Data determination system and data determination method

Abstract

This data determination system comprises: an acquisition unit that acquires observation data of an observation point and other observation data of another observation point provided in the periphery of the observation point; a calculation unit that calculates representative data of the another observation point on the basis of the other observation data; and an assessing unit that assesses whether or not the observation data is included in the allowable range of the representative data.

Description

Data judgment system and data judgment method

[0001] The present disclosure relates to a data determination system and a data determination method.

[0002] To help understand the marine environment's impact on climate change, Argo floats are being deployed around the world, with one in every 300 km square, for a total of approximately 3,000 units (Non-Patent Document 1). Argo floats repeatedly float up and down, observing data on the marine environment using onboard sensors.

[0003] The Argo float observation data is made public within 24 hours as real-time data after simple corrections by the Japan Meteorological Agency, and is made public within six months to a year as delayed data after more rigorous corrections by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC). In this way, the Argo float observation data is made public with a certain level of quality control guaranteed (Non-Patent Document 2).

[0004] "Argo Mission and Objectives," JAMSTEC, [Retrieved July 26, 2024], Internet <URL: https: / / www.jamstec.go.jp / argo / j / about / > Kanako Sato, "Super Lesson: How to Use Argo Float Data - Data Format and Quality Control," JAMSTEC, [Retrieved July 26, 2024], Internet <URL: https: / / www2.jpgu.org / a / wp-content / uploads / sites / 15 / 2022 / 06 / JpGU2022_SuperLesson_Argo_KS_short.pdf>

[0005] In addition, observation equipment such as wave gliders and spotter buoys are sometimes used to monitor the marine environment. These observation equipment are smaller and cheaper than Argo floats, so many of them can be deployed in a relatively small area. These observation equipment allow for monitoring the marine environment at a finer level of detail.

[0006] However, the sensors installed in these observation instruments were inexpensive, resulting in low accuracy of the observation data, often outside the acceptable range. Furthermore, correcting the observation data, as with Argo floats, to ensure accuracy could negate the cost advantage of using inexpensive observation instruments.

[0007] The present disclosure has been made in consideration of such circumstances, and aims to ensure the reliability of observation data from observation equipment while keeping costs down.

[0008] One aspect of the present disclosure is a data judgment system comprising an acquisition unit that acquires observation data of an observation point and other observation data of other observation points located around the observation point, a calculation unit that calculates representative data of the other observation points based on the other observation data, and a judgment unit that determines whether the observation data is within an acceptable range of the representative data.

[0009] One aspect of the present disclosure is a data determination method that acquires observation data from an observation point and other observation data from other observation points located around the observation point, calculates representative data for the other observation points based on the other observation data, and determines whether the observation data is within an acceptable range for the representative data.

[0010] According to the present disclosure, it is possible to ensure the reliability of observation data from observation equipment while keeping costs down.

[0011] Fig. 1 is a functional block diagram of a data judgment system according to an embodiment. Fig. 2 is a diagram showing an observation point where an observation device is installed and other observation points. Fig. 3 is a flowchart showing an example of the operation of the data judgment system. Fig. 4 is a diagram showing an example of the hardware configuration.

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0013] (1) Configuration of the Data Determination System The configuration of a data determination system 10 of this embodiment will be described with reference to Fig. 1. As shown in Fig. 1, the data determination system 10 includes a collection unit 100 that collects various data such as observation data, a storage unit 200 that stores the data, a processing unit 300 that determines the accuracy of the observation data, and a user interface 400.

[0014] The collection unit 100 includes an equipment data registration unit 110, an observation data acquisition unit 120, and an external data acquisition unit 130.

[0015] The device data registration unit 110 registers information about the observation device V that acquires observation data. The information about the observation device V includes, for example, the identification number of the observation device V, the location of the observation device V, the specifications of the sensors installed in the observation device V (detection range, accuracy, etc.), and the usability status of the observation device V ("usable" or "unusable"). The information about the observation device V may be registered in advance via the input unit 410 of the user interface 400, or may be registered via the observation data acquisition unit 120 simultaneously with the acquisition of observation data, which will be described later. The device data registration unit 110 stores the information about the observation device V in the device data storage unit 210 of the storage unit 200.

[0016] The observation device V is, for example, a wave glider or a spotter buoy. A wave glider is a plate-shaped floating body equipped with various sensors for acquiring observation data, a GPS, solar panels, communication equipment, etc. A wave glider can propel itself across the ocean by converting the up-and-down motion of waves into forward-and-back motion using a glider suspended in the sea. A spotter buoy is a roughly spherical floating body equipped with various sensors for acquiring observation data, a GPS, solar panels, communication equipment, etc.

[0017] It is assumed that a plurality of observation devices V are installed on the sea. The locations where the observation devices V are installed are referred to as observation points m. In this embodiment, the observation devices V and the observation points m can be read as interchangeable terms.

[0018] The observation data may be, for example, wave height, seawater temperature, salinity, and sea surface pressure, but is not limited to these. The observation data may be any data related to the marine environment or weather, such as wind direction, wind speed, temperature, humidity, atmospheric pressure, precipitation, solar radiation, and ocean currents. The observation data also includes the observation time. The observation data may also include information related to the observation equipment V described above.

[0019] The observation data acquisition unit 120 acquires observation data from the observation device V. The acquisition of observation data by the observation data acquisition unit 120 is assumed to be performed periodically. The observation data acquisition unit 120 stores the observation data in the observation data storage unit 220 of the storage unit 200. The observation data acquisition unit 120 may acquire information about the observation device V from the observation device V and register it in the device data registration unit 110.

[0020] Furthermore, when an observation device V becomes unable to acquire observation data due to a sensor failure or the like, the observation data acquisition unit 120 can detect the observation device V. For this detection, for example, the specifications (detection range, accuracy, etc.) of the sensor described above may be used. That is, the observation data acquisition unit 120 can detect an observation device V that becomes unable to acquire observation data based on the sensor specifications (detection range, accuracy, etc.).

[0021] Furthermore, the observation data acquisition unit 120 may notify the user of the observation device V that can no longer acquire observation data via the output unit 420 of the user interface 400. The user, upon receiving this, may update the information about the observation device V registered in the device data registration unit 110 via the input unit 410 of the user interface 400. That is, the user may update the usability status of the observation device V described above to "unusable." Furthermore, when the observation device V that can no longer acquire observation data is collected and repaired or replaced, the user may update the usability status of the observation device V described above to "usable" again. The device data registration unit 110 stores the updated information about the observation device V in the device data storage unit 210.

[0022] The external data acquisition unit 130 acquires observation data from an external database DB. The acquisition of observation data by the external data acquisition unit 130 is assumed to be performed periodically. The observation data in the external database DB is area data including observation data at multiple observation points. A layout grid G ​​indicating the observation points is attached to the area data. In other words, the observation points of the observation data correspond to the intersections of the layout grid G.

[0023] The observation data in the external database DB may be referred to as "public data" or "other observation data" to distinguish it from the observation data of the observation equipment V. Similarly, the observation points of the other observation data may be referred to as "other observation points."

[0024] The external data acquisition unit 130 performs processing to adapt the data format of the other observation data to the data format of the observation data of the observation device V. The external data acquisition unit 130 stores the other observation data with the adapted data format in the external data storage unit 230 of the storage unit 200.

[0025] The external database DB is a database that stores observation data that is publicly available from the Japan Meteorological Agency, JAMSTEC, the Japan Aerospace Exploration Agency (JAXA), etc. In other words, the external database DB is a database that is publicly available from the Japan Meteorological Agency, JAMSTEC, JAXA, etc.

[0026] The observation data in the external database DB may be high-precision data obtained by correcting Argo float observation data by the Japan Meteorological Agency or JAMSTEC, or may be high-precision data acquired by JAXA's artificial satellite "Himawari." Furthermore, the observation data stored in the external database DB is not limited to data acquired by Argo floats or artificial satellites, but may also be data acquired by, for example, Doppler radar, radiosondes, or Triton buoys. In any case, the observation data stored in the external database DB is higher-precision data than the observation data acquired by the observation equipment V.

[0027] The storage unit 200 includes an equipment data storage unit 210 , an observation data storage unit 220 , an external data storage unit 230 , a setting data storage unit 240 , and a processing data storage unit 250 .

[0028] The equipment data storage unit 210 stores information about the observation equipment V. The observation data storage unit 220 stores observation data acquired from the observation equipment V. The external data storage unit 230 stores other observation data whose data format matches the observation data.

[0029] The setting data storage unit 240 stores initial settings such as criteria for the processing unit 300 to determine the accuracy of observation data. Specific initial settings will be described later. The processing data storage unit 250 stores processing data such as the determination results of the processing unit 300. Specific processing data will be described later.

[0030] The processing unit 300 includes a setting unit 310 , an extraction unit 320 , a calculation unit 330 , a determination unit 340 , and a decision unit 350 .

[0031] The setting unit 310 performs various initial settings. These initial settings include the tolerance range for ensuring the accuracy of the observation data (e.g., the coefficient n of the standard deviation σ in a normal distribution), the range of public data used for comparison with the observation data (e.g., the radius L (km) centered on the observation device V), the number of consecutive deviations from the tolerance range (e.g., the number of consecutive alerts s), the number of consecutive alerts w that have occurred within the same number of consecutive alerts s, the calculation method for the representative data calculated based on the public data, the comparison method for the observation data and the representative data, and the evaluation method (e.g., evaluation criteria) for determining the accuracy of the observation data. These initial settings may be predetermined initial values ​​or may be set via the user interface 400. The setting unit 310 stores these initial settings in the setting data storage unit 240.

[0032] The tolerance range that ensures the accuracy of observation data will be explained in more detail below. The tolerance range is defined, for example, by the following formula:

[0033]

[0034] Here, the standard deviation σ is set to the numerical value of the allowable error described in the data sheet of the sensor mounted on the observation device V. This is because the measurement error of the sensor can be considered as the standard deviation. The coefficient n of the standard deviation σ may also be set for each observation device V. Furthermore, observation_data is a symbol indicating the center of the allowable range. The value of the representative data described later is set to observation_data.

[0035] The extraction unit 320 references the device data storage unit 210 and the observation data storage unit 220, and extracts (selects) the observation device V (observation point m) from which the observation data should be acquired in order to determine the accuracy of the observation data. The extraction unit 320 stores the extracted observation device V in the processing data storage unit 250 as the extraction result.

[0036] The extraction of observation devices V may be performed based on wave height, which is one of the observation data. For example, the extraction unit 320 may extract observation devices V that have acquired observation data with a wave height of 0.1 m or less (or 0.5 m or less). In this case, if multiple observation devices V are extracted, the extraction unit 320 may extract the observation device V that has acquired observation data that is the average or median value of the observation data of the multiple observation devices V.

[0037] The extraction of the observation device V may be achieved by image processing. For example, the extraction unit 320 may perform image processing on image data of the Japan Meteorological Agency's "Wave Status and Forecast Map" to extract areas with wave heights of 0.1 m or less (or 0.5 m or less), and then extract the observation device V included in that area. Such two-stage extraction may be performed, for example, by superimposing image data in which the position of the observation device V is mapped onto image data in which areas with wave heights of 0.1 m or less (or 0.5 m or less) are mapped using image processing. In other words, the observation device V included in the area with wave heights of 0.1 m or less (or 0.5 m or less) may be extracted from the superimposed image. Note that the data to be subjected to image processing is not limited to the Japan Meteorological Agency's "Wave Status and Forecast Map," but may also be data provided by a web service such as Windy (URL: https: / / www.windy.com / ).

[0038] The extraction of the observation devices V may be performed by a user instead of the extraction unit 320. That is, the observation devices V may be extracted via the user interface 400. For example, the user may check the Japan Meteorological Agency's "Actual Wave Conditions and Forecast Map" or a web service such as Windy to extract observation devices V installed in areas with wave heights of 0.1 m or less (or 0.5 m or less). The positions of the observation devices V are acquired by the GPS described above.

[0039] The calculation unit 330 references the external data storage unit 230 and the setting data storage unit 240 to extract other observation data for comparison with the observation data. Furthermore, the calculation unit 330 calculates representative data from the other observation data. The calculation unit 330 stores the calculated representative data or its running median in the processed data storage unit 250 as the calculation result.

[0040] The extraction of other observation data and the calculation of representative data will be described with reference to Figure 2. As shown in Figure 2, the calculation unit 330 extracts other observation data in an area of ​​radius L (km) centered on observation point m where observation equipment V is installed, based on initial settings. Specifically, the calculation unit 330 extracts other observation points (intersections of the above-mentioned placement grid G) included in the area of ​​radius L (km) centered on observation point m, and extracts the observation data of those other observation points.

[0041] For convenience of explanation, the other observation points extracted by the calculation unit 330 are referred to as other observation points p i , or simply another observation point p i In addition, in Fig. 2, other observation points p i are six points from p1 to p6, but are not limited to these. Here, the coordinates of observation point m are (x m , y m ) and other observation points p i The coordinates of (x pi , y pi ) then, observation point m and other observation point p i Distance r i is expressed by the following formula:

[0042]

[0043] The calculation unit 330 calculates the other observation point p i Representative data is calculated from the observed data (i.e., other observed data). The representative data is expressed by, for example, the following formula:

[0044]

[0045] The representative data may also be expressed by the following formula:

[0046]

[0047] Note that v_public_data in these formulas i is the other observation point p i This refers to other observational data corresponding to

[0048] Furthermore, the calculation unit 330 calculates the time t i At time t, representative data may be calculated and the moving median of the representative data may be calculated. i is not the calculation time of the representative data, but the observation time of other observation data that is the basis of the representative data. For example, the calculation unit 330 calculates representative data 1 from multiple other observation data at observation time t1, calculates representative data 2 from multiple other observation data at observation time t2, and calculates representative data 3 from multiple other observation data at observation time t n The calculation unit 330 calculates the moving median of the representative data 1 to n from the plurality of other observation data. i are, for example, multiple times included within one hour before and after the observation time of the observation data of observation point m.

[0049] The representative data may also be calculated using an optimal interpolation method from other observation data extracted by the calculation unit 330. That is, the representative data may be an estimated value of the observation data at observation point m, calculated based on other observation data extracted by the calculation unit 330. Calculation of the estimated value using the optimal interpolation method may be realized, for example, by MATLAB.

[0050] The determination unit 340 refers to the observation data storage unit 220, the setting data storage unit 240, and the processing data storage unit 250 to determine the accuracy of the observation data of the observation device V. Specifically, the determination unit 340 determines whether the observation data of observation point m falls within the above-mentioned allowable range centered on the representative data calculated by the calculation unit 330. If the observation data falls within the allowable range, the determination unit 340 determines that the observation data is a normal value, and if the observation data is not within the allowable range, the determination unit 340 determines that the observation data is an abnormal value. The determination unit 340 stores the determination result in the processing data storage unit 250.

[0051] The determination unit 340 may use the running median of the representative data described above instead of the representative data as the center of the acceptable range. Alternatively, the determination unit 340 may use the interquartile range of the representative data calculated by the calculation unit 330 as the acceptable range. That is, the determination unit 340 may determine the accuracy of the observation data using the range from the first quartile to the third quartile of the representative data calculated by the calculation unit 330 as the acceptable range.

[0052] The decision unit 350 decides whether or not to use the observation data by referring to the setting data storage unit 240 and the processing data storage unit 250. The decision unit 350 stores the decision result, whether or not the observation data can be used, in the output unit 420.

[0053] For example, if the observation data is judged to be an abnormal value s times in a row, the decision unit 350 decides not to use the observation data or not to use the observation equipment V that acquired the observation data.

[0054] The decision unit 350 may consider s consecutive abnormal value determinations of observation data as one alert, and if this alert occurs w consecutive times, may decide not to use the observation data or not to use the observation equipment V that acquired the observation data.

[0055] The user interface 400 includes an input section 410 and an output section 420 .

[0056] The input unit 410 is, for example, a keyboard through which the user can input various information. The input unit 410 instructs the processing unit 300 to determine the accuracy of the observation data. This instruction includes the general area for which the user wishes to determine the accuracy of the observation data and the observation date and time. In other words, the user can instruct the processing unit 300 via the input unit 410 to determine the accuracy of the observation data for a desired area and date and time. Furthermore, as described above, the user can register (or update) information about the observation device V, perform initial settings, and extract the observation device V via the input unit 410.

[0057] The output unit 420 is, for example, a display that displays the determination result of the determination unit 350 .

[0058] (2) Operation of the Data Judgment System The operation of the data judgment system 10 of this embodiment will be described with reference to Figure 3. As a premise, the observation data acquisition unit 120 and the external data acquisition unit 130 periodically acquire observation data from multiple observation devices V (observation points m) and other observation data from an external database DB (step S01). The setting unit 310 also performs various initial settings (step S02). Note that the order of steps S01 and S02 may be reversed.

[0059] First, upon receiving a request from a user to determine the accuracy of observation data, the extraction unit 320 extracts one observation device V that is suitable for acquiring observation data (step S03). The extraction of the observation device V may be performed based on the wave height at the observation point m where the observation device V is installed. The wave height may be calculated based on the observation data of the observation device V, or may be calculated by the image processing described above.

[0060] Next, calculation unit 330 extracts observation data from other observation points (i.e., other observation data) based on the initial settings, and calculates representative data from the extracted other observation data (step S04). Furthermore, determination unit 340 compares the extracted observation data from observation point m with the representative data based on the initial settings, and determines whether the extracted observation data from observation point m is included in an allowable range centered on the representative data (step S05).

[0061] Finally, the decision unit 350 decides whether or not to use the observation data from the observation point m (step S06) based on the determination result of the judgment unit 340. If it is decided to use the observation data from the observation point m, the observation data will be used, for example, for marine environment monitoring.

[0062] The determination of whether or not the observation data can be used may use the results of multiple determinations. That is, the determination unit 350 may determine not to use the observation data if the observation data deviates from the allowable range s consecutive times. The determination unit 350 may also determine not to use the observation data if the deviation from the allowable range s consecutive times occurs w consecutive times. The determination of whether or not the observation data can be used is output to the output unit 420 of the user interface 400.

[0063] The user may update information about an observation device V for which it has been decided that the observation data will not be used, in the same way as for an observation device V for which it is no longer possible to obtain observation data.

[0064] (3) Effects As described above, the data judgment system 10 of this embodiment compares the observation data of the observation point m with the observation data of other observation points p around the observation point m. i and an acquisition unit (observation data acquisition unit 120 and external data acquisition unit 130) that acquires other observation data of other observation points p i and a determination unit 340 that determines whether the observation data is within an acceptable range for the representative data. This allows the data determination system 10 to detect a decrease in the accuracy of the observation data at observation point m due to a failure or deterioration of a sensor mounted on the observation equipment V. Furthermore, the data determination system 10 can reduce costs by determining the accuracy of the observation data using publicly available external data.

[0065] The data determination system 10 of this embodiment may include a determination unit 350 that determines whether or not to use the observation data based on the determination result of the determination unit 340. This allows the data determination system 10 to determine not to use the observation data with reduced accuracy as data to be used for marine environment monitoring. Furthermore, upon receiving this determination, the user can reduce unnecessary costs by blocking the communication function of the observation device V corresponding to the observation data that has been determined not to be used. Furthermore, the user can collect such observation device V and repair or replace it.

[0066] The data judgment system 10 of this embodiment may include an extraction unit 320 that extracts the observation device V that acquires observation data (i.e., the observation point m from which observation data should be acquired) based on the wave height at the observation point m, and the extraction unit 320 may calculate the wave height based on image data of the area including the observation point m. As a result, even if the observation device V is not equipped with a sensor that detects wave height, the data judgment system 10 can calculate the wave height at the observation point m where the observation device V is installed, and can extract observation data when waves are calm, such as when the wave height is 0.1 m or less (or 0.5 m or less).

[0067] The data judgment system 10 described above can be implemented, for example, by a general-purpose computer system such as that shown in Fig. 4. The illustrated computer system includes a CPU (Central Processing Unit, processor) 901, a memory 902, a storage 903 (HDD: Hard Disk Drive, SSD: Solid State Drive), a communication device 904, an input device 905, and an output device 906. The memory 902 and the storage 903 are storage devices. In this computer system, the CPU 901 executes a predetermined program loaded onto the memory 902, thereby realizing each function of the data judgment system 10.

[0068] The data determination system 10 may be implemented on a single computer or multiple computers. The data determination system 10 may also be a virtual machine implemented on a computer. The program for the data determination system 10 may be stored on a computer-readable recording medium such as a HDD, SSD, USB (Universal Serial Bus) memory, CD (Compact Disc), or DVD (Digital Versatile Disc), or may be distributed via a network. The computer-readable recording medium may be, for example, a non-transitory recording medium.

[0069] The present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the present disclosure.

[0070] REFERENCE SIGNS LIST 10 Data judgment system 100 Collection unit 110 Equipment data registration unit 120 Observation data acquisition unit 130 External data acquisition unit 200 Storage unit 210 Equipment data storage unit 220 Observation data storage unit 230 External data storage unit 240 Setting data storage unit 250 Processing data storage unit 300 Processing unit 310 Setting unit 320 Extraction unit 330 Calculation unit 340 Determination unit 350 Decision unit 400 User interface 410 Input unit 420 Output unit V Observation equipment DB External database

Claims

1. A data judgment system comprising: an acquisition unit that acquires observation data of an observation point and other observation data of other observation points located around the observation point; a calculation unit that calculates representative data of the other observation points based on the other observation data; and a judgment unit that determines whether the observation data is within an acceptable range of the representative data.

2. The data determination system according to claim 1, further comprising a determination unit that determines whether or not to use the observation data based on the determination result of the determination unit.

3. The data judgment system according to claim 1, further comprising an extraction unit that extracts the observation points from which the observation data should be acquired based on the wave heights at the observation points, and the extraction unit calculates the wave heights based on image data of an area including the observation points.

4. A data determination method comprising: acquiring observation data from an observation point and other observation data from other observation points located around the observation point; calculating representative data for the other observation points based on the other observation data; and determining whether the observation data is within an acceptable range for the representative data.

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