WO2023195207A1

WO2023195207A1 - Weather prediction system and meteoropathy prediction system

Info

Publication number: WO2023195207A1
Application number: PCT/JP2022/048490
Authority: WO
Inventors: 宗義吹田; 邦彦西村
Original assignee: 三菱電機株式会社
Priority date: 2022-04-07
Filing date: 2022-12-28
Publication date: 2023-10-12
Also published as: JP7490162B2; JPWO2023195207A1

Abstract

A vital sign acquisition unit (11) of a weather prediction system (100) acquires a vital sign for a person as well as information about the place of occurrence and time of occurrence of the vital sign. A weather observation data acquisition unit (12) acquires weather observation data. A weather prediction unit (13) uses a weather prediction model (23a) trained using the correlation between persons' vital signs and changes in the weather at the places of occurrence of the vital signs to predict the weather from the vital sign for the person acquired by the vital sign acquisition unit (11) and weather observation data acquired by the weather observation data acquisition unit (12) for the place of occurrence and time of occurrence of the vital sign. The results of the weather prediction made by the weather prediction unit (13) are sent to a user of the weather prediction system (100).

Description

Weather prediction system and meteorological disease prediction system

The present disclosure relates to a weather prediction system that predicts the weather and a weather disease prediction system that predicts the onset of weather diseases.

Conventionally, weather prediction systems predict future weather based on weather observation data measured by weather measuring instruments installed in various places.

In addition, diseases that develop due to changes in weather conditions are called "weather diseases." For example, in Patent Document 1 below, a user's weather condition is determined based on predicted weather information and user's personal weather disease information. A meteorological disease prediction system for predicting the onset of diseases has been disclosed.

Japanese Patent Application Publication No. 2002-311158

In conventional weather forecasting systems, in order to improve the accuracy of local weather forecasting, it is necessary to increase the number of weather measuring instruments installed. However, in order to increase the number of meteorological measuring instruments installed, it is necessary to secure a new location for installing the meteorological measuring instruments, and as the number of installed meteorological measuring instruments increases, the maintenance cost of the meteorological measuring instruments also increases. There are also challenges.

The present disclosure has been made to solve the above-mentioned problems, and aims to improve the accuracy of local weather forecasting without increasing the number of weather measuring instruments installed.

The weather forecasting system according to the present disclosure includes a vital sign acquisition unit that acquires information on a person's vital signs and the appearance point and time of the vital signs, a weather observation data acquisition unit that acquires weather observation data, and a weather observation data acquisition unit that acquires weather observation data. Using a weather prediction model obtained by learning the correlation between a sign and a change in weather at the point where the vital sign appears, the vital sign acquisition section acquires the person's vital signs and the point where the vital sign appears. A weather prediction unit that performs weather prediction from weather observation data at the time of appearance.

According to the present disclosure, since information on a person's vital signs is taken into account in weather prediction, the accuracy of local weather prediction can be improved without increasing the number of weather measuring instruments installed. .

1 is a diagram showing the configuration of a weather prediction system according to Embodiment 1. FIG. FIG. 3 is a diagram showing an example of vital signs and weather observation data. 3 is a flowchart showing the operation of the weather forecasting device according to the first embodiment. 3 is a flowchart showing the operation of the weather prediction model creation device according to the first embodiment. FIG. 2 is a diagram showing the configuration of a weather prediction system according to a second embodiment. 7 is a flowchart showing the operation of the weather forecasting device according to Embodiment 2. FIG. FIG. 6 is a diagram showing a modification of the weather prediction system according to Embodiments 1 and 2. FIG. 3 is a diagram showing the configuration of a meteorological disease prediction system according to Embodiment 3. FIG. 12 is a flowchart showing the operation of the meteorological disease prediction device according to Embodiment 3. It is a figure showing the composition of the meteorological disease prediction system concerning Embodiment 4. 12 is a flowchart showing the operation of the meteorological disease prediction device according to Embodiment 4. It is a figure showing the 1st modification of the meteorological disease prediction system concerning Embodiment 3 and 4. It is a figure which shows the 2nd modification of the meteorological disease prediction system based on Embodiment 3 and 4. 1 is a diagram illustrating an example of a hardware configuration of a weather prediction device, a weather prediction model creation device, and a weather disease prediction device. 1 is a diagram illustrating an example of a hardware configuration of a weather prediction device, a weather prediction model creation device, and a weather disease prediction device.

<Embodiment 1>
FIG. 1 is a diagram showing the configuration of a weather prediction system 100 according to the first embodiment. As shown in FIG. 1, the weather prediction system 100 according to the first embodiment includes a weather prediction device 10 that predicts weather, and a weather prediction model creation device 20 that creates a weather prediction model 23a used by the weather prediction device 10 for weather prediction. Contains. The weather prediction model 23a created by the weather prediction model creation device 20 is a weather model obtained by learning the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear.

Although the weather prediction device 10 and the weather prediction model creation device 20 are shown as separate devices in FIG. The prediction device 10 and the weather prediction model creation device 20 may be configured as an integrated device.

Here, vital signs are information indicating the presence or absence or degree of symptoms of a disease. Since all kinds of diseases can be influenced by the weather, the diseases indicated by vital signs need not be limited to those generally recognized as "weather diseases" such as migraines and neuralgia. In addition, there are no particular restrictions on the symptoms that vital signs indicate, such as pain, malaise, itching, dizziness, diarrhea, lacrimation, runny nose, sensory imbalance, sensory imbalance, and changes in body balance. But that's fine.

First, the configuration of the weather forecasting device 10 will be explained. As shown in FIG. 1, the weather prediction device 10 includes a vital sign acquisition section 11, a weather observation data acquisition section 12, a weather prediction section 13, and a weather prediction transmission section 14.

The vital sign acquisition unit 11 acquires a person's vital signs and information on the appearance point and appearance time of the vital signs. In the first embodiment, it is assumed that a user of a mobile terminal such as a mobile phone or a smartphone can transmit his or her vital signs to the weather prediction device 10 using the mobile terminal. At this time, the mobile terminal adds its own position information and information on the input time of the vital sign to the vital sign as information on the point and time of appearance of the vital sign, and transmits it to the weather prediction device 10. By receiving these pieces of information, the vital sign acquisition unit 11 can acquire the person's vital signs and information on the appearance point and appearance time of the vital signs. Here, the "vital sign appearance point" is the location where the person was when the vital sign appeared, and the "vital sign appearance time" is the time when the vital sign appeared. For example, if a mobile terminal user inputs vital sign information into the mobile terminal some time after the vital signs appear, the position and time of the mobile terminal at the time of inputting the vital signs is the same as the appearance of the vital signs. The location and time of appearance may be significantly different. Therefore, in such a case, the user of the mobile terminal also needs to input information on the appearance point and appearance time of the vital signs into the mobile terminal.

Furthermore, if the consent of the user of the mobile terminal is obtained, the vital sign acquisition unit 11 acquires and analyzes texts or images posted by the user of the mobile terminal to a social networking service (SNS), thereby obtaining the vital signs of the person. Also, information on the appearance point and appearance time of the vital sign may be acquired. For example, the vital sign acquisition unit 11 searches and detects predetermined keywords such as "headache," "low back pain," "knee pain," "neuralgia," and "vertigo" from texts posted by users of mobile terminals. The searched keywords may be acquired as vital signs. Keywords are not limited to the names of the diseases listed above, but include, for example, ``pain,'' ``feeling tired,'' ``tension,'' ``numbness,'' ``throbbing,'' ``light-headed,'' and ``unable to walk straight.'' , "delayed sensation," "feeling of pressure," "feeling of expansion," or other sensations may be used. For example, the vital sign acquisition unit 11 detects and analyzes the user's face and skin of hands and feet from an image posted by the user of the mobile terminal, and based on the facial expression, complexion, condition of the skin of the hands and feet, condition of pupils, etc. Vital signs may also be detected.

Further, the vital sign acquisition unit 11 may acquire not only vital sign information but also weather information as information related to the vital sign from a text or image posted by a user of a mobile terminal to an SNS. For example, the vital sign acquisition unit 11 searches for predetermined keywords such as "sunny," "rain," "cloudy," "snow," and "typhoon" from sentences posted by the user of the mobile terminal, and The weather information corresponding to the keyword may be used as vital sign related information. The keywords are not limited to those directly indicating the weather as described above, but may also be keywords expressing sensations such as "dazzling," "hot," "cold," and "glaring." For example, the vital sign acquisition unit 11 may analyze an image posted by a user of a mobile terminal and detect weather information from clouds, rain, snow, fog, puddles, snowfall, etc. appearing in the image. For example, with respect to clouds, weather information may be detected from cloud movements and changes, such as cloud speed and cloud thickness distribution changes.

Alternatively, a wearable or portable pain detection device may be used to automatically input the user's vital signs into the mobile terminal, and the mobile terminal may automatically transmit the vital signs to the weather forecasting device 10. . In addition, the mobile terminal acquires the output signal of the pressure sensor built into the shoes worn by the user of the mobile terminal, and the mobile terminal detects changes in the balance of the user's body as a vital sign and sends it to the weather forecasting device 10. You may. In addition, the mobile terminal acquires the output signal of the brain wave detection sensor attached to the head of the mobile terminal user, and the mobile terminal detects changes in the user's body condition as vital signs and sends them to the weather forecasting device 10. Good too.

The weather observation data acquisition unit 12 acquires weather observation data from weather measuring instruments installed in various places. The weather measuring instrument may be one used in conventional weather forecasting systems. The weather observation data acquired by the weather observation data acquisition unit 12 includes at least data corresponding to the appearance point and appearance time of the vital sign acquired by the vital sign acquisition unit 11. However, the meteorological observation data acquired by the meteorological observation data acquisition unit 12 includes data of a certain size area including the appearance point of vital signs, and data of a certain length of time including the appearance time of vital signs. Preferably, series data is included.

The weather prediction unit 13 uses the weather prediction model 23a held in the weather prediction model creation device 20 to obtain the vital signs acquired by the vital sign acquisition unit 11 and weather observation data at the appearance point and time of the vital signs. From this, weather forecasts are made. As described above, the weather prediction model 23a is a weather model obtained by learning the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear. Details of the weather prediction model creation device 20 and the weather prediction model 23a will be described later.

The weather prediction transmitting unit 14 transmits the results of the weather prediction by the weather prediction unit 13 to the users of the weather prediction system 100, for example, through a network such as the Internet. There are no restrictions on the users of the weather forecasting system 100 (that is, the recipients of the weather forecast results); for example, there are broadcasters such as television and radio broadcasters who broadcast weather forecast programs, and businesses that operate websites that provide weather forecast information. Possible reasons include:

Furthermore, in response to a request from a specific user of the weather prediction system 100, the weather prediction transmitter 14 may notify the user of the results of local weather prediction at a point specified by the user. The specific user is assumed to be, for example, an owner of a business that is easily affected by the weather, such as an outdoor event organizer, a transportation company, a logistics company, or a producer of ice cream or the like.

Next, the configuration of the weather prediction model creation device 20 will be explained. As shown in FIG. 1, the weather prediction model creation device 20 includes a data storage section 21, a weather prediction model creation section 22, and a weather prediction model storage section 23.

The data storage unit 21 stores the vital signs of the person acquired by the vital sign acquisition unit 11 of the weather prediction device 10 and information on the appearance point and time of the vital signs, and the information acquired by the weather observation data acquisition unit 12 of the weather prediction device 10. It is a storage medium that stores weather observation data. FIG. 2 shows an example of vital sign information and weather observation data stored in the data storage unit 21. Weather observation data items include observation point, observation time, temperature, air temperature, humidity (or water vapor amount), atmospheric pressure, precipitation (or snowfall amount), wind speed, wind direction, cloud shape and movement, and short information on these observation data. It can include anything such as data that shows changes over time.

The weather prediction model creation unit 22 uses the information accumulated in the data storage unit 21 to learn the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, and based on the learning results. A weather prediction model 23a is created.

The learning method performed by the weather prediction model creation unit 22 may be any method. For example, the weather prediction model creation unit 22 classifies vital sign information and weather data by item, creates weather models according to all combinations of them, and for each weather model, A possible method is to learn a probable weather model by verifying the degree to which it matches vital sign information (stored in the data storage unit 21) and weather data (number of hits). When this method is adopted, it is preferable to construct the weather prediction model 23a using only weather models whose degree of matching with actually obtained vital sign information and weather data is equal to or higher than a predetermined threshold.

Further, for example, the weather prediction model creation unit 22 classifies vital sign information and weather data by item, creates weather models according to all combinations of them, and calculates actual results for each weather model. A possible method is to learn a probable weather model by verifying the vital sign information (stored in the data storage unit 21) and the degree of change (number of hits) in weather data over time. When this method is adopted, it is preferable to construct the weather prediction model 23a using only information on actually obtained vital signs and weather models in which the degree of change in weather data with respect to time is equal to or greater than a predetermined threshold. Although the amount of change in weather data with respect to time has been explained here, the weather prediction model 23a may also be constructed using the amount of change in weather data with respect to temperature, the amount of change in weather data with respect to sunshine hours, etc. I don't mind.

The created weather prediction model 23a is stored in the weather prediction model storage unit 23. The weather prediction model storage unit 23 is accessible from the weather prediction device 10, and the weather prediction unit 13 of the weather prediction device 10 makes weather predictions using the weather prediction model 23a stored in the weather prediction model storage unit 23. It can be carried out.

Next, the operation of the weather forecasting device 10 will be explained with reference to the flowchart in FIG. 3. Here, to simplify the explanation, it is assumed that the sender of the vital signs is always present.

First, the vital sign acquisition unit 11 acquires a person's vital signs and information on the appearance point and appearance time of the vital signs (step S101). Furthermore, the weather observation data acquisition unit 12 acquires weather observation data from weather measuring instruments installed in various places (step S102).

Then, using the weather prediction model 23a held in the weather prediction model creation device 20, the weather prediction unit 13 uses the vital signs acquired by the vital sign acquisition unit 11 in step S101 and the weather observation data acquisition unit in step S102. Based on the meteorological observation data at the appearance point and appearance time of the vital sign acquired by 12, the weather prediction for the area including the appearance point of the vital sign is performed (step S103).

Thereafter, the weather forecasting unit 13 evaluates the credibility of the weather prediction results by comparing the weather prediction results with the weather observation data (step S104). For example, the weather prediction unit 13 calculates the degree of deviation between the result of the weather prediction and the current weather observation data, and if the calculated degree of deviation is equal to or less than a predetermined threshold, the reliability of the result of the weather prediction is high. Otherwise, it is determined that the credibility of the weather prediction results is low.

If it is determined that the reliability of the weather prediction result is high (YES in step S105), the weather prediction transmitter 14 transmits the weather prediction result to the outside (step S106), and returns to step S101. If it is determined that the credibility of the weather prediction result is low (NO in step S105), the weather prediction result is not transmitted to the outside and the process returns to step S101.

Next, the operation of the weather prediction model creation device 20 will be described with reference to the flowchart in FIG. 4. Here, to simplify the explanation, it is assumed that the data storage unit 21 has already accumulated enough information for learning to create the weather prediction model 23a.

First, the weather prediction unit 13 collects the information newly acquired by the weather prediction device 10, that is, the vital signs of the person newly acquired by the vital sign acquisition unit 11 of the weather prediction device 10, and the appearance point and appearance time of the vital signs. information and the newly acquired weather observation data by the weather observation data acquisition unit 12 of the weather forecasting device 10 (step S201).

Next, the weather prediction model creation unit 22 uses the information accumulated in the data storage unit 21 to learn the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear (step S202). . Then, the weather prediction model creation unit 22 creates a weather prediction model 23a based on the learning results (step S203).

Thereafter, the weather prediction model 23a created by the weather prediction model creation unit 22 is stored in the weather prediction model storage unit 23 (step S204), and the process returns to step S201.

According to the weather forecasting system 100 according to the first embodiment, weather forecasting is performed not only based on weather observation data measured by a weather measuring instrument, but also taking into account people's vital signs, so that weather forecasting can be performed regardless of the area where there are people. For example, it can be expected to improve the accuracy of local weather forecasts in the same way as increasing the number of weather measuring instruments installed. In other words, the accuracy of local weather prediction can be improved without increasing the number of weather measuring instruments installed.

<Embodiment 2>
FIG. 5 is a diagram showing the configuration of a weather prediction system 100 according to the second embodiment. The configuration of the weather prediction system 100 in FIG. 5 is such that a vital data acquisition section 15 is added to the configuration in FIG.

The vital data acquisition unit 15 acquires the person's vital data and information on the measurement point and measurement time of the vital data, and provides the acquired information to the weather prediction unit 13.

Here, vital data is biological information that can be measured from the human body, and representative examples include body temperature, blood pressure, heart rate, respiratory rate, brain waves, and blood sugar level. Vital data is not limited to what can be directly measured from the human body, but may also be information obtained by analyzing, for example, blood, saliva, sweat, excrement collected from the human body, or food ingested by the human body. Vital data can basically be measured as quantitative numbers, and there are already wearable vital data measurement devices such as watch-type, earphone-type, and hat-type devices, so vital data is information that is relatively easy to obtain. be.

In the second embodiment, it is assumed that a mobile terminal such as a mobile phone or a smartphone, for example, acquires the user's vital data at all times or at regular intervals and automatically transmits it to the weather forecasting device 10 with the user's consent. At this time, the mobile terminal adds information about the vital data measurement point and measurement time to the vital data, and transmits the vital data to the weather forecasting device 10. By receiving these pieces of information, the vital data acquisition unit 15 can acquire vital data of the person and information on the measurement point and measurement time of the vital data. Here, the "vital data measurement point" is the location where the person was when the person's vital data was measured, and the "vital data measurement point" is the time when the vital data was measured. For example, even if vital data is measured at a remote location in online medical treatment, the vital data measurement point is the point where the person whose vital data is measured (the patient in the online medical treatment) is located. Furthermore, when vital data is measured from a specimen such as blood collected from a human body, the point and time at which the specimen is collected becomes the vital data measurement point and measurement time.

The sender of vital data is not limited to the mobile terminal user either. For example, a sensor and a transmitter that detect vital data and transmit it to the weather prediction device 10 may be installed in a toilet or bathroom of a medical institution or a general home.

In addition, in the second embodiment, the weather prediction model 23a held in the weather prediction model creation device 20 calculates not only the correlation between a person's vital signs and the weather change at the point where the vital signs appear, but also the This is obtained by learning the correlation between the data and changes in the weather at the measurement point of the vital data.

The weather prediction unit 13 uses the weather prediction model 23a to obtain the vital signs of the person acquired by the vital sign acquisition unit 11 and the meteorological observation data at the appearance point and time of the vital signs, and the vital data acquisition unit 15 acquires them. Weather predictions are made from the vital data of the person who has taken the test, as well as the meteorological observation data at the measurement point and time of the vital data.

FIG. 6 is a flowchart showing the operation of the weather prediction device 10 according to the second embodiment. The flowchart in FIG. 6 is the flowchart in FIG. 3 with step S110 inserted.

In step S110, the vital data acquisition unit 15 acquires the person's vital data and information on the measurement point and measurement time of the vital data. Furthermore, in step S103, the weather forecasting unit 13 performs weather forecasting taking into account the information acquired in step S110. The other steps are the same as those shown in FIG. 3, so the description here will be omitted.

The configuration of the weather prediction model creation device 20 in the second embodiment is the same as that in FIG. 1, and its operation is basically the same as the flowchart in FIG. 4. However, in the second embodiment, the data storage unit 21 stores not only the information on the person's vital signs acquired by the vital sign acquisition unit 11 and the meteorological observation data acquired by the weather observation data acquisition unit 12, but also the vital data acquisition unit 15. Vital data information acquired by the user is also stored. In addition, the weather prediction model creation unit 22 uses the information accumulated in the data storage unit 21 to determine the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, and A weather prediction model 23a is created by learning the correlation between the data and changes in weather at the measurement point of the vital data.

According to the weather prediction system 100 according to the second embodiment, weather prediction is performed taking into account not only the weather observation data measured by a weather measuring instrument but also the vital signs and vital data of the person. For regional areas, it can be expected to improve the accuracy of local weather forecasts in the same way as increasing the number of weather measuring instruments installed. In other words, the accuracy of local weather prediction can be improved without increasing the number of weather measuring instruments installed.

<Modifications of Embodiments 1 and 2>
FIG. 7 is a diagram showing a modification of the weather prediction system 100. The configuration of the weather prediction system 100 in FIG. 7 is such that a disaster prediction section 16 and a disaster prediction notification section 17 are added to the weather prediction system 100 in the first embodiment (FIG. 1).

The disaster prediction unit 16 predicts the occurrence of a disaster based on the results of the weather prediction by the weather prediction unit 13. Any method may be used to predict the occurrence of a disaster. For example, the disaster prediction unit 16 monitors the amount of precipitation, snowfall, wind speed, etc. predicted by the weather prediction unit 13 in each region, and identifies areas where any of these values exceeds a predetermined threshold. It may be determined that the area is a predicted area. Since the weather prediction device 10 can predict local weather with high accuracy, it is expected that the accuracy of disaster prediction by the disaster prediction unit 16 will improve.

The disaster prediction notification unit 17 notifies users in areas where a disaster is predicted to occur by the disaster prediction unit 16 of disaster prediction information. For example, the disaster prediction notification unit 17 transmits disaster prediction information to mobile terminals of users in areas where a disaster is predicted to occur.

Although FIG. 7 shows an example in which the disaster prediction unit 16 and disaster prediction notification unit 17 are added to the weather prediction system 100 of the first embodiment (FIG. 1), they are the same as those of the second embodiment (FIG. 5). It can also be applied to the weather prediction system 100.

<Embodiment 3>
FIG. 8 is a diagram showing the configuration of a meteorological disease prediction system 200 according to the third embodiment. The meteorological disease prediction system 200 in FIG. 8 is based on the weather prediction system 100 according to Embodiment 1 or 2 (the weather prediction system 100 shown in FIG. 8 is according to Embodiment 1, but the weather prediction system 100 according to Embodiment 2 ) and a meteorological disease prediction device 30 that predicts the onset of a weather disease in a user based on the results of weather prediction by the weather prediction system 100. The weather prediction system 100 is as described in Embodiment 1 or 2, so the description here will be omitted.

As shown in FIG. 8, the weather disease prediction device 30 includes a user information storage section 31, a user position acquisition section 32, a weather disease prediction section 33, and a weather disease prediction notification section 34.

The user information storage unit 31 is a storage medium in which information regarding weather diseases of users of the weather disease prediction system 200 is registered. A user can register information regarding his or her weather disease in the user information storage unit 31 using a communication terminal (for example, a mobile terminal or a personal computer). Information regarding meteorological diseases may include the type (name) of the weather disease, its symptoms, and the conditions under which it is likely to develop (for example, weather conditions, time of day, location, etc.). Conditions that are likely to cause symptoms do not need to be medically backed, and may be based on the user's past experience (for example, ``when a heavy rain warning is issued'', ``when the distance between isobars in the east-west direction is narrow'', `` (e.g., "in the morning," "while at work," etc.)

The user location acquisition unit 32 acquires information on the user's current location. The user's location information can be acquired from, for example, the user's mobile terminal or the navigation system of the vehicle in which the user rides. Furthermore, if the user's location information cannot be acquired, a pre-registered location such as the user's home or workplace may be regarded as the user's current location.

The meteorological disease prediction unit 33 acquires the weather prediction result for the user's current location from the weather prediction device 10 of the weather prediction system 100, and records the weather prediction result for the user's current location and the information registered in the user information storage unit 31. The onset of a user's weather disease is predicted based on information regarding the user's weather disease. In other words, the weather disease prediction unit 33 predicts the time period and probability that the weather at the user's current location will be in a state where the weather disease is likely to develop.

The meteorological disease prediction notification unit 34 notifies users predicted to develop a weather disease by the weather disease prediction unit 33 of weather disease prediction information (for example, the time period in which the weather disease will develop, the probability of onset, etc.). . For example, the weather disease prediction notification unit 34 transmits weather disease prediction information to the mobile terminal of a user who is predicted to develop a weather disease, for example, through a network such as the Internet.

Next, the operation of the meteorological disease prediction device 30 will be explained with reference to the flowchart in FIG. Here, to simplify the explanation, it is assumed that information regarding the user's weather disease has already been registered in the user information storage unit 31.

First, the user location acquisition unit 32 acquires information on the user's current location (step S301).

Subsequently, the meteorological disease prediction unit 33 acquires the weather prediction results for the user's current location (excluding those determined to have low credibility) from the weather prediction device 10 of the weather prediction system 100 (step S302). Then, the meteorological illness prediction unit 33 determines whether the user has a meteorological illness based on the weather prediction result for the user's current location acquired in step S302 and the information regarding the user's meteorological illness registered in the user information storage unit 31. The onset of the disease is predicted (step S303).

Thereafter, the weather disease prediction notification unit 34 notifies the user predicted to develop a weather disease in step S303 of weather disease prediction information (for example, the time period in which the weather disease will develop, the probability of onset, etc.) Step S304).

According to the present embodiment, the onset prediction of the user's weather illness is performed based on the highly accurate weather prediction predicted by the weather forecasting device 10, so it can be expected that the accuracy of the prediction of the onset of the weather illness will be improved.

Here, a configuration has been described in which the weather prediction system 100 is included in the weather disease prediction system 200, but for example, the weather disease prediction device 30 and the weather prediction model storage unit 23 are provided in a mobile terminal to perform weather prediction. The weather prediction results from the weather prediction unit 13 may be obtained from the user via the network. In that case, when the weather prediction device 10 newly acquires information, the weather prediction model in the weather prediction model storage unit 23 can be updated via the network.

<Embodiment 4>
FIG. 10 is a diagram showing the configuration of a meteorological disease prediction system 200 according to the fourth embodiment. The configuration of the meteorological disease prediction system 200 in FIG. 10 is such that a user vital data acquisition section 35 is added to the configuration in FIG.

The user vital data acquisition unit 35 acquires the vital data of the user of the meteorological illness prediction system 200 and information on the measurement point and measurement time of the vital data, and provides the acquired information to the meteorological illness prediction unit 33.

In Embodiment 4, it is assumed that a user uses a mobile terminal such as a mobile phone or a smartphone to transmit his or her own vital data to the meteorological disease prediction device 30 at all times or at regular intervals. At this time, the mobile terminal adds information on the vital data measurement point and measurement time to the vital data, and transmits the vital data to the meteorological disease prediction device 30. By receiving this information, the user vital data acquisition unit 35 can acquire the user's vital data and information on the measurement point and measurement time of the vital data.

The means for transmitting the user's vital data is not limited to mobile terminals. For example, a sensor and a transmitter that detect the user's vital data and transmit it to the meteorological disease prediction device 30 may be installed in the toilet or bathroom of the user's home.

In addition, in the fourth embodiment, the meteorological disease prediction unit 33 uses the weather prediction result of the user's current position acquired from the weather prediction device 10 of the weather prediction system 100 and the user's information registered in the user information storage unit 31. The onset of a weather disease in a user is predicted based on the information regarding the weather disease and the user's vital data acquired by the user vital data acquisition unit 35. Since vital data can sometimes give signs of weather disease, incorporating vital data into the prediction of the onset of weather disease will further improve the accuracy of predicting the onset of weather disease.

FIG. 11 is a flowchart showing the operation of the weather prediction device 10 according to the fourth embodiment. The flowchart in FIG. 11 is the flowchart in FIG. 9 with step S310 inserted.

In step S310, the user vital data acquisition unit 35 acquires the user's vital data and information on the measurement point and measurement time of the vital data. Furthermore, in step S303, the meteorological disease prediction unit 33 performs weather prediction, taking into account the information acquired in step S310. The other steps are the same as those shown in FIG. 9, so the description here will be omitted.

According to the weather disease prediction system 200 according to the fourth embodiment, since the vital data of the user is taken into account when predicting the onset of the user's weather disease, the accuracy of predicting the onset of the user's weather disease can be improved compared to the third embodiment. can be improved.

In addition, since vital data is considered to be influenced by the time of day and location, when adding vital data to the user's weather disease onset prediction, the meteorological disease prediction unit 33 also includes the measurement time and measurement point of the vital data. May be taken into consideration. This can be expected to further improve the accuracy of users' predictions of the onset of weather diseases.

<Modifications of Embodiments 3 and 4>
FIG. 12 is a diagram showing a first modification of the meteorological disease prediction system 200. The configuration of the weather disease prediction system 200 in FIG. 12 is the same as the weather disease prediction system 200 in the third embodiment (FIG. 8) by adding a dosage timing notification section 36.

The dosing timing notification unit 36 notifies the user who is predicted to develop a weather disease by the weather disease prediction unit 33 of the timing to take a medicine to suppress the onset of the weather disease. For example, the dosing timing notification unit 36 transmits a notification of the dosing timing of the medicine to the user's mobile terminal.

Any method may be used to determine the timing of taking the medicine. For example, the timing for taking the medicine may be a certain period of time before the predicted time when the weather disease will develop. By prompting the user to take medicine before the weather disease develops, it is possible to prevent the onset of the weather disease.

FIG. 13 is a diagram showing a second modification of the weather disease prediction system 200. The configuration of the weather disease prediction system 200 in FIG. 13 is such that a recommended action notification section 37 is added to the weather disease prediction system 200 in the third embodiment (FIG. 8).

The recommended action notification unit 37 notifies the user predicted to develop a weather disease by the weather disease prediction unit 33 of recommended actions before or after the onset of the weather disease. For example, the recommended behavior notification unit 37 notifies the user's mobile terminal of the recommended behavior.

Recommended actions before and after the onset of a weather disease include, for example, refraining from going out, going to the hospital, refraining from driving, refraining from exercise, refraining from eating certain foods, and refraining from eating certain foods. It may encourage intake, but this varies depending on the type of weather disease. By informing the user of recommended actions before the onset of a weather disease, the user can take actions to prevent the onset of the weather disease or accidents caused by it.

Note that FIGS. 12 and 13 show an example in which the dosing timing notification unit 36 or the recommended action notification unit 37 is added to the meteorological disease prediction system 200 of the third embodiment (FIG. 8); 4 (FIG. 10). Furthermore, when the meteorological disease prediction system 200 is provided with the dosing timing notification section 36 or the recommended action notification section 37, the meteorological disease prediction notification section 34 may be omitted.

<Hardware configuration example>
The weather prediction device 10, the weather prediction model creation device 20, and the weather disease prediction device 30 shown above can be realized by a hardware configuration as shown in FIG. 14 or 15, respectively.

When the weather forecasting device 10 is realized by the processing circuit 50 shown in FIG. 14, the weather forecasting device 10 acquires the vital signs of the person, the appearance point and time of appearance of the vital signs, and acquires weather observation data. , a processing circuit 50 is provided for making weather predictions from a person's vital signs and weather observation data at the appearance point and appearance time of the vital signs using a weather prediction model.

Furthermore, when the weather prediction model creation device 20 is realized by the processing circuit 50 shown in FIG. A processing circuit 50 is provided for creating a weather prediction model by learning the correlation between a person's vital signs and weather changes at the point where the vital signs appear, using the accumulated information.

Furthermore, when the weather disease prediction device 30 is realized by the processing circuit 50 shown in FIG. A processing circuit 50 is provided for predicting the onset of a weather disease in a user based on information regarding the weather disease.

The processing circuit 50 may be dedicated hardware, or may be a processor (Central Processing Unit (CPU), processing device, arithmetic device, microprocessor, microcomputer, etc.) that executes a program stored in memory. It may be configured using a DSP (also called Digital Signal Processor).

When the processing circuit 50 is dedicated hardware, the processing circuit 50 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), or an FPGA (Field-Programmable Circuit). Gate Array), or a combination of these. The functions of each component of the weather forecasting device 10 may be realized by separate processing circuits, or these functions may be realized by a single processing circuit.

FIG. 15 shows an example of the hardware configuration of the weather prediction device 10, the weather prediction model creation device 20, and the weather disease prediction device 30 in a case where the processing circuit 50 is configured using a processor 51 that executes a program. . In this case, the functions of the components of the weather prediction device 10, the weather prediction model creation device 20, and the weather disease prediction device 30 are realized by software or the like (software, firmware, or a combination of software and firmware). Software etc. are written as programs and stored in the memory 52. The processor 51 implements the functions of each section by reading and executing programs stored in the memory 52.

When the weather prediction device 10 is realized by the processor 51 and memory 52 shown in FIG. 15, the weather prediction device 10, when executed by the processor 51, calculates the vital signs of a person and the point and time of appearance of the vital signs. The process includes a process of acquiring information, a process of acquiring weather observation data, and a process of making weather predictions using a weather prediction model from the person's vital signs and the weather observation data at the appearance point and time of the vital signs. A memory 52 is provided for storing programs that will eventually be executed.

Further, when the weather prediction model creation device 20 is realized by the processor 51 and the memory 52 shown in FIG. A weather prediction model is created by accumulating information on the appearance point and time of appearance, and using this accumulated information to learn the correlation between a person's vital signs and changes in the weather at the appearance point of the vital sign. , and a memory 52 for storing a program to be executed as a result.

Furthermore, when the weather disease prediction device 30 is realized by the processor 51 and the memory 52 shown in FIG. , a process for predicting the onset of a user's weather disease based on the weather prediction results for the user's current location and information regarding the user's weather disease; and a memory for storing a program that will be executed as a result. 52.

In other words, each of the above programs can be said to cause a computer to execute the operating procedures and methods of the components of the weather prediction device 10, the weather prediction model creation device 20, or the weather disease prediction device 30.

Here, the memory 52 is, for example, a non-volatile or Volatile semiconductor memory, HDD (Hard Disk Drive), magnetic disk, flexible disk, optical disk, compact disk, mini disk, DVD (Digital Versatile Disc) and their drive devices, as well as all storage media that will be used in the future. Good too.

The above describes the configuration in which the functions of the constituent elements of the weather prediction device 10, the weather prediction model creation device 20, and the weather disease prediction device 30 are realized by either hardware, software, or the like. However, the present invention is not limited to this, and some of the components of the weather forecasting device 10, the weather forecasting model creation device 20, and the weather disease prediction device 30 may be realized by dedicated hardware, and other components may be realized by software. The configuration may be realized by, etc. For example, for some components, the functions are realized by the processing circuit 50 as dedicated hardware, and for some other components, the processing circuit 50 as the processor 51 executes the program stored in the memory 52. The function can be realized by reading and executing it.

As described above, the weather prediction device 10, the weather prediction model creation device 20, and the weather disease prediction device 30 can implement the above-mentioned functions using hardware, software, etc., or a combination thereof.

Note that it is possible to freely combine each embodiment, or to modify or omit each embodiment as appropriate.

Hereinafter, various aspects of the present disclosure will be collectively described as supplementary notes.

(Additional note 1)
a vital sign acquisition unit that acquires information on a person's vital signs and the point and time of appearance of the vital signs;
a weather observation data acquisition unit that acquires weather observation data;
Using a weather prediction model obtained by learning the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, the vital signs of the person acquired by the vital sign acquisition unit and the vital signs of the person concerned are a weather forecasting unit that makes weather predictions from weather observation data at the appearance point and appearance time;
A weather forecasting system equipped with

(Additional note 2)
further comprising a vital data acquisition unit that acquires the person's vital data and information on the measurement point and measurement time of the vital data,
The weather prediction model learns not only the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, but also the correlation between the person's vital data and changes in the weather at the point where the vital data is measured. This is a weather prediction model obtained by
The weather prediction unit uses the weather prediction model to obtain the human vital signs acquired by the vital sign acquisition unit, weather observation data at the appearance point and time of the vital signs, and the vital signs acquired by the vital data acquisition unit. Making weather predictions from human vital data and meteorological observation data at the measurement point and time of the vital data;
The weather prediction system described in Appendix 1.

(Additional note 3)
The vital sign acquisition unit analyzes a text or image posted to a social networking service and extracts the vital signs of the person who posted the text or image.
The weather forecasting system described in Supplementary Note 1 or Supplementary Note 2.

(Additional note 4)
Further comprising a weather forecast transmission unit that notifies the user of the result of the weather forecast for a point specified by the user in response to a request from the user.
The weather prediction system according to any one of Supplementary notes 1 to 3.

(Appendix 5)
a disaster prediction unit that predicts the occurrence of a disaster based on the results of the weather prediction by the weather prediction unit;
a disaster prediction and notification unit that notifies users in areas where a disaster is predicted to occur, of disaster prediction information;
further comprising,
The weather prediction system according to any one of Supplementary notes 1 to 4.

(Appendix 6)
a data storage unit that stores information on the person's vital signs acquired by the vital sign acquisition unit and the appearance point and time of the vital signs, and weather observation data acquired by the weather observation data acquisition unit;
a weather prediction model creation unit that creates the weather prediction model by learning the correlation between a person's vital signs and weather changes at the point where the vital signs appear, using the information accumulated in the data storage unit; ,
further comprising,
The weather prediction system described in Appendix 1.

(Appendix 7)
Information on the person's vital signs acquired by the vital sign acquisition unit and the appearance point and time of appearance of the vital signs, and information on the person's vital data acquired by the vital data acquisition unit and the measurement point and measurement time of the vital data. and a data storage unit that stores the weather observation data acquired by the weather observation data acquisition unit;
Using the information accumulated in the data storage unit, the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, and the changes in the person's vital data and the weather at the measurement point of the vital data. a weather prediction model creation unit that creates the weather prediction model by learning the correlation between the
further comprising,
The weather prediction system described in Appendix 2.

(Appendix 8)
a user information storage unit in which information regarding the user's meteorological illness is registered;
a user location acquisition unit that acquires information on the current location of the user;
Based on the result of the weather prediction of the user's current location obtained from the weather prediction system according to any one of Supplementary Notes 1 to 7 and information regarding the weather disease of the user, the onset of the weather disease of the user. A meteorological disease forecasting department that predicts
Equipped with
Meteorological disease prediction system.

(Appendix 9)
further comprising a user vital data acquisition unit that acquires the user's vital data,
The weather disease prediction unit predicts the onset of a weather disease in the user, taking into account the user's vital data.
The meteorological disease prediction system described in Appendix 8.

(Appendix 10)
The user vital data acquisition unit acquires information on the measurement time and measurement point of the vital data in addition to the user's vital data,
The meteorological disease prediction unit predicts the onset of a meteorological disease in the user, taking into consideration the measurement time and measurement point of the user's vital data.
The meteorological disease prediction system described in Appendix 9.

(Appendix 11)
further comprising a weather disease prediction notification unit that notifies a user who is predicted to develop a weather disease of weather disease prediction information;
The meteorological disease prediction system according to any one of Supplementary notes 8 to 10.

(Appendix 12)
further comprising a dosing timing notification unit that notifies a user who is predicted to develop a weather disease of the timing of taking a medicine to suppress the onset of the weather disease;
The meteorological disease prediction system according to any one of Supplementary notes 8 to 11.

(Appendix 13)
further comprising a recommended action notification unit that notifies a user who is predicted to develop a weather disease of recommended actions before or after the onset of the weather disease;
The meteorological disease prediction system according to any one of Supplementary notes 8 to 12.

100 Weather prediction system, 10 Weather prediction device, 11 Vital sign acquisition unit, 12 Weather observation data acquisition unit, 13 Weather prediction unit, 14 Weather prediction transmission unit, 15 Vital data acquisition unit, 16 Disaster prediction unit, 17 Disaster prediction notification unit , 20 Weather prediction model creation device, 21 Data storage unit, 22 Weather prediction model creation unit, 23 Weather prediction model storage unit, 23a Weather prediction model, 200 Weather disease prediction system, 30 Weather disease prediction device, 31 User information storage unit, 32 User position acquisition section, 33 Weather disease prediction section, 34 Weather disease prediction notification section, 35 User vital data acquisition section, 36 Dosing timing notification section, 37 Recommended action notification section, 50 Processing circuit, 51 Processor, 52 Memory.

Claims

a vital sign acquisition unit that acquires information on a person's vital signs and the point and time of appearance of the vital signs;
a weather observation data acquisition unit that acquires weather observation data;
Using a weather prediction model obtained by learning the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, the vital signs of the person acquired by the vital sign acquisition unit and the vital signs of the person concerned are a weather forecasting unit that makes weather predictions from weather observation data at the appearance point and appearance time;
A weather forecasting system equipped with
further comprising a vital data acquisition unit that acquires the person's vital data and information on the measurement point and measurement time of the vital data,
The weather prediction model learns not only the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, but also the correlation between the person's vital data and changes in the weather at the point where the vital data is measured. This is a weather prediction model obtained by
The weather prediction unit uses the weather prediction model to obtain the human vital signs acquired by the vital sign acquisition unit, weather observation data at the appearance point and time of the vital signs, and the vital signs acquired by the vital data acquisition unit. Making weather predictions from human vital data and meteorological observation data at the measurement point and time of the vital data;
The weather prediction system according to claim 1.
The vital sign acquisition unit analyzes a text or image posted to a social networking service and extracts the vital signs of the person who posted the text or image.
The weather prediction system according to claim 1 or 2.
Further comprising a weather forecast transmission unit that notifies the user of the result of the weather forecast for a point specified by the user in response to a request from the user.
The weather prediction system according to any one of claims 1 to 3.
a disaster prediction unit that predicts the occurrence of a disaster based on the results of the weather prediction by the weather prediction unit;
a disaster prediction and notification unit that notifies users in areas where a disaster is predicted to occur, of disaster prediction information;
further comprising,
The weather prediction system according to any one of claims 1 to 4.
a data storage unit that stores information on the person's vital signs acquired by the vital sign acquisition unit and the appearance point and time of the vital signs, and weather observation data acquired by the weather observation data acquisition unit;
a weather prediction model creation unit that creates the weather prediction model by learning the correlation between a person's vital signs and weather changes at the point where the vital signs appear, using the information accumulated in the data storage unit; ,
further comprising,
The weather prediction system according to claim 1.
Information on the person's vital signs acquired by the vital sign acquisition unit and the appearance point and time of appearance of the vital signs, and information on the person's vital data acquired by the vital data acquisition unit and the measurement point and measurement time of the vital data. and a data storage unit that stores the weather observation data acquired by the weather observation data acquisition unit;
Using the information accumulated in the data storage unit, the correlation between a person's vital signs and changes in the weather at the point where the vital signs appear, and the changes in the person's vital data and the weather at the measurement point of the vital data. a weather prediction model creation unit that creates the weather prediction model by learning the correlation between the
further comprising,
The weather prediction system according to claim 2.
a user information storage unit in which information regarding the user's meteorological illness is registered;
a user location acquisition unit that acquires information on the current location of the user;
The weather disease of the user is determined based on the result of the weather prediction of the current location of the user obtained from the weather prediction system according to any one of claims 1 to 7 and information regarding the weather disease of the user. a meteorological disease prediction department that predicts the onset of
Equipped with
Meteorological disease prediction system.
further comprising a user vital data acquisition unit that acquires the user's vital data,
The weather disease prediction unit predicts the onset of a weather disease in the user, taking into account the user's vital data.
The meteorological disease prediction system according to claim 8.
The user vital data acquisition unit acquires information on the measurement time and measurement point of the vital data in addition to the user's vital data,
The meteorological disease prediction unit predicts the onset of a meteorological disease in the user, taking into consideration the measurement time and measurement point of the user's vital data.
The meteorological disease prediction system according to claim 9.
further comprising a weather disease prediction notification unit that notifies a user who is predicted to develop a weather disease of weather disease prediction information;
The meteorological disease prediction system according to any one of claims 8 to 10.
further comprising a dosing timing notification unit that notifies a user who is predicted to develop a weather disease of the timing of taking a medicine to suppress the onset of the weather disease;
The meteorological disease prediction system according to any one of claims 8 to 11.
further comprising a recommended action notification unit that notifies a user who is predicted to develop a weather disease of recommended actions before or after the onset of the weather disease;
The meteorological disease prediction system according to any one of claims 8 to 12.