JP7764017B2 - Agricultural environmental information generating device and generating method, agricultural environmental information display system, and plant growth prediction system - Google Patents

Description

The present invention relates to an agricultural environmental information generation device and generation method, an agricultural environmental information display system, and a plant growth prediction system.

In recent years, greenhouses have become larger as large-scale operations enter the greenhouse horticulture industry. In large greenhouses, the vastness of the greenhouse space makes it difficult to maintain consistent environmental factors such as temperature and humidity throughout the greenhouse, and environmental factors can vary depending on location within the greenhouse. This creates environmental variations in three dimensions, both vertically and horizontally, within the greenhouse. The resulting variations in crop growth and harvest quality can be a major problem for greenhouse horticulture management. To prevent these variations and control the greenhouse environment to maintain consistent environmental factors, it is necessary to accurately understand the environmental factors within the greenhouse.

Technology that uses sensors to understand environmental factors inside a greenhouse is known. Patent Document 1 describes a greenhouse information management device that visualizes greenhouse environmental information based on data acquired from sensors and displays it to the user.

Patent Publication No. 2021-7339

In large greenhouses, sensors need to be installed at multiple points within the greenhouse, but depending on the sensor's installation location, there is a risk that sensing and data transfer may be obstructed by the greenhouse's frame members or plants. Furthermore, even if the data acquisition environment is good when the sensor is installed, there is a risk that the data acquisition environment will deteriorate as the plants grow. If such sensing or data transfer problems occur, the data acquisition conditions will deteriorate, making it impossible to obtain the necessary data, and it may not be possible to fully understand the environmental factors within the greenhouse.

Utilizing sensing data while taking into account the data acquisition status requires technology and software with the information processing capabilities to appropriately process massive amounts of sensing data, which is not easy to implement at production sites. Furthermore, in order to respond to deterioration in data acquisition status as plants grow, it is necessary to check the data acquisition status over time.

The technology described in Patent Document 1 does not take into consideration the data acquisition conditions, so there is a possibility that environmental factors within the greenhouse may not be fully understood.

One aspect of the present invention has been made to solve the above-mentioned problems, and its purpose is to provide technology for understanding environmental factors in agricultural environments, including plant cultivation environments, taking into account the data acquisition conditions.

A generating device according to one aspect of the present invention generates agricultural environment information representing the state of an agricultural environment, and includes an acquisition unit that acquires sensing data acquired by multiple sensors installed in the agricultural environment, a calculation unit that calculates the acquisition rate of the sensing data, an extraction unit that references the acquisition rate within a predetermined period and extracts the sensing data when the acquisition rate is equal to or greater than a predetermined threshold, and a generation unit that generates the agricultural environment information based on the extracted sensing data.

An agricultural-environmental information display system according to one aspect of the present invention includes a generating device according to one aspect of the present invention and a display device that displays the agricultural-environmental information generated by the generating device.

A plant growth prediction system according to one aspect of the present invention includes a generating device according to one aspect of the present invention and a prediction device that predicts the growth level of plants growing in the agricultural environment based on the agricultural environment information generated by the generating device.

A generation method according to one aspect of the present invention is a method for generating agricultural environment information representing the state of an agricultural environment, and includes an acquisition step of acquiring sensing data obtained by multiple sensors installed in the agricultural environment, a calculation step of calculating the acquisition rate of the sensing data, an extraction step of referencing the acquisition rate within a predetermined period of time and extracting the sensing data when the acquisition rate is equal to or greater than a predetermined threshold, and a generation step of generating the agricultural environment information based on the extracted sensing data.

One aspect of the present invention provides technology for understanding environmental factors within an agricultural environment, taking into account the data acquisition situation.

1 is a block diagram showing an example of the configuration of a main part of an agricultural environmental information display system according to one embodiment of the present invention. FIG. 1 shows the inside of a greenhouse, an agricultural environment. FIG. 1 is a diagram illustrating the installation location of sensors in an agricultural environment. 10 is a graph showing an example of an acquisition rate of sensing data calculated by a generating device according to an aspect of the present invention. FIG. 1 is a diagram showing an example of agricultural environment information generated by a generating device according to an aspect of the present invention. 10 is a flowchart illustrating an example of a generation process executed by a generation device according to an aspect of the present invention. 10 is a flowchart illustrating another example of the generation process executed by the generation device according to an aspect of the present invention. 1 is a block diagram showing an example of a configuration of a main part of a plant growth prediction system according to an embodiment of the present invention.

[Agricultural Environment Information Display System]
The present invention provides an agricultural environment information display system including an agricultural environment information generating device according to an embodiment of the present invention, and a display device for displaying the agricultural environment information. The agricultural environment information generating device according to an embodiment of the present invention generates agricultural environment information that represents the state of an agricultural environment.

Agricultural environment information may be information that represents environmental factors that affect plant growth or animal rearing in a cultivation environment where plants are grown or a rearing environment where animals are raised. Examples of such environmental factors include temperature, humidity, carbon dioxide concentration, light conditions, wind speed, etc. Agricultural environments are intended to refer to spaces for cultivating plants or rearing animals, and may be open or closed spaces. Examples of agricultural environments include fields, greenhouses, plant factories, screen houses, rain shelters, livestock barns, etc.

An agricultural environment information display system according to one aspect of the present invention provides agricultural environment information to help farmers properly understand environmental factors within the agricultural environment and also to support cultivation management. By providing agricultural environment information, an agricultural environment information display system according to one aspect of the present invention can be used to understand the suitability of an agricultural environment for plant growth.

The display system (agricultural environmental information display system) 100 will be described with reference to Figure 1. Figure 1 is a block diagram showing an example of the main configuration of the display system 100 according to one aspect of the present invention. The display system 100 includes a generating device 10 and a display device 20. The display system 100 also includes an input device 30 and a storage device 40. The display system 100 may include the generating device 10 and the display device 20 as separate devices, or may include them integrated within a single device.

(Generation device 10)
The generating device 10 is a device that generates agricultural environment information that represents the state of environmental factors in an agricultural environment. The generating device 10 includes an acquisition unit 12, a calculation unit 13, an extraction unit 14, and a generation unit 15. The generating device 10 also includes a control unit 11 that controls these units of the generating device 10. The control unit 11 is realized, for example, by a processor and a memory. In this example, the processor accesses a storage (not shown), loads a program (not shown) stored in the storage into the memory, and executes a series of instructions included in the program. This constitutes each unit of the control unit 11. As each unit, the control unit 11 includes an acquisition unit 12, a calculation unit 13, an extraction unit 14, a generation unit 15, a determination unit 16, and an interpolation unit 17.

<Acquisition unit 12>
The acquisition unit 12 acquires sensing data acquired by a plurality of sensors installed in the agricultural environment. The acquisition unit 12 may acquire the sensing data continuously, or may acquire the sensing data at predetermined intervals or when the input device 30 receives an input from a user indicating that acquisition of sensing data should begin. The acquisition unit 12 outputs the acquired sensing data to the calculation unit 13.

Sensors that acquire sensing data are permanently installed in the agricultural environment and connected to the acquisition unit 12 via wired or wireless communication. The sensors transmit sensing data obtained by sensing to detect or measure environmental factors in the agricultural environment to the acquisition unit 12. The sensors may sense environmental factors continuously, may sense environmental factors at predetermined intervals, or may sense environmental factors when the input device 30 receives input from the user to start sensing. The sensors may also transmit sensing data to the acquisition unit 12 each time they acquire it, or may transmit sensing data to the acquisition unit 12 when the input device 30 receives input from the user to start acquiring sensing data. Examples of sensors that can be used include thermometers, hygrometers, carbon dioxide concentration measuring devices, and solar radiation measuring devices.

The agricultural environment in which the sensors are installed and the installation locations of the sensors will now be described with reference to Figures 2 and 3. Figure 2 is a diagram showing the inside of a greenhouse, which is an agricultural environment. Figure 3 is a diagram explaining the installation locations of sensors in an agricultural environment. Large greenhouses such as the one shown in Figure 2 have an area of over 1 hectare, and some have eaves heights of around 5 m. There are also cases where several such large greenhouses are connected together.

In such large greenhouses, environmental factors tend to vary in the width, depth, and eave directions, creating the problem of environmental unevenness within the greenhouse. For example, the temperature and humidity can vary greatly between the center of the greenhouse and the side walls, and the amount of solar radiation can vary greatly between the ceiling and the ground. For this reason, it is preferable to install multiple sensors in directions where environmental unevenness is likely to occur within the greenhouse, accurately detecting or measuring the environmental factors at each installation location and understanding the environmental factors throughout the greenhouse.

As shown in Figure 3, the acquisition unit 12 acquires sensing data acquired by multiple sensors installed in the frontage direction, depth direction, and eave height direction of the agricultural environment. There is no particular limit to the number of sensors installed in the agricultural environment.

<Calculation unit 13>
The calculation unit 13 calculates the sensing data acquisition rate. The sensing data acquisition rate is an index showing the operating status of the sensor. As an example, the calculation unit 13 calculates the number of sensing data acquired per unit time from each sensor, and calculates the proportion of points where the acquired number is equal to or greater than a predetermined threshold as the sensing data acquisition rate per unit time. The calculation unit 13 outputs the calculated sensing data acquisition rate to the extraction unit 14.

The sensing data acquisition rate can be defined, for example, as shown in the following equation (1).

When using formula (1), the calculation unit 13 first counts the number of pieces of sensing data acquired per unit time at a specific sensor installation location. Here, the unit time can be any time, such as one hour or two hours. The data acquisition rate threshold is a threshold for the data acquisition rate per sensor set by the user, and is set to, for example, 0.8, 0.9, etc. Then, the calculation unit 13 uses formula (1) to calculate the data acquisition rate per unit time over a predetermined period.

The data acquisition rate per unit time calculated by the calculation unit 13 can be used to generate a graph showing temporal variations in the data acquisition rate, as shown in Figure 4, for example. Figure 4 is a graph showing an example of the sensing data acquisition rate calculated by the calculation unit 13 of the generation device 10. In Figure 4, the vertical axis represents the data acquisition rate (%) and the horizontal axis represents time. As an example, the threshold for the data acquisition rate of each sensor measuring temperature is set to 80%, and the proportion of sensors exceeding the threshold is shown as the data acquisition rate.

The generating device 10 may generate a graph showing the time variation in the sensing data acquisition rate, as shown in Figure 4, and display it on the display device 20 to present to the user. By presenting such a graph to the user, the user can easily and accurately grasp the sensing data acquisition status.

<Extraction part 14>
The extraction unit 14 refers to the acquisition rate of sensing data within a predetermined period, and extracts the sensing data when the acquisition rate is equal to or greater than a predetermined threshold. The extraction unit 14 extracts sensing data from a period when the acquisition rate of sensing data is high. The extraction unit 14 outputs the extracted sensing data to the generation unit 15. The extraction unit 14 may output information about the extracted period to the generation unit 15 together with the extracted sensing data.

For example, in the case of the data acquisition rate shown in Figure 4, the extraction unit 14 extracts sensing data for the period indicated by the dashed circle. This period exceeds the minimum data acquisition rate set by the user, and is a period during which the data acquisition rate remains high, and can be said to be a period of good data acquisition. Note that, in order to ignore localized data loss, a period during which the data acquisition rate is below the minimum data acquisition rate for less than five unit hours can also be considered a period of good data acquisition.

Data from periods when the acquisition rate of sensing data is low is unreliable and may not accurately capture environmental factors within the agricultural environment. By using the extraction unit 14 to extract data from periods when the acquisition rate of sensing data is high, it is possible to use only data that is highly reliable and accurately captures environmental factors within the agricultural environment.

<Generation unit 15>
The generating unit 15 generates agricultural environment information based on the extracted sensing data. The agricultural environment information generated by the generating unit 15 may include the numerical values of the sensing data themselves, but it is preferable that the sensing data is presented in a form that is easy for the user to understand. As an example, the generating unit 15 may generate images, videos, etc. that represent the sensing data as agricultural environment information.

The generation unit 15 may generate, as agricultural environment information, a distribution map that displays the extracted sensing data in correspondence with the locations where multiple sensors are installed in the space within the agricultural environment. The distribution map of the sensing data may be one that grasps the three-dimensional distribution from multiple two-dimensional distribution maps, or it may be a three-dimensional distribution map.

The agricultural environment information generated by the generation unit 15 may be, for example, a spatial distribution map as shown in FIG. 5. FIG. 5 is a diagram showing an example of agricultural environment information generated by the generation unit 15 of the generation device 10. In FIG. 5, the installation height of the sensors is assumed to be uniform, and two-dimensional contour maps are shown in the horizontal plane at each height (upper, middle, and lower). Also, in FIG. 5, the line thickness is given a gradation according to the magnitude of the numerical value in the overall sensing data within the agricultural environment, and the numerical value of the sensing data is shown on the line. This makes it possible to represent agricultural environment information in a way that makes it easy to visually grasp environmental factors within the agricultural environment, particularly environmental unevenness. Note that agricultural environment information may also be represented by giving a gradation to the color of the line according to the magnitude of the numerical value in the overall sensing data.

The agricultural environment information generated by the generation unit 15 makes it easy to visually grasp the state of environmental factors within the agricultural environment and the occurrence of environmental unevenness, making it possible to easily and accurately grasp the environmental factors within the agricultural environment.

The generation unit 15 may generate agricultural environment information using the extracted sensing data as is, or may, for example, calculate the average value of the sensing data for a period or time period specified by the user. In other words, the generation unit 15 may generate agricultural environment information using the average value of the extracted sensing data. The distribution diagram shown in Figure 5 shows, as an example, the average values of temperatures sensed from 11:00 to 14:00 over a specified five-day period.

<Determination unit 16>
The determination unit 16 determines whether or not there is missing data in the extracted sensing data. There may be unavoidable missing data in the sensing data extracted by the extraction unit 14. Therefore, in order to more accurately grasp environmental factors in the agricultural environment, the determination unit 16 may determine whether or not there is missing data in the sensing data extracted by the extraction unit 14. The determination unit 16 determines whether or not there is missing data by determining whether or not the sensing data extracted by the extraction unit 14 includes sensing data from all sensors, i.e., whether or not there is any data that is not included.

The determination unit 16 outputs the determination result of data loss to the interpolation unit 17. If the determination unit 16 determines that there is data loss, it may output information about the sensor that was supposed to acquire the missing data to the interpolation unit 17 together with the determination result.

<Interpolation unit 17>
When there is missing data in the sensing data, the interpolation unit 17 references other data in the sensing data to interpolate the missing data. Based on information about the sensor that was supposed to acquire the missing data, the interpolation unit 17 interpolates the missing data that was supposed to be acquired by the sensor. The interpolation unit 17 outputs the sensing data in which the missing data has been interpolated to the generation unit 15.

The interpolation unit 17 may use a conventionally known data interpolation method to interpolate the missing data. The interpolation unit 17 may refer to the distance between the sensor with missing data and another sensor and interpolate the missing data from sensing data from the other sensor. As an example, the interpolation unit 17 may interpolate the data by referring to the distance between the sensor with missing data and a nearby sensor, or may interpolate the data by referring to the distance between the sensor with missing data and a sensor that is not nearby. An example of the data interpolation method used by the interpolation unit 17 is the inverse distance weighting method. According to the inverse distance weighting method, the data to be interpolated can be calculated, for example, using the following equation (2):

The inverse distance weighting method is a technique primarily used in geographic information systems, and can be used to calculate missing data u(x) for target point x using equation (2) with a weighting coefficient wi defined as the inverse of the qth power (q is usually 1 to 2) of the distance d(x, xi) between target point x and surrounding points xi. All measurement points within the greenhouse can be used as surrounding points.

The extraction unit 14 extracts sensing data from periods with a high acquisition rate, but there may be unavoidable data loss even in sensing data from such periods. Even in such cases, the determination unit 16 determines whether or not there is data loss in the sensing data, and the interpolation unit 17 interpolates the missing data, thereby generating agricultural environment information that accurately represents environmental factors within the agricultural environment.

The display device 20 displays the agricultural environment information generated by the generation device 10. The display device 20 may also display the acquisition rate of sensing data calculated by the generation device 10. The agricultural environment information may be, for example, a distribution map that displays sensing data in correspondence with the locations where multiple sensors are installed in the space within the agricultural environment.

The display device 20 displays the information as an image, for example. The display device 20 may also be the display of a mobile device, such as a smartphone, that displays the agricultural environment information generated by the generation device 10.

The input device 30 accepts input operations by the user to the display system 100. As an example, the input device 30 accepts input to start generating agricultural environmental information in the generation device 10. The input device 30 also accepts input to display agricultural environmental information on the display device 20.

The storage device 40 stores programs and data used by the display system 100 and the prediction system 110 described below. The storage device 40 stores, as an example, various data input via the input device 30. The storage device 40 also stores, as an example, training data used to generate a prediction model in the model generation device 10 and the generated prediction model. The storage device 40 also stores, as an example, a prediction model, input information, and output information used in the prediction device 120 to predict the growth of horticultural crops such as tomatoes, strawberries, and cucumbers. The storage device 40 may have a database on the cloud or a server that stores various data.

The generating device 10 takes into account the data acquisition status of the sensors and generates agricultural environment information using only data from periods when data acquisition conditions are good, making it possible to generate agricultural environment information that accurately represents environmental factors within the agricultural environment. Therefore, by using the agricultural environment information generated in this way, it is possible to accurately grasp environmental factors within the agricultural environment, such as environmental unevenness that occurs within the agricultural environment. Furthermore, even if there is missing sensing data, the generating device 10 can interpolate the missing data to generate agricultural environment information that accurately represents environmental factors within the agricultural environment.

Sensors installed in agricultural environments are often installed outdoors or in environments where water is constantly in use, making them harsh environments and prone to malfunction. However, by taking into account the data acquisition conditions of the sensors using the generation device 10, it is possible to effectively utilize data acquired from sensors used in harsh environments. By controlling the environment based on sensing data that takes into account the data acquisition conditions, it is also possible to achieve high-quality, planned agricultural production.

(Generation process)
The flow of the generation process (generation method) of agricultural environmental information by the generation device 10 will be described with reference to Figs. 6 and 7. Fig. 6 is a flowchart showing an example of the generation process executed by the generation device according to one aspect of the present invention. Fig. 7 is a flowchart showing another example of the generation process executed by the generation device according to one aspect of the present invention.

As shown in FIG. 6 , first, the acquisition unit 12 acquires sensing data acquired by multiple sensors installed in a greenhouse, which is an agricultural environment (step S1, acquisition process). Next, the calculation unit 13 calculates the acquisition rate of the sensing data acquired by the acquisition unit 12 (step S2, calculation process). The extraction unit 14 references the acquisition rate within a predetermined period calculated by the calculation unit 13 and extracts sensing data for a period in which the acquisition rate is equal to or greater than a threshold (step S3, extraction process).

The generation unit 15 then calculates the average value for each sensor that acquired the sensing data extracted by the extraction unit 14 (step S4). Next, the generation unit 15 generates a distribution map as agricultural environment information, in which the calculated average values are displayed in correspondence with the positions of the sensors that acquired the sensing data (step S5, generation process). The generation unit 15 then outputs the generated distribution map to the display device 20 and displays it on the display device 20 (step S6), thereby completing the generation process.

The generation process shown in Figure 7 is a process for generating agricultural environmental information when there is a gap in the sensing data. As shown in Figure 7, the processes performed by the acquisition unit 12, calculation unit 13, and extraction unit 14 in steps S1 to S3 are the same as those in the generation process shown in Figure 6. In the generation process shown in Figure 7, first, the average value of the sensing data is calculated (step S14). Next, the determination unit 16 determines whether there is a gap in the sensing data (step S15).

In step S15, if the determination unit 16 determines that there is missing data in the sensing data (YES), the interpolation unit 17 references data from points where there is no missing data, interpolates the missing data (step S16), and proceeds to step S17. In step S15, if the determination unit 16 determines that there is no missing data in the sensing data (NO), proceeds to step S17.

The generation unit 15 calculates the average value for each sensor for the sensing data extracted by the extraction unit 14 or the sensing data interpolated by the interpolation unit 17 (step S16). Next, the generation unit 15 generates, as agricultural environment information, a distribution map that displays the calculated average values in correspondence with the positions of the sensors that acquired the sensing data (step S17). The generation unit 15 then outputs the generated distribution map to the display device 20 and displays it on the display device 20 (step S18), thereby completing the generation process.

With this configuration, the state of environmental factors within the agricultural environment can be visualized and understood, and the agricultural environment can be managed to reduce the occurrence of environmental unevenness, thereby reducing the waste of energy used to control the agricultural environment. Furthermore, with this configuration, proper control of the agricultural environment can promote the appropriate growth of plants, thereby realizing a stable food supply. This can contribute to the achievement of the Sustainable Development Goals (SDGs).

[Software implementation example]
The generating device according to each aspect of the present invention may be realized by a computer. In this case, the cultivation management information generation control program of the generating device, which realizes the device by a computer by operating the computer as each part (software element) of the device, and the computer-readable recording medium on which it is recorded, also fall within the scope of the present invention.

The functions of the generation device 10 (hereinafter referred to as the "device") can be realized by a program that causes a computer to function as the device, and by a program that causes a computer to function as each control block of the device (particularly each unit included in the control unit 11).

In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The functions described in each of the above embodiments are realized by executing the program using this control device and storage device.

The above program may be stored non-transitory on one or more computer-readable storage media. These storage media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

Furthermore, some or all of the functions of each of the above control blocks can be realized by logic circuits. For example, integrated circuits incorporating logic circuits that function as each of the above control blocks are also included in the scope of the present invention. In addition, the functions of each of the above control blocks can also be realized by, for example, a quantum computer.

Furthermore, each process described in the above embodiment may be executed by AI (Artificial Intelligence). In this case, the AI may run on the control device, or on another device (such as an edge computer or cloud server).

[Plant growth prediction system]
A plant growth prediction system according to one embodiment of the present invention includes a generation device according to the above-described embodiment of the present invention and a prediction device that predicts the degree of growth of plants growing in an agricultural environment based on agricultural environment information generated by the generation device.

Environmental factors within the agricultural environment in which plants are grown affect plant growth, and differences in environmental factors can affect the extent of growth, such as plant components and growth rate. For example, it is known that the sugar content and harvest time of fruit vegetables and fruits such as tomatoes vary depending on the temperature during the growing period.

Environmental factors that affect plant growth can vary depending on the plant's location, height, etc. within the agricultural environment. For example, in a greenhouse, plants located near the center may experience different temperatures and humidity levels than plants located further out, and the same plant may receive different amounts of sunlight at higher and lower locations.

By referring to the agricultural environment information generated by a generating device according to one embodiment of the present invention, it is possible to understand the environmental factors that affect plant growth for each plant's location within the agricultural environment, making it possible to predict differences in the degree of growth based on differences in environmental factors.

The plant growth prediction system 110 will be described with reference to Figure 8. Figure 8 is a block diagram showing an example of the main components of the plant growth prediction system 110 according to one embodiment of the present invention. The plant growth prediction system 110 includes a prediction device 120 in addition to the display system 100 shown in Figure 1. The prediction device 120 includes a control unit 121, which includes an acquisition unit 122 and a prediction unit 123.

The acquisition unit 122 acquires the agricultural environment information generated by the generation device 10. The prediction unit 123 references the agricultural environment information and predicts the degree of growth of plants growing in the agricultural environment. For example, the prediction unit 123 calculates the integrated value of environmental factors for each sensor installation position in the agricultural environment over a specified period based on the agricultural environment information, and predicts plant components and harvest time based on the integrated temperature value. As an example, the prediction unit 123 may predict the degree of plant growth using a prediction model constructed to input agricultural environment information and output the degree of plant growth. As such a prediction model, a prediction model constructed using a conventionally known method can be used.

The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention.

REFERENCE SIGNS LIST 10 Generation device 12 Acquisition unit 13 Calculation unit 14 Extraction unit 15 Generation unit 16 Determination unit 17 Interpolation unit 20 Display device 100 Display system (agricultural environmental information display system)
110 Plant growth prediction system

Claims (8)

A generating device for generating agricultural environment information representing a state in an agricultural environment, comprising:
an acquisition unit that acquires sensing data acquired by a plurality of sensors installed in the agricultural environment;
a calculation unit that calculates an acquisition rate of the sensing data;
an extracting unit that refers to the acquisition rate within a predetermined period and extracts the sensing data when the acquisition rate is equal to or greater than a predetermined threshold;
a generating unit that generates the agricultural environment information based on the extracted sensing data ,
calculating the acquisition rate by the calculation unit includes calculating an acquisition number of sensing data per unit time of each of the plurality of sensors;
The acquisition rate is the data acquisition rate (γ _data ) shown in equation (1).
generator. a determination unit that determines whether or not there is data loss in the extracted sensing data;
an interpolation unit that, when there is data loss in the sensing data, interpolates the lost data by referring to other data in the sensing data;
The generating device according to claim 1 , wherein the generating unit generates the agricultural environment information based on interpolated sensing data. The generation device described in claim 2, wherein the interpolation unit references the distance between the sensor with missing data and another sensor, and interpolates the missing data from the sensing data of the other sensor. The generating device described in any one of claims 1 to 3, wherein the generating unit generates, as the agricultural environment information, a distribution map that displays the extracted sensing data in correspondence with the locations in the space within the agricultural environment where the multiple sensors are installed. The generating device described in any one of claims 1 to 4, wherein the generating unit generates the agricultural environment information using an average value of the sensing data calculated for each sensor that acquired the extracted sensing data. A generating device according to any one of claims 1 to 5;
An agricultural environmental information display system comprising: a display device that displays the agricultural environmental information generated by the generation device. A generating device according to any one of claims 1 to 5;
A plant growth prediction system comprising: a prediction device that predicts the degree of growth of plants growing in the agricultural environment based on the agricultural environment information generated by the generation device. 1. A method for generating agricultural environment information representative of a situation in an agricultural environment, the method comprising :
an acquisition step of acquiring sensing data acquired by a plurality of sensors installed in the agricultural environment;
a calculation step of calculating an acquisition rate of the sensing data;
an extraction step of referring to the acquisition rate within a predetermined period and extracting the sensing data when the acquisition rate is equal to or greater than a predetermined threshold;
and generating the agricultural environment information based on the extracted sensing data,
Calculating the acquisition rate in the calculation step includes calculating the number of acquired sensing data per unit time from each of the plurality of sensors;
The acquisition rate is the data acquisition rate (γ _data ) shown in equation (1).
Generation method.