Plant and animal digital twin system

Abstract

To make a prediction regarding plants and animals by using a digital twin regarding plants and animals constructed by using data regarding plants and animals in a real world.SOLUTION: A plant and animal digital twin system 10 includes a database server 14, an application server 15, and an information terminal 13 used by a user. A digital twin storage unit 144 of the database server 14 stores a plant and animal digital twin regarding plants and animals constructed from data regarding plants and animals in a real world. The application server 15 acquires data obtained from the plant and animal digital twin, executes a predetermined simulation based on the acquired data to calculate prediction data regarding plants and animals in a real world, and sends the prediction data to the information terminal 13. The information terminal displays the prediction data in its display unit.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an animal and plant digital twin system.

Background Art

[0002] Conventionally, technologies for providing the living conditions of observation targets such as plants and animals have been known (for example, Patent Documents 1-3). Also, technologies for providing pest information have been known (for example, Patent Documents 4-5). Also, technologies for green space planning have been known (for example, Patent Documents 6-10). Also, methods for providing clinical services for plants have been known (for example, Patent Document 11).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Patent Document 3

Patent Document 4

Patent Document 5

Patent Document 6

Patent Document 7

Patent Document 8

Patent Document 9

Patent Document 10

Patent Document 11

Summary of the Invention

[0004] Incidentally, in recent years, a technology has become known for reproducing various data collected from the real world on a computer, and this technology is also called a digital twin. For this reason, it is thought that it may be possible to realize a plant digital twin, for example, by reproducing data on plants in the real world on a computer.

[0005] In the above-mentioned prior art, plant databases are used in the form of plant databases (e.g., Patent Document 8), tree databases (e.g., Patent Document 9), and plant catalogs (e.g., Patent Document 11). Furthermore, the technology in Patent Document 2 discloses an observation target related information storage unit that stores related information on observation targets such as plants and animals.

[0006] However, since plants are influenced by animals, and animals are influenced by plants, it is unlikely that simply using a plant database will allow for accurate prediction of the state of plants in the real world.

[0007] Furthermore, the technology described in Patent Document 2, upon receiving a request from an information requester, merely provides the requester with relevant information about the objects of observation, such as plants and animals, and does not provide information based on any kind of prediction.

[0008] This invention was made in view of the above facts, and aims to make predictions about plants and animals using a digital twin of plants and animals constructed using data on plants and animals in the real world. [Means for solving the problem]

[0009] A first aspect of the present invention is a digital twin system for plants and animals, comprising a database server, an application server, and an information terminal used by a user, wherein the database server's digital twin storage unit stores a digital twin of plants and animals constructed from data relating to plants and animals in the real world, the application server acquires data obtained from the digital twin of plants and animals, calculates predictive data relating to plants and animals in the real world by performing a predetermined simulation based on the acquired data, transmits the predictive data to the information terminal, and the information terminal displays the predictive data on its display unit. This makes it possible to make predictions about plants and animals using a digital twin of plants and animals constructed using data relating to plants and animals in the real world.

[0010] Furthermore, in the second embodiment of the present invention, when the information terminal receives designation data specifying animals and plants, it transmits the designation data and the location data of the information terminal to the application server. The application server, based on the designation data, the location data, and the data obtained from the animal and plant digital twin, performs a predetermined simulation to calculate prediction data including the location and time at which the animals and plants specified by the designation data will appear in the real world. The application server then transmits the prediction data to the information terminal, which adds the prediction data to the map data and displays it. This makes it possible to suppress contact or interaction with animals and plants specified by the user.

[0011] Furthermore, the designated data in the third aspect of the present invention includes range data representing an area on a map, and the application server transmits the prediction data to the information terminal when it is predicted that the animals and plants specified by the designated data will appear within the area represented by the range data on the map. This makes it possible to suppress contact or interaction with animals and plants with a higher degree of accuracy by specifying not only the animals and plants themselves, but also their range.

[0012] Furthermore, in the fourth aspect of the present invention, when the information terminal receives placement specification data specifying the arrangement of predetermined plants and animals, it transmits the placement specification data to the application server. The application server calculates the prediction data by performing a predetermined simulation based on the placement specification data and data obtained from the plant and animal digital twin, transmits the prediction data to the information terminal, and displays the prediction data by adding it to the map data. This allows the user to specify placement specification data specifying the arrangement of predetermined plants and animals (for example, trees), and predict what kinds of organisms will be attracted according to the growth of those plants and animals.

[0013] In the fifth aspect of the present invention, the information terminal, upon receiving monitoring range specification data that specifies a monitoring range on a map for planted plants as flora and fauna, transmits the monitoring range specification data to the application server. The application server calculates the prediction data by performing a predetermined simulation based on the monitoring range specification data and data obtained from the plant and fauna digital twin, transmits the prediction data within the map range represented by the monitoring range specification data to the information terminal, and the information terminal displays the prediction data on its display unit. This makes it possible to predict how the planted plants will grow within the monitoring range based on the data from the plant and fauna digital twin.

[0014] The sixth aspect of the present invention provides a digital twin of plants and animals that is pre-constructed based on relational data representing the relationship between animal species and plant species. This improves the prediction accuracy of the prediction data.

[0015] The seventh aspect of the present invention provides a digital twin of plants and animals that is pre-constructed based on meteorological condition data representing the relationship between animal species and meteorological conditions. This makes it possible to improve the prediction accuracy of the forecast data.

Advantages of the Invention

[0016] According to the present invention, an effect can be obtained that predictions regarding animals and plants can be made using a digital twin regarding animals and plants constructed by using data regarding animals and plants in the real world.

Brief Description of the Drawings

[0017] [Figure 1] It is a block diagram showing an example of the configuration of an animal and plant digital twin system according to an embodiment. [Figure 2] It is a diagram for explaining an animal and plant digital twin. [Figure 3] It is a diagram showing an example of the computer configuration of each device of the animal and plant digital twin system according to an embodiment. [Figure 4] It is a diagram showing an example of a sequence executed in the animal and plant digital twin system according to an embodiment. [Figure 5] It is a diagram showing an example of a flowchart executed in the animal and plant digital twin system according to an embodiment. [Figure 6] It is a diagram showing an example of data used when constructing an animal and plant digital twin. [Figure 7] It is a diagram showing an example of data used when constructing an animal and plant digital twin. [Figure 8] It is a diagram showing an example of data used when constructing an animal and plant digital twin. [Figure 9] It is a diagram showing an example of a sequence executed in the animal and plant digital twin system according to an embodiment. [Figure 10] It is a diagram showing an example of the display format of prediction data. [Figure 11] It is a diagram of a scene where a user encounters a bear, which is an example of a harmful animal. [Figure 12] It is a diagram showing an example of a sequence executed in the animal and plant digital twin system according to an embodiment. [Figure 13]This figure shows an example of a sequence executed in the animal and plant digital twin system of the embodiment. [Modes for carrying out the invention]

[0018] Embodiments of the present invention will be described in detail below with reference to the drawings.

[0019] [Summary of the Embodiment]

[0020] This embodiment aims to improve people's quality of life (QOL), streamline planting planning and maintenance, and promote measures against invasive species and biological control by utilizing a digital twin of nature encompassing plants and animals. In this embodiment, first, a database containing data on plants and animals in the real world is prepared in order to construct a digital twin of plants and animals using data on plants and animals in the real world. The data stored in this database includes data obtained from various sensors installed in the real world. Next, various applications are constructed using this digital twin of plants and animals. Specifically, predictive data on plants and animals in the real world is calculated by performing predetermined simulations on plants and animals (for example, simulations of plant growth, animal movements, etc.) using various data obtained from the digital twin of plants and animals. Then, this predictive data is used to create opportunities for users to interact with plants and animals, to reduce encounters between users and harmful animals, to formulate green space plans that attract organisms, and to monitor planting and pruning. A detailed explanation follows below.

[0021] [First Embodiment] <Configuration of the Plant and Animal Digital Twin System> Figure 1 is a block diagram showing an example of the configuration of a plant and animal digital twin system 10 according to the first embodiment. Functionally, the plant and animal digital twin system 10 can be represented as a configuration including multiple sensors 12A, 12B, ..., an information terminal 13, a database server 14, and an application server 15, as shown in Figure 1. The multiple sensors 12A, 12B, ..., the information terminal 13, the database server 14, and the application server 15 are connected to each other via a communication network 16 such as the Internet. In addition to the database server and application server with specific connection destinations, a cloud system with similar functional services may also be used.

[0022] The first embodiment of the plant and animal digital twin system 10 provides an application that creates opportunities for interaction between the user and plants and animals (for example, birds, insects, and trees, which are examples of animals).

[0023] The multiple sensors 12A, 12B, ... are various types of sensors placed in the real world. The multiple sensors 12A, 12B, ... detect sensor data related to plants and animals in the real world.

[0024] Each of the multiple sensors 12A, 12B, ... is, for example, a camera, thermometer, hygrometer, sound sensor, and position sensor such as GPS. More specifically, each of the multiple sensors 12A, 12B, ... is, for example, a birdbath camera, a camera that images perches, an RFID tag, a sound-collecting microphone, and a camera trap, and collects dynamic data of plants and animals as sensor data. Alternatively, a drone-mounted camera may be used as a sensor, and point cloud data of trees may be collected, for example. The various sensor data detected by each of the multiple sensors 12A, 12B, ... are transmitted to the database server 14, which will be described later. In the following, one of the multiple sensors 12A, 12B, ... will simply be referred to as sensor 12.

[0025] The information terminal 13 is operated by the user. The information terminal 13 is, for example, a personal computer or a smartphone.

[0026] The database server 14 acquires various sensor data detected by each of the multiple sensors 12A, 12B, ..., and generates a digital twin of plants and animals in the real world based on this sensor data. Figure 2 shows a diagram illustrating the digital twin of plants and animals. As shown in Figure 2, the digital twin of plants and animals is constructed on the database server 14 using data R about plants and animals in the real world.

[0027] Functionally, the database server 14 comprises a database control unit 140, a database storage unit 142, and a digital twin storage unit 144.

[0028] The application server 15 provides applications that create opportunities for users to interact with living organisms (for example, birds) based on various data of plant and animal digital twins stored in the digital twin storage unit 144. Functionally, the application server 15 comprises a server control unit 150 and a server storage unit 152.

[0029] The sensor 12, information terminal 13, database server 14, and application server 15 can be implemented by a computer 60, for example, as shown in Figure 3. The computer 60 that implements the sensor 12, information terminal 13, database server 14, and application server 15 includes a CPU 61, memory 62 as a temporary storage area, and a non-volatile storage unit 63. The computer 60 also includes an input / output interface (I / F) 64 to which input / output devices (not shown) are connected, and a read / write (R / W) unit 65 that controls the reading and writing of data to the recording medium 69. The computer also includes a network I / F 66 that connects to a network such as the Internet. The CPU 61, memory 62, storage unit 63, input / output I / F 64, R / W unit 65, and network I / F 66 are connected to each other via a bus 67.

[0030] The storage unit 63 can be implemented using a Hard Disk Drive (HDD), Solid State Drive (SSD), flash memory, etc. The storage unit 63, as a storage medium, stores programs that enable the computer to function. The CPU 61 reads the programs from the storage unit 63, loads them into memory 62, and sequentially executes the processes contained within the programs.

[0031] <Functions of the Plant and Animal Digital Twin System 10>

[0032] Next, the operation of the first embodiment of the plant and animal digital twin system 10 will be described.

[0033] When sensor data detected by each of the multiple sensors 12A, 12B, ... is transmitted to the database server 14, the sequence shown in Figure 4 is executed. Note that the sequence shown in Figure 4 is the sequence when sensor data is transmitted from one sensor 12 to the database server 14.

[0034] In step S100, the sensor 12 transmits the sensor data it has acquired to the database server 14. For example, the sensor 12 transmits location data representing its own position, image data of its surroundings, and time data representing the time when that data was acquired to the database server 14. Other types of sensors 12 transmit other types of data to the database server 14, such as a combination of location data, temperature data, and time data.

[0035] Next, in step S102, the database control unit 140 of the database server 14 receives the sensor data transmitted from the sensor 12.

[0036] Then, in step S104, the database control unit 140 stores the sensor data in the database storage unit 142.

[0037] The sequence shown in Figure 4 is repeatedly executed, resulting in the storage of multiple sensor data into the database storage unit 142. The database storage unit 142 also stores various data on plants and animals collected manually. The database storage unit 142 stores various data such as images of plants and animals, location data coordinates of plants and animals, point cloud data of plants and animals, the number of times plants and animals appear, the location of appearance, the season of appearance, and the time of appearance. Hereafter, the data stored in the database storage unit 142 will also be simply referred to as "plant and animal data."

[0038] Next, the database control unit 140 constructs a digital twin of real-world flora and fauna based on multiple flora and fauna data stored in the database storage unit 142. The database server 14 executes the flowchart shown in Figure 5.

[0039] In step S106, the database control unit 140 reads multiple animal and plant data from the database storage unit 142.

[0040] In step S108, the database control unit 140 constructs a digital twin of plants and animals, which is a digital twin of real-world plants and animals, based on the multiple plant and animal data read in step S106. Specifically, the database control unit 140 predicts and interpolates the habitat distribution of plants and animals using parameters such as seasonality, temporality, and location, based on the multiple plant and animal data stored in the database, and constructs a three-dimensional digital twin of plants and animals by reflecting this data in three-dimensional space. This digital twin of plants and animals is updated sequentially each time new plant and animal data is stored in the database storage unit 142.

[0041] Furthermore, when constructing a digital twin of plants and animals, considering data on the preferred conditions of each animal species makes it possible to more accurately reproduce the degree of mutual influence between animals and plants. This can also improve the prediction accuracy of the applications described later. For example, a digital twin of plants and animals is constructed that reflects the following data.

[0042] Figures 6 to 8 show examples of data used when constructing a digital twin of flora and fauna. Figures 6 to 8 are examples of relational data representing the relationship between animal species and plant species, or meteorological condition data representing the relationship between animal species and meteorological conditions.

[0043] Figure 6 shows a survival probability model for each species of organism, taking into account seasonality and tree characteristics. In Figure 6, "tree layer density," "tree layer area," and "shrub layer density" refer to the tree species, respectively. The horizontal axis of the graph in Figure 6 represents the score indicating the magnitude of "density" or "area," and the vertical axis represents the survival probability (or occurrence probability) of each bird species b1 to b5.

[0044] As shown in Figure 6, the probability of survival near a tree differs depending on the bird species b1 to b5. Furthermore, as shown in Figure 6, the probability of bird survival (or appearance) also differs depending on the tree's "density" or "area." The solid, dotted, and dashed lines in the graph in Figure 6 represent seasonality (more specifically, differences in weather conditions due to the season).

[0045] For example, the database control unit 140 of the database server 14 uses the data from the graph shown in Figure 6 to predict and supplement the habitat distribution of plants and animals, thereby constructing a digital twin of flora and fauna. This improves the prediction accuracy of each application described later.

[0046] Figure 7 shows data representing plants and vegetation that animals tend to gather on. For example, the database control unit 140 of the database server 14 constructs a digital twin of flora and fauna by referring to data that associates information on the density and species of trees at each hierarchy level with a score representing the likelihood of animals gathering, as shown in Figure 7. Figure 7 is an example of a table that associates tree hierarchy with a score representing the likelihood of various animals gathering on the site; the higher the score, the more likely animals are to gather. Figure 7 is merely an example. More detailed information can be provided regarding tree hierarchy and animal species. For example, data related to the interaction between food resources (locations where insects appear, fruiting status, fish habitats, etc.) and nesting sites (tree cavities, earthen walls for kingfishers, etc.) could be used. Alternatively, data showing that the shorter the distance between food resources and nesting sites, the more animals appear at the location of the food resources could be used.

[0047] Figure 8 is a diagram representing matching data between animals and plants based on external environmental factors. For example, the database control unit 140 of the database server 14 constructs a digital twin of flora and fauna by referring to data that associates weather conditions with scores related to animal behavior, as shown in Figure 8. Figure 8 is an example of a table that associates weather conditions with scores representing the likelihood of various animals appearing; the higher the score, the more likely the animal is to appear. Figure 8 is merely an example, but the animal species and weather conditions could be made more detailed, for example, butterflies are more likely to fly on sunny days, or birds of prey are more likely to fly during strong winds.

[0048] For example, the database control unit 140 of the database server 14 performs simulations of real-world flora and fauna based on relational data representing the relationship between animal species and plant species, as shown in Figures 6 to 8, and meteorological condition data representing the relationship between animal species and meteorological conditions. It then constructs a digital twin of flora and fauna by predicting and supplementing the habitat distribution of flora and fauna by referring to the simulation results.

[0049] Next, the application server 15 generates predictive data for predicting the dynamics of plants and animals based on various data of the plant and animal digital twins stored in the digital twin storage unit 144 of the database server 14. The application server 15 executes the sequence shown in Figure 9. Note that the sequence shown in Figure 9 is the sequence in which the user specifies the plants and animals they wish to interact with, and the application server 15 generates predictive data regarding when and where those plants and animals will appear.

[0050] First, the user specifies the plants and animals they wish to interact with and inputs that information into the information terminal 13.

[0051] Next, in step S200, the information terminal 13 receives the user's specification of the plants and animals they wish to interact with, and transmits the specification data representing the specified plants and animals, along with the location data of the information terminal 13, to the application server 15.

[0052] In step S202, the server control unit 150 of the application server 15 receives the combination of specified data and location data transmitted from the information terminal 13 in step S200.

[0053] In step S204, the server control unit 150 of the application server 15 sends a request signal to the database server 14 that indicates a request for data related to the plants and animals represented by the specified data in the vicinity of the location represented by the location data (for example, a predetermined range).

[0054] In step S206, the database control unit 140 of the database server 14 reads data from the plant and animal digital twins stored in the digital twin storage unit 144 in response to a request signal sent from the application server 15. Then, the server control unit 150 of the application server 15 sends the data read from the plant and animal digital twins to the application server 15.

[0055] For example, consider a case where the specified data represents bird A and the location data represents a certain location P. In this case, the server control unit 150 of the application server 15 sends a request signal to the database server 14 indicating a request for data regarding the location, time, and environment in which bird A was observed more than a predetermined number of times in the green space surrounding location P during the past year. The environmental data may include, for example, data regarding weather, temperature, and humidity.

[0056] In this case, the database control unit 140 of the database server 14 acquires data corresponding to the request signal from the plant and animal digital twin and transmits the acquired data to the application server 15.

[0057] In step S208, the server control unit 150 of the application server 15 receives the data transmitted from the database server 14 in step S206 and temporarily stores it in the server storage unit 152. Then, in step S208, the server control unit 150 of the application server 15 calculates prediction data, including the location and time at which the specified plants and animals appear in the real world, by performing a predetermined simulation based on the specified data, location data, and data obtained from the plant and animal digital twin.

[0058] For example, the server control unit 150 of the application server 15 calculates predictive data about flora and fauna by performing simulations of real-world flora and fauna based on specified data, location data, data obtained from a digital twin of flora and fauna, and relationship data representing the relationship between animal species and plant species, as shown in Figures 6 to 8, as well as meteorological condition data representing the relationship between animal species and meteorological conditions.

[0059] For example, if the specified data represents bird A, which is bird b1, then the information from the graph of bird b1 shown in Figure 6 is used to calculate prediction data including the location and date (including time) in which bird b1 will appear in the green space surrounding location P, which is represented by the location data.

[0060] In step S210, the server control unit 150 of the application server 15 transmits the predicted data calculated in step S208 to the information terminal 13.

[0061] In step S212, the information terminal 13 displays the prediction data sent from the application server 15 in step S210 on its own display unit (not shown). For example, the information terminal 13 adds the prediction data to the map data and displays it on the display unit (not shown).

[0062] Figure 10 shows an example of the display format for prediction data. For example, if the specified data represents bird A, prediction data representing the location and time (not shown in the figure) when bird A will appear will be added to the map data and displayed in the display unit (not shown), as shown in Figure 10. Alternatively, if the specified data represents insect B, prediction data representing the location and time when insect B will appear will be added to the map data and displayed in the display unit (not shown), as shown in Figure 10. Alternatively, if the specified data represents a tree C, prediction data representing the location of tree C and the date and time it will bloom will be added to the map data and displayed in the display unit (not shown), as shown in Figure 10.

[0063] As described above, the first embodiment of the animal and plant digital twin system is an animal and plant digital twin system including a database server, an application server, and an information terminal used by a user. The database server's digital twin storage unit stores an animal and plant digital twin constructed from data on animals and plants in the real world. The application server acquires data from the animal and plant digital twin, calculates predictive data on animals and plants in the real world by performing a predetermined simulation based on the acquired data, and transmits the predictive data to the information terminal. The information terminal displays the predictive data on its display unit. This allows predictive data on animals and plants to be calculated using an animal and plant digital twin constructed using data on animals and plants in the real world and used in various applications. Specifically, by pre-specifying the animals and plants that the user wishes to interact with, the application server can predict when and where the specified animals and plants will appear based on the data obtained from the animal and plant digital twin constructed by the database server, thereby creating opportunities for users to interact with animals and plants with a high degree of certainty.

[0064] [Second Embodiment] Next, a second embodiment will be described. The second embodiment of the animal and plant digital twin system 10 differs from the first embodiment in that the application server 15 provides an application for monitoring pests. Note that the second embodiment of the animal and plant digital twin system 10 has the same configuration as the first embodiment, so its description will be omitted.

[0065] The application provided by the application server 15 of the plant and animal digital twin system 10 in the second embodiment is an application that reduces the chances of the user encountering harmful animals.

[0066] Figure 11 shows a scene in which user U encounters bear B1, an example of a harmful animal. In the first embodiment, we explained an example in which predictive data representing the location and time of appearance of plants and animals is added to map data and displayed on the display unit of the information terminal 13 for the purpose of interacting with plants and animals. However, there are harmful animals that users would like to avoid contact with, such as bear B1 shown in Figure 11. Therefore, in the second embodiment, we provide an application to reduce the chances of the user encountering harmful animals.

[0067] <Functions of the Plant and Animal Digital Twin System 10> The operation of the plant and animal digital twin system 10 of the second embodiment will be described.

[0068] The plant and animal digital twin system 10 of the second embodiment executes the sequences shown in Figures 4 and 9 and the flowchart shown in Figure 5, similar to the first embodiment.

[0069] In the second embodiment, the user first specifies the animals or plants they wish to avoid contact with (for example, harmful animals such as bears) and inputs that information into the information terminal 13.

[0070] Therefore, the specified data sent to the application server 15 in step S200 of Figure 9 is data representing the plants and animals that the user wants to avoid coming into contact with.

[0071] Steps S202 to S212 are performed in the same manner as in the first embodiment.

[0072] Furthermore, the predictive data displayed on the information terminal 13 in step S212 functions as an alert to avoid contact with harmful animals.

[0073] As explained above, in the second embodiment of the plant and animal digital twin system, by having the user specify in advance which plants and animals they wish to avoid contact with, the application server can predict when and where those plants and animals will appear based on the plant and animal digital twin, thereby suppressing contact between the user and plants and animals with a high degree of accuracy.

[0074] Furthermore, the specified data in the first and second embodiments described above may include range data representing an area on a map. In this case, the application server 15 sends prediction data to the information terminal 13 when it predicts that the animals and plants specified by the specified data will appear within the area represented by the range data on the map. This allows for a higher degree of accuracy in suppressing contact with animals and plants by specifying not only the animals and plants themselves but also their range. In addition, by specifying a range, the frequency of data output from the application server 15 can be reduced, thereby reducing the processing load on the application server 15.

[0075] [Third Embodiment] Next, a third embodiment will be described. The third embodiment of the flora and fauna digital twin system 10 differs from the first and second embodiments in that the application server 15 provides an application for a green space plan that attracts organisms. Note that the third embodiment of the flora and fauna digital twin system 10 has the same configuration as the first embodiment, so its description will be omitted.

[0076] The application provided by the application server 15 of the third embodiment of the plant and animal digital twin system 10 is an application for green space planning that attracts organisms.

[0077] In the third embodiment, first, the user formulates a green space plan on the plant and animal digital twin by virtually placing predetermined trees and plants on the plant and animal digital twin. Then, the application server 15 of the third embodiment predicts what animal species will be attracted to the trees and plants virtually placed in the provisional green space plan.

[0078] <Functions of the Plant and Animal Digital Twin System 10> The operation of the third embodiment of the plant and animal digital twin system 10 will be explained.

[0079] The third embodiment of the plant and animal digital twin system 10 executes the sequence shown in Figure 4 and the flowchart shown in Figure 5, similar to the first embodiment. In addition, the third embodiment of the plant and animal digital twin system 10 executes the sequence shown in Figure 12 instead of the sequence shown in Figure 9.

[0080] In the third embodiment, first, the user specifies the arrangement of predetermined plants and animals (for example, trees and plants) and inputs this information into the information terminal 13. This specification is input into the information terminal 13 as arrangement specification data that specifies the arrangement of trees and plants.

[0081] In step S300 of Figure 12, the information terminal 13 receives the specification of the placement of plants and animals entered by the user and sends placement specification data representing that specification to the application server 15.

[0082] In step S302, the server control unit 150 of the application server 15 receives the placement specification data transmitted from the information terminal 13 in step S300.

[0083] In step S304, the server control unit 150 of the application server 15 sends a request signal to the database server 14 that indicates a request for data related to plants and animals at the location represented by the placement specification data.

[0084] In step S306, the database control unit 140 of the database server 14 reads data from the plant and animal digital twins stored in the digital twin storage unit 144 in response to a request signal sent from the application server 15. Then, the database control unit 140 of the database server 14 sends the data read from the plant and animal digital twins to the application server 15.

[0085] For example, if other plants or animals exist in the location indicated by the placement specification data within the plant and animal digital twin, data representing them is sent to the application server 15.

[0086] In step S308, the server control unit 150 of the application server 15 calculates prediction data by executing a predetermined simulation based on the placement specification data received in step S300 and the data obtained from the plant and animal digital twin. Specifically, the server control unit 150 virtually places the trees and plants represented by the placement specification data on the plant and animal digital twin and executes a simulation related to the plants and animals to calculate prediction data regarding the plants and animals that will be attracted to the virtually placed trees and plants as time progresses. At this time, the server control unit 150 of the application server 15 calculates the prediction data by referring to various data as shown in Figures 6 to 8.

[0087] In step S310, the server control unit 150 of the application server 15 transmits the predicted data calculated in step S308 to the information terminal 13.

[0088] In step S312, the information terminal 13 displays the prediction data sent from the application server 15 in step S310 on its own display unit (not shown). For example, the information terminal 13 adds the prediction data to the map data and displays it on the display unit (not shown).

[0089] As described above, in the third embodiment of the plant and animal digital twin system, by having the user specify the placement of predetermined plants and animals (for example, trees), the application server can predict what kinds of organisms will be attracted to those plants and animals in accordance with their growth, based on the data obtained from the plant and animal digital twin and the fact that new plants and animals have been placed there.

[0090] [Fourth Embodiment] Next, the fourth embodiment will be described. The fourth embodiment of the plant and animal digital twin system 10 differs from the first to third embodiments in that the application server 15 provides a planting and pruning monitoring application. Note that the fourth embodiment of the plant and animal digital twin system 10 has the same configuration as the first embodiment, so its description will be omitted.

[0091] The application provided by the application server 15 of the plant and animal digital twin system 10 in the fourth embodiment is an application for monitoring planting and pruning.

[0092] In the fourth embodiment, first, the user specifies a monitoring range on a map for the plants and animals. Then, the application server 15 of the fourth embodiment predicts how the plants within the monitoring range will grow.

[0093] <Functions of the Plant and Animal Digital Twin System 10> The operation of the fourth embodiment of the plant and animal digital twin system 10 will be explained.

[0094] The fourth embodiment of the plant and animal digital twin system 10 executes the sequence shown in Figure 4 and the flowchart shown in Figure 5, similar to the first embodiment. In addition, the fourth embodiment of the plant and animal digital twin system 10 executes the sequence shown in Figure 13 instead of the sequence shown in Figure 9.

[0095] In the fourth embodiment, first, the user specifies a monitoring range on a map for planted flora and fauna, and inputs this information into the information terminal 13. This specification is input into the information terminal 13 as monitoring range specification data that specifies a monitoring range on a map for planted flora and fauna.

[0096] In step S400 of Figure 13, the information terminal 13 receives the monitoring range specification entered by the user and sends monitoring range specification data representing that specification to the application server 15.

[0097] In step S402, the server control unit 150 of the application server 15 receives the monitoring range specification data transmitted from the information terminal 13 in step S400.

[0098] In step S404, the server control unit 150 of the application server 15 sends a request signal to the database server 14 that indicates a request for data related to plants and animals in the area represented by the monitoring range specification data.

[0099] In step S406, the database control unit 140 of the database server 14 reads data from the plant and animal digital twins stored in the digital twin storage unit 144 in response to a request signal sent from the application server 15. Then, the database control unit 140 of the database server 14 sends the data read from the plant and animal digital twins to the application server 15.

[0100] For example, if other plants or animals exist in the area represented by the monitoring range specification data within the plant and animal digital twin, data representing that location is sent to the application server 15.

[0101] In step S408, the server control unit 150 of the application server 15 calculates prediction data by executing a predetermined simulation based on the monitoring range specification data received in step S400 and the data obtained from the plant and animal digital twin. Specifically, the server control unit 150 places virtual plants within the range represented by the monitoring range specification data in the plant and animal digital twin and executes a simulation related to plants and animals to calculate prediction data about how the virtually placed plants will grow over time. At this time, the server control unit 150 of the application server 15 calculates the prediction data by referring to various data as shown in Figures 6 to 8.

[0102] In step S410, the server control unit 150 of the application server 15 transmits the predicted data calculated in step S408 to the information terminal 13.

[0103] In step S412, the information terminal 13 displays the prediction data sent from the application server 15 in step S410 on its own display unit (not shown). For example, the information terminal 13 adds the prediction data to the map data and displays it on the display unit (not shown).

[0104] As described above, in the fourth embodiment of the plant and animal digital twin system, the user specifies a monitoring range on a map for the plantings, and the application server 15 can predict how the plantings will grow within that monitoring range based on the plant and animal digital twin data.

[0105] Incidentally, in conventional technology, simulations are performed within a predetermined range, but this does not allow for interaction with other areas, resulting in inappropriate simulation results. In contrast, in the fourth embodiment, while a monitoring range is set, a digital twin of plants and animals is constructed, and a simulation is performed that also considers interaction with areas outside the monitoring range, thus enabling the acquisition of more appropriate simulation results.

[0106] Furthermore, according to the third and fourth embodiments described above, it is also possible to formulate a green space plan that takes into account plants and animals to create a more appropriate environment.

[0107] It should be noted that the present invention is not limited to the embodiments described above, and various modifications and applications are possible without departing from the spirit of the invention.

[0108] For example, in the above embodiment, the case in which the database server 14 stores data detected by the sensor 12 was described as an example, but it is not limited to this. Since it is difficult to equip plants and animals themselves with the sensor 12, there may be cases where there is insufficient data to build a plant and animal digital twin. For this reason, processing to compensate for this (for example, reflecting temporary plants and animals on the plant and animal digital twin) may be performed.

[0109] Furthermore, according to the first embodiment, it is possible to create tools (e.g., biodiversity maps) that encourage users to go outdoors and induce the use of green spaces. Also, according to the first embodiment, it is possible to develop a system that attracts target organisms to designated locations and monitors them based on predictive data about plants and animals. Furthermore, according to the first embodiment, the user's health is promoted through walking, due to the incentive for users to go outdoors and use green spaces. Furthermore, according to the first embodiment, by utilizing the biodiversity maps generated based on predictive data about plants and animals for disseminating local information, it is possible to revitalize local communities and promote the local tourism industry. Furthermore, by utilizing the biodiversity maps as an environmental learning tool, awareness of biodiversity conservation can be increased. Furthermore, according to the first embodiment, by creating spaces where users can interact with organisms and feel nature, users can obtain relaxation and healing effects. Furthermore, according to the first embodiment, communication within the company and with neighboring communities is promoted by a system that provides timely information on organisms that visit green spaces and the changing seasons.

[0110] Furthermore, according to the second embodiment, a system can be established that contributes to the rapid management and control of invasive alien species and organisms that cause biological damage. Specifically, according to the second embodiment, countermeasures can be taken from the initial stages of invasion of invasive alien species that adversely affect the ecosystem on the site. Furthermore, according to the second embodiment, it may lead to the eradication of invasive alien species within the managed area. Furthermore, according to the second embodiment, it is possible to create a comfortable outdoor and indoor environment by preventing the intrusion of harmful birds (pigeons and crows, etc.) and harmful animals (rats and raccoons, etc.) that cause harm to people. Furthermore, according to the second embodiment, by combining timely identification and prediction of damage caused by harmful animals in the initial stages with highly effective intimidation techniques, the deterrent effect can be maximized.

[0111] Furthermore, according to the third and fourth embodiments, the planning and maintenance of exterior structures and plantings can be made more efficient. Specifically, according to the third and fourth embodiments, habitat simulations of biological species based on the size of the green space can be used to create optimal future plans for the green space. In addition, identifying the optimal pruning locations for plantings leads to more efficient maintenance. Furthermore, for example, by utilizing mobile planter robots, it is possible to create the optimal growing environment for planting maintenance. In addition, by utilizing automatic cleaning robots, the efficiency of outdoor environmental conservation can be promoted. In addition, by utilizing pest control robots, the efficiency of outdoor environmental conservation can be promoted.

[0112] Furthermore, although the above describes an embodiment in which the program according to the present invention is pre-stored (installed) in a memory unit, the program according to the present invention can also be provided in a form recorded on a recording medium such as a CD-ROM, DVD-ROM, or microSD card. [Explanation of Symbols]

[0113] 10. Digital Twin System for Animals and Plants 12 sensors 13 Information terminals 14 Database Servers 15 Application Server 16 Communication Networks 60 Computer 140 Database Control Unit 142 Database Storage Unit 144 Digital Twin Memory Unit 150 Server Control Unit 152 Server Storage Unit

Claims

1. A digital twin system of plants and animals, including a database server, an application server, and an information terminal used by the user, The digital twin storage unit of the aforementioned database server stores digital twins of plants and animals constructed from data on plants and animals in the real world. When the information terminal receives designation data specifying plants and animals, it transmits the designation data and the location data of the information terminal to the application server. The application server, based on the data obtained from the digital twin of plants and animals, the specified data, and the location data, performs a predetermined simulation to calculate prediction data including the location and time at which the plants and animals specified by the specified data will appear in the real world, and transmits the prediction data to the information terminal. The information terminal adds the prediction data to the map data and displays it on its own display unit. A digital twin system for plants and animals.

2. A digital twin system of plants and animals, including a database server, an application server, and an information terminal used by the user, The digital twin storage unit of the aforementioned database server stores a digital twin of flora and fauna, which is a digital twin of flora and fauna constructed from data relating to flora and fauna in the real world, and is a digital twin of flora and fauna that is pre-constructed based on meteorological condition data representing the relationship between animal species and meteorological conditions. The application server acquires data obtained from the digital twin of plants and animals, calculates predictive data about plants and animals in the real world by performing a predetermined simulation based on the acquired data, and transmits the predictive data to the information terminal. The information terminal displays the prediction data on its own display unit. A digital twin system for plants and animals.

3. The specified data includes range data representing the area on the map. The application server transmits the prediction data to the information terminal when it is predicted that the animals and plants specified by the specified data will appear within the range represented by the range data on the map. The plant and animal digital twin system according to claim 1.

4. When the information terminal receives placement specification data specifying the arrangement of predetermined plants and animals, it transmits the placement specification data to the application server. The application server calculates the prediction data by performing a predetermined simulation based on the placement specification data and the data obtained from the plant and animal digital twin, and transmits the prediction data to the information terminal. The information terminal displays the prediction data by adding it to the map data. The plant and animal digital twin system according to claim 1 or claim 2.

5. When the information terminal receives monitoring range specification data that specifies the monitoring range on a map for planted plants and animals, it transmits the monitoring range specification data to the application server. The application server calculates the prediction data by performing a predetermined simulation based on the monitoring range specification data and the data obtained from the plant and animal digital twin, and transmits the prediction data within the map area represented by the monitoring range specification data to the information terminal. The information terminal displays the prediction data on its own display unit. The plant and animal digital twin system according to claim 1 or claim 2.

6. The aforementioned animal and plant digital twin is a digital twin pre-constructed based on relational data representing the relationships between animal species and plant species. The plant and animal digital twin system according to claim 1 or claim 2.

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