Estimation device, estimation method, and estimation program

Abstract

To accurately estimate future changes in fish catches. [Solution] The estimation device 100 according to this embodiment includes a marine information collection unit 121, a fish catch information collection unit 122, and an estimation unit 124. The marine information collection unit 121 collects information on the state of the ocean. The fish catch information collection unit 122 collects information on the catch volume of marine products. The estimation unit 124 inputs the information on the state of the ocean collected by the marine information collection unit 121 and the information on the catch volume collected by the fish catch information collection unit 122 into a generation model, and estimates the future catch volume of marine products in a predetermined area based on the output from the generation model.

Description

Technical Field

[0001] The present invention relates to an estimation device, an estimation method, and an estimation program.

Background Art

[0002] In recent years, due to climate change caused by global warming and the like, the sea surface water temperature has been on the rise. The change in the sea surface water temperature has led to a change in the ecosystem, and an increase or decrease in the catch of seafood has occurred across the country.

[0003] Also, in recent years, a technique for calculating an estimated catch amount that a fishing boat harvests from the capabilities of the fishing boat and ocean information has been published (see, for example, Patent Document 1). In the prior art, the catch amount is estimated from the capabilities of the fishing boat and ocean information, and a schedule for each fishing boat is generated so that a client can obtain a certain profit within the catch limit for one day at each location.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the prior art, there are cases where the change in the future catch amount cannot be appropriately estimated. For example, conventionally, the catch amount in the relatively near future for a specific location is estimated, but the catch amount several years later cannot be estimated, and the change situation of the catch amount on an annual basis cannot be estimated.

Means for Solving the Problems

[0006] To solve the above-mentioned problems and achieve the objective, the estimation device according to this embodiment is characterized by comprising: an ocean information collection unit that collects information on the state of the ocean; a catch amount information collection unit that collects information on the catch amount of marine products; and an estimation unit that inputs the information on the state of the ocean collected by the ocean information collection unit and the information on the catch amount collected by the catch amount information collection unit into a generation model and estimates the future catch amount of marine products in a predetermined area based on the output from the generation model. [Effects of the Invention]

[0007] The present invention has the effect of being able to appropriately estimate future changes in fish catches. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 shows an example of the overall configuration of the estimation system according to the embodiment. [Figure 2] Figure 2 shows an example of the configuration of the estimation device according to the embodiment. [Figure 3] Figure 3 shows a specific example of data stored in the marine information storage unit according to this embodiment. [Figure 4] Figure 4 shows a specific example of data stored in the estimated information storage unit according to the embodiment. [Figure 5] Figure 5 shows a series of processing steps related to the estimation of the catch volume according to the embodiment. [Figure 6] Figure 6 is a flowchart showing an example of the processing procedure of the estimation device according to the embodiment. [Figure 7] Figure 7 shows an example of a hardware configuration. [Modes for carrying out the invention]

[0009] The following describes in detail, with reference to the drawings, embodiments for implementing the estimation device, estimation method, and estimation program according to the present application. Note that these embodiments do not limit the estimation device, estimation method, and estimation program according to the present application. Furthermore, the same parts are denoted by the same reference numerals in each of the following embodiments, and redundant descriptions are omitted.

[0010] [Overall structure] First, the overall configuration of the system according to this embodiment will be described. Figure 1 is a diagram showing an example of the overall configuration of the estimation system according to this embodiment. The estimation system 10 shown in the example of Figure 1 has an estimation device 100 that inputs ocean climate information and past catch data into a generation model to estimate future catches, and a management server 200 that manages data such as ocean climate information and catch statistics.

[0011] Furthermore, regarding the system configuration shown in Figure 1, each device may communicate via any communication network, whether wired or wireless, such as the Internet, LAN (Local Area Network), or VPN (Virtual Private Network). Note that the configuration shown in Figure 1 is merely an example, and the specific configuration and the number of devices are not particularly limited.

[0012] The estimation device 100 is an information processing device that takes data on the state of the ocean and data on the catch volume of marine products in each region stored in the management server 200 (described later) as input into a generation model, and uses the information output from the generation model to estimate the future catch volume of each marine product in a specific region. It is implemented using a computer or the like. For example, when the estimation device 100 receives a designation of a region to be estimated from an external source, it inputs statistical information on ocean data and catch volume data into the generation model and obtains the estimated result of the catch volume of marine products in the target region several years in the future, which is output from the generation model.

[0013] The management server 200 is an information processing device that manages various statistical information used by the estimation device 100 to estimate catch volume, and is implemented by a server device or cloud system. For example, the management server 200 stores statistical information related to the ocean, such as sea surface temperature, ocean currents, and marine plankton, as well as statistical information on the catch volume of marine products in various regions throughout Japan, and statistical information on the market prices of harvested marine products.

[0014] [Overview of the processing of the estimation device 100] The estimation device 100 collects information on the state of the ocean and information on the catch volume of marine products. The estimation device 100 then inputs the collected information on the state of the ocean and the catch volume into a generative model and estimates the future catch volume of marine products in a predetermined area based on the output from the generative model.

[0015] For example, the estimation device 100 collects several years' worth of statistical information stored in the management server 200 regarding sea surface temperature, ocean currents, marine plankton distribution, and the amount of marine fish catches in various parts of Japan. The estimation device 100 then sets a prompt message in the generation model that specifies that the estimated amount of marine fish catches in the target region one year from now should be output using the collected information, and obtains the estimated amount of marine fish catches in the target region one year from now output by the generation model, thereby estimating the amount of marine fish catches one year from now.

[0016] As a result, the estimation device 100 can output estimated catch figures for several years in the future from a generative model based on ocean data and catch statistics for the target area received from an external source, thereby enabling accurate estimation of future changes in catch figures.

[0017] [Configuration of the estimation device 100] Hereinafter, an example of the functional configuration of the above-described estimation device 100 will be described. FIG. 2 is a diagram showing a configuration example of the estimation device according to the embodiment. As shown in FIG. 2, the estimation device 100 includes a communication unit 110, a control unit 120, and a storage unit 130.

[0018] The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. For example, the communication unit 110 controls communication regarding various information exchanged with the connected devices, and mediates the processing of each processing unit included in the control unit 120 described later.

[0019] The storage unit 130 is realized by, for example, a storage device such as a RAM (Random Access Memory) or a hard disk. The storage unit 130 stores data and programs necessary for various processes by the control unit 120. Note that the storage device may be realized by a storage system or the like installed outside the estimation device 100. As shown in FIG. 2, the storage unit 130 includes, for example, a marine information storage unit 131, a catch amount information storage unit 132, a price information storage unit 133, and an estimation information storage unit 134.

[0020] The marine information storage unit 131 stores information managed as statistical information regarding the ocean. FIG. 3 is a diagram showing a specific example of data stored in the marine information storage unit according to the embodiment. As shown in FIG. 3, the marine information storage unit 131 stores information such as "date", "sea surface water temperature information", "ocean current information", and "marine plankton information".

[0021] "Date" stores information on the date when statistical data regarding the ocean was measured. "Sea surface water temperature information" stores numerical values and the like of the measurement results of the sea surface water temperature. "Ocean current information" stores information such as the direction and distance of ocean currents. "Marine plankton information" stores information such as the observed number and types of marine plankton.

[0022] For example, the marine information storage unit 131 stores, for the ocean off the coast of Japan, an image showing each piece of information on a map together with the information on the observation date and time.

[0023] The catch volume information storage unit 132 stores statistical information on the catch volume of marine products in various parts of Japan. For example, the catch volume information storage unit 132 stores information on the catch volume of each type of marine product, which is made public as statistical information by each prefecture in Japan, on an annual basis.

[0024] The price information storage unit 133 stores information about the market price of harvested seafood. For example, the price information storage unit 133 stores price data (market price) for each type of seafood collected from the market, associated with date information.

[0025] The estimation information storage unit 134 stores the estimated future catch volume of marine products, which is estimated by the estimation unit 124 described later. Figure 4 shows a specific example of the data stored in the estimation information storage unit according to this embodiment. As shown in Figure 4, the estimation information storage unit 134 stores, for example, the estimated catch volume for several years in the future, such as 2025, 2026, etc., from the present (2024) onwards, for each type of marine product, such as tuna, sea bream, squid, etc.

[0026] The control unit 120 is implemented by a processor such as an integrated circuit (CPU), MPU, ASIC (Application Specific Integrated Circuit), or FPGA (Field Programmable Gate Array) executing various programs stored in the memory device inside the estimation device 100 using RAM or the like as the working area. For example, in the example shown in Figure 2, the control unit 120 includes a marine information collection unit 121, a catch amount information collection unit 122, a price information collection unit 123, an estimation unit 124, and a display unit 125.

[0027] The oceanographic information collection unit 121 collects information about the state of the ocean. For example, the oceanographic information collection unit 121 collects measurement data published by the Japan Meteorological Agency and other specialized organizations regarding sea surface temperature, ocean currents, and marine plankton. Here, the oceanographic information collection unit 121 collects the aforementioned measurement data at regular intervals, such as daily or monthly, and stores it in the oceanographic information storage unit 131, associating it with the date information.

[0028] Furthermore, the Oceanographic Information Collection Unit 121 is not particularly limited in the format of the data it collects. For example, it may be a text file listing measured values, or an image file showing the measured data reflected on a map of the seas around Japan. In addition, the Oceanographic Information Collection Unit 121 may directly collect the aforementioned measured data from websites managed by the Japan Meteorological Agency or other specialized organizations, or it may indirectly collect it from data stored on the management server 200.

[0029] The Catch Volume Information Collection Unit 122 collects information on the catch volume of marine products. For example, the Catch Volume Information Collection Unit 122 collects information on the catch volume of each marine product, which is made public by the Ministry of Agriculture, Forestry and Fisheries and each prefecture, for marine products harvested at fishing ports throughout Japan. Here, the Catch Volume Information Collection Unit 122 collects, for example, statistical values ​​of catch volumes that are made public on an annual basis, and stores them in the Catch Volume Information Storage Unit 132, associating them with the information for each year.

[0030] The fish catch information collection unit 122 may, for example, directly collect the aforementioned statistical values ​​from websites managed by the Ministry of Agriculture, Forestry and Fisheries or each prefecture, or it may collect them indirectly from data stored on the management server 200.

[0031] The price information collection unit 123 collects information on the prices of marine products. For example, the price information collection unit 123 collects information on the prices and market prices of marine products, such as listed landing prices and wholesale prices for each type of marine product, as published in fisheries statistics information released by the Fisheries Agency, etc. Here, the price information collection unit 123 collects price information published on an annual basis, for example, and stores it in the price information storage unit 133 in association with the year's information.

[0032] Furthermore, the price information collected by the price information collection unit 123 is not limited to the data described above; for example, it may also collect information such as the price per seafood in a market in a designated area. In addition, the price information collection unit 123 may directly collect the price information described above from a website managed by, for example, the Fisheries Agency, or it may indirectly collect it from data stored in the management server 200.

[0033] The estimation unit 124 inputs information on the state of the ocean collected by the ocean information collection unit 121 and information on the catch collected by the catch information collection unit 122 into a generation model, and estimates the future catch of marine products in a predetermined area based on the output from the generation model.

[0034] For example, the estimation unit 124 sets a prompt message in the generation model that includes the phrase, "Refer to the data shown below and tell me the catch volume for each type of fish that will be caught in the XX region △ years from now (for example, 1 year from now)," along with image data representing the aforementioned ocean data and text data showing the aforementioned catch statistics. The estimation unit 124 then obtains the estimated results of the seafood catch volume output and stores them in the estimation information storage unit 134 for each estimated year.

[0035] Here, the generative model is a model that generates a response in natural language in response to a command (prompt) set in natural language. Note that the prompt set in the generative model may include images in addition to natural language, and the response output by the generative model may include images in addition to text, or images may be used instead of text.

[0036] Furthermore, the estimation unit 124 inputs the price information collected by the price information collection unit 123 into a generation model and estimates the future price of marine products in a predetermined region based on the output from the generation model.

[0037] For example, the estimation unit 124 sets a prompt message in the generation model that includes the phrase, "Refer to the data shown below and tell me the price trend of Thai fish in the XX region up to △ years from now (for example, 5 years from now)," along with image data representing the aforementioned ocean data, text data showing statistical values ​​for Thai fish catches, and text data showing prices such as the wholesale price of Thai fish and the market price per fish. The estimation unit 124 then retrieves the outputted estimation results for the price of Thai fish up to 5 years from now and stores them in the estimation information storage unit 134 for each estimated year.

[0038] For example, the region targeted for estimation by the estimation unit 124 may be a narrow area such as a specific prefecture or fishing port that has been set externally in advance, or it may be a broad area such as the Pacific side or the Sea of ​​Japan side. Also, for example, the range of data described in the prompt statement that the estimation unit 124 sets in the generation model may be changed according to the region to be estimated.

[0039] The display unit 125 displays the trend of the estimated catch volume of marine products estimated by the estimation unit 124 in predetermined period units. For example, the display unit 125 displays the trend of the estimated catch volume by displaying a graph plotting the catch volume values ​​using the estimated catch volume of marine products up to several years in advance that is stored in the estimation information storage unit 134.

[0040] The display unit 125 displays the types of marine products whose future catch volume, estimated by the estimation unit 124, is above a threshold. For example, the display unit 125 displays the types of marine products for which the estimated catch volume exceeds a pre-set threshold (a catch volume that is expected to be profitable) from among the estimated catch volume results for each marine product stored in the estimation information storage unit 134, as marine products that are expected to be profitable in the future.

[0041] Furthermore, the display unit 125 uses the estimated future catch volume of marine products estimated by the estimation unit 124 to display the types of marine products for which the difference between the estimated catch volume and past catch volumes is greater than or equal to a threshold. For example, the display unit 125 calculates the difference between each of the estimated catch volume results for each marine product stored in the estimation information storage unit 134 and the latest catch volume statistics, and displays the types of marine products for which the difference is greater than or equal to a certain value as marine products with large fluctuations in future catch volume.

[0042] (Specific example) Next, a series of processes performed by the estimation device 100 according to the embodiment will be explained using Figure 5. Figure 5 is a diagram showing the flow of a series of processes related to the estimation of the catch amount according to the embodiment.

[0043] First, the estimation device 100 collects statistical information necessary for estimating the catch from a management server 200 that manages data such as ocean climate information, including sea surface temperature and ocean current information, as well as plankton information, catch information, and marine product price information, which are published by the Japan Meteorological Agency, the Ministry of Agriculture, Forestry and Fisheries, the Fisheries Agency, and other specialized organizations (Figure 5(1)).

[0044] The estimation device 100 then generates a prompt message that describes the collected statistical information and prompts the user to estimate the catch volume several years in the future. After setting the generated prompt message in the generation model, the device obtains the outputted catch volume estimation result (Figure 5(2)).

[0045] The estimation device 100 then uses the estimated catch volume to create graphs and tables showing the trends in catch volume for each type of marine product several years in the future, as well as the trends in prices for each type of marine product, and displays them on the output screen (Figure 5(3)).

[0046] Through the series of processes described above, the estimation device 100 can collect past oceanographic information, catch data, and price data, input them into a generative model, and then obtain the estimated catch data output by the generative model. This allows it to appropriately estimate future changes in catch data.

[0047] (flowchart) Next, an example of the overall processing by the estimation device 100 will be described with reference to Figure 6. Figure 6 is a flowchart showing an example of the processing procedure of the estimation device according to the embodiment. Note that each step in the flowchart shown in Figure 6 can be executed in a different order, and additional or omitted processes may be included.

[0048] First, the estimation device 100 determines whether or not it has received a designation of the area to be estimated (S101). If it has received a designation of the area to be estimated (S101; Yes), the estimation device 100 collects information on the ocean climate, etc. (S102). On the other hand, if it has not received a designation of the area to be estimated (S101; No), the estimation device 100 waits until it receives a designation of the area to be estimated.

[0049] After processing in S102, the estimation device 100 collects information on the catch volume of marine products (S103). The estimation device 100 then sets prompt statements containing information on the ocean and information on the catch volume in the generation model (S104). The estimation device 100 then uses the information output by the generation model to estimate the future catch volume of marine products in the target area (S105). The estimation device 100 then displays the trend of the estimated catch volume (S106) and terminates the process.

[0050] (effect) The estimation device 100 according to this embodiment includes a marine information collection unit 121, a fish catch information collection unit 122, and an estimation unit 124. The marine information collection unit 121 collects information on the state of the ocean. The fish catch information collection unit 122 collects information on the catch volume of marine products. The estimation unit 124 inputs the information on the state of the ocean collected by the marine information collection unit 121 and the information on the catch volume collected by the fish catch information collection unit 122 into a generation model, and estimates the future catch volume of marine products in a predetermined area based on the output from the generation model.

[0051] As a result, the estimation device 100 can output estimated catch figures for several years in the future from a generative model based on ocean data and catch statistics for the target area received from an external source, thereby enabling accurate estimation of future changes in catch figures.

[0052] Furthermore, the estimation device 100 has a display unit 125. The display unit 125 displays the trend of the estimated catch volume of marine products estimated by the estimation unit 124 in predetermined period units. As a result, the estimation device 100 can display the trend of the estimated catch volume up to several years into the future and indicate the types of marine products whose catch volume is expected to increase or decrease in the future.

[0053] Furthermore, the display unit 125 displays the types of marine products whose future catch volume, estimated by the estimation unit 124, is above a threshold. This allows the estimation device 100 to display the types of marine products for which a profitable catch volume is estimated, based on catch volume estimates for several years into the future, thereby providing information to fisheries stakeholders and others to support future business decisions.

[0054] Furthermore, the display unit 125 uses the estimated future catch volume of marine products estimated by the estimation unit 124 to display the types of marine products for which the difference between the estimated catch volume and past catch volumes exceeds a threshold. In this way, the estimation device 100 can display the types of marine products that show a large fluctuation from the current catch volume among the estimated catch volume results for several years into the future, and provide information to support fishing stakeholders in deciding future business policies.

[0055] Furthermore, the estimation device 100 includes a price information collection unit 123. The price information collection unit 123 collects information regarding the prices of marine products. In this case, the estimation unit 124 further inputs the price information collected by the price information collection unit 123 into a generation model and estimates the future prices of marine products in a predetermined region based on the output from the generation model.

[0056] As a result, the estimation device 100 can use data from the outside, including ocean data, catch statistics, and seafood price statistics, to generate a generative model that outputs estimated prices for seafood several years in the future. This allows for accurate estimation of future changes in seafood prices.

[0057] Furthermore, the oceanographic information collection unit 121 collects information on sea surface temperature, ocean currents, and marine plankton, or one or more of these information, in predetermined period units. This allows the estimation device 100 to appropriately estimate fish catches based on predictions of ocean conditions several years in the future, using statistical data on the state of the ocean near Japan.

[0058] [System configuration, etc.] Of the processes described in the above embodiments, some of those described as being performed automatically can be performed manually. Alternatively, all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and various data and parameters shown in the above document and drawings can be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0059] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions. Moreover, each processing function performed by each device can be implemented, in whole or in any part, by a CPU and the program that is analyzed and executed by that CPU, or by hardware using wired logic.

[0060] For example, some or all of the memory unit 130 shown in Figure 2 may be stored in a storage server or the like, rather than being held by the estimation device 100. In this case, the estimation device 100 obtains various information by accessing the storage server.

[0061] [Hardware configuration] Figure 7 shows an example of a hardware configuration. The estimation device 100 according to the above embodiment is implemented by a computer 1000 having a configuration such as that shown in Figure 7.

[0062] Computer 1000 has, for example, memory 1010 and CPU 1020. Computer 1000 also has a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0063] Memory 1010 includes ROM (Read Only Memory) 1011 and RAM 1012. ROM 1011 stores, for example, a boot program such as BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to the hard disk drive 1090. The disk drive interface 1040 is connected to the disk drive 1041. For example, a removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1041. The serial port interface 1050 is connected to, for example, a mouse 1110 and a keyboard 1120. The video adapter 1060 is connected to, for example, a display 1130.

[0064] The hard disk drive 1090 stores, for example, an OS (Operating System) 1091, an application program 1092, a program module 1093, and program data 1094. That is, the program that defines each process of the estimation device 100 is implemented as a program module 1093 in which code executable by the computer 1000 is written. The program module 1093 is stored, for example, in the hard disk drive 1090. For example, a program module 1093 for performing the same processes as the functional configuration in the estimation device 100 is stored in the hard disk drive 1090. Note that the hard disk drive 1090 may be replaced by an SSD (Solid State Drive).

[0065] Furthermore, the configuration data used in the processing of the above-described embodiment is stored as program data 1094 in, for example, memory 1010 or hard disk drive 1090. The CPU 1020 then reads the program module 1093 and program data 1094 stored in memory 1010 or hard disk drive 1090 into RAM 1012 as needed and executes them.

[0066] Furthermore, the program module 1093 and program data 1094 are not limited to being stored on the hard disk drive 1090; for example, they may be stored on a removable storage medium and read by the CPU 1020 via a disk drive 1041 or the like. Alternatively, the program module 1093 and program data 1094 may be stored on another computer connected via a network (LAN, WAN, etc.). The program module 1093 and program data 1094 may then be read by the CPU 1020 from the other computer via a network interface 1070. [Explanation of Symbols]

[0067] 100 Estimator 110 Communications Department 120 Control Unit 121 Oceanographic Information Gathering Unit 122 Fish Catch Information Collection Department 123 Price Information Collection Department 124 Estimation Department 125 Display section 130 Storage section 131 Marine Information Storage Department 132 Catch information storage unit 133 Price information storage unit 134 Estimated information storage unit 200 Management Servers

Claims

1. The Oceanographic Information Collection Department collects information on the state of the ocean, The Catch Information Collection Department collects information on the amount of marine products caught, An estimation unit inputs information on the state of the ocean collected by the ocean information collection unit and information on the catch collected by the catch information collection unit into a generation model, and estimates the future catch of the marine products in a predetermined region based on the output from the generation model. An estimation device characterized by having the following features.

2. The estimation device according to claim 1, further comprising a display unit that displays the trend of the estimated catch amount of the marine product estimated by the estimation unit in units of a predetermined period.

3. The estimation device according to claim 2, characterized in that the display unit displays the types of marine products whose future catch volume estimated by the estimation unit is above a threshold.

4. The estimation device according to claim 2, characterized in that the display unit displays the types of marine products for which the difference between the estimated catch amount and past catch amounts is greater than or equal to a threshold, using the estimated future catch amount of the marine products estimated by the estimation unit.

5. The system further includes a price information collection unit that collects information on the prices of the aforementioned marine products. The estimation unit further inputs the price information collected by the price information collection unit into a generation model and estimates the future price of the marine product in the predetermined region based on the output from the generation model. The estimation device according to feature 1.

6. The estimation device according to claim 1, characterized in that the oceanographic information collection unit collects information on sea surface temperature and one or more of the following information: information on ocean currents and information on marine plankton, in units of a predetermined period.

7. An estimation method performed by an estimation device, The process of collecting marine information is to collect information about the state of the ocean, A process for collecting information on the amount of marine products caught, An estimation step is performed by inputting information on the state of the ocean collected by the ocean information collection step and information on the catch collected by the catch information collection step into a generative model, and estimating the future catch of the marine products in a predetermined region based on the output from the generative model. An estimation method characterized by including the following.

8. Procedures for collecting oceanographic information to gather information on the state of the ocean, Procedures for collecting information on the amount of marine products caught, An estimation procedure which involves inputting information on the state of the ocean collected by the aforementioned ocean information collection procedure and information on the catch collected by the aforementioned catch information collection procedure into a generative model, and estimating the future catch of the marine product in a predetermined region based on the output from the generative model, An estimation program characterized by having a computer execute it.

Images