defined as including all means for ventilating the inside and outside air in the facility house, including doors, windows, and ventilation fans in the facility house.

The lighting control means in the present invention is defined as including all means capable of transmitting light including incandescent lamps.

The heating means referred to in the present invention includes a stove, a fumigant, and a heating circulation pump, and is defined as including a means capable of adjusting the internal temperature of the agricultural facility house.

The means for supplying CO ₂ in the present invention is defined as including all means capable of supplying carbon dioxide into the agricultural facility house.

The light shielding means in the present invention is defined as including all means for blocking or controlling the transmission of light into the agricultural facility house such as window screens and curtains.

The means for providing natural extracts referred to in the present invention is used to promote the growth of crops or remove pests and diseases, and is defined as including all extracts prepared from natural products.

The humidity control means referred to in the present invention is defined as including all means for controlling the humidity by supplying moisture into the agricultural facility house such as a sprinkler.

The environmental control means in the present invention includes a window opening and closing means, a lighting control means, a heating means, a CO ₂ supply means, a light shielding means, a natural extract providing means and a humidity control means in the agricultural facility house, Temperature, humidity, insolation, geothermal temperature, humidity refers to a means to control the concentration of carbon dioxide. In addition, the environmental control means is not limited to the window opening and closing means, lighting control means, heating means, CO ₂ supply means, light shielding means, natural extract providing means and humidity control means.

In the control method of a smart farm using a decision tree according to the present invention, the first environmental information sensing step includes a temperature that significantly affects the growing environment of crops through an environmental sensor installed inside or outside the first crop facility house, It refers to the step of collecting information on the growth environment of crops including insolation, ground temperature, humidity and carbon dioxide. In addition, the sensing may be performed at regular time intervals.

Meanwhile, the environmental information is not limited to information collected from sensors installed inside or outside the facility house, and the atmospheric environment information of the Meteorological Administration is transmitted through the Meteorological Administration database or generated from the Rural Development Administration in the area where the facility house of the crop is located. This includes receiving information about pests and diseases.

The environmental prediction step refers to deriving a value of environmental information in the agricultural facility house predicted when the environmental control means in the agricultural facility house operates.

In more detail, when the humidity in the agricultural facility house is measured below an appropriate level, water in the agricultural facility house may be supplied using a sprinkler as a means for increasing the humidity. In this case, the humidity of the facility house supplied with water increases, but it is exposed to new environmental changes in which the ground temperature decreases due to the supplied water.

In addition, when the temperature in the agricultural facility house is below an appropriate level, when the temperature in the facility house is increased using a heater, a new environmental change factor in which the humidity changes according to the temperature change occurs.

That is, since basic environmental items such as temperature, insolation, ground temperature, humidity, and carbon dioxide have a direct effect on each other, it is necessary to consider changes in comprehensive environmental items. In particular, because pests and other growing environments are complexly entangled, when one of the environmental control means is operated, there are a plurality of environmental items that change, so it is necessary to consider a plurality of environmental items that are changed by a certain environmental control means.

Accordingly, the environmental prediction step refers to predicting changes in environmental items that occur when one environmental control means is operated, and predicting whether the resulting value is within the range of an appropriate growing environment for crops. In addition, if necessary, it may be to predict changes in environmental items that occur when a plurality of environmental control means operate.

The decision-making step is a step of determining whether the environmental control means is operated or not and control by evaluating whether or not an appropriate growth environment of the crop targets is grown based on the predicted value of the information derived in the environmental prediction step.

Since the decision-making step is determined as the change value of the environmental factor that is most optimal for the growing environment of the target crop based on the predicted value of the environmental prediction step, it is possible to determine the control plan of the environmental control means most reasonable for the growth of the crop. have.

The control step refers to a step in which the environmental control means determined in the decision making step is operated and controlled through a control unit.

The second environmental information sensing step refers to a step of measuring the environmental information of the facility house of agricultural crops changed according to the actual operation of the environmental control means and evaluating how much it differs from the predicted value in the environmental prediction step. The accuracy of the environment prediction step may be improved by accumulating the result value of the environment control module through the second environment information sensing step so that the predicted value is corrected.

The decision making step uses a decision tree model, and a result of comparing the predicted environment information and the second environment information value may be cumulatively reflected in the decision making step.

In the case of using the decision tree, the most suitable range for the growth of crops can be derived as a whole while controlling the environmental areas located in the dangerous areas by predicting environmental factors that are mutually affected by one environmental control means.

In the method for controlling a smart farm using the decision tree, the environmental information may further include environmental information received from an external database.

As described above, the weather information of the area where the agricultural facility house is located can be received from the database of the Meteorological Administration, and the information on the disease and pests in the area where the agricultural facility house is located from the database of the Rural Development Administration, or information on the risk of disease occurrence is received from the database of the Rural Development Administration. You can do it.

In the control method of the smart farm using the decision tree, the ideal environment information may be based on indoor and outdoor environmental information values of the second agricultural facility house previously determined.

The second agricultural crop facility house refers to a space and facility in which agricultural experts determined arbitrarily to grow crops. This is distinguished from the agricultural plant facility house, that is, the first agricultural plant facility house, to which the smart farm control method using a decision tree that controls environmental factors is applied.

Environmental information affecting crops has a mutual influence, and factors that are indirect factors besides direct influence are significant. Therefore, the indoor and outdoor environment information values of the second agricultural facility house managed by a specific agricultural expert are measured, and based on the measured value, the environmental factor of the first crop facility house is matched with the facility house value of the second crop. It says to adjust.

Therefore, if ideal environmental information is based on the environmental information of the second crop facility house in the decision-making step, the same environment as the growing environment of the crops operated by an actual expert can be derived, and through this, the know-how of the expert is first It can be applied to the agricultural facility house as it is, and the decision-making module can derive a decision-making step similar to that of the expert through repeated learning. That is, even if the environmental information value of the second crop facility house provided in real time is not provided after the repetitive step progression, the growing environment of the first crop facility house can be optimized for the corresponding crop.

In the control method of a smart farm using the decision tree, a value obtained by evaluating a crop produced in the second agricultural facility house and a value obtained by evaluating a crop produced in the first farm facility house are received through a terminal. The crop evaluation input step and the decision module should be improved in the first crop facility house by comparing the environmental information of the second crop facility house and the first crop facility house during the growing period of the crop based on the input crop evaluation value. It may further include an analysis step of analyzing environmental information to be performed.

By applying the information according to the analysis step to the decision module as a correction value in the decision-making step, the environmental factors required to produce optimal agricultural products and the range of environmental factors for each period and period are evaluated by evaluating the produced crops. Can be improved.

In the method for controlling a smart farm using the decision tree, the decision module may reflect information obtained in the analysis step to the decision tree model.

In the control method of a smart farm using the decision tree, the natural extract providing means is that the natural extract is sprayed through the spraying device installed at predetermined intervals in the first crop facility house, and the natural extract is extracted with hot water. It can be.

The natural extract not only exhibits antibacterial activity against plant pathogens, but also can be used as a plant fertilizer to promote the growth of crops and to cultivate crops having high color and sugar content.

In the control method of a smart farm using a decision tree, the crop may be any one of tomato and paprika, and the hot water extract may be a mixture of non-sprout extract and ramie extract.

Not only does it exhibit antibacterial activity against plant pathogens using a natural extract in which the extracts of the bisquat tree and ramie extract are mixed, but also improves the soil quality to promote the growth of tomatoes and paprika and make the color of tomatoes and paprika appear excellent. .

Preferably, the natural extract may be a mixture of 10 to 30 parts by weight of ramie plant and 40 to 80 parts by weight of plum tree extract, based on 100 parts by weight of the extract of birch tree. In the case of the above range, not only the antibacterial activity against pathogens of plants is high, but also the growth activity of tomatoes and paprika can be increased by improving soil quality.

The tree is 8-15m in size and 50-120cm in diameter, and its age is unknown, but it is estimated to be about 300 to 500 years old. Bismuth trees hate barren and dry places, and have strong sound resistance, but their growth is very slow. Female and male trees are different, and flowers bloom in April, and the fruit ripens in the following autumn, and looks like almonds.

Ramie grass is native to Southeast Asia and has been cultivated for a long time for the purpose of making cloth by obtaining the bast fiber of the stem. In Egypt it was already used as mummy cloth along with flax 7,000 years ago. It was introduced in Europe in the 18th century, and it was cultivated in Korea from the Goryeo Dynasty. Until the introduction of cotton, it was the most important textile crop in East Asia, including Korea, China, and Japan. The Chinese character of ramie grass is called jeoma (苧麻).

More preferably, the natural extract is a hot water extract, and 0.0001 to 0.001 parts by weight of liquid potassium silicate may be mixed with respect to 100 parts by weight of the hot water extract. In the case of the above range, it is possible to cultivate tomatoes and paprika having excellent colors with the effect of increasing the growth activity of tomatoes and paprika by improving the soil quality.

If the liquid potassium silicate is contained in an amount of less than 0.0001, the effect of improving soil quality does not appear, and if it is included in 0.001 parts by weight, the land becomes too hard, which interferes with plant growth, and may exceed the proper pH, so it is not recommended for periodic use. It can be a problem.

On the other hand, the hot water extract and liquid potassium silicate must be directly mixed and sprayed onto the land immediately. When the liquid potassium silicate and the hot water extract are separately sprayed on the land, there is a problem in that the hot water extract cannot be effectively absorbed due to the occurrence of hardening parts for each land. In addition, when the liquid potassium silicate and the natural extract are directly mixed and left to stand, there is a problem that a floating matter is partially generated due to the physical properties and basicity of the liquid potassium silicate, or the antibacterial activity and soil quality improvement effect of the natural extract is rapidly reduced.

Therefore, the natural extract and the liquid potassium silicate must be mixed immediately at the time of spraying on the land. Therefore, in the case of using in the control method of the smart farm using the decision tree of the present invention, the nozzle connected to the tank providing the natural extract and the nozzle connected to the tank providing the liquid potassium silicate are installed to maintain less than 180° from each other. Therefore, it is preferable that the natural extract and liquid potassium silicate are sprayed on the land while the natural extract and the liquid potassium silicate are mixed in the air while the natural extract and the liquid potassium silicate are respectively sprayed from the nozzle.

The natural extract and mixed spray device of the smart farm according to the present invention provides a natural extract that exhibits antibacterial activity and productivity enhancing effect against harmful factors so that eco-friendly agriculture of the smart farm can proceed, and the natural extract is in the smart farm. It is to provide a mixing spray device that can be applied effectively.

In addition, the natural extract and mixed spray device is applied to the optimal environmental conditions of the crop through the decision tree in the smart farm, so that eco-friendly agricultural products can have higher productivity.

In the case of a smart farm using a decision tree according to the present invention, it is possible to more easily implement a smart farm based on organic farming that does not use artificial compounds.

1 is an exemplary diagram of a method for controlling a smart farm according to the present invention.
Figure 2 relates to a natural extract and mixing spray device spray nozzle according to an embodiment of the present invention.
3 is a graph exemplifying the result of the MATLAB Compact Tree Graph of a smart farm according to the present invention.
Figure 4 relates to learning environmental data on the temperature and humidity of the smart farm in the present invention.
Figure 5 relates to learning environmental data about the temperature and carbon dioxide concentration of the smart farm in the present invention.

Hereinafter, embodiments of the present invention will be described in detail so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein.

[Production Example 1: Preparation of natural extract]

In order to confirm the effective characteristics of the natural extract according to the present invention, the hot water extract was mixed according to the composition shown in [Table 1] below.

M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 A 100 100 100 100 100 100 100 100 100 100 100 B - 5 10 20 30 40 20 20 20 20 20 C - - - - - - 20 40 60 80 100

(Unit: parts by weight) A: Bismuth extract

B: ramie extract

C: Plum tree extract

[Experimental Example 2: Inhibitory Activity Test for Plant Fungi]

Plant molds (mycorrhizal fungi) and land formed in pots transplanted with seedlings from tomato and paprika seedlings were collected, and the M1 to M11 were periodically applied over 10 days. Purified water was applied as a control group, and the degree of proliferation of the plant fungus was evaluated in relation to the group to which purified water was applied, and expressed as an index of 1 to 10, and is shown in Table 2 below. When the purified water was used, the index was 10, and the lower the number, the better the inhibitory activity against the growth of plant fungi.

M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 Con Inhibitory activity 10 10 8 8 8 10 8 6 4 5 9 10

(Unit: Index) Referring to [Table 2], it can be seen that the natural extract can exhibit inhibitory activity against plant fungi in a certain mixed range. In particular, it can be seen that the effect is very excellent in the case of M8 to M10.

[Experimental Example 3: Growth Test 1]

The M1 to M11 were sprayed at regular intervals into pots in which seedlings were transplanted from the seedlings of tomatoes and paprika, and the growth properties were evaluated for 20 days. The plant extract was not sprayed as a control, and compared with the growth property (index: 5) of the control group so that the enhancing effect on the growth property can be directly compared, it was evaluated with an index of 1 to 10. The following index is the higher the number, the better the effect. The results are shown in the following [Table 3].

M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 Con Growth 5 4 6 6 6 5 7 8 8 7 5 5

(Unit: Index) Referring to [Table 3] above, it can be seen that the growth properties for tomato and paprika seedlings are improved within a specific range in which the plant extract is mixed. Therefore, in the case of the above range, it can be used as a fertilizer composition that increases the growth properties of tomatoes and paprika.

[Experimental Example 4: Growth Test 2]

The liquid potassium silicate was diluted and adjusted so that the M9 and the liquid potassium silicate were mixed in the range of 100:0.0005 to evaluate the growth property according to the mixing of M9 and the liquid potassium silicate. However, the nozzle through which the liquid potassium silicate and M9 are sprayed form an angle of less than 180° so that the liquid potassium silicate and M9 are mixed and sprayed in the air. As a result, it was confirmed that when the liquid potassium silicate is mixed, the growth rate of seedlings is increased by about 12.4% compared to M9.

On the other hand, when the M9 and the liquid potassium silicate were directly mixed and left for a certain period of time or longer, a fine suspended matter was formed. When this was used, it was confirmed that the growth of seedlings was reduced by 30% or more compared to M9.

[Production Example 2: Data processing of smart farm]

The crops grown in the smart farm were selected as paprika and tomatoes, and temperature, solar radiation, earth temperature, humidity, and carbon dioxide concentration were selected as environmental factors. In addition, control items were configured as shown in [Table 4] below.

Installation equipment control items Application sensor Control content Skylight, double glazing,
Side window motor opening and closing Indoor temperature/indoor humidity/outdoor temperature/sunshine/rainfall/wind direction/wind speed sensor Ventilation control Shading, keeping warm, opening and closing the side curtain motor Indoor temperature/indoor humidity/outdoor temperature/sunshine sensor Shading, insulation, side curtain control CO2 supply valve CO2 sensor/room humidity/sunshine sensor CO2 supply amount control Floating fan Room temperature/room humidity sensor Air flow control Beam light Solar sensor Beam control Fumigator timer Fumigator control Sprinkler Room temperature/room humidity sensor Roof SP control Exhaust fan Room temperature/room humidity sensor Air exhaust control Heating circulation pump Room temperature/room humidity sensor Heating control Heating 3-way valve Room temperature/heating water temperature sensor Heating control

Based on the information collected from each sensor, the control target equipment to be controlled was selected based on the data according to the following [Table 5], and the presence or absence of control was selected.

Season, growth Insolation
(J) inside
Temperature
(°C) Humidity
(%) Remaining
CO2
(ppm) Absorption amount (ml) spring 1,500~
2,000 More than 18.5 Less than 78.0 395~474 More than 3,928 summer More than 2,000 More than 18.5 78.0~84.2 395~474 More than 3,928 autumn 900-1,500 More than 18.5 78.0~
84.2 395~474 More than 3,928 winter Less than 900 More than 18.5 More than 84.2 More than 474 2,579~3,928 reproduction 900-1,500 20.3~
21.6 81.0~
85.6 More than 399 3,350~4,699 nutrition More than 2,000 20.5~23.4 66.8~
77.5 More than 348 More than 5,713

In order to proceed with the decision-making stage for the decision-making module, it is checked whether the sensor value according to each growth is appropriate or high or low, and according to each environmental sensor value, the presence or absence of the installation equipment control suitable for the situation is determined to form data as shown in Figs. I did it.

After that, using the data in MATLAB, we trained using 2940 training data for each season using only the precision tree model, and we checked using 1440 test data for each season, and the learning accuracy of the training data was 96.5%. The result was confirmed to be 81.2%.

The precision of the prediction can be calculated and provided as in Equation 1 according to [Table 6] below.

division Predicted value Class=Yes Class=No Actual value Class=Yes TP FN Class=No FP TN

[Equation 1]

Although the preferred embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements by those skilled in the art using the basic concept of the present invention defined in the following claims are also present. It belongs to the scope of rights of

10: first tank
11: 1st nozzle connecting hose
12: first nozzle
13: first nozzle nozzle
20: second tank
20: second tank
21: second nozzle connection hose
22: second nozzle
23: second nozzle nozzle
110: user terminal
210: network
1000: crop facility house
1001: first crop facility house
1002: second crop facility house
1r: virtual line in the spray direction of the first nozzle
2r: virtual line in the spray direction of the second nozzle

Claims (7)

It is installed inside the smart farm,
A first nozzle connected to a first tank containing a first liquid phase;
And a second nozzle connected to a second tank containing a second liquid phase,
The first nozzle and the second nozzle are sprayed in the spray direction of the first nozzle and the spraying of the second nozzle so that the spray discharged through the first nozzle and the spray discharged through the second nozzle are mixed in the air. It is installed so that the direction is obtuse,
The first liquid phase contains a natural extract,
The second liquid phase contains liquid potassium silicate,
The natural extract is a mixture of 10 to 30 parts by weight of ramie extract and 40 to 80 parts by weight of plum tree extract based on 100 parts by weight of the birch extract,
The smart farm is
A control unit;
An environmental sensor including an air temperature sensor, a geothermal temperature sensor, a humidity sensor, an insolation sensor, and a CO ₂ sensor installed inside or outside the first agricultural facility house; And
It comprises an environmental control means including a window opening and closing means, lighting control means, heating means, CO ₂ supply means, light shielding means, natural extract providing means and humidity control means in the agricultural facility house
Smart Farm's mixing spray device. delete The method of claim 1,
The smart farm further includes a data receiver,
The data receiver is to receive environmental information from an external database.
Smart Farm's mixing spray device. The method of claim 1,
The smart farm further includes a data receiver,
It receives the measured information through the environmental sensor installed inside or outside the second agricultural facility house.
The result of comparing the expected environmental information and the second environmental information is cumulatively reflected in the decision-making stage.
Smart Farm's mixing spray device. The method of claim 1,
The mixing spray device of the smart farm is controlled by receiving a signal from the control unit
Smart Farm's mixing spray device. The method of claim 1,
The extract is a hot water extract
Smart Farm's mixing spray device. The method of claim 1,
The crop is either tomato or paprika
Smart Farm's mixing spray device.

Images