JP2007057271A - System for detecting amount of change in accumulated heat - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To highly accurately predict how much a specific person actually feels cold and heat in a period between the following day until few days later or at an outside location. <P>SOLUTION: The system is provided with an input means 2 capable of inputting specific data including information on at least time and date or areas; a meteorological information database 3 in which meteorological data is accumulated; an information processing means 4 for computing both the amount of heat S accumulated in a human body and the amount of change Δ in accumulated heat through the use of both the specific data and the meteorological data; and an output means 5 for outputting the calculated amount of heat S accumulated in the human body and the calculated amount of change Δ in accumulated heat. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention is a system for detecting a change in heat storage that can be suitably used when it is desired to know in advance how much light or thick clothing should be worn on the day of going out or outdoor events. It is about.

One of the concerns for those who are planning to go out or travel, such as travel, business trips, etc., is whether it is hot or cold on the day or in the local area, and how thin should it be if it is hot, and how cold it is If so, how thick should I wear? In such cases, many refer to the weather forecast.
However, only the weather data such as temperature and humidity obtained from the weather forecast is ambiguous, for example, "It will be hot because it is sunny and over 30 degrees Celsius" Only the result is obtained and it is not necessarily accurate.

By the way, various calculations using weather data are performed, and the calculation result is verified by a report of bodily sensation, etc., and an index (hereinafter referred to as a thermal environment index) that derives “comfort” and “discomfort” has already been obtained. Has been developed. For example, Yaglow's effective temperature (ET), discomfort index (DI) adopted by US weather stations, etc., wet bulb globe temperature index (WBGT), wind cooling index (WCI) adopted by ISO, new effective temperature SET of Gaggi The Fanger comfort equation (PMV).
On the other hand, conventionally, a weather information experience information notification system has been proposed (see Patent Document 1). In this system, it is explained that weather data obtained from weather forecast etc. and system user's sensation information can be integrated, the degree of sensation temperature can be corrected systematically, and the sensation temperature close to the actual feeling can be derived. ing.
JP 2004-53520 A

As described above, based on only the weather data included in the weather forecast, we can accurately predict how a particular individual will feel hot and cold the next day to several days ahead or on the go. It is very difficult to determine how thin or thick to wear.
Therefore, using the above-mentioned thermal environment index, it seems that “comfort” and “discomfort” can be obtained as numerical values and it is possible to know the experience, but in fact, it is important to use the thermal environment index. There is a problem.
First of all, the thermal environment index is defined on the assumption that it is used indoors where the environment can be controlled. For example, the temperature 22 is set to a comfortable temperature at the new effective temperature (SET) of Gaggi. Considering ˜26 ° C., calm airflow, and humidity of 20-80%, every day becomes an unpleasant day in the outdoor environment except for a certain period of spring and autumn, and the information itself has no value at all. The discomfort index DI is merely a ratio of how many people feel discomfort regarding the correlation between temperature and humidity, and it seems to be useful only in summer. In view of these matters, the thermal environment index is not sufficient as an index of the bodily sensation that humans use outdoors.

Secondly, the time zone, individual differences, etc. are not considered at all in the process of calculating the thermal environment index, so it is not possible to predict the feeling of a specific individual with high accuracy. Taking the discomfort index 80 (80% of people feel uncomfortable) as an example, there are many cases in which it is not possible to determine whether the person is included in the 80% side or the 20% side.
On the other hand, the system disclosed in Patent Document 1 calculates the sensible temperature, but Patent Document 1 does not disclose a specific method for calculating the sensible temperature. It is thought that indicators are used. Therefore, as described above, it is not possible to determine the experience. In addition, it is said that it is possible to derive a temperature that is close to the actual feeling by correcting the degree of the temperature to be experienced systematically, but there is a lack of explanation on how to “correct it systematically”. .

As a result of repeated research, the inventors of the present application paid attention to the fact that the human sensation is affected by various factors. In other words, not only temperature and humidity but also factors such as wind speed and solar radiation have a great influence on the bodily sensation. In addition, even at the same temperature, factors such as the season, the amount of activity of the human body, differences among individuals, and the difference from the environment immediately before that have a great influence. This can be easily understood from the fact that a person who has entered a room with a room temperature of 20 ° C. from a room having a higher temperature and a person who has entered the room from a room having a lower temperature have different feelings (feelings).
Therefore, the inventor of the present application searches for physical quantities calculated from a plurality of factors such as weather data, personal data, seasons, etc., and as a result, the amount of heat accumulated in the human body (the amount of heat stored in the human body) and the amount of change (the amount of stored heat change). ). By using the amount of heat stored in the human body and the amount of change in stored heat, for example, it is possible to surely know the sensation that humans feel outdoors, and to eliminate seasonal differences and individual differences related to the sensation.

  The present invention has been made in view of the above circumstances, and based on the idea of human body heat storage amount and heat storage change amount, a specific individual can find out as a feeling from the next day to the next few days or on the go. The amount of heat storage change that can predict how hot or cold is felt with high accuracy and can be used effectively in real life (for example, how much light or thick should be worn) An object of the present invention is to provide a detection system.

In order to achieve the above object, the present invention has taken the following measures.
That is, the heat storage change amount detection system according to the present invention is input by input means capable of inputting specific data including at least date / time or area information, a weather information database storing weather data, and the input means. Information processing means for calculating a human body heat storage amount that is a heat amount accumulated in a human body using specific data and weather data of a weather information database, and calculating a heat storage change amount that is a change amount of the human body heat storage amount; Output means for outputting the heat storage change amount calculated by the information processing means, and the information processing means provides the user with a reference value and a scheduled value of specific data required to output the heat storage change amount. An information requesting unit that prompts the user to input, an information collecting unit that captures a reference value and a scheduled value of the input specific data, and weather data corresponding to the reference value of the specific data. A reference value calculation unit that obtains a reference value of the human body heat storage amount using the weather data and the reference value of the specific data, and imports the weather data corresponding to the scheduled value of the specific data from the weather information database In addition, a predicted value calculation unit for obtaining a predicted value of the human body heat storage amount using the meteorological data and the predetermined value of the specific data, and taking a difference between the obtained reference value and the predicted value of the human body heat storage amount as a heat storage change amount It has a change amount calculation unit to be obtained, and a change amount output unit for sending the heat storage change amount obtained by the change amount calculation unit to the output means.

Preferably, the information processing unit converts the heat storage change amount obtained by the change amount calculation unit into a body sensitivity felt by a human due to the heat storage change amount, and outputs the body sensitivity. It is good to have a part.
Further, the body sensitivity determination unit determines body sensitivity as “cold” or “cool” when the sign of the heat storage change amount is negative, and “hot” or “when the sign of the heat storage change amount is positive. The body sensitivity may be determined as “warm”.
In addition, the information processing means obtains in the past a personal information database in which a relationship between a human body heat storage amount, a heat storage change amount, and body sensitivity is recorded for each user, registration information for identifying the user, and the like. The information request unit that prompts the user to input the body sensitivity actually held for the amount of stored heat storage and the corresponding amount of stored human body, the input body sensitivity and the amount of stored heat storage obtained in the past, and After associating the corresponding human body heat storage amount, the learning unit that stores the input registration information in the personal information database, the human body heat storage amount, the heat storage change amount, and the body sensitivity stored in the personal information database It is preferable to include a determination correction unit that calculates body sensitivity in accordance with a user's sense from the heat storage change amount using the relationship.

  The calculation of the amount of heat stored in the human body in the prediction value calculation unit and the reference value calculation unit described above may be performed using Equation (1).

  R, C, K, and E in equation (1) may be calculated using equations (2) to (5).

  The information processing means is realized by a server computer connected to a network, the input means and the output means are realized by a client computer connected to the network, and the weather information database is stored in the network. It may be configured to be provided in another computer connected to the computer.

  In the heat storage change detection system according to the present invention, based on the idea of heat storage change that shows how the human body heat storage changes, a specific individual from there the next day to a few days ahead, or on the go It is possible to predict with high accuracy how you feel the heat and cold. Accordingly, this can be used effectively in real life (for example, determination of how thin or thick to wear).

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[First Embodiment]
FIG. 1 shows a first embodiment of a heat storage change detection system 1 according to the present invention.
This detection system 1 is for knowing the heat storage change amount Δ (how the human body heat storage amount S changes), and the user of the system (the person to be detected of the heat storage change amount Δ) is the next day to several In order to predict how the heat or cold will be felt on the day or on the go, this is a system for determining the amount of heat storage change Δ as a numerical value and notifying the user.

The detection system 1 has an input means 2 capable of inputting specific data including at least date / time or area information. In addition, it has a weather information database 3 in which weather data is accumulated. Furthermore, the detection system 1 uses the specific data and weather data described above to calculate the amount of heat stored in the human body, information processing means 4 that calculates the amount of change based on the amount of stored heat of the human body, and the calculated heat stored in the human body. Output means 5 for outputting the quantity S and the heat storage change amount Δ.
Specifically, the input means 2 is used to input specific data including information such as date and time, region, and the user's activity status, and the output means 5 is a human body heat storage amount S and a heat storage change amount Δ toward the user. Is about to be output. In this embodiment, as these input means 2 and output means 5, a client computer integrated with each other, or a portable information terminal such as a mobile phone, PHS, or PDA (hereinafter also referred to as a client) is adopted. The case is shown. Specifically, in the case of a computer, a keyboard or mouse is used as the input unit 2 and a monitor is used as the output unit 5.

The information processing means 4 is realized in the form of a program on a server computer (hereinafter also referred to as a server).
The weather information database 3 stores weather data such as temperature and humidity (water vapor pressure) for each date and time and region. Although it may be data recorded on a hard disk in the server, in this embodiment, weather data published by the Japan Meteorological Agency or the like is used.
These input / output means 2 and 5 (client computer), information processing means 4 (server computer), and weather information database 3 are connected via the Internet, and can transmit information to each other.

As shown in FIG. 2, the information processing means 4 in the server includes an information request unit 10, a reference value information collection unit 11, a reference value calculation unit 12, a planned value information collection unit 13, and a prediction. A value calculation unit 14, a change amount calculation unit 15, and a change amount output unit 16 are included.
The information requesting unit 10 prompts the user to input a reference value and a scheduled value of specific data necessary for obtaining the heat storage change amount Δ.
The standard value of specific data refers to the type of activity, such as the season, date and time (date / time element), place (regional element), walking or running, etc., used as the reference when calculating the heat storage change Δ Element) information. Further, the scheduled value of the specific data is a date / time element, a regional element, an activity element, or the like for which it is desired to know the heat storage change amount Δ.

Specifically, the date and time element is, for example, July 30, 2005, 13:00. When the user moves beyond the date change line between the reference value of the specific data and the planned value, if the time difference is small, either local time may be used, but if the time difference is extremely large It is preferable to use a local time that matches the reference value and the scheduled value.
The regional element is, for example, a place name such as Tokyo, Osaka, Chiyoda Ward, Mitaka City, Naniwa Ward or Suita City. It may be a pin point such as Shimbashi or Umeda. Of course, country information is included if necessary. In order to increase the accuracy, it is preferable to include topographic features such as a building street, a residential area, a golf course, the sea, and a mountainous area.

The activity element is a type of activity such as rest, walking, sports, and various work. A discriminant or numerical table that can be indexed, such as human metabolic rate or exercise intensity, for each type of activity may be provided in the information processing means 4 in advance.
The reference value and the scheduled value of these specific data are naturally allowed when the regional element and the activity element are the same, but at least the date and time elements must be different.
When the user inputs such information via the input means 2 of the client, the information is transmitted to the server through the Internet, and the information collecting unit 11 for reference values takes in the information.

The reference value calculation unit 12 downloads weather data corresponding to the reference value of the specific data captured by the reference value information collecting unit 11 from the weather information database 3. The meteorological data to be captured is the temperature, humidity (water vapor pressure), and the like actually measured at a reference value (a date / time element, a regional element, an activity element, etc. as a reference for comparison). In addition, the reference value calculation unit 12 uses the weather data and the reference value of the specific data to obtain the reference value S _B of the human body heat storage amount.
The human body heat storage amount S is obtained using equation (1).

The units of S, M, R, C, K, and E are all (W / m ² ), but may be (kcal / m ² h).
When the human body heat storage amount S calculated by this equation is +, this indicates a state in which heat flows into the human body, and generally means a state of feeling “hot”. On the other hand, when the human body heat storage amount S is −, this indicates a state in which heat flows out from the human body, and generally means a state of feeling “cold”.

In the formula (1), M is the caloric output heat (metabolic calorie) of the human body, and is a value specified by the “activity element” included in the scheduled value or the reference value. When walking on a flat ground, it is about 116 (W / m ² ).
R is the amount of heat radiated from the human body or the amount of heat transferred by radiation from the surroundings to the human body. In the case of this embodiment, Formula (2) is used.

Equation (2) uses Stefan-Boltzmann's law. t _s is the average human skin temperature (about 33 ° C.), t _r is the temperature of the peripheral wall (black body), and σ is the Stefan-Boltzmann constant (5.67 × 10 ⁻⁸ Wm ⁻² K ⁻⁴ ). It is. It should be noted that the t _r can be used for the temperature.
C is the amount of heat that enters and exits the human body when the wind strikes the human body, in other words, the amount of heat that enters and exits the human body as air convects. In the case of the present embodiment, Equation (3) is used. calculate.

In this equation, h _c is k√V, k is a constant (usually 2.0, but there are individual differences), and V uses the wind speed (m / s). T _a is the ambient temperature [° C.].
The amount of heat indicated by K in the formula (1) means the amount of heat taken away or given by a person touching something. For example, it is the amount of heat taken from the human body to the clothes, and in the case of the present embodiment, it is calculated using Equation (3).

h _k is the thermal conductivity (W / m ² · ° C.) of the contact object (for example, underwear or clothes), but since the value is very small, the calculation of K itself can be ignored.
E is the amount of heat released due to human sweating, and is the amount of heat taken away as the sweat evaporates. Therefore, in the formula (1), addition is only performed with a minus value. In the case of this embodiment, it calculates using Formula (5).

In this equation, ω is an amount indicating the wetness of the skin, and takes a value of ω = 0 (dry) to 1 (wet). h _e may be defined as 2.2h _c, p _ssk is the average skin temperature (e.g., 33 ° C.) saturated steam pressure (hPa), p _a is the water vapor pressure of the air surrounding the periphery (hPa) is there.
In calculating the human body heat storage amount S, it is preferable to take into account the influence of the thermal conductivity of the clothes worn by the user. In this case, what is necessary is just to make it include the material and type (skin exposure degree) of clothes, the number of layered clothes, etc. as an input item to the input means 2 which the said information request | requirement part 10 prompts a user.

On the other hand, the information collecting unit 13 for the planned value is to capture the planned value input from the input unit 2.
The predicted value calculation unit 14 downloads weather data corresponding to the scheduled value of the specific data captured by the information collection unit 13 from the weather information database 3. The meteorological data to be taken in is the predicted temperature, predicted humidity (expected water vapor pressure), etc. corresponding to the planned value (date element, regional element, activity element, etc. for knowing the heat storage change amount Δ). In addition, the predicted value calculation unit 14 uses the predetermined value of the specific data and the weather data to obtain the prediction value S _P output body heat storage amount. For the calculation of the human body heat storage amount S, the formula (1) already described is used.

The human body heat storage amounts S _B and S _P obtained by the reference value calculation unit 12 and the predicted value calculation unit 14 are sent to the change amount calculation unit 15. In the change amount calculating unit 15 calculates the heat storage amount of change Δ as the difference between the predicted value S _P output reference value S _B and the human body heat storage amount of the human body heat storage amount. S _B <heat storage amount of change if S _P delta is obtained as a positive value, S _B> is S heat storage amount of change if _P delta obtained as a negative value, the heat storage changes if S _B = S _P The quantity Δ is zero.
Thus, the reason for obtaining the heat storage change amount Δ as the difference of the human body heat storage amount S is as follows.

That is, as described above, when the human body heat storage amount S is positive, it indicates a situation where heat flows into the human body, and when the human body heat storage amount S is negative, the situation where heat flows out from the human body. Show.
However, the inventor of the present application has revealed that it is not only related to the amount of heat accumulated in the human body that humans feel hot and cold, but also to changes thereof.
For example, the human body heat storage amount (reference value) S _B at a certain point in time yesterday is 80 (W / m ² ), and the human body heat storage amount (planned value) in the afternoon today is 40 (W / m ² ). In this case, looking only at the value of the heat storage amount of the human body, it is the same “hot” situation yesterday and today, but when the heat storage change amount Δ which is the change amount is obtained, it is −40 (W / m ² ). Many people will feel “cool” or “comfortable”.

Also, consider a case where a person working for a company in Osaka travels to Tokyo from noon. The human body heat storage (reference value) S _B in Osaka in the morning was −80 (W / m ² ), and the human body heat storage (planned value) in the afternoon in Tokyo was −30 (W / m ² ). In this case, looking only at the amount of heat stored in the human body, both Osaka and Tokyo are in the same “cold” situation, but the amount of change in heat storage Δ, which is the amount of change, is +50 (W / m ² ). Would feel "Tokyo is warm".
In other words, the thermal storage change amount Δ has a great influence on the thermal sensation (sensation) of heat and cold. Therefore, the detection system of the thermal storage change amount of the present embodiment is the reference value (reference) of the specific data. and the human body heat storage amount S _B location and at the date and time data), determine the human body heat storage amount S _P output preset value of the specific data (location and time data want to know), so that determining the heat storage amount of change Δ is the difference .

The obtained heat storage change amount Δ is output via the change amount output unit 16. At the same time, the predicted human body heat storage amount S _P is also output.
Next, a usage mode of the heat storage change amount detection system 1 having the above configuration will be described based on a flowchart shown in FIG.
A user who intends to use the heat storage change amount Δ detection system 1 first makes a state in which a client can access the server through the Internet.
After that, a login screen is displayed on the client, and the user inputs registration information (name, address, sex, date of birth, code number, user ID, password, etc.) using the input means 2, User authentication is performed (S100). It is sufficient to input a plurality of these at the first time, and thereafter, the user ID and password become the registration information.

After the personal authentication is completed, the information processing means 4 displays a screen as shown in FIG. 4 on the client computer and allows the user to select and confirm the purpose of use of the system. When the user selects the prediction of the heat storage change amount Δ, the information processing means 4 displays the screen shown in FIG. 5 by the information request unit 10 and prompts the user to input a reference value. Therefore, the user performs a predetermined input using the input means 2 according to this (in this case, walking state in Chuo-ku, Osaka City at 9:00 February 2, 2005).
At the same time, the information request unit 10 prompts the user to input a scheduled value. Accordingly, the user makes a predetermined input using the input means 2 according to this (in this case, at 9 o'clock on February 3, 2005, in a walking state in Chuo-ku, Osaka city, and at 15:00 on February 3, 2005, Tokyo). Walking state in Chiyoda-ku) (S101). As for the planned value, a plurality of types having different contents are input to the user, and the collection of meteorological data and the calculation of the predicted human body heat storage amount S _P are executed according to each input scheduled value. It may be. In that case, a plurality of input fields may be provided in the display screen as shown in FIG.

Thereafter, by pressing a transmission button on the screen of FIG. 5, the reference value and the scheduled value of the specific data described above are transferred to the server via the Internet. The transferred reference value and scheduled value are taken in by the reference value information collecting unit 11 and the scheduled value information collecting unit 13 provided in the information processing means 4 on the server.
Next, the reference value calculation unit 12 and the predicted value calculation unit 14 take in the meteorological data corresponding to the taken in reference value and scheduled value from the weather information database 3 (S102).
Then, the reference value calculation unit 12 obtains the reference human body heat storage amount S _B using the captured weather data and the reference value, and the predicted value calculation unit 14 uses the acquired weather data and the planned value to calculate the planned human body. A heat storage amount S _P is obtained (S103).

Next, the change amount calculation unit 15 compares the reference human body heat storage amount S _B obtained by the reference value calculation unit 12 with the predicted human body heat storage amount S _P obtained by the prediction value calculation unit 13. And the thermal storage change amount (DELTA) is calculated | required (S104).
The heat storage change amount Δ is output to the output means 5 by the change amount output unit 16 (S105). Therefore, on the output means 5 (client), as shown in FIG. 6, a screen such that the heat storage change amount Δ is +30.0 (W / m ² ) is displayed. By looking at the amount of heat storage change Δ displayed as a numerical value in this way, the user can determine whether it is hot or cold depending on whether it is positive or negative, and how much heat is actually felt from the magnitude of the numerical value. You can expect it to feel as cold.

Therefore, this can be used effectively in real life (for example, determination of how thin or thick to wear).
In addition, in FIG. 7, the example of each calculation result of Formula (1)-Formula (5) and the calculation result example of thermal storage variation | change_quantity (DELTA) are shown.

[Second Embodiment]
FIG. 8 shows a second embodiment of the heat storage change detection system according to the present invention. In the present embodiment, “body sensitivity”, which is the degree of feeling for weather conditions such as “hot” and “cold” actually felt by the user, based on the heat storage change Δ obtained by the change calculator 15. The body sensitivity determination unit 17 for obtaining
As described above, when the heat storage change Δ is positive, many people feel “hot” or “warm”, and when the heat storage change Δ is negative, many people feel “cold” or “cool”. . Therefore, the body sensitivity determination unit 17 determines body sensitivity as “cold” or “cool” when the sign of the heat storage change amount Δ is negative, and “hot” when the sign of the heat storage change amount is positive. The body sensitivity is judged as “warm”.
Specifically, the body sensitivity determination unit 17 includes a conversion table in which the human body heat storage amount S, the heat storage change amount Δ, and the body sensitivity are associated with each other, and the heat storage change amount Δ is calculated based on the human body heat storage amount S according to the conversion table. I try to change it to body sensitivity.

The conversion table is preferably created so that the human body heat storage amount S and the heat storage change amount Δ are distributed to a plurality of classes, and the average human feeling is applied to each rank. Naturally, if the class is set finely, it is possible to make a more detailed “heat storage change Δ → body sensitivity” conversion.
This eliminates the need for the user to determine whether the user is hot or cold by looking at the value of the heat storage change amount Δ, and makes the heat storage change amount detection system 1 easier to use.

[Third Embodiment]
As described above, when the heat storage change amount Δ is a positive value, it is felt as “warm to hot”, when it is negative, it is felt as “cool to cold”, and when it is zero, it is felt the same.
However, if everyone has the same heat storage change amount Δ, if everyone has the same body sensitivity, it is not so, and the way of feeling the heat storage change amount Δ varies from user to user.
In order to make the system reflecting such individual differences, the information processing means 4 of the heat storage change amount detection system 1 of this embodiment includes a personal information database 6 as shown in FIG. The personal information database 6 includes the user registration information (name, address, gender, date of birth, code number, user ID, password, etc.) as well as the human body heat storage amount S _B and the corresponding heat storage change amount Δ. The information (individual body sensitivity data) such as what body sensitivity the user actually has is accumulated.

In other words, the personal body sensitivity data is the amount of heat storage change Δ (actual value of heat storage change amount) at a certain point in the past and the amount of heat stored in the human body (the amount of heat stored in the human body) based on the meteorological data at that time. The reference value S _B ) is associated with the body sensitivity (hot, cold, etc.) held by the user having the user ID (ID-ABCD) at that time.
In addition, the information processing means 4 includes a learning unit 18. The learning unit 18 is a part that creates personal body sensitivity data (conversion table) stored in the personal information database 6.
Furthermore, the information processing means 4 uses the body sensitivity data (relationship between the body heat storage amount S, the heat storage change amount Δ, and the body sensitivity) stored in the personal information database 6 so that the body sensitivity conforms to the sense of the user. It has the determination correction | amendment part 19 which calculates.

The flow of processing in this embodiment is as follows.
Similar to the second embodiment, the change amount calculation unit 15 determines the heat storage change amount Δ.
Thereafter, the body sensitivity is determined based on the calculated heat storage change amount Δ. In the case of this embodiment, the body sensitivity determination unit 17 using a predetermined conversion table for all persons performs the determination. is not. The determination correction unit 19 determines body sensitivity using the personal body sensitivity data in the personal information database 6. By doing so, it is possible to reliably determine body sensitivity in accordance with the user's individual sense, and for example, individual differences such as gender differences and race differences can be eliminated.

The determined body sensitivity is output to the client output means 5 through the Internet.
In addition, without determining body sensitivity, the heat storage change amount Δ calculated by the change amount calculation unit 15 and the personal body sensitivity data are output and displayed on the client together, and the final judgment is made to be made by the user. There is no problem.
As shown in FIG. 10, in order to reliably update the personal body sensitivity data in the personal information database 6, the information requesting unit 10 sets the heat storage change amount Δ obtained in the past and the human body heat storage amount S corresponding thereto. On the other hand, it has a function of requesting the input means 2 to input the body sensitivity actually held by the user. The time of input is not particularly limited, and may be set when the system is used next time, may be set as the next day of the system use day or a convenient later day, or set as a daily routine. May be.

By the way, this invention is not limited to the said embodiment, It can change suitably according to embodiment.
The use of the system 1 is not limited to targeting humans, and it can be used for animal and plant breeding, seasonal product sales prediction, and indoor air conditioning control.
In calculating the human body heat storage amount S, “maximum value / minimum value of human body heat storage amount in one day”, “maximum value / minimum value of human body heat storage amount in one year”, or the like may be used.

It is a conceptual diagram of the detection system of the thermal storage change amount. It is a block block diagram of the information processing means concerning 1st Embodiment. It is the flowchart which showed the process in 1st Embodiment. It is the figure which showed the example of a screen display in a client. It is the figure which showed the example of a screen display in a client. It is the figure which showed the example of a screen display in a client. It is a figure which shows an example of the calculation result of a human body heat storage amount. It is a block block diagram of the information processing means concerning 2nd Embodiment. It is a block block diagram of the information processing means concerning 3rd Embodiment. It is the figure which showed the example of a screen display in a client.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Heat storage change detection system 2 Input means 3 Weather information database 4 Information processing means 5 Output means 6 Personal information database 10 Information request part 11 Information collection part for reference values 13 Information collection part for planned values 12 Reference value calculation part 14 predicted values Δ heat storage amount of change in the reference value S _P body heat storage amount of the predicted value calculation unit 15 change amount calculation unit 16 change amount output unit 17 sensible degree determining unit 18 learning unit 19 determines the correction unit S _B human body heat storage amount

Claims (7)

An input means capable of inputting specific data including at least date / time or area information;
A weather information database in which weather data is accumulated;
Using the specific data input by the input means and the weather data of the weather information database, the human body heat storage amount that is the amount of heat stored in the human body is calculated, and the heat storage change amount that is the change amount of the human body heat storage amount is calculated. Information processing means for calculating;
Output means for outputting the heat storage change amount calculated by the information processing means,
The information processing means includes
An information requesting unit that prompts the user to input a reference value and a scheduled value of specific data necessary to output the heat storage change amount;
An information collection unit that captures a reference value and a scheduled value of the input specific data;
A reference value calculation unit that obtains meteorological data corresponding to a reference value of the specific data from a weather information database, and calculates a reference value of the human body heat storage amount using the meteorological data and the reference value of the specific data;
A meteorological data corresponding to the scheduled value of the specific data is fetched from a meteorological information database, and a predicted value calculation unit for obtaining a predicted value of the human body heat storage amount using the meteorological data and the scheduled value of the specified data;
A change amount calculation unit that obtains a difference between a reference value and a predicted value of the obtained human body heat storage amount as a heat storage change amount,
A heat storage change amount detection system comprising: a change amount output unit that sends the heat storage change amount obtained by the change amount calculation unit to output means.   The information processing means includes a body sensitivity determination unit that converts the heat storage change amount obtained by the change amount calculation unit into a body sensitivity felt by a human due to the heat storage change amount, and outputs the body sensitivity. The heat storage change amount detection system according to claim 1, wherein:   The body sensitivity determination unit determines body sensitivity as “cold” or “cool” when the sign of the heat storage change amount is negative, and “hot” or “warm” when the sign of the heat storage change amount is positive. The system according to claim 2, wherein the body sensitivity is determined. The information processing means is a personal information database in which the relationship between the human body heat storage amount, the heat storage change amount and the body sensitivity is recorded for each user,
Registration information for identifying the user, an information requesting unit that prompts the user to input the body heat sensitivity actually held with respect to the heat storage change amount obtained in the past and the human body heat storage amount corresponding thereto,
A learning unit for storing the input body sensitivity, the amount of heat storage change obtained in the past and the human body heat storage amount corresponding to the input body sensitivity, and storing it in the personal information database together with the input registration information,
A determination correction unit that calculates body sensitivity in accordance with a user's sense from the heat storage change amount, using the relationship between the human body heat storage amount and the heat storage change amount and body sensitivity accumulated in the personal information database; The heat storage change amount detection system according to any one of claims 1 to 3, wherein the heat storage change amount detection system is provided. 5. The heat storage change detection system according to claim 1, wherein the human body heat storage amount is calculated by the formula (1) in the predicted value calculation unit and the reference value calculation unit.

6. The heat storage change detection system according to claim 5, wherein R, C, K, and E in equation (1) are calculated using equations (2) to (5).

The information processing means is realized by a server computer connected to a network, and the input means and the output means are realized by a client computer connected to the network,
The system for detecting a change in heat storage according to any one of claims 1 to 6, wherein the weather information database is provided in another computer connected to the network.

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