KR102320987B1 - Cloud-based real-time greenhouse environment decision support server and real-time greenhouse environment decision support system using the same - Google Patents

Abstract

A real-time greenhouse environment decision support server according to an embodiment of the present invention includes: a weekly greenhouse environment control module for calculating a weekly environmental control value based on a crop growth phase determined according to a weekly crop image received from a crop image photographing device; a daily greenhouse environment control module that selects past weather data having a pattern similar to the current weather data and calculates a daily environmental control value within the weekly environmental control value based on the corresponding past greenhouse data; and a real-time greenhouse environment control module for calculating a real-time environmental control value within a daily environmental control value based on the greenhouse environmental data received from the greenhouse sensor, wherein the current weather data includes first forecast data that is weekly weather forecast data; The second forecast data, which is daily weather forecast data, is included, and the real-time greenhouse environment control module includes: a greenhouse graph mapping unit that maps and visualizes the greenhouse data on a Moller diagram; and an environmental prediction value calculating unit configured to calculate a predicted value of at least one environmental element of cooling, heating, humidification, and dehumidification based on the Moller diagram.

Description

CLOUD-BASED REAL-TIME GREENHOUSE ENVIRONMENT DECISION SUPPORT SERVER AND REAL-TIME GREENHOUSE ENVIRONMENT DECISION SUPPORT SYSTEM USING THE SAME}

The present invention relates to a cloud-based real-time greenhouse environment decision support server and a real-time greenhouse environment decision support system using the same.

Recently, smart farms that can remotely and automatically manage crop growth environments and increase production efficiency by applying information and communication technologies to agricultural technologies are in the spotlight.

However, it is unclear whether such a smart farm environmental control system has a substantial effect on crop production and quality in the long term. In many cases, it is confirmed that the environment of the greenhouse does not reach the set target value even after the control command is executed, which does not take into account the environmental factors in the greenhouse that change in real time for each greenhouse, and standard environmental data for maximum production of existing crops It is believed that this is because it is applied as it is to all greenhouses.

In the case of the current smart farm environmental control system, the problem of not sufficiently considering these uncertainties continues to occur, and accordingly, the need for the development of an environmental control system that can efficiently manage the smart farm has been raised.

An object of the present invention is a real-time greenhouse that can provide the most optimal environment for crop growth by calculating an environmental control value in consideration of the temperature, relative humidity, dew point, etc. of the environment in the greenhouse that change in real time for each greenhouse It is to provide an environmental decision support server and a real-time greenhouse environmental decision support system using the same.

In addition, it is an object of the present invention to reflect the most optimal lead farmhouse data in consideration of the similarity of crop growth and weather graph patterns without applying the sample data of the lead farmhouse as it is, thereby further improving the growth of crops in real time It is to provide a greenhouse environment decision support server and a real-time greenhouse environment decision support system using the same.

A real-time greenhouse environment decision support server according to an embodiment of the present invention includes: a greenhouse graph mapping unit for mapping the greenhouse environment data including the first and second environmental values received from the greenhouse sensor to the Moller diagram; A greenhouse that receives the mapped first and second environmental values from the greenhouse graph mapping unit, generates time series data that changes in specific time units, respectively, and displays a preset reference range according to crop items and growth times data visualization information generation unit; and an environmental predicted value calculator configured to calculate a first predicted environmental value for the first environmental value and a second predicted environmental value for the second environmental value so that the greenhouse environment is controlled within a reference range.

In an embodiment of the present invention, the greenhouse data visualization information generating unit generates data for visualizing a second environmental predicted value that is changed according to the first environmental predicted value when the first environmental predicted value is an independent variable, and the second environment When the predicted value is an independent variable, data for visualizing the first environmental predicted value changed according to the second environmental predicted value is generated.

A real-time greenhouse environment decision support server according to an embodiment of the present invention includes: a weekly greenhouse environment control module for calculating a weekly environmental control value based on a crop growth phase determined according to a weekly crop image received from a crop image photographing device; a daily greenhouse environment control module that selects past weather data having a pattern similar to the current weather data and calculates a daily environmental control value within the weekly environmental control value based on the corresponding past greenhouse data; and a real-time greenhouse environment control module for calculating a real-time environmental control value within a daily environmental control value, based on the greenhouse environment data, wherein the current weather data includes first forecast data, which is weekly weather forecast data, and daily weather forecast data. and the second forecast data, wherein the real-time greenhouse environment control module is configured to control the greenhouse environment within the range of the minimum and maximum values of the daily environmental control value, the real-time environmental control value in consideration of the first environmental prediction value and the second environmental prediction value and a real-time environment control value calculation unit for calculating .

In one embodiment of the present invention, the daytime greenhouse environment control module, the environmental control element determining unit for determining the environmental control element based on crop growth; and an environmental control value determining unit configured to determine an environmental control value in consideration of a temperature difference and a humidity difference calculated by comparing the first forecast data, past weather data, and corresponding past greenhouse data.

In an embodiment of the present invention, the weekly greenhouse environment control module further includes an environmental limit value setting unit configured to set an environmental limit value having a maximum value and a minimum value based on an environmental control range of past greenhouse data.

In an embodiment of the present invention, the daytime greenhouse environment control module further includes a daytime environment control value calculator configured to calculate a daytime environment control value within an environmental limit value based on the environmental control element and the environmental control value.

In one embodiment of the present invention, the daily greenhouse environment control module, the daily greenhouse environment control module compares the patterns of current weather data and past weather data to select a similar graph having a similar pattern to the current weather data. including the electoral division.

In an embodiment of the present invention, the similarity graph selection unit selects the weekly similarity graph with the smallest distance difference from the pattern of the first forecast data within the past data while changing the section of the past data to around 7 days. electoral division; and a daily similarity graph selecting unit for selecting a daily similarity graph having the smallest distance difference from the pattern of the second forecast data from within the weekly similarity graph selected by the weekly similarity graph selecting unit.

In an embodiment of the present invention, the similarity graph selecting unit selects a similarity graph having the smallest distance difference between the current weather data and each time period by using an Euclidean similarity distance difference calculation equation.

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는 그래프의 시작점으로부터의 경과 시간을 의미한다.In an embodiment of the present invention, the Euclidean Similarity distance difference calculation formula,

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is the elapsed time from the starting point of the graph.

In an embodiment of the present invention, the daily greenhouse environment control module calculates a daily environmental prediction value by applying a difference value between the past weather data of the daily similar graph and the past greenhouse data to the second forecast data, and It further includes a daily environmental control value calculation unit for calculating a daily environmental control value in consideration of the daily environmental prediction value so that the greenhouse environment is controlled within the minimum and maximum value ranges.

A real-time greenhouse environment decision support system according to an embodiment of the present invention includes: a crop image photographing device for photographing a crop image; a database in which past data including past weather data and corresponding past greenhouse data of leading farms are stored for each crop item; a greenhouse sensor provided in the greenhouse to detect greenhouse environmental data; a real-time greenhouse environment decision support server that calculates real-time environmental control values through data transmission/reception with a crop image capturing device, a database, and a greenhouse sensor; and a greenhouse controller for controlling the greenhouse environment based on the real-time environmental control value received from the real-time greenhouse environment decision support server, wherein the real-time greenhouse environment decision support server includes a first environmental value and a second a greenhouse graph mapping unit that maps greenhouse environment data including environmental values to a Moller diagram; A greenhouse that receives the mapped first and second environmental values from the greenhouse graph mapping unit, generates time series data that changes in specific time units, respectively, and displays a preset reference range according to crop items and growth times data visualization information generation unit; and an environmental predicted value calculator configured to calculate a first predicted environmental value for the first environmental value and a second predicted environmental value for the second environmental value so that the greenhouse environment is controlled within a reference range.

A real-time greenhouse environment decision support method according to an embodiment of the present invention comprises: a greenhouse graph mapping step of mapping greenhouse environment data including a first environment value and a second environment value received from a greenhouse sensor to a Moller diagram; A greenhouse that receives the mapped first and second environmental values from the greenhouse graph mapping unit, generates time series data that changes in specific time units, respectively, and displays a preset reference range according to crop items and growth times data visualization information generation step; and an environmental prediction value calculating step of calculating a first environmental predicted value for the first environmental value and a second environmental predicted value for the second environmental value so that the greenhouse environment is controlled within a reference range.

In a computer-readable recording medium comprising a program for executing a real-time greenhouse environment decision support method according to an embodiment of the present invention, the real-time greenhouse environment decision support method comprises: a first environmental value received from a greenhouse sensor; a greenhouse graph mapping step of mapping the greenhouse environment data including the second environmental value to the Moller diagram; A greenhouse that receives the first and second environmental values mapped in the greenhouse graph mapping step, generates time-series data that change at a specific time unit, respectively, and displays a preset reference range according to the item and growth period of the crop data visualization information generation step; and an environmental prediction value calculating step of calculating a first environmental predicted value for the first environmental value and a second environmental predicted value for the second environmental value so that the greenhouse environment is controlled within a reference range.

When using the real-time greenhouse environment decision support server and the real-time greenhouse environment decision support system using the same according to an embodiment of the present invention, the temperature, relative humidity, dew point, etc. of the environment in the greenhouse that change in real time for each greenhouse are considered Thus, by calculating the environmental control value, there is an effect that can provide the most optimal environment for the growth of crops.

In addition, there is an effect of further improving the growth of crops by reflecting the most optimal data of the leading farmer in consideration of the similarity of the crop growth and weather graph patterns without applying the sample data of the lead farmer as it is.

1 is a schematic diagram illustrating a real-time greenhouse environment decision support server according to an embodiment of the present invention.
2 is a schematic diagram illustrating a real-time greenhouse environment decision support server according to an embodiment of the present invention.
3 is a schematic diagram illustrating a real-time greenhouse environment decision support system according to an embodiment of the present invention.
4 is a flowchart illustrating a method of calculating a weekly environment control value according to an embodiment of the present invention.
5 is a view showing an implementation screen of the step of determining the growth of crops.
6 and 7 are flowcharts illustrating a method of calculating a daily environment control value according to an embodiment of the present invention.
8 is a view showing an execution screen of the daily environment control value calculation step according to an embodiment of the present invention.
9 is a flowchart illustrating a method of calculating a real-time environment control value according to an embodiment of the present invention.
10 is a view showing an execution screen of a step of calculating a real-time environment control value according to an embodiment of the present invention.

Hereinafter, some embodiments of the present invention will be described in detail with reference to exemplary drawings. In adding reference numerals to the components of each drawing, it should be noted that the same components are given the same reference numerals as much as possible even though they are indicated on different drawings. In addition, in describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description thereof will be omitted.

The real-time indoor environmental system of the present invention is for optimally controlling environmental factors affecting crop quality, such as temperature and humidity of the indoor environment, in the production process of crops. In particular, the present invention has the advantage of further improving the growth of crops by calculating the most optimal environmental control value in consideration of the graph pattern for each environmental element without applying the sample data of the leading farmhouse of the crop as it is. There is this.

The present invention can be mainly used in crop cultivation areas, especially smart greenhouses, but the subject is not limited thereto and can be used in various fields.

1 is a schematic diagram illustrating a real-time greenhouse environment decision support server according to an embodiment of the present invention.

Referring to FIG. 1 , the real-time greenhouse environment decision support server 1000 of the present invention includes a greenhouse graph mapping unit 310 , a greenhouse data visualization information generating unit 320 , an environment prediction value calculating unit 330 , and a real-time environment and a control value calculating unit 340 .

First, the greenhouse graph mapping unit 310 performs a function of mapping the greenhouse environment data including the first and second environmental values received in real time from the greenhouse sensor 40 to a Mollier diagram. .

The first environment value and the second environment value may be current temperature and humidity inside the greenhouse.

On the Mollier diagram, the environmental factors of temperature (T), relative humidity (RH), absolute humidity (AH), dew point temperature (DEW), moisture deficiency (HD), and water vapor pressure differential (VPD) are comprehensively summarized. The considered reference area may be provided to be displayed together.

Here, the reference area represents the reference range representing the maximum and minimum values of the moisture deficiency (HD) and the water vapor pressure differential (VPD) most suitable for the growth period of each crop in the form of an area having an area on the Moller diagram. means that

The reference range refers to the data corresponding to the maximum production environment for each period of the initial, middle, and end of growth by each crop item and growth period. is set

At this time, the water vapor pressure differential (VPD) refers to the difference between the absolute moisture content that can be saturated at the current temperature of the greenhouse air and the water vapor pressure corresponding to the current air moisture content. It has a different standard range for each item and growing period.

The present invention is to set the standard range of water vapor pressure differential (VPD) and moisture deficiency (HD) most suitable for the growth of crops, and to maintain the relative humidity within the standard range by controlling the temperature and humidity to satisfy them, Control the greenhouse environment by further including components.

Subsequently, the greenhouse data visualization information generating unit 320 receives the mapped first and second environment values from the greenhouse graph mapping unit 310, and generates time series data that change in specific time units, respectively, of crops. According to the item and growth period, the preset reference range is also indicated.

For example, it is possible to generate an hourly unit environmental value as time series data for greenhouse environment data that changes in real time, and display it in the form of a bar graph or a line graph, and display a reference range together.

Subsequently, the environmental prediction value calculation unit 330 enables the above-described greenhouse data visualization information generation unit 320 to easily analyze the time-wise trend of the greenhouse environment for the reference range as the reference range is displayed together on the graph. . Accordingly, it is possible to derive an appropriate environmental prediction value for the hourly greenhouse environment and use it as data for performing greenhouse environment control.

The environmental predicted value calculator 330 calculates a first predicted environmental value for the first environmental value and a second predicted environmental value for the second environmental value so that the greenhouse environment is controlled within a reference range.

Here, the first environmental predicted value means a predicted value derived by considering the reference range for the first environmental value, and the second environmental predicted value means a predicted value derived by considering the reference range for the second environmental value.

That is, the first environmental prediction value may be a temperature change amount with respect to the current temperature in the greenhouse, and the second environmental prediction value may be a humidity change amount with respect to the current humidity in the greenhouse.

For example, when the reference range for temperature is 17°C to 20°C, when the first environmental value is 16°C, the first predicted environmental value is calculated as +1°C to satisfy the minimum value of the reference range.

The first environmental predicted value and the second environmental predicted value have a correlation with each other.

For example, the relative humidity is low because the temperature is high during the day and the amount of saturated water vapor is large, and the relative humidity is high because the amount of saturated steam is small when the temperature is low at night or dawn.

Here, the relative humidity is used to indicate the degree of dryness and moisture in the air in daily life, and refers to the ratio of the actual water vapor pressure to the saturated water vapor amount at a given temperature as a percentage.

Referring to FIG. 10 , even when the temperature in the greenhouse is changed, in order to control the relative humidity within the reference range corresponding to the greenhouse data of the leading farmhouse, it can be seen that the humidity changing according to the temperature must be considered.

That is, in order to satisfy the reference range of the relative humidity, the environmental prediction value calculator 330 predicts the dependent value of the other variable with respect to one independent variable in real time in consideration of the correlation between the two variables as described above. By doing so, more accurate data for satisfying the reference range can be calculated.

In addition, when the greenhouse data visualization information generating unit 320 of the present invention described above is an independent variable, the first environmental predicted value generates data for visualizing the second environmental predicted value that is changed according to the first environmental predicted value, and the second When the environmental predicted value is an independent variable, data for visualizing the first environmental predicted value that is changed according to the second environmental predicted value is generated and provided, thereby improving visibility so that the user can more intuitively and easily grasp the environmental predicted value There is this.

The first and second predicted environmental values calculated in this way are compared with the current greenhouse internal environmental data by a pre-stored algorithm, and signals of cooling, heating, humidification, and dehumidification are output and transmitted to the greenhouse controller. It may be implemented to be controlled.

Next, the real-time environmental control value calculator 340 calculates a real-time environmental control value in consideration of the first and second predicted environmental values so that the greenhouse environment is controlled within the range of the minimum and maximum values of the daily environmental control values.

The real-time environment control value calculation unit 340 applies the predicted environmental value calculated above as much as possible, but corrects the predicted value exceeding the maximum value of the daily environmental control value to the maximum value, and corrects the predicted value less than the minimum value to the minimum value, so that the real-time environment A control value can be calculated.

For example, when the range of the daily environmental control value for temperature is 18°C to 20°C, when the first environmental prediction value is 17°C, the real-time environmental control value is set to 18°C to satisfy the minimum value of the daily environmental control value. is calculated

By transmitting heating, cooling, humidification, and dehumidification signals to the greenhouse controller according to the calculated real-time environmental control value, it may be implemented to control at least one of temperature and humidity of an indoor environment in which crops are grown.

When using the real-time greenhouse environment control module of the present invention described above, by calculating the environmental control value in consideration of the temperature, relative humidity, dew point, etc. of the environment in the greenhouse that change in real time for each greenhouse, it is the most effective for the growth of crops. It has the effect of providing an optimized environment.

In one embodiment of the present invention, the above-described components may be provided in a form included in the real-time greenhouse environment control module, and the real-time greenhouse environment decision support server of the present invention is in a form further including the following components can be implemented.

2 is a schematic diagram illustrating a real-time greenhouse environment decision support server according to an embodiment of the present invention.

Referring to FIG. 2 , the real-time greenhouse environment decision support server of the present invention may include the following configuration to receive data from the outside.

First, the crop image receiving unit 101 performs a function of receiving the weekly crop image photographed from the crop image photographing apparatus.

The weather data receiving unit 102 is provided to receive current weather data including first forecast data, which is weekly weather forecast data, and second forecast data, which is daily weather forecast data, by communicating with the Korea Meteorological Administration or a weather data provision infrastructure.

For example, the weather data receiver 210 may be provided to receive the first forecast data for each day and receive the second forecast data for each hour.

Communication with the meteorological agency or infrastructure may be provided to be done using a network. Here, the network may be a wired or wireless Internet, and in addition to a wired public network, a wireless mobile communication network, or a core network integrated with the mobile Internet, etc., Cellular technology (5G communication technology, LTE communication technology, 3GPP technology), etc. may be utilized. .

In addition, the weather data receiving unit 102 may be provided to receive and store weather forecast data using various known technologies to be initialized and updated weekly.

In addition, the weather data receiving unit 102 may be provided to accumulate and store the received weather forecast data into a database, which will be described later.

The past data receiving unit 103 receives, from the database, past data including past meteorological data of the leading farmhouse corresponding to the crop item and past greenhouse data of the leading farmhouse corresponding thereto.

The greenhouse data receiving unit 104 is provided to receive greenhouse environment data including at least one of temperature, humidity, dew point, and relative humidity inside the greenhouse from the greenhouse sensor.

In addition, according to an embodiment of the present invention, in order to calculate a greenhouse environment control value based on the data received from the above-described configurations, the real-time greenhouse environment decision support server 1000 of the present invention includes a weekly greenhouse environment control module ( 100 ), a daily greenhouse environment control module 200 , and a real-time greenhouse environment control module 300 may be provided to further include.

Continuing to refer to FIG. 2 , the daytime greenhouse environment control module 100 includes the following components.

The environmental control element determining unit 110 receives the weekly crop image from the crop image receiving unit 101 and determines the crop growth phase.

In this case, crop images may be accumulated and stored in a database to be described later, and an algorithm for analyzing crop images may be pre-stored in the database.

Accordingly, big data for analyzing the growth of crops can be built, and such big data can be applied when analyzing images to further improve the crop image recognition rate.

Crop images may be images including flowers, stems, leaves, fruits, flower beds, stems, and growth points of crops, and are used as data for judging crop growth.

Crop growth is determined in consideration of the growth phase and growth intensity of crops.

The table below shows the methods for judging the growth phase of crops.

division reproductive growth vegetative growth
flowering Close to the growing point (less than 15cm) Fast flower opening
Flowers in the flower room are uniform
fast flowering Flowering is far away
The boards are glued together
Non-uniformity of flower size and flowering in the flower room
leaf color and
color Deep yellow flower color, flower room curled, stem thickness 11mm or less
small leaves and flowers
The leaves are small and hard.
Little signs of growth light color
The flowerbed is straight and the flowers are large.
Stem thickness 11mm or more
big and soft
Lots of growth marks flower stem thick, tough, short, curled slender, long, extending upwards
fruit Large in size, many fruits
good quality,
rapid development small in size
low number of fruits
not good quality
slow development

Referring to Table 1, the growth phase is used as an index indicating the growth direction between vegetative growth and reproductive growth, and is determined according to reproductive growth or the degree of vegetative growth. The growth phase is determined based on at least one of the flowering rate, flowering distance, distance between flowers, stem shape, leaf color, flower color, flowering uniformity, number of fruit trees, fruit development rate, and fruit quality. is an index indicating the growth size of a crop, and is determined based on at least one of a growth point, a stem thickness, and a height of a flower bed. Here, the growth point means the highest position of the crop in the vertical direction.

By judging the growth phase of crops as described above, there is an advantage that can induce balanced growth by preventing bias between vegetative and reproductive growth of crops, and accordingly, the number of fruits, size, and quality of crops are improved has the effect of being

The environmental control element determining unit 110 determines the environmental control element of the greenhouse based on the determined crop growth rate, and the determined environmental control element may be accumulated and stored in a database provided in the form of a cloud. The environmental control element may include at least one or more of a daytime temperature, a daytime humidity, a nighttime temperature, a nighttime humidity, an average temperature, and an average humidity.

The figure below shows a method of determining an environmental control factor according to crop growth in an embodiment of the present invention.

[Figure 1]

Referring to Figure 1, based on the growth phase including growth phase and growth intensity, environmental control factors can be determined.

For example, when reproductive growth is strong and growth intensity is strong, an environmental control factor may be determined to increase the night temperature.

In addition, according to an embodiment of the present invention, the control direction of the average temperature may be determined.

Hereinafter, in one embodiment of the present invention, a method for determining an environmental control factor is shown.

division stem thickness height of the room fruit load Lowering the average temperature 10.5mm or less 13.5cm or less lowness increase the average temperature 10.5mm or less 13.5cm or less height Maintain average temperature 10.5mm~11.5mm 13.5cm~17.0cm commonly increase the average temperature 11.5mm or less 17.0cm or less height

Referring to Table 2, the environmental control factor can be determined by deriving the degree of fruiting load in consideration of the stem thickness and the height of the flower room. For example, when the height of the flower room is large compared to the thickness of the stem, the fruit load increases, so the average temperature Environmental control factors can be determined to increase growth balance.

Next, the environmental control value determination unit 120 determines the environmental control value based on past data including past weather data for crops received from the past data receiving unit 103 and past greenhouse data of the leading farmhouse corresponding thereto. .

_{At this time, the past greenhouse data may include data such as temperature, humidity, CO 2} , EC, pH, cumulative solar radiation, etc. corresponding to the maximum production environment for each period of the initial, middle, and end of growth according to crop items. have.

The purpose of the real-time greenhouse environment decision support server of the present invention is to provide an environment most optimized for the growth of crops by controlling the temperature and humidity among the past greenhouse data.

The data may be provided so that the maximum production environment control value for each period is derived through statistical processing based on the maximum amount of crop data according to the greenhouse data of each leading farmhouse, and may be provided monthly.

Next, the environmental threshold setting unit 130 sets environmental thresholds having the maximum and minimum values based on the greenhouse environment control range according to the monthly past greenhouse data of the leading farmhouse.

The environmental threshold may be set differently during the daytime and at night depending on the crop item, and may be provided to be initialized and updated during the day, so that the most optimized environmental threshold value for the daytime may be derived.

Next, the weekly environmental control value calculating unit 140 calculates a temperature difference and a humidity difference by comparing the weekly weather forecast data with the past data, and determines an environmental control value in consideration of the calculated temperature difference and humidity difference. In this case, the environmental control value may be determined by calculating a difference value between the past greenhouse data and the weekly weather forecast data of the past data.

For example, if the current external weather temperature is 17°C and the indoor temperature of a small farmhouse past the same period is 20°C, the difference value of +3°C may be determined as an environmental control value.

That is, by controlling the temperature and humidity to correspond to the environmental data of the leading farmhouse of the last crop, it is possible to create a crop growth environment similar to that of the last crop.

Further, in another embodiment, the environmental control value may be determined by calculating a difference value between the past weather data and the past greenhouse data and applying it to the weekly weather forecast data.

For example, if the current external meteorological temperature is 17℃, and the external weather temperature of the fresh farmhouse past the same period is 16℃ and the indoor temperature is 20℃, calculate the difference between the internal and external temperature of the fresh farmhouse and apply it to the current external weather temperature. Depending on the application, +4°C may be determined as an environmental control value.

Next, the daytime environment control value calculation unit 140 calculates the daytime environment control value based on the environment control element and the environment control value.

In this case, the weekly environmental control value calculator 140 may be provided to calculate the weekly environmental control value within the environmental limit value obtained based on the monthly data of the fresh farmhouse.

To explain with the above example, if the current external weather temperature is 17°C and the environmental limit value is set to 18°C to 20°C, the environmental control value is determined as +4°C, but it exceeds the environmental limit value, so take this into account Thus, the weekly environmental control value can be calculated as 17 ℃ + 3 ℃ = 20 ℃.

Daytime environmental control values may be provided to have different values over time within environmental limits. The weekly environment control value calculated in this way is accumulated and stored in a database to be described later provided in the form of a cloud, so that big data can be built.

As the present invention includes the above-described weekly greenhouse environment control module, there is an advantage in that it is possible to induce balanced growth by preventing bias between vegetative and reproductive growth of crops. Accordingly, there is an effect of improving the number of fruits, size, and quality of crops.

In addition, by utilizing the environmental data of leading farms together, an environment similar to the maximum production environment is provided, but there is an advantage in that an environment optimized for crops can be provided by considering the growth of crops together.

Next, the daily greenhouse environment control module 200 may be provided to include the following components.

First, the similar graph selector compares the patterns of the current weather data and the past weather data to make a similar graph having a pattern similar to the current weather data, and the weekly similar graph selector 210 and the daily similar graph select unit ( 220) may be configured to include.

The weekly similarity graph selection unit 210 performs a function of selecting the weekly similarity graph with the smallest distance difference from the pattern of the first forecast data from within the past data while changing the section of the past data to around 7 days.

The daily similarity graph selecting unit 220 performs a function of selecting a daily similarity graph having the smallest distance difference from the pattern of the second forecast data from the weekly similarity graph selected by the weekly similarity graph selecting unit 210 .

In this case, the daily similarity graph selection unit 220 may be provided to update the second forecast data twice a day and select a daily similarity graph having a pattern most similar to the pattern of the updated second forecast data. .

For example, in order to reflect the second forecast data that is changed in real time, it may be provided to select a daily similarity graph having a similar pattern to the second forecast data updated once at 10:00 and 14 o'clock, respectively.

The daily similarity graph selection method is not limited to the above example, and the time and number of times may be variously set according to a user's setting.

The similarity graph selecting unit selects a similarity graph having the smallest distance difference between the current weather data and each time period by using an Euclidean similarity distance difference calculation equation.

The Euclidean distance means a distance between two object coordinates on a plane, and the distance between objects in the Euclidean distance concept indicates a degree of similarity. The Euclidean distance can be obtained using the Pythagorean theorem.

That is, by using the Euclidean distance, the past and present temperature and humidity graphs can be compared on a plane, and the similarity can be compared by calculating the distance difference.

Euclidean similarity distance difference calculation formula used in the present invention is as follows.

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는 그래프의 시작점으로부터의 경과 시간을 의미한다.here,

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is the elapsed time from the starting point of the graph.

In the case of selecting the weekly similar graph, the following equation can be used.

는 그래프의 시작점으로부터의 경과 시간을 의미하므로 n = 24(시간) x 7(일) = 168로 설정될 수 있으며, a는 과거 주간 데이터의 24시간 단위 시작일의 순번을 의미한다.At this time,

is the elapsed time from the starting point of the graph, so it can be set to n = 24 (hours) x 7 (days) = 168, and a means the sequence number of the 24-hour unit start date of the past weekly data.

Accordingly, when a weekly similar graph is selected by using the Euclidean distance difference calculation formula, the graph of the first forecast data in units of 24 hours within the past data corresponding to 15 days before and after the received first forecast data By calculating each Euclidean distance difference while moving , the past data having the smallest distance difference can be selected as the weekly similarity graph.

For example, when calculating the Euclidean distance difference for the first forecast data from November 8 to November 14, within the historical data from November 1 to November 21, in 24-hour units Move the graph of the first forecast data.

)를 모두 구하여, 가장 작은 값을 갖는 주간 유사 그래프를 선출한다.At this time, the distance difference (

), and the weekly similar graph with the smallest value is selected.

The following is an example showing the formula for calculating the distance difference between the first forecast data from November 8 to November 14 and the past weather data from November 7 to November 13 of the last crop period.

In the case of selecting a daily similarity graph, the following formula can be used.

는 그래프의 시작점으로부터의 경과 시간을 의미하므로 n = 24로 설정될 수 있으며, a는 과거 일간 데이터의 24시간 단위 시작일의 순번, b는 과거 일간 데이터의 1시간 단위 시작 시간을 의미한다.At this time,

is the elapsed time from the starting point of the graph, so it can be set to n = 24, a is the sequence number of the 24-hour start date of the past daily data, and b is the 1-hour start time of the past daily data.

Accordingly, when a daily similar graph is selected by using the Euclidean distance difference calculation formula, each of the graphs of the first forecast data is moved in units of time within the past weekly data corresponding to the received second forecast data. By calculating the Euclidean distance difference of , past data having the smallest distance difference can be selected as a daily similarity graph.

For example, when calculating the Euclidean distance difference for the second forecast data on November 4 within the historical data from November 1 to November 7, the graph of the first forecast data in units of one hour move the

)를 모두 구하여, 가장 작은 값을 갖는 주간 유사 그래프를 선출한다.At this time, the distance difference (

), and the weekly similar graph with the smallest value is selected.

The following is an example showing the expression for calculating the distance difference between the second forecast data from 00:00 to 24:00 on November 4 and the past weather data from 02:00 on November 3 to 02:00 on November 4.

As described above, by moving the graph back and forth in units of 24 hours to calculate the weekly similarity graph first, and then moving the graph back and forth by one hour to calculate the daily similarity graph, the similar graph can be selected more easily and quickly. This has the advantage that the required time can be shortened.

In addition, compared to selecting a similar graph by considering only the graph pattern for one day, by limiting the range of past data with the most similar graph pattern for the week first, and selecting the daily similar graph within, the simple numerical value of the weather graph is reduced. There is an advantage in that it is possible to select a graph that is easier to apply to the actual weather environment by focusing on the non-traditional pattern.

Next, the daily environment control value calculation unit 230 calculates a difference value between the past weather data and the past greenhouse data of the similar graph, and applies the difference value to the current weather data to calculate a daily environment prediction value.

The daily environment prediction value includes at least one of an indoor temperature with respect to the current external temperature and an indoor humidity with respect to the current external humidity.

For example, if the current outside weather temperature is 17°C, and the outside weather temperature of the fresh farmhouse past the same period is 16°C and the indoor temperature is 20°C, calculate the difference between the inside and outside temperature +4°C of the fresh farmhouse and convert it to the current outside temperature. As applied to the weather temperature, 21°C can be calculated as a daily environmental prediction value.

Thereafter, the daily environment control value calculation unit 230 considers the daily environment prediction value within the weekly environment control value so that the indoor environment is controlled within the range of the minimum and maximum values of the weekly environment control value set based on the past data. Calculate the control value.

For example, if the daily environmental prediction value is 21°C, but when the range of the weekly environmental control value is set to 18°C to 20°C, 20°C is calculated as the daily environmental control value so that the daily environmental prediction value does not exceed the weekly environmental control value can do.

The daytime environment control value is a value received from the above-described daytime greenhouse environment control module 100 , and a detailed description thereof is referred to above.

By utilizing the daily greenhouse environment control module of the present invention, the greenhouse data of the leading farmhouse is not applied as it is, but in consideration of the past greenhouse data for the past weather data having a pattern most similar to the weather pattern of the area where the greenhouse is located. An optimal environmental control value can be calculated.

That is, as customized application for each greenhouse is possible, the greenhouse control most optimized for the current weather pattern becomes possible.

Next, as described above with reference to FIG. 1 , the real-time greenhouse environment control module 300 includes a greenhouse graph mapping unit 310 , a greenhouse data visualization information generating unit 320 , an environmental prediction value calculating unit 330 , and real-time It includes an environment control value calculation unit 340, and a description thereof is referred to above.

In the above, we looked at the real-time greenhouse environment decision support server. Hereinafter, a real-time greenhouse environment decision support system using the above-described real-time greenhouse environment decision support server will be described. For convenience of explanation, content overlapping with those described with reference to FIG. 1 will be omitted or simply described.

3 is a schematic diagram illustrating a real-time greenhouse environment decision support system according to an embodiment of the present invention.

Referring to FIG. 3 , the real-time greenhouse environment decision support system 10 of the present invention may be provided to include the following configuration.

First, the crop image photographing apparatus 20 captures the crop image during the day. The crop image photographing apparatus 20 may be provided in the form of a camera or a portable terminal that the user can carry, and the user may manually operate the crop image photographing apparatus 20 to photograph the crop image. In addition, the crop image photographing apparatus 20 may be implemented to automatically recognize each crop and photograph a crop image because autonomous driving is possible within the cultivation area.

Thereafter, the database 30 stores past data including past weather data of the last crop and past greenhouse data of the leading farmhouse corresponding thereto, and may be provided to accumulate and update the past data to be stored.

The database 30 may store, classify, and manage environmental control values according to crop items as a database (DB) for each period.

For example, the database 30 is a relational database management system (RDBMS) such as Oracle, Informix, Sybase, DB2, Gemston, Orion, It can be implemented for the purpose of the present application using an object-oriented database management system (OODBMS) such as O2, and has appropriate fields to achieve its function.

In one embodiment of the present invention, the database 30 is provided in the form of a cloud and the data received by the weekly greenhouse environment decision support server 100 of the present invention is converted into a database and accumulated and stored to build big data. can

For example, big data may be constructed as crop images are accumulated and stored in the database 30 according to the growth time of each item, and an algorithm for analyzing crop images may be stored separately. Accordingly, it is possible to further improve the crop image recognition rate.

In addition, in the database 30, the greenhouse environment data corresponding to the maximum production environment for each period of the initial, middle, and end of growth according to the item of the crop is converted into a database for each field and accumulated and stored, so big data may be built. have.

In addition, in the database 30, real-time environmental control values calculated according to the real-time greenhouse environment are converted into a database, accumulated and stored, and big data is constructed. When this is applied to the present invention, the greenhouse environmental data of the leading farmer can replace the test bed data, and as the work speed and accuracy are improved, the real-time environmental control value most optimized for the growth of crops can be calculated. there will be

Then, the greenhouse sensor 40 is provided inside the greenhouse, and functions to sense greenhouse environmental data including at least one of _{temperature, humidity, CO 2 , EC, pH, and cumulative solar radiation.}

The real-time greenhouse environment decision support server 1000 calculates a weekly environmental control value through data transmission/reception with the above-described crop image capturing apparatus 20 , the database 30 , and the greenhouse sensor 40 .

The greenhouse controller 50 controls the temperature and humidity of the indoor environment in which crops are grown based on the real-time environmental control value received from the real-time greenhouse environment decision support server 1000 .

The above-described real-time greenhouse environment decision support server 1000 includes: a greenhouse graph mapping unit for mapping the greenhouse environment data including the first and second environmental values received from the greenhouse sensor to the Moller diagram; and receiving the mapped first and second environmental values from the greenhouse graph mapping unit, generating time series data that change in specific time units, respectively, and displaying a preset reference range according to the item and growth period of the crop. Greenhouse data visualization information generation unit; and an environmental predicted value calculator configured to calculate a first environmental predicted value for the first environmental value and a second environmental predicted value for the second environmental value so that the greenhouse environment is controlled within a reference range.

In one embodiment of the present invention, the above-described real-time greenhouse environment decision support server 1000 is in the form of various cloud servers such as IaaS (Infrastructure as Service), PaaS (Platform as a Service), SaaS (Software as a Service), etc. can be provided as

If the cloud server is utilized, it is possible to remotely automatically control the greenhouse controller 50 provided in the greenhouse environment in which crops are grown based on the crop image and weather data provided from the crop image capturing device 20 and the Korea Meteorological Administration.

In addition, although not shown in the drawings, a manager terminal capable of connecting to the real-time greenhouse environment decision support server 1000 may be separately provided.

The manager terminal may be provided with any type of wired/wireless communication device that is equipped with a normal web browser and can use various web services by accessing the agricultural production production distribution management server.

Accordingly, it is possible to monitor the environment in which crops are grown on the manager terminal, and it may be implemented to enable manual control of the greenhouse controller 50 .

Hereinafter, a real-time greenhouse environment decision support method using the real-time greenhouse environment decision support system of the present invention will be described.

Hereinafter, in the process of explaining each step, the content overlapping with the parts described with reference to FIGS. 1 to 3 will be omitted or simply described, and FIGS. 1 to 3 will be referred to together for better understanding of the description. In addition, unless otherwise specified, it is assumed that the subject performing each step described below is the real-time greenhouse environment decision support server shown in FIGS. 1 to 3 .

The real-time greenhouse environment decision support method consists of a weekly environmental control value calculation step, a daily environmental control value calculation step, and a real-time environmental control value calculation step.

First, the step of calculating the weekly environment control value will be described.

4 is a flowchart illustrating a method of calculating a weekly environment control value according to an embodiment of the present invention.

5 is a view showing an implementation screen of the step of determining the growth of crops.

Referring to FIGS. 4 and 5 , first, a crop growth phase determination step ( S110 ) of receiving a weekly crop image from the crop image photographing apparatus to determine the crop growth phase is performed. This step can be implemented to monitor the growth of the crop by measuring the height (cm) and the stem thickness (cm) of the crop as shown in FIG.

Thereafter, the environmental control element determination step ( S120 ) of determining the greenhouse environmental control element based on the crop growth phase is performed. In this step, only the environmental control factor is determined, and a specific control value is calculated in the following steps. For example, if the reproductive growth is strong and the growth intensity is strong, the environmental control factor may be determined as “a rise in night temperature”.

Thereafter, the monthly data receiving step (S130) of receiving the fresh farmhouse monthly data for crops from the database is performed.

Thereafter, an environmental threshold setting step ( S140 ) of setting an environmental threshold having a maximum value and a minimum value based on the greenhouse environment control range of the monthly data of the leading farmhouse is performed.

Thereafter, a weather data receiving step ( S150 ) of receiving weekly weather forecast data from the Korea Meteorological Administration is performed.

Thereafter, a weather data comparison step ( S160 ) of calculating a temperature difference and a humidity difference by comparing the weekly weather forecast data and the monthly data of the leading farmhouse is performed. At this time, since the weather forecast may be changed in real time, it may be provided to check whether the weather forecast is changed at a specific time and perform the weather data reception step S10 again so that the changed weather forecast data can be applied. Accordingly, there is an advantage in that the environmental control value can be determined based on the most accurate weekly weather forecast data in real time.

Thereafter, the environmental control value determination step (S170) of determining the greenhouse environmental control value in consideration of the temperature difference and the humidity difference is performed. In the weather data comparison step ( S160 ) and the environmental control numerical determination step ( S170 ), the difference value between the past greenhouse data of the monthly data of the lead farm and the external weather data of the monthly data of the lead farm is calculated, and this is applied to the current weather forecast data By doing so, it is also possible to determine the environmental control value.

Thereafter, a weekly environment control value calculation step ( S180 ) of calculating a daytime environment control value within the environmental limit value is performed. The weekly environmental control value is calculated by considering both the environmental control factor determined in the environmental control element determination step S120 and the environmental control value determined in the environmental control value determination step S170 . At this time, in consideration of the environmental limit value set in the environmental limit value setting step ( S140 ), the weekly environmental control value is calculated within the limiting range.

Next, the step of calculating the daily environmental control value will be described.

6 and 7 are flowcharts illustrating a method of calculating a daily environment control value according to an embodiment of the present invention.

6 and 7 , first, the weather data receiving step S210 of receiving current weather data from the Korea Meteorological Administration is performed.

Thereafter, a past data receiving step ( S220 ) of receiving past data including past weather data and past greenhouse data of the last crop leading farmhouse corresponding to the item of crop is performed from the database.

Thereafter, a similar graph selection step of selecting a similar graph having a pattern similar to that of the current weather data is performed by comparing the patterns of the current weather data and the past weather data. The similar graph selection step may be provided to include a weekly similar graph selection step (S230) and a daily similar graph selection step (S240).

In the weekly similar graph selection step (S230), a step of searching for past data including past weather data and past greenhouse data for the first forecast data is performed, and thereafter, while changing the section of the past data to around 7 days, the second 1 A step of selecting a weekly similar graph with the smallest distance difference from the pattern of the forecast data is performed.

In the daily similarity graph selection step (S240), a step of searching for past data within the weekly similarity graph selected above for the second forecast data is performed, and thereafter, while changing the past data in the weekly similarity graph in units of time , selecting a daily similarity graph with the smallest distance difference from the pattern of the second forecast data is performed.

Thereafter, a daily environment prediction value calculation step ( S250 ) of calculating a difference value between the past weather data of the similar graph and the past greenhouse data and applying the difference value to the current weather data to calculate a daily environment prediction value is performed.

Thereafter, the daily environmental control value calculation step S260 of calculating the daily environmental control value by considering the weekly environmental control value together with the calculated daily environmental control value is performed.

8 is a view showing an execution screen of the daily environment control value calculation step according to an embodiment of the present invention.

7 and 8, based on the environmental control element according to the growth of crops and the weekly environmental control value determined according to the environmental control value according to the weekly weather forecast data, the control method of the greenhouse environment during the day is analyzed and the user It can be implemented to be provided to

In addition, it is possible to provide the user with a daily environmental control value according to the daily weather forecast data within the range of the weekly environmental control value, and it may be implemented so that the internal environment of the greenhouse is automatically controlled by transmitting the daily environmental control value to the greenhouse controller .

Next, the step of calculating the real-time environment control value will be described.

9 is a flowchart illustrating a method of calculating a real-time environment control value according to an embodiment of the present invention.

Referring to FIG. 9 , first, receiving the greenhouse environment data including the first environment value and the second environment value received from the greenhouse sensor ( S310 ) is performed, and in this case, the first environment value and the second environment value are performed. The values may be temperature and humidity.

Thereafter, a greenhouse graph mapping step S320 of mapping the first and second environmental values received in real time to a Mollier diagram is performed.

Hereinafter, the greenhouse graph mapping step ( S320 ) and subsequent steps will be described with further reference to FIG. 10 .

10 is a view showing an execution screen of a step of calculating a real-time environment control value according to an embodiment of the present invention.

9 and 10, on the Mollier diagram, temperature (T), relative humidity (RH), absolute humidity (AH), dew point temperature (DEW), moisture deficiency (HD), and water vapor pressure differential (VPD) ) may be provided so that the reference range comprehensively considered is displayed as an area having an area on the graph. The area may be preset according to past greenhouse data of the leading farmer received from the database. In this case, the past greenhouse data may be data corresponding to the maximum production environment for each period of the initial, middle, and late growth period for each crop item and growth period.

Thereafter, a greenhouse data visualization information generation step (S330) of receiving the first and second environmental values mapped in the greenhouse graph mapping step (S320), and generating data for visualization respectively as time series data that change in a specific time unit (S330) ) is performed. In this case, it may be provided so that a preset reference range is displayed together according to the item and the growth period of the crop.

For example, an hourly unit environmental value may be visualized as time series data for greenhouse environment data that changes in real time, and may be represented in the form of a bar graph or a line graph.

Thereafter, an environmental prediction value calculation step ( S340 ) of calculating a first environmental predicted value for the first environmental value and a second environmental predicted value for the second environmental value is included so that the greenhouse environment is controlled within the reference range.

As the reference range is displayed together on the graph in the above-described greenhouse data visualization information generation step ( S330 ), it is possible to easily analyze the time-wise trend of the greenhouse environment with respect to the reference range. Accordingly, it is possible to derive an appropriate environmental prediction value for the hourly greenhouse environment and use it as data for performing greenhouse environment control.

Thereafter, real-time environmental control for calculating a real-time environmental control value in consideration of the first and second predicted environmental values so that the greenhouse environment is controlled within the range of the minimum and maximum values of the daily environmental control values received from the daily greenhouse environmental control module A value calculation step (S350) is performed.

Thereafter, a greenhouse control step ( S360 ) of controlling at least one of temperature and humidity of an indoor environment in which crops are grown by transmitting a real-time environmental control value to the greenhouse controller is performed.

When using the daily greenhouse environment decision support server of the present invention as described above, the daily greenhouse environment decision support system using the same, and the daily greenhouse environment decision support method, the advantage of calculating the optimal environmental control value for each greenhouse is have.

That is, the environment most suitable for the maximum growth of crops is created by detecting the environmental factors in the greenhouse that change in real time for each greenhouse, and calculating the optimal real-time environmental control value by considering all the change values of the dependent variables according to the independent variables. effect that can be provided.

Furthermore, a computer-readable recording medium including a program for executing the daily greenhouse environment decision support method according to an embodiment of the present invention may be implemented.

In this case, the real-time greenhouse environment decision support method includes: a greenhouse graph mapping step of mapping the greenhouse environment data including the first and second environmental values received from the greenhouse sensor to the Moller diagram; and receiving the mapped first and second environmental values from the greenhouse graph mapping unit, generating time series data that change in specific time units, respectively, and displaying a preset reference range according to the item and growth period of the crop. Greenhouse data visualization information generation step; and an environmental prediction value calculating step of calculating a first environmental predicted value for the first environmental value and a second environmental predicted value for the second environmental value so that the greenhouse environment is controlled within the reference range.

In the above, even though it has been described that all components constituting the embodiment of the present invention are combined or operated in combination, the present invention is not necessarily limited to this embodiment. That is, within the scope of the object of the present invention, all the components may operate by selectively combining one or more.

In addition, terms such as "comprises", "comprises" or "have" described above mean that the corresponding component may be embedded, unless otherwise stated, so that other components are excluded. Rather, it should be construed as being able to further include other components. All terms, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs, unless otherwise defined. Terms commonly used, such as those defined in the dictionary, should be interpreted as being consistent with the meaning of the context of the related art, and are not interpreted in an ideal or excessively formal meaning unless explicitly defined in the present invention.

The above description is merely illustrative of the technical spirit of the present invention, and various modifications and variations will be possible without departing from the essential characteristics of the present invention by those skilled in the art to which the present invention pertains. Therefore, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain, and the scope of the technical spirit of the present invention is not limited by these embodiments. The protection scope of the present invention should be construed by the following claims, and all technical ideas within the equivalent range should be construed as being included in the scope of the present invention.

10: Real-time greenhouse environment decision support system
1000: Real-time greenhouse environment decision support server
100: weekly environment control value calculation module
110: environmental control factor determining unit
120: environmental control numerical value determination unit
130: environment limit value setting unit
140: weekly environment control value calculation unit
200: daily environment control value calculation module
210: weekly similar graph selection unit
220: daily similar graph selection unit
230: daily environment control value calculation unit
300: real-time environment control value calculation module
310: greenhouse graph mapping unit
320: Greenhouse data visualization information generation unit
330: environmental prediction value calculation unit
340: real-time environment control value calculation unit
20: crop imaging device
30: database
40: greenhouse sensor
50: greenhouse controller

Claims (14)

a greenhouse graph mapping unit that maps the greenhouse environment data including the temperature value and the humidity value received from the greenhouse sensor to the Moller diagram, and calculates a moisture deficiency value and a water vapor pressure differential value;
Receives the moisture deficiency value and the water vapor pressure differential value from the greenhouse graph mapping unit, generates time series data that changes in specific time units based on the moisture deficiency value and the water vapor pressure differential value, respectively, and sets a first reference range a greenhouse data visualization information generating unit to display together with the Moller diagram and the time series data;
an environment prediction value calculation unit for calculating a first environment prediction value for the temperature value and a second environment prediction value for the humidity value based on the first reference range; and
a real-time environment control value calculator configured to calculate a real-time environment control value for the first environment prediction value and the second environment prediction value based on a preset second reference range;
The first reference range is a reference range set according to a crop item and a growth period with respect to the moisture deficiency value and the water vapor pressure differential value,
The second reference range is a reference range defined by the minimum and maximum values of daily environmental control values calculated based on past weather data and past greenhouse data having a pattern most similar to the current weather data,
When the temperature value and the humidity value are out of the first reference range, the environment prediction value calculating unit corrects the temperature value and the humidity value to a value within the first reference range to obtain the first environment prediction value and the second environment value Calculate the predicted value,
The real-time environment control value calculator corrects the first environment prediction value and the second environment prediction value to a value within the second reference range when the first environment prediction value and the second environment prediction value are out of the second reference range. A real-time greenhouse environment decision support server that calculates the real-time environmental control value.
According to claim 1,
The greenhouse data visualization information generating unit,
When the first environmental predicted value is an independent variable, generating data for visualizing the second environmental predicted value that is changed according to the first environmental predicted value;
When the second environmental predicted value is an independent variable, a real-time greenhouse environment decision support server that generates data for visualizing the first environmental predicted value that is changed according to the second environmental predicted value. According to claim 1,
a weekly greenhouse environment control module for calculating a weekly environmental control value based on the crop growth phase determined according to the weekly crop image received from the crop image photographing apparatus;
Further comprising a daily greenhouse environment control module for calculating the daily environmental control value within the weekly environmental control value,
The current weather data is a real-time greenhouse environment decision support server including first forecast data that is weekly weather forecast data, and second forecast data that is daily weather forecast data.
4. The method of claim 3,
The weekly greenhouse environment control module,
an environmental control element determining unit that determines an environmental control element based on the crop growth phase; and
A real-time greenhouse environment decision support server comprising an environment control value determination unit that determines an environmental control value in consideration of a temperature difference and a humidity difference calculated by comparing the first forecast data, the past weather data, and the past greenhouse data.
5. The method of claim 4,
The weekly greenhouse environment control module,
The real-time greenhouse environment decision support server further comprising an environmental limit value setting unit for setting an environmental limit value having a maximum value and a minimum value based on the environmental control range of the past greenhouse data. 6. The method of claim 5,
The weekly greenhouse environment control module,
The real-time greenhouse environment decision support server further comprising a weekly environmental control value calculation unit for calculating the weekly environmental control value within the environmental limit value based on the environmental control element and the environmental control value.
4. The method of claim 3,
The daily greenhouse environment control module,
and a similar graph selection unit for selecting a similar graph having a pattern similar to that of the current weather data by comparing the patterns of the current weather data and the past weather data.
8. The method of claim 7,
The similar graph selection unit,
a weekly similarity graph selecting unit for selecting a weekly similarity graph with the smallest distance difference from the pattern of the first forecast data from within the past data while changing the section of the past data to around 7 days; and
A real-time greenhouse environment decision support server including a daily similarity graph selection unit that selects a daily similarity graph with the smallest distance difference from the pattern of the second forecast data within the weekly similarity graph selected by the weekly similarity graph selection unit. 9. The method of claim 8,
The similar graph selection unit,
A real-time greenhouse environment decision support server that selects a similar graph with the smallest distance difference between the current weather data and each time period by using a Euclidean similarity distance difference calculation formula. 10. The method of claim 9,
The Euclidean Similarity distance difference calculation formula,

is,

(

,

,

, ?? ,

) is the current weather data,

(

,

,

, ?? ,

) is historical weather data,

is a real-time greenhouse environment decision support server that means the elapsed time from the starting point of the graph.
9. The method of claim 8,
The daily greenhouse environment control module,
calculating a daily environmental forecast value by applying a difference value between the past weather data of the daily similarity graph and the past greenhouse data to the second forecast data,
Real-time greenhouse environment decision support server further comprising a daily environmental control value calculation unit for calculating the daily environmental control value in consideration of the daily environmental prediction value so that the greenhouse environment is controlled within the minimum and maximum value ranges of the weekly environmental control value .
Crop image photographing apparatus for photographing crop images;
a database in which past data including past weather data and past greenhouse data of leading farms corresponding to the past weather data are stored for each crop item;
a greenhouse sensor provided in the greenhouse to detect greenhouse environmental data;
a real-time greenhouse environment decision support server that calculates a real-time environmental control value through data transmission/reception with the crop image capturing device, the database, and the greenhouse sensor; and
A greenhouse controller for controlling the greenhouse environment based on the real-time environmental control value received from the real-time greenhouse environment decision support server,
The real-time greenhouse environment decision support server,
a greenhouse graph mapping unit that maps the greenhouse environment data including the temperature value and the humidity value received from the greenhouse sensor to a Moller diagram, and calculates a moisture deficiency value and a water vapor pressure differential value;
Receives the moisture deficiency value and the water vapor pressure differential value from the greenhouse graph mapping unit, generates time series data that changes in specific time units based on the moisture deficiency value and the water vapor pressure differential value, respectively, and sets a first reference range a greenhouse data visualization information generating unit to display together with the Moller diagram and the time series data; and
an environment prediction value calculation unit for calculating a first environment prediction value for the temperature value and a second environment prediction value for the humidity value based on the first reference range; and
a real-time environment control value calculation unit configured to calculate the real-time environment control value for the first environment prediction value and the second environment prediction value based on a preset second reference range;
The first reference range is a reference range set according to a crop item and a growth period with respect to the moisture deficiency value and the water vapor pressure differential value,
The second reference range is defined by the minimum and maximum values of the daily environmental control values calculated based on the past weather data and the past greenhouse data having a pattern most similar to the current weather data among the past weather data and the past greenhouse data. is the reference range,
When the temperature value and the humidity value are out of the first reference range, the environment prediction value calculating unit corrects the temperature value and the humidity value to a value within the first reference range to obtain the first environment prediction value and the second environment value Calculate the predicted value,
The real-time environment control value calculator corrects the first environment prediction value and the second environment prediction value to a value within the second reference range when the first environment prediction value and the second environment prediction value are out of the second reference range. A real-time greenhouse environment decision support system for calculating the real-time environmental control value.
As a real-time greenhouse environment decision support method performed by a real-time greenhouse environment decision support server,
a greenhouse graph mapping step of mapping the greenhouse environment data including the temperature value and the humidity value received from the greenhouse sensor on the Moller diagram, and calculating the moisture deficiency value and the water vapor pressure differential value; and
receiving the moisture deficiency value and the water vapor pressure differential value, generating time-series data that changes in specific time units based on the moisture deficiency value and the water vapor pressure differential value, respectively, and setting a preset first reference range in the Moller diagram and Greenhouse data visualization information generating step to display together with the time series data;
an environmental prediction value calculating step of calculating a first environmental prediction value for the temperature value and a second environmental prediction value for the humidity value based on the first reference range; and
a real-time environment control value calculation step of calculating a real-time environment control value for the first environment prediction value and the second environment prediction value based on a preset second reference range;
The first reference range is a reference range set according to a crop item and a growth period with respect to the moisture deficiency value and the water vapor pressure differential value,
The second reference range is a reference range defined by the minimum and maximum values of daily environmental control values calculated based on past weather data and past greenhouse data having a pattern most similar to the current weather data,
In the environmental prediction step, when the temperature value and the humidity value are out of the first reference range, the temperature value and the humidity value are corrected to a value within the first reference range, and the first environmental prediction value and the second environment Calculate the predicted value,
In the step of calculating the real-time environment control value, when the first environment prediction value and the second environment prediction value are out of the second reference range, the first environment prediction value and the second environment prediction value are corrected to values within the second reference range. A real-time greenhouse environment decision support method for calculating the real-time environmental control value.
A computer-readable recording medium comprising a program for executing a real-time greenhouse environment decision support method,
The real-time greenhouse environment decision support method is,
a greenhouse graph mapping step of mapping the greenhouse environment data including the temperature value and the humidity value received from the greenhouse sensor on the Moller diagram, and calculating the moisture deficiency value and the water vapor pressure differential value; and
receiving the moisture deficiency value and the water vapor pressure differential value, generating time-series data that changes in specific time units based on the moisture deficiency value and the water vapor pressure differential value, respectively, and setting a preset first reference range in the Moller diagram and Greenhouse data visualization information generating step to display together with the time series data;
an environmental prediction value calculating step of calculating a first environmental prediction value for the temperature value and a second environmental prediction value for the humidity value based on the first reference range; and
a real-time environment control value calculation step of calculating a real-time environment control value for the first environment prediction value and the second environment prediction value based on a preset second reference range;
The first reference range is a reference range set according to a crop item and a growth period with respect to the moisture deficiency value and the water vapor pressure differential value,
The second reference range is a reference range defined by the minimum and maximum values of daily environmental control values calculated based on past weather data and past greenhouse data having a pattern most similar to the current weather data,
In the environmental prediction step, when the temperature value and the humidity value are out of the first reference range, the temperature value and the humidity value are corrected to a value within the first reference range, and the first environmental prediction value and the second environment Calculate the predicted value,
In the step of calculating the real-time environment control value, when the first environment prediction value and the second environment prediction value are out of the second reference range, the first environment prediction value and the second environment prediction value are corrected to values within the second reference range. to calculate the real-time environment control value.

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