Information processing method, program, and information processing apparatus

Abstract

The present invention provides an information processing method, etc., that can suitably estimate solar radiation. [Solution] The information processing method acquires the amount of sunlight at an observation point and observation time information indicating the time of observation of the sunlight. Based on the acquired sunlight and observation time information, a computer performs a process to estimate the amount of solar radiation at the observation point. Preferably, the amount of solar radiation is estimated based on the acquired sunlight and observation time information using a regression equation that shows the relationship between the amount of solar radiation, the ratio of sunlight, and the observation time.

Description

Technical Field

[0001] The present invention relates to an information processing method, a program, and an information processing apparatus.

Background Art

[0002] There is a technique for estimating solar radiation. For example, in Patent Document 1, based on the observed values of meteorological data, the observed values of solar radiation, and the clear-sky solar radiation, a relational expression representing the relationship between each value is calculated by using the partial least squares method or a statistical index (AIC), and a solar radiation calculation device that calculates a predicted value of solar radiation based on the forecast value of meteorological data, the clear-sky solar radiation, and the relational expression is disclosed.

Prior Art Documents

Patent Documents

[0003] <00"00018>

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In one aspect, an object is to provide an information processing method or the like that can preferably estimate solar radiation.

Means for Solving the Problems

[0005] An information processing method includes: a computer obtaining the sunshine amount at an observation point and observation time information indicating the observation time point of the sunshine amount, and based on the obtained sunshine amount and observation time information, executing a process of estimating the solar radiation amount at the observation point. <"

Effects of the Invention

[0006] In one aspect, solar radiation can be preferably estimated.

Brief Description of the Drawings

[0007] [Figure 1]This is an explanatory diagram showing an example configuration of a WBGT estimation system. [Figure 2] This is a block diagram showing an example server configuration. [Figure 3] This graph shows the relationship between solar radiation / sunlight and the time of observation. [Figure 4] This flowchart shows the procedure for deriving the regression equation. [Figure 5] This is a flowchart showing the procedure for estimating WBGT. [Modes for carrying out the invention]

[0008] The present invention will be described in detail below with reference to the drawings illustrating its embodiments. (Embodiment 1) Figure 1 is an explanatory diagram showing an example configuration of a WBGT estimation system. In this embodiment, a WBGT estimation system is described that estimates solar radiation from the amount of sunlight at an observation point and the time of observation of said sunlight, and estimates the WBGT (Wet Bulb Globe Temperature, also known as the heat index) at an observation point based on the estimated solar radiation, etc. The WBGT estimation system includes an information processing device 1 and a sensor 2. The information processing device 1 and the sensor 2 are communicated together via a network N such as the Internet.

[0009] The information processing device 1 is an information processing device capable of various information processing and information transmission and reception, such as a server computer or a personal computer. In this embodiment, the information processing device 1 is assumed to be a server computer, and for simplicity, it will be referred to as Server 1 below. Server 1 estimates the amount of solar radiation from the amount of solar irradiance (illuminance) measured by Sensor 2 and the time of observation (observation day) of said solar irradiance. Then, Server 1 estimates the WBGT of the observation site based on the estimated amount of solar radiation, as well as the temperature, relative humidity, and average wind speed measured by Sensor 2.

[0010] Sensor 2 is a sensor that measures solar irradiance and other parameters, and is connected to Server 1 via a gateway (not shown). Sensor 2 is equipped with an illuminometer 21, a thermometer 22, a hygrometer 23, and an anemometer 24, and measures illuminance, temperature, relative humidity, and average wind speed at the observation point. In addition to illuminance, Sensor 2 can also measure atmospheric pressure, rainfall, ultraviolet intensity, acceleration, rotational speed, etc.

[0011] Figure 2 is a block diagram showing an example configuration of Server 1. Server 1 comprises a control unit 11, a main memory unit 12, a communication unit 13, and an auxiliary memory unit 14. The control unit 11 is a processor such as one or more CPUs (Central Processing Units), MPUs (Micro-Processing Units), or GPUs (Graphics Processing Units), and performs various information processing by reading and executing programs P stored in the auxiliary storage unit 14. The main memory unit 12 is a temporary storage area such as SRAM (Static Random Access Memory) or DRAM (Dynamic Random Access Memory), and temporarily stores data necessary for the control unit 11 to perform calculations. The communication unit 13 is a communication module for performing communication-related processing, and sends and receives information with the outside. The auxiliary storage unit 14 is a non-volatile storage area such as a hard disk or large-capacity memory, and stores programs P (program products) and other data necessary for the control unit 11 to perform processing.

[0012] Server 1 may be a multi-computer system consisting of multiple computers, or it may be a virtual machine created virtually by software.

[0013] In addition, in this embodiment, the server 1 is not limited to the above configuration. For example, it may include an input unit that receives operation inputs, a display unit that displays images, and the like. Further, the server 1 may be provided with a reading unit that reads a portable storage medium 1a such as a CD (Compact Disk)-ROM or a DVD (Digital Versatile Disc)-ROM, and reads and executes the program P from the portable storage medium 1a.

[0014] FIG. 3 is a graph showing the relationship between solar radiation amount / sunshine duration and the observation time point. Based on FIG. 3, the outline of this embodiment will be described.

[0015] As described above, in this system, WBGT is estimated from each measured value of the sensor 2. WBGT is defined by the following mathematical formula (1).

[0016] WBGT = 0.7*Tw + 0.2*Tg + 0.1Ta …(1)

[0017] Tw is the wet-bulb temperature, Tg is the black globe temperature, and Ta is the dry-bulb temperature. However, the wet-bulb temperature, the black globe temperature, and the dry-bulb temperature are not common meteorological elements globally and cannot be measured by the sensor 2 used in this system either.

[0018] Thus, the Ono model was devised to predict WBGT using more common meteorological elements, namely air temperature, relative humidity, solar radiation amount (global solar radiation amount), and average wind speed. The mathematical formula for calculating WBGT according to the Ono model is shown in mathematical formula (2).

[0019] WBGT = 0.735*Ta + 0.0374*RH + 0.00292*Ta*RH + 7.619*SR - 4.557*SR 2 -0.0572*WS - 4.064 …(2)

[0020] Ta is the air temperature, RH is the relative humidity, SR is the solar radiation amount, and WS is the average wind speed. However, in the sensor 2 used in this system, although the sunshine amount (quantifying the intensity only for the visible light region among the sunlight reaching the ground surface) can be measured, the solar radiation amount (quantifying the intensity for the entire wavelength region of the sunlight reaching the ground surface) cannot be measured. Therefore, in this embodiment, the solar radiation amount is estimated from the sunshine amount that has a relationship close to the solar radiation amount, and the WBGT is estimated based on the estimated solar radiation amount.

[0021] Specifically, based on the observation data group in which the sunshine amount and the solar radiation amount are measured for each observation day (observation time point) of the year at a certain observation location, the server 1 derives a regression equation showing the relationship between the ratio of the solar radiation amount and the sunshine amount (solar radiation amount / sunshine amount) and the observation day. When estimating the solar radiation amount, the server 1 uses the regression equation to estimate the solar radiation amount of the observation location from the sunshine amount of the observation location and the observation day of the sunshine amount. The regression equation is shown in formula (3).

[0022] Solar radiation amount / Sunshine amount = k * Observation day + l …(3)

[0023] k is the regression coefficient and l is the regression intercept. As shown in formula (3), the server 1 derives a simple regression equation with the solar radiation amount / sunshine amount as the objective variable and the observation day (observation time point) as the explanatory variable.

[0024] When estimating the solar radiation amount more accurately, it is necessary to know not only the observation day but also the observation time and the meteorological information of the observation location at that time. However, if we try to cover all times and all weather conditions, the calculation formula will become very complex and the calculation cost will be high. Therefore, in this embodiment, we narrow it down to relatively important times and weather conditions, and derive a calculation formula that captures the change in the solar radiation amount / sunshine amount on a daily basis.

[0025] Specifically, Server 1 uses a set of observational data measured at solar noon on clear days to derive a regression equation that estimates solar radiation / sunlight at solar noon. The reason for using observational data from clear days and solar noon as the basis for deriving the regression equation is that, in this system, solar radiation is estimated for the purpose of estimating WBGT, so it is prioritized to focus on times and weather conditions with a high risk of heatstroke. In addition, the regression coefficients for cloudy or rainy days are often close to the regression coefficients for sunny days at solar noon.

[0026] Furthermore, to estimate solar radiation more accurately, it is conceivable to add the meridian altitude to the explanatory variables. However, determining the meridian altitude requires knowing the location information of the observation point, and since some information about the meridian altitude is included on the observation day, the meridian altitude is not included as an explanatory variable in this embodiment.

[0027] As described above, Server 1 derives a regression equation from a set of observational data measuring solar radiation and sunshine at solar noon on a clear day. Figure 3 shows the set of observational data for solar radiation / sunshine (plot) and the regression equation (straight line) derived from the said set of observational data.

[0028] In the graph in Figure 3, the horizontal axis represents the observation date, with January 1st as day 1 and December 31st as day 365. According to the inventor's research, solar radiation / sunlight tends to decrease from day 1 to day 180, and then begins to increase from day 180 to day 365. Since the graph in Figure 3 illustrates approximately days 180 to 280, the solar radiation / sunlight shows an increasing trend.

[0029] Server 1 estimates the solar radiation at the observation point where Sensor 2 is installed, and then estimates the WBGT, using a regression equation derived from the observation data set shown in Figure 3. Specifically, Server 1 acquires observation data from Sensor 2, including solar radiation, temperature, relative humidity, average wind speed, and observation time information indicating the observation date (observation time) for solar radiation, etc. Server 1 calculates solar radiation / solar radiation from the observation date using the regression equation, and estimates the solar radiation from the calculated solar radiation / solar radiation and the measured solar radiation. Based on the estimated solar radiation and the measured temperature, relative humidity, and average wind speed, Server 1 estimates the WBGT using equation (2).

[0030] Server 1 determines whether the estimated WBGT is above a threshold, and if it is, outputs a predetermined alert to a terminal (not shown). This allows Server 1 to warn about the need to be vigilant against heatstroke, etc.

[0031] Based on the above, according to this embodiment, when the amount of solar radiation at an observation point cannot be measured, the amount of solar radiation can be suitably estimated from the amount of sunshine and the time of observation, and the WBGT can be estimated.

[0032] Figure 4 is a flowchart showing the procedure for deriving the regression equation. Based on Figure 4, the process for deriving the regression equation that shows the relationship between solar radiation / sunlight and the observation time will be explained. The control unit 11 of server 1 acquires a set of observation data including the amount of sunlight and solar radiation at the observation point, and observation time information indicating the time of observation (observation day) for said sunlight and solar radiation (step S11). Based on the set of observation data, the control unit 11 derives a regression equation with the time of observation as the explanatory variable and solar radiation / sunlight as the dependent variable (step S12). Specifically, the control unit 11 derives a simple regression equation. The control unit 11 then completes the series of processes.

[0033] Figure 5 is a flowchart showing the procedure for estimating WBGT. Based on Figure 5, the process for estimating WBGT at observation points will be explained. The control unit 11 of server 1 acquires observation data from sensor 2, including solar radiation, temperature, relative humidity, and average wind speed at the observation site, as well as observation time information indicating the time of observation for solar radiation, etc. (step S31). The control unit 11 uses a regression equation that shows the relationship between solar radiation / solar radiation and the time of observation to estimate the solar radiation at the observation site based on the solar radiation and time of observation included in the observation data (step S32).

[0034] The control unit 11 estimates the WBGT of the observation site based on the estimated solar radiation and the temperature, relative humidity, and average wind speed included in the observation data acquired in step S31 (step S33). The control unit 11 determines whether the WBGT is above a threshold (step S34). If it is determined that the WBGT is above a threshold (S34: YES), the control unit 11 outputs an alert (step S35). After executing the process in step S35, or if the result in step S34 is NO, the control unit 11 terminates the series of processes.

[0035] Although regression analysis was used as the algorithm for estimating solar radiation in the above embodiment, this embodiment is not limited to this. For example, Server 1 may generate a machine learning model (such as a neural network) from the observation data set to estimate solar radiation when it receives observation data including solar irradiance and observation time information (observation date), and then estimate solar radiation by inputting observation data at the observation point where Sensor 2 is installed into the machine learning model. Thus, Server 1 only needs to be able to estimate solar radiation from solar irradiance and observation time, and its estimation algorithm is not limited to regression analysis.

[0036] Furthermore, in this embodiment, solar radiation was estimated only from sunshine duration and observation time, but explanatory variables such as the sun's altitude at noon and meteorological information at the observation time may also be added.

[0037] Based on the above, according to this embodiment, the amount of solar radiation can be suitably estimated.

[0038] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of the present invention is indicated by the claims, not in the sense described above, and all modifications within the sense and scope equivalent to the claims are intended.

[0039] The matters described in each embodiment can be combined with each other. Furthermore, the independent and dependent claims described in the claims can be combined with each other in any combination, regardless of the form of reference. In addition, the claims use a form in which claims referencing two or more other claims (multi-claim form), but are not limited to this. A form in which multi-claims referencing at least one multi-claim (multi-multi-claim) may also be used. [Explanation of Symbols]

[0040] 1. Server (Information Processing Device) 11 Control Unit 12 Main memory 13 Communications Department 14 Auxiliary storage P Program 2 sensors 21 Illuminance meter 22 Thermometer 23 Hygrometer 24 Anemometer

Claims

1. The amount of sunlight at the observation point and the observation time information indicating the time when the sunlight was observed are obtained. Based on the acquired solar radiation amount and observation time information, the solar radiation amount at the observation point is estimated. An information processing method in which a computer performs the processing.

2. Using a regression equation that shows the relationship between the ratio of solar radiation and sunshine duration and the observation time, the solar radiation is estimated based on the acquired sunshine duration and observation time information. The information processing method according to claim 1.

3. Further acquisition of temperature, relative humidity, and average wind speed at the aforementioned observation point, Based on the estimated solar radiation, the acquired temperature, relative humidity, and average wind speed, the heat index of the observation point is estimated. The information processing method according to claim 1 or 2.

4. An alert is output according to the estimated heat index. The information processing method according to claim 3.

5. The amount of sunlight at the time of solar noon at the observation point is obtained, The amount of solar radiation at the time of solar noon at the aforementioned observation point is estimated. The information processing method according to any one of claims 1 to 4.

6. The amount of sunlight at the observation point and the observation time information indicating the time when the sunlight was observed are obtained. Based on the acquired solar radiation amount and observation time information, the solar radiation amount at the observation point is estimated. A program that instructs a computer to perform a process.

7. An information processing device comprising a control unit, The control unit, The amount of sunlight at the observation point and the observation time information indicating the time when the sunlight was observed are obtained. Based on the acquired solar radiation amount and observation time information, the solar radiation amount at the observation point is estimated. Information processing device.

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