DE112020007162T5 - Greening shading system and cooling island system - Google Patents

Abstract

A green roof shading system (1) comprises a green roof shading unit (10) which creates a shady space by a green roof shading formed using a plant (12), a spray unit (16) which converts water into mist and sprays the mist onto the plant ( 12) sprays, and a mist control unit (26) that controls the operation of the spraying of the mist performed by the spraying unit (16) based on an air temperature of an environmental control area including the shaded space and a temperature schedule showing a target temperature of the environmental control area in represents each time range.

Description

Area

The present disclosure relates to a greenery shade system and a cooling island system, which are used outdoors as a countermeasure against heat mainly in summer.

background

Countermeasures are commonly taken against outdoor heat in summer, such as installing greenery shade to block sunlight and artificially create a shady space, and atomizing water and spraying the atomized water to make the air temperature fall below the ambient temperature to permit.

For example, Patent Literature 1 describes, as a shading cooling device, a device that includes a frame unit for growing a plant, poles for supporting the frame unit at a height higher than a human height, an artificial imitation plant made of a water-absorbent material and on the frame unit and spraying means for spraying water onto the plant and the imitation plant, the device cooling a shaded space created by the plant and the imitation plant by evaporation of water from the surfaces of the plant and the imitation plant.

citation list

patent literature

Patent Literature 1: Japanese Patent Laid-Open No. 2005-237261

Overview of the Invention

Technical problem

The technology described in Patent Literature 1 makes it possible to effectively block the sunlight even when the plant has not grown sufficiently by placing the imitation plant on the stand unit. Further, spraying water on the plant and plant imitation allows to lower the air temperature in the shaded room.

However, in the technology described in Patent Literature 1, the water is sprayed at predetermined intervals or at predetermined times. That is, water is sprayed without considering the conditions such as the temperature of the shaded space, which poses a problem that the shaded space cannot be maintained in a comfortable condition in some cases. For example, if the air temperature is high, the water may be insufficiently sprayed, so the air temperature will drop only slightly and a comfortable environment cannot be created. In addition, water can be sprayed even when there is no need to lower the air temperature, thereby lowering the air temperature, which may deteriorate a sense of comfort.

The present disclosure has been made in view of the above, and an object of the present disclosure is to provide a plant shade system capable of maintaining the interior of a shaded space created by a plant shade in a desired state.

the solution of the problem

In order to solve the above-described problems and achieve the object, a plant shade system according to the present disclosure includes: a plant shade unit for creating a shaded space by a plant shade formed using a plant; a spray unit for converting water into mist and spraying the mist onto the plant; and a mist control unit for controlling a mist spraying operation performed by the spraying unit based on an air temperature of an environmental control area including the shaded space and a temperature map representing a target temperature of the environmental control area in each time range.

Advantageous Effects of the Invention

A vegetation shading system according to the present disclosure has an advantage that it can maintain the interior of a shaded space created by a vegetation shading in a desired state.

character list

• 1 14 is a diagram showing an example configuration of a refrigerated island system implemented using greenery shade systems according to a first embodiment.
• 2 14 is a diagram showing an example configuration of a plant shade unit of the plant shade system according to the first embodiment.
• 3 14 is a diagram showing an example configuration of an environment control device of the green plant shade system according to the first embodiment.
• 4 14 is a diagram showing an example configuration of a data management device according to the first embodiment.
• 5 14 is a flowchart showing an example of operation of a mist control unit of the grass shade system according to the first embodiment.
• 6 14 is a diagram showing an example of hardware that implements the environment control device of the plant shade system according to the first embodiment.
• 7 14 is a diagram showing an example configuration of a refrigerated island control device according to the first embodiment.
• 8th 14 is a diagram for describing an operation of the refrigerated island control device according to the first embodiment.
• 9 14 is a diagram showing an example of the functional block configuration of a user terminal according to the first embodiment.
• 10 14 is a diagram showing an example of the functional block configuration of a management terminal for maintenance according to the first embodiment.
• 11 12 is a diagram showing an example of the functional block configuration of a management terminal operated by planning personnel according to the first embodiment.
• 12 14 is a diagram showing an example configuration of a mist control unit included in an environment control device according to a second embodiment.
• 13 14 is a diagram showing an example configuration of a greenery shade installation site selection function unit included in a refrigerated island control device according to the second embodiment.
• 14 14 is a diagram showing an example configuration of a mist control unit included in an environment control device according to a third embodiment.
• 15 Fig. 12 is a diagram showing an example configuration of a neural network.

Description of the embodiments

A green roof system and a cooling island system according to the embodiments of the present disclosure will be described in detail below with reference to the drawings.

First embodiment

1 10 is a diagram showing an example configuration of a refrigerated island system 100 implemented using greenery shade systems according to a first embodiment.

The refrigerated island system 100 includes one or more

Greenery shading systems 1, a data management device 3, a refrigerated island control device 4, a user terminal 5, a management terminal 6 for maintenance purposes, and a management terminal 7 operated by planning personnel.

Each of the greenery shade systems 1 includes a greenery shade unit 10 that creates a shaded space by a greenery shade formed using a plant such as passionflower, and an environment control device 20 that controls the greenery shade unit 10 . The vegetation shade system 1 sprays atomized water onto the vegetation shade of the vegetation shade unit 10 and allows the sprayed water to evaporate to cause the air temperature to drop below ambient temperature.

The data management device 3 , in conjunction with the environment control device 20 , controls a forest therapy effect generated by negative ions, phytoncides and the like within the shaded space created by the greenery shading unit 10 .

The cooling island control device 4 controls the operation of each of the greenery shading systems 1 from a more macroscopic perspective, and thus causes a wind to blow in a local area where each of the greenery shading systems 1 is installed to achieve the cooling effect of the wind.

The user terminal 5 is a terminal carried by a user who uses the grass shade system 1 . The user terminal 5 collects information about the green plant shade system 1 via the data management device 3 to provide services to the user such as guiding the user to a nearby vegetation shading system 1 and providing notification of a condition, such as air temperature, within the shaded space created by the vegetation shading system 1 .

The management terminal 6 for maintenance is a terminal for use by a worker involved in the configuration and maintenance of the grass shade system 1 . The management terminal 6 for maintenance is used by a worker for remote initialization and remote maintenance of the environmental control device 20, the data management device 3, and the refrigerated island control device 4.

The management terminal 7 for planners is a terminal for use by the planners of the refrigerated island system 100, and has functions to support decision-making of the planners regarding the installation locations and the number of installations of the greenery shading systems 1.

in the in 1 As shown, the refrigerated island system 100 implements the data management device 3 and the refrigerated island control device 4 in the cloud. The data management device 3 and the environment control device 20 of the green cover shading system 1 can communicate with each other via cables or wirelessly. Further, the data management device 3 and each of the user terminal 5, the management terminal 6 for maintenance and the management terminal 7 operated by planning personnel can communicate with each other for wireless.

In the cooling island system 100 configured as described above, each of the greenery shade systems 1 sprays atomized water on the greenery shade formed using passion flowers to create an environment with an air temperature lower than the ambient temperature in which a visitor feels comfortable . The atomized water is prepared taking into account the conditions (particularly, air temperature, humidity and/or the like) of the shady space created by shading the passion flower and also keeping the conditions suitable for the growth of the passion flower in mind , sprayed, details of which will be described later. It should be noted that in the following description, atomizing and spraying of water, i. H. the spraying of atomized water, which can possibly be described as "spraying a mist".

In the cold island system 100, the data management device 3 provides the user with information about each of the greenery shading systems 1, such as information on the operation status of each of the greenery shading systems 1, conditions such as the temperature, humidity and wind of the shaded space created by each of the greenery shading systems 1, the Installation location of each of the green roof shading systems 1 and the like. This information is made available to the user using the user terminal 5 . Further, the refrigerated island control device 4 in the refrigerated island system 100 individually controls the operation of each of the plurality of greenery shade systems 1 installed in a local area remote from each other, thus generating a higher air temperature place and a lower air temperature place in the local area thereby letting a wind blow in the local area.

2 12 is a diagram showing an example configuration of the plant shade unit 10 of the plant shade system 1 according to the first embodiment. The green area shading unit 10 comprises a shading frame 11, a passion flower bush 12, a misting unit 13, an irrigation unit 14 and a pump 15.

The green roof shading unit 10 has a basic part including the shading frame 11 and the passion flower bush 12 intertwined with the shading frame 11 and forming a roof. This part serves as the greenery shade that creates the shaded space. The misting unit 13 converts the water supplied by the operation of the pump 15 into mist and sprays this mist onto the leaves of the passion flower bush 12. The heat of vaporization of the water droplets generates cool air, which means that the air temperatures in and around the green shading can be reduced. The irrigation unit 14 provides automatic irrigation in which the water supplied by the pump 15 is directed to the root areas of the passion flower bush 12 without manual intervention, so that daily manual irrigation can be eliminated.

It should be noted that although the green cover shade unit 10 uses the passion flower shrub 12 of the passiflora family formed from the passion flower, in the present embodiment, besides the passion flower shrub 12, any plant which is unlikely to be contaminated with water in a Environment with high air temperature rots. Furthermore, there is the Bescha The frame 11 is made of iron or a resin, but the material is not limited to this and may be made of wood. The use of wood causes the wood to absorb water and provide a higher cooling effect through heat of vaporization. In addition, a water-absorbing material, such as glued wood chips or urethane, can be incorporated into the passiflora bush 12 . As a result, the cooling effect can be further improved by the evaporation heat.

The environment inside the shaded space created by the greenery shade unit 10 is controlled by the environment control device 20 and the data management device 3 in conjunction. The amount of mist to be sprayed and the timing of spraying the mist on the passion flower bush 12 are controlled by these components in conjunction to provide a comfortable shaded space by maintaining the air temperature and/or the like in the shaded space at an appropriate level. and to ensure the growth of the passion flower bush 12 and the maintenance of the green cover shading state by taking into account parameters (e.g. air temperature, CO2, lighting, etc.) that need to be considered in mist control for the passion flower bush 12 growth. That is, the environmental control device 20 controls the amount of mist to be sprayed and the timing of the spraying to provide a comfortable shaded space within the ranges of parameters (e.g., air temperature, CO2, lighting, etc.) considered for the growth of the passionflower bush 12 must. The environmental control device 20 controls the parameters that need to be considered for growth before the parameters that need to be considered for shaded space adjustment.

3 12 is a diagram showing an example configuration of the environment control device 20 of the green plant shade system 1 according to the first embodiment. The environmental control device 20 comprises a cloud interface unit 21, a device interface unit 22, a sensor unit 23, an actual data acquisition unit 24, a control unit 25 configured to have a fog control unit 26 and an irrigation control unit 27, a fog operation time management unit 28 and a Temperature plan management unit 29 includes. This environment control device 20 works in conjunction with the data management device 3 to control the environment, such as air temperature, inside and near the shaded space created by the greenery shading of the greenery shading unit 10 . The environmental control device 20 is configured using a personal computer (PC), programmable logic controller (PLC), and/or the like.

4 12 is a diagram showing an example configuration of the data management device 3 according to the first embodiment. The data management device 3 comprises an interface unit 31, a temperature change prediction unit 32, an actual data collection unit 33, a user application 34 configured to include a user service 341 and a remote control service 342, a fog operation time setting unit 35 and a temperature schedule setting unit 36.

The components of the environmental control device 20 and the components of the data management device 3 are described below. First, the components of the environmental control device 20 will be described.

The cloud interface unit 21 receives temperature change forecast information from the data management device 3, receives a setting request or change request related to mist operating time from the data management device 3, receives a setting request or change request related to a temperature schedule from the data management device 3, receives a change request related to a setting value of the environmental control device 20 from the data management device 3, receives an inquiry request for operational status information or an inquiry request for setting value information of the environmental control device 20 from the data management device 3, transmits greenery shade environmental data to the data management device 3, and transmits operational status information or setting value information of the environmental control device 20 to the data management device 3.

In this regard, the temperature change forecast information is information about a predicted air temperature change in one day in a local area where the green roof is installed, and is, for example, either meteorological information published by an external organization or information obtained through processing of this meteorological information is generated taking into account information specific to the local area where the green cover is installed. Fer Next, the mist operating time is the time range in which a spray unit 16, ie the spray unit 13, which forms the spray unit 16 with the pump 15, sprays a mist. This fog operation time range is set based on the temperature change forecast information. For example, a time range in which a predicted temperature is greater than or equal to a predetermined threshold is set as the fog operation time range. It should be noted that in an actual mist spraying operation, whether mist should be sprayed and/or is/are controlled in consideration of the data received from the sensor unit 23, ie the result of the observation by the sensor unit 23, as well as the spraying in the mist operation time range the amount of water to be sprayed as a mist. Further, the greenery shading environment data is data of air temperature, humidity, CO2, illumination, wind speed and the like inside and near the shaded space provided by the greenery shading.

The sensor unit 23 includes various sensors that are arranged in and around the green shading to collect data such as air temperature, humidity, CO2, lighting and/or wind speed inside and outside the green shading. Examples of the sensors included in the sensor unit 23 are a temperature sensor, a CO2 sensor, a humidity sensor, and an illumination sensor. The sensor unit 23 transmits the data detected by the various sensors to the device interface unit 22 as the plant cover environment data. The device interface unit 22 receives the data detected by the sensor unit 23, including the temperatures or the like inside and outside the plant shade, from the sensor unit 23 as the greening shading environment data. The green cover shading environment data is used by the mist control unit 26 (described later) to control the mist spraying operation performed by the spray unit 16 , and is transmitted to the data management device 3 via the actual data acquisition unit 24 and the cloud interface unit 21 .

The actual data acquisition unit 24 acquires the green area shading environment data output by the sensor unit 23 via the device interface unit 22 and supplies the green area shading environment data to the cloud interface unit 21 for transmission to the data management device 3.

The fog operation time management unit 28 manages the fog operation time. The fog operation time represents the fog operation time range, which is the time range in which the spraying unit 16 of the green cover shading unit 10 sprays a fog. Specifically, the fog operation time management unit 35 of the data management device 3 receives a setting request or a change request regarding the fog operation time range for the greenery shade from the maintenance-use management terminal 6 and a change request regarding the fog operation time range for the greenery shade from the cold island control device 4 and updates the setting thereof accordingly.

The temperature map management unit 29 manages the temperature map representing a target temperature of an environmental control area in each time range. Specifically, the temperature schedule management unit 29 receives a setting request or a change request related to the temperature schedule for greenery shade from the maintenance-use management terminal 6 and a change request related to the temperature schedule for greenery shade from the refrigerated island control device 4 via the temperature schedule setting unit 36 of the data management device 3 and updates the setting thereof accordingly. As used herein, the environmental control area refers to the area in which the sensor unit 23 senses the vegetation shading environment data and corresponds to a specific area in and around the shaded space created by the vegetation shading.

The mist control unit 26 controls the spraying operation of a mist performed by the spray unit 16 taking into account the green area shading environment data detected by the sensor unit 23 , the mist operating time range managed by the mist operating time management unit 28 and the temperature plan managed by the temperature plan management unit 29 . Specifically, the mist control unit 26 controls the pump 15 of the spray unit 16 to reduce a difference between the current air temperature obtained by the sensor unit 23 from the greenery shading environmental data and the target temperature specified at the actual time in the temperature map managed by the temperature map management unit 29, thereby reducing the amount and adjust the timing of spraying the mist on the leaves of the passiflora bush 12. Thus, the cool air resulting from the heat of vaporization of the water droplets is adjusted so that the air temperature of the environmental control area approaches the target temperature so as to be comfortable to create a pleasant environment. It should be noted that the mist control unit 26 may control the adjusting means instead of the pump 15 to adjust the amount of mist to be sprayed, or it may control both the pump 15 and the adjusting means to adjust the amount of mist to be sprayed and the timing of spraying the mist if an adjusting means for adjusting the amount of water, such as a misting unit faucet 17, is provided on the way of supplying water to the misting unit 13.

The fog control unit 26 adjusts the amount of fog spraying and the timing of the spraying, taking into account parameters (e.g. air temperature, CO2, lighting, etc.) that must be taken into account for the growth of the green cover, thus achieving both growth and maintenance the greening shading as well as the provision of a comfortable shady room. Further, when the sensor unit 23 acquires temperature information from temperature sensors installed in multiple locations, the mist control unit 26 adjusts the amount of mist to be sprayed and the timing of mist spraying to compensate for the variations in air temperature depending on the locations, and when When multiple pumps 15 are installed, it adjusts the amount of mist to be sprayed and the timing of mist spraying based on the individual pumps 15. In addition, in order to counteract cooling delay from the temperature schedule by the heat of vaporization, the mist control unit 26 can acquire the temperature change forecast information from the data management device 3 and proactively introduce the cooling to mitigate or prevent the cooling delay and achieve the target temperature more reliably. For example, the fog control unit 26 checks the predicted temperature at the start time of the fog operation time range at a time a certain period of time before the start of the fog operation time range, and starts controlling the spray unit 16 at a time based on the result of the comparison between the predicted air temperature and the current air temperature. thus proactively cooling the environmental control area.

The fog control unit 26 controls the spraying of fog in the green covering shading system 1, for example according to FIG 5 shown flowchart. 5 14 is a flowchart showing an example of the operation of the fog control unit 26 of the green plant shade system 1 according to the first embodiment.

As in 5 1, the fog control unit 26 first checks whether the current time falls within the fog operation time range (step S11). That is, the fog control unit 26 checks whether the current time falls within the fog time range managed by the fog time management unit 28 . If the current time is outside the fogging time range (step S11: No), the fog control unit 26 repeats the checking operation as to whether the current time falls within the fogging time range.

If the current time falls within the fog operation time range (step S11: Yes), the fog control unit 26 obtains sensor observation data, i. H. the greenery shade environment data, from the sensor unit 23 (step S12).

Next, the fog control unit 26 checks whether it is raining (step S13). When the sensors included in the sensor unit 23 include a rain sensor, the fog control unit 26 determines whether it is raining based on the grass shade environmental data obtained in step S12. If the sensors included in the sensor unit 23 do not include a rain sensor, the fog control unit 26 may be able to determine whether it is raining based on precipitation data for each local area that is available from an external organization. Alternatively, the determination of whether it is raining may be based on information about humidity observed by a humidity sensor rather than an amount of precipitation observed by a rain sensor. In view of the fact that the humidity reaches almost 100% when it rains, the mist control unit 26 determines that it is raining when the humidity is higher than a predetermined threshold value. If it rains (step S13: Yes), the fog control unit 26 returns to step S11 and continues the operation. That is, when it rains, there is no need to spray mist, and accordingly the mist control unit 26 does not cause mist to be sprayed.

Meanwhile, if it is not raining (step S13: No), the fog control unit 26 checks whether the air temperature of the environmental control area observed by the sensor unit 23 is higher than the target temperature (step S14). That is, the mist control unit 26 checks the temperature map managed by the temperature map management unit 29 to find the target temperature at the current time, and checks whether the air temperature of the environmental control area at the current time is higher than the target temperature. When the air temperature of the environmental control area is less than or equal to the target temperature (step S14: No), the Mist control unit 26 returns to step S11 and continues operation. That is, the mist control unit 26 does not cause a mist to be sprayed when the air temperature of the environment control area is equal to or lower than the target temperature in order to prevent an air temperature drop.

Alternatively, when the air temperature of the environmental control area is higher than the target temperature (step S14: Yes), the mist control unit 26 checks whether the humidity is lower than a target humidity (step S15). The target humidity may be a predetermined fixed value or a value calculated from the target temperature at the current time used in the determination in step S14. It is known that the level of comfort felt by a person depends mainly on air temperature and humidity, and that higher air temperature with the same humidity leads to greater discomfort. Accordingly, the fog controller 26 may set the target humidity to a lower value for a higher target temperature and the target humidity to a higher value for a lower target temperature. Otherwise, in step S15, the mist control unit 26 may use a discomfort index calculated from a combination of air temperature and humidity instead of humidity and determine whether the discomfort index is less than or equal to a threshold. When the humidity is equal to or higher than the target humidity (step S15: No), the fog control unit 26 returns to step S11 and continues the operation. That is, the mist control unit 26 does not spray mist when the humidity of the environmental control area is greater than or equal to the target humidity to compensate for a rise in humidity, i. H. to prevent an increase in discomfort.

Alternatively, if the humidity is below the target humidity (step S15: Yes), the mist control unit 26 checks whether a growth condition of the greenery shade is satisfied (step S16). The growth condition of the green shading is represented by parameters that must be taken into account for the growth of the passion flower bush 12 forming the green shading, in particular, the air temperature, the amount of water supplied, the temperature of the soil in which the passion flower bush 12 is planted, the water content of the soil and the like. For example, assuming that the air temperature suitable for the growth of the passion flower bush 12 is approximately between 20°C and 30°C, a temperature range of 20°C to 30°C is determined as the growing condition of the air temperature. Furthermore, water must be supplied to prevent the soil for the growth of the passion flower bush 12 from drying out. However, overwatering can cause root rot and death. Therefore, when the parameters include air temperature and watering amount, the mist control unit 26 checks whether the conditions are met, such as whether the air temperature falls within a temperature range suitable for the growth of the passion flower bush 12 and whether the watering amount does not reach a predetermined upper limit has. The upper limit of the watering amount is defined by a combination of the upper limit of the amount of water supplied to the passion flower bush 12 per watering operation and the upper limit of the amount of water supplied to the passion flower bush 12 in a predetermined period of time. When neither the amount of water supplied in a watering operation nor the total amount of water supplied in a predetermined period of time has reached the upper limit value, the mist control unit 26 determines that the watering amount has not reached the predetermined upper limit value. It should be noted that the mist control unit 26 also considers the amount of water supplied by the irrigation unit 14 to the passion flower bush 12 when determining whether the watering amount has reached the upper limit. That is, the mist control unit 26 determines that the growth condition is not satisfied when the sum of the amount of mist sprayed from the misting unit 13 to the passion flower bush 12 and the amount of water supplied from the irrigation unit 14 to the passion flower bush 12 has reached the upper limit. Although the above description refers to air temperature and watering rate, the mist controller 26 also determines whether the temperature and soil water content fall within the respective ranges suitable for growth.

If the growth condition of the grass shade is not satisfied (step S16: No), the mist control unit 26 returns to step S11 and continues the operation. That is, the fog control unit 26 does not cause a fog to be sprayed when the state of the environment control area does not satisfy the growth condition of the greenery shade.

Alternatively, when the growth condition of the greenery shade is satisfied (step S16: Yes), the mist control unit 26 causes a mist to be sprayed (step S17). In particular, the mist control unit 26 drives the pump 15 of the spray unit 16 for a predetermined fixed Period of time to spray a mist from the spray unit 13. With this operation, the mist control unit 26 can intermittently spray a mist from the spray unit 13 by repeatedly driving and stopping the pump 15 instead of driving the pump 15 continuously. The fog control unit 26 can adjust the amount of fog to be sprayed by the fog unit 13 based on the illumination or wind speed detected by the sensor unit 23 . For example, since the air temperature tends to rise when the weather is nice and the lighting is high, the mist control unit 26 controls that more mist is sprayed when the lighting is higher. In addition, since strong wind lowers the perceived temperature, the mist control unit 26 controls that less mist is sprayed when the wind is strong. In addition, when the spray unit 16 is configured to include multiple pumps 15, the mist control unit 26 controls the pumps 15 to create a homogeneous air temperature distribution in the environmental control area. That is, the mist control unit 26 controls the pumps 15 so that more mist is sprayed from the spray unit 13 installed in an area with a higher air temperature than from the spray unit 13 installed in an area with a lower air temperature. After the mist has been sprayed for the specified period of time, the mist control unit 26 returns to step S11 and continues the operation.

It should be noted that the mist control unit 26 may check in the above step S11 whether the current point in time is between a time that is a certain period of time before the start time of the mist operating time range and the end time of the mist operating time range, instead of checking whether the current time falls within the fog operating time range. For example, if the fog operating time range is from 12:00 p.m. to 2:00 p.m., the fog controller 26 checks whether the current time is between 50 minutes past 11:00 a.m. (11:50 a.m.) and 2:00 p.m. In this way, a control for proactively cooling the environmental control area can be performed before the start time of the mist operation time area.

As additional information, the heat of vaporization caused by spraying a mist has a cooling effect, and it is expected that the heat of vaporization caused by spraying a mist typically causes an air temperature drop of about 2°C to 3°C causes. For example, when measuring the effect of air temperature drop by spraying a mist in outdoor and semi-outdoor areas, an effect of air temperature drop of about 1.5 °C in outdoor and about 2 °C to 3 °C in semi-outdoor was observed.

Furthermore, it is reported that when using dry fog (fine fog with a size of 10 to 30 microns), an air temperature drop of 5 °C or more is expected, although the air temperature in a green house is lowered.

It is also reported that in addition to the effect of spraying a mist on leaves, a "water sprinkler effect" caused by the mist also being sprayed on the ground is said to lower the sensitive temperature by about 1.5°C.

In addition, it is reported that spraying a super fine mist (dry mist) has the following green shade growing effect. Spraying with superfine mist increases daytime humidity by about 10% on average and keeps the saturation deficit constant at a lower value than under non-superfine mist conditions. Furthermore, the superfine mist reduces the amount of CO2 consumed due to its ventilation-reducing effect. Spraying with superfine mist increases stomata opening, which increases the number of cut flowers by 5% to 19% of the three species studied. No difference in life before withering and nutrient content was found between super fine mist spraying and non-super fine mist spraying, so it can be assumed that super fine mist spraying improves the CO2 supply efficiency.

Returning to the description with reference to FIG 3 , the irrigation control unit 27 controls the pump 15 and the irrigation unit 14 based on information about the irrigation time, the irrigation amount, and the like that have been set in the irrigation control unit 27 . In this operation, the watering control unit 27 controls the watering unit 14 based on the watering amount by the watering unit 14 and the watering amount for the passion flower bush 12 provided by spraying a mist by the misting unit 13 . That is, the irrigation control unit 27 controls the pump 15 and the irrigation unit 14, making sure that the sum of the irrigation amount provided via the irrigation unit 14 and the irrigation amount provided via the spray unit 13 has an upper limit of the irrigation amount suitable for the growth of the passion flower bush 12 does not exceed.

A hardware configuration of the environmental control device 20 of the greening plant shading system 1 will now be described. 6 14 is a diagram showing an example of hardware that implements the environment control device 20 of the green plant shade system 1 according to the first embodiment.

Environmental control device 20 may be implemented using processor 101, memory 102, communication device 103, and interface circuitry 104. FIG. Examples of the processor 101 are a central processing unit (CPU) (also known as a processing unit, arithmetic unit, microprocessor, microcomputer, and digital signal processor (DSP)) and a system large scale integration (LSI). Examples of memory 102 are non-volatile or volatile semiconductor memory such as random access memory (RAM), read-only memory (ROM), and flash memory, and magnetic disk.

The actual data acquisition unit 24, the fog control unit 26, the irrigation control unit 27, the fog operation time management unit 28 and the temperature schedule management unit 29 of the environmental control device 20 are implemented by executing a program by the processor 101 to cause the processor 101 to work as these components. The program for causing the processor 101 to function as the actual data acquisition unit 24, the mist control unit 26, the irrigation control unit 27, the mist operation time management unit 28, and the temperature schedule management unit 29 is stored in the memory 102 in advance. The processor 101 reads this program from the memory 102 and executes the program, causing the processor 101 to function as the actual data collection unit 24, the mist controller 26, the irrigation controller 27, the mist run time manager 28, and the temperature schedule manager 29.

Further, the cloud interface unit 21 of the environmental control device 20 is implemented in the communication device 103 , and the device interface unit 22 is implemented in the interface circuit 104 . The interface circuit 104 is also used to output control data to the pump 15 and to the irrigation unit 14 .

The components of the data management device 3 are described below.

The interface unit 31 receives the greenery shade environment data from the environment control device 20, receives the operating state information or setting value information of the environment control device 20 from the environment control device 20, transmits the temperature change forecast information to the environment control device 20, transmits an inquiry request related to the operating state information or an inquiry request related to the setting value information of the environment control device 20 to the environment control device 20, transmits a change request to a setting value of the environment control device 20 to the environment control device 20, transmits a setting request or change request to the fog operation time to the environment control device 20, transmits a setting request or change request to the tempera turplan, receives a greening shading information request from the user terminal 5, transmits greening shade list information to the user terminal 5, transmits greening shading status information to the user terminal 5, transmits heatstroke warning information to the user terminal 5, receives an inquiry request related to the operating condition information or related to the setting value information of a specific environmental control device 20 from the maintenance-use management terminal 6, receives a change request related to the setting value of a certain environmental control device 20 from the maintenance-use management terminal 6, receives a setting request or change request related to the misting operation time of the greenery shade from the maintenance-use management terminal 6, receives a setting request or change request in Reference to the temperature plan for green cover shading from the maintenance-use management terminal 6, transmits the operating state information or setting value information of a specific environmental control device 20 to the maintenance-use management terminal 6, and receives predicted air temperature information from an air temperature forecasting service offered by an external organization.

The temperature change prediction unit 32 predicts the air temperature in each local area in each time area of this day, taking into account the air temperature forecast information acquired by the air temperature forecasting service offered by an external organization, and taking into account the independently predicted air temperature obtained under is derived from each applicable portion of the vegetation shading environment data captured in the actual data capture unit 33 using specific logic. The tempera The temperature change prediction unit 32 then transmits the temperature change prediction information, which is the prediction result, to the environment control device 20 via the interface unit 31

The actual data collection unit 33 aggregates the pieces of the grass shade environment data periodically collected from each of the environment control devices 20 via the interface unit 31 and collects the grass shade environment data in a database.

The user application 34 includes the user service 341 and the remote control service 342. The user service 341 has two functions, one of which is a vegetation shade search and status display function and the other is a heat stroke warning display function. The greenery shade search and status display function provides a list of greenery shades that meet a certain condition, such as being near a certain place, in response to a greenery shade information request from the user terminal 5 to this user terminal 5, and additionally reads information about the conditions (the air temperature, etc.) of a specific green cover from the actual data collection unit 33 and provides this information to this user terminal 5. The heat stroke warning display function sends heat stroke warning information to the user terminal 5 located in a local area where due to an air temperature rise to or above a there is a high risk of heat stroke at a certain level based on heat island information managed by the refrigerated island control device 4 . The heat island information is information showing the air temperature distribution in a local area where a plurality of the greenery shade systems 1 are installed. By examining this heat island information, information such as the air temperature at any location and the air temperature difference between any pair of locations in the local area can be determined.

When an inquiry request regarding the operating status information or regarding the setting value information of a specific environmental control device 20 is issued from the maintenance-use management terminal 6, the remote control service 342 acquires the operating status information or setting value information of that specific environmental control device 20 and transmits this information to the maintenance-use management terminal 6, that made the request. Further, when a request for a change in the setting value of a certain environmental control device 20 is issued from the maintenance-use management terminal 6, the remote control service 342 transmits the request for a change in the setting value to that environmental control device 20. The watering time, the watering amount, and the like in the watering control unit 27 in the environmental control device 20 described above are set and changed with this functionality

When a setting request or a change request regarding the fog operation time range for the greenery shade is issued from the maintenance-use management terminal 6, the fog operation time setting unit 35 receives this setting request or change request via the interface unit 31 and updates its setting based on the request. When a change request regarding the fog operation time range for the greenery shade is issued from the cold island control device 4, the fog operation time setting unit 35 updates its setting based on this change request. In any case, the fog operation time setting unit 35 transmits the setting request or change request to the environment control device 20 via the interface unit 31, and the fog operation time management unit 28 of the environment control device 20 receives the request via the cloud interface unit 21 and updates the setting accordingly.

When a setting request or a change request regarding the temperature schedule for the green cover is issued from the maintenance-use management terminal 6, the temperature schedule setting unit 36 receives this setting request or change request via the interface unit 31 and updates its setting based on the request. Further, the temperature schedule setting unit 36 updates the settings based on these change requests when change requests related to the fog operation time range and related to the temperature schedule for the green shade are issued from the cooling island control device 4 . In any case, the temperature schedule setting unit 36 transmits the setting request or change request to the environment control device 20 via the interface unit 31, and the temperature schedule management unit 29 of the environment control device 20 receives the request change via the cloud interface unit 21 and updates its setting accordingly.

It should be noted that the data management device 3 described above is implemented in an electronic computer in which a program for providing the functionality to be provided by the data management device 3 is installed. That is, the execution of the above program by the processor of the electronic computer implements the data management device 3.

The refrigerated island control device 4 will be described next. 7 12 is a diagram showing an example configuration of the refrigerated island control device 4 according to the first embodiment. Furthermore 8th 12 is a diagram for explaining an operation of the refrigerated island control device 4 according to the first embodiment, and illustrates a relationship between the refrigerated island control device 4 and the data management device 3.

The cold island control device 4 includes a greening shade installation site selection function unit 41, a cold island control function unit 42, a heat island situation management unit 43, and a wind data acquisition unit 44.

The plant shade installation location selection engine 41 simulates the wind generation caused by the plant shade installation and the cooling effect of that wind, thus aiding the decision-making of the refrigerated island system planning personnel regarding the plant shade installation sites and number of installations.

In particular, the refrigerated island system planning personnel uses the vegetation shading installation site selection engine 41 to change a theoretical air temperature of each local area by adjusting the number of vegetation shading installations at each applicable location and then simulating the wind (wind speed and wind direction) generated by a resulting temperature difference between the local areas is caused and the cooling effect of the wind. This makes it easier to consider and determine how many plant shades to install in which locations to lower the air temperature, especially in a warm area.

The cooling island control functional unit 42 controls the amount of mist to be sprayed and the timing of the mist spraying by the greenery shading unit 10 of each greenery shading system 1 with the intention of affecting the air temperature of the entire local area. This is done by comprehensively considering heat island information (information about the air temperature at each applicable location in that local area) managed by the heat island situation management unit 43, wind speed and wind direction data managed by the wind data acquisition unit 44, data such as the temperature managed by the actual data acquisition unit 33 of the data management device 3 and the temperature change forecast information of that day managed by the temperature change forecast unit 32 . This is done for a purpose of generating a wind by artificially generating a temperature difference between local areas. A specific control method is that, as in 8th 1, the cooling island control functional unit 42 issues a change request for changing the fog operation time range of each of the greenery shading systems 1 managed by the fogging operation time setting unit 35 of the data management device 3 and for changing the temperature schedule of each of the greenery shading systems 1 managed by the temperature schedule setting unit 36, which are then stored in the environmental control device 20 of each of the greenery shading systems 1 accordingly be updated. Each of the environment control devices 20 adjusts the amount of mist to be sprayed and the timing of the spraying to the grass shading unit 10 to thereby adjust the air temperature in each of the grass shading units 10 . The change in the air temperature in each of the green roof shading units 10 in turn affects the air temperature of the entire area. As described above, adjusting the air temperature of each area (each area where the greenery shade unit 10 is installed) in a local area results in a temperature difference between the local areas, thereby generating a wind. This wind has a cooling effect on the entire local area. In particular, the above control is performed for a warm area to cool the local area.

The heat island situation management unit 43 collects data including the aforementioned heat island information from an external organization that collects meteorological data, i. H. publishes air temperature data at each applicable location in the local area, and compiles the collected air temperature data to generate and maintain heat island information.

The wind data acquisition unit 44 accumulates wind speed and wind direction data acquired by the environmental control device 20 of the vegetation shading system 1 using the sensor unit 23, and wind speed and wind direction data for each time range specific to each local area acquired by an external organization.

As supplementary information to support the operability of generating the wind generation effect by the refrigerated island control device 4, a mechanism of wind generation by a temperature difference will be described below. The weight (specific gravity) of air varies with air temperature. That is, warmer air is lighter and colder air is heavier. Lighter air has a larger volume for the same weight, i. H. a lower atmospheric pressure. Therefore, a warmer atmosphere has lower air pressure, while a cooler atmosphere has higher air pressure. Wind is a phenomenon that occurs when air is pushed from a room with higher air pressure into a room with lower air pressure. Thus, if local areas have different air temperatures, a wind will blow from the local area with a lower temperature to the local area with a higher temperature.

It should be noted that the refrigerated island control device 4 described above is implemented in an electronic computer in which a program for providing the functionality to be provided by the refrigerated island control device 4 is installed. That is, the execution of the above program by the processor of the electronic computer implements the refrigerated island control device 4.

Next, the user terminal 5 will be described. The user terminal 5 is a terminal such as a user's smartphone. 9 12 is a diagram showing an example of a functional block configuration of the user terminal 5 according to the first embodiment.

The user terminal 5 to be used by a general user includes a user application 51. The user application 51 includes an interface unit 511, a green cover search and status display unit 512, a heat stroke warning information display unit 513, and an other function unit 514.

The interface unit 511 receives the greening shade list information from the data management device 3, receives the greening shade status information from the data management device 3, receives the heatstroke warning information from the data management device 3, and transmits a greening shade information request to the data management device 3.

The greenery shade search and status display unit 512 allows the user to search for a greenery shade in the vicinity of the user terminal 5 and also shows the surrounding conditions, i. H. the temperature, the air humidity, the wind speed and the like, for each of the green roof shading systems 1 found by the search.

The heat stroke warning information display unit 513 displays the heat stroke warning information pushed from the user service 341 of the data management device 3 .

The other functional unit 514 is an application that allows the user to offer a new business using the grass shading system 1, and enables, for example, a functionality for providing a notification of the crowding situation of each of the grass shading units 10, a functionality for sale of passion fruit and the like is additionally provided.

The maintenance-use management terminal 6 will be described next. The management terminal 6 for maintenance purposes is, for example, a tablet terminal, a notebook PC or the like. 10 12 is a diagram showing an example of the function block configuration of the maintenance-use management terminal 6 according to the first embodiment.

The maintenance management terminal 6 for use by a person who sets and maintains greenery shades includes a remote maintenance application 61. The remote maintenance application 61 includes an interface unit 611, a fog operation time setting unit 612, a temperature schedule setting unit 613 and a remote maintenance unit 614.

The interface unit 611 receives the operational status information or setting value information of a specific environmental control device 20 from the data management device 3, transmits an inquiry request related to the operational status information or setting value information of a specific environmental control device 20 to the data management device 3, transmits a change request for the setting value of a certain environmental control device 20 to the data management device 3, transmits a setting request or a change request for fog operation time of a grass shading device to the data management device 3, and transmits a setting request or a change request for temperature plan information of a grass shading device to the data management device 3.

The fog operation time setting unit 612 initializes and changes the fog operation time range managed by the fog operation time management unit 28 of the environment control device 20 via the fog operation time setting unit 35 of the data management device 3.

The temperature schedule setting unit 613 initializes and changes the temperature schedule managed by the temperature schedule management unit 29 of the environment control device 20 via the temperature schedule setting unit 36 of the data management device 3.

The remote maintenance unit 614 displays the operating status information of a specific environmental control device 20 via the remote control service 342 of the data management device 3, and initializes and changes the setting value of a specific environmental control device 20. The irrigation time, the irrigation amount and the like in the irrigation control unit 27 are set and changed with this functionality.

The management terminal 7 operated by planning personnel will be described next. The management terminal 7 operated by planning personnel is a PC, for example. 11 14 is a diagram showing an example of the functional block configuration of the management terminal 7 operated by planning personnel according to the first embodiment.

The management terminal 7 operated by planning personnel includes a greening shade installation site selection evaluation unit 71 and a heat island situation verification unit 72.

The plant shade installation site selection evaluation unit 71 allows the planning personnel to simulate the wind generation caused by plant shade installation and the cooling effect of the generated wind by adjusting the number of plant shades at each applicable location. The heat island situation review unit 72 provides the planning personnel with the heat island situation, i. H. Information representing an air temperature distribution in the local area.

As described above, the refrigerated island system 100 according to the first embodiment includes one or more green roof systems 1. Each of the green roof systems 1 controls the amount of mist falling on a green roof that includes the shade frame 11 and the passion flower bush 12 intertwined with the shade frame 11 to form a roof to be sprayed based on the air temperature and humidity of the environmental control area including a shaded space created by the plant shade and the growth state of the plant shade. In this way, the environmental control area can be maintained in a desired state. This can also prevent the occurrence of a problem such as root rot due to overwatering of the passion flower bush 12 forming a green shade, and thus keep the green shade in good condition.

Second embodiment

Next, a second embodiment will be described. The cooling island system and the greenery shade system according to the second embodiment are configured similarly to those of the first embodiment. The present embodiment will be described below in terms of differences from the first embodiment.

The refrigerated island system 100 according to the second embodiment uses machine learning to provide the operation described in the first embodiment. Machine learning is used in two cases. The first case is the use of machine learning when the environment control device 20 of the green plant shade system 1 controls the environment of the environment control area. The second case involves the use of machine learning when the refrigerated island controller 4 assists in the determination of installation locations and the number of installations of greenery shades made by the refrigerated island system design personnel.

The environmental control device 20 and the refrigerated island control device 4 according to the second embodiment will be described below.

The environmental control device 20 according to the second embodiment includes an in 12 shown fog control unit 26a instead of the fog control unit 26 of the environment control device 20 according to the first embodiment. 12 12 is a diagram showing an example configuration of the fog control unit 26a included in the environment control device 20 according to the second embodiment.

The fog controller 26a includes a machine learning device 80 . The device 80 for machine learning comprises a state observation unit 81 and a learning unit 82.

The fog control unit 26a controls the environment of the environment control area using a result of learning performed by the machine learning device 80 . Specifically, the mist control unit 26a determines, based on a learning result, at what point in time the spraying unit 16 of the greenery shade unit 10 should start spraying a mist based on a change in air temperature, a predicted level of crowding, a wind condition, and the like. The vegetation shade unit 10 experiences a temperature drop due to the heat of vaporization of the mist, resulting in a time delay before a cooling effect occurs due to the heat of vaporization of the mist. In view of the fact that most of the users who use the green grass shading system 1 are probably using it for the first time, a comfortable environment must be provided in a timely manner. Therefore, it is important to minimize the time lag. That is, in order to provide a comfortable environment at the time of the user's arrival at the installation site of the green plant shade system 1, mist spraying must start before a target time (e.g., the start time of the mist operation time range), the user's arrival time. However, as described in the description of the first embodiment, the mist spraying is controlled in consideration of the air temperature and humidity of the environmental control area and the growth state of the greenery shade. This prevents the amount of mist to be sprayed from being constant and hence the time it takes from starting mist spraying to reaching a comfortable environment from being constant. Therefore, the mist control unit 26a determines the timing to start spraying mist based on the machine learning result. For example, if the user has been informed that the start time for the operation of the vegetation shading system 1, i. H. the start time for providing a comfortable environment by mist spraying is 10 o'clock, the mist control unit 26a determines, based on the result of the machine learning, at what time to start mist spraying to cool the surrounding area and the surrounding area fully comfortable before 10am. The mist control unit 26a then starts controlling spraying of mist at the specified timing.

The learning data that is input to the machine learning device 80 when the machine learning device 80 is to perform machine learning includes fog operating state data (hereinafter referred to as operating state data), predicted crowd density level data (hereinafter referred to as crowd density forecast data), forecast data of an increase in air temperature (hereinafter referred to as air temperature forecast data), forecast data of wind speed and wind direction (hereinafter referred to as wind forecast data), data of actual air temperature, humidity, wind direction and wind speed at the green cover installation site (hereinafter referred to as actual environment data), data of the actual situation of human density at the green roof shading installation site (hereinafter referred to as human density situation data), and data of the residence time of humansc hen at the greening shading installation site (hereinafter referred to as residence time data).

The running condition data is data indicating the timing of starting spraying of mist and the amount of mist to be sprayed. The fog spray start time is the time when the fog spray starts before the target time. When the spraying unit 16 controls the repeated start and stop of mist spraying, the amount of mist to be sprayed is expressed by the duration of spraying mist and the amount of mist to be sprayed, and the duration of not spraying a mist.

The crowding prediction data is data showing a predicted value of the degree of crowding at the target time point of the greenery shading installation site. This data is collected using, for example, crowd density prediction data (participation number prediction) provided by an external system. When it is difficult to crowd forecast data at the green cover shading installation site instead, since a correlation is expected between the attendance count at a location (sightseeing site, etc.) close to the plant shading installation site and the attendance count at the plant shading installation site, attendance count prediction data at a location near the plant shading installation site is used instead.

The air temperature forecast data is data representing a predicted value of the air temperature at the target time point at the plant shade installation site. Similar to the crowd density forecast data described above, the air temperature forecast data is also collected using data provided by an external system. If air temperature forecast data at the plant shading installation site is difficult to collect, air temperature forecast data at a location close to the plant shading installation site will be used instead.

The wind forecast data is data showing the predicted values of the wind direction and the wind speed at the target time at the green roof installation site. Similar to the crowd density forecast data described above, the wind forecast data is also collected using data provided by an external system. Further, when wind forecast data at the plant shading installation site is difficult to acquire, wind forecast data at a location close to the plant shading installation site is used instead.

The actual environmental data is data that represents the current air temperature, humidity, wind direction and wind speed at the installation site of the green roof shading. The actual surroundings data are recorded by the sensor unit 23 .

The crowding situation data is data representing the current degree of crowding at the plant shading installation site, and is acquired by, for example, analyzing an image of the plant shading installation site picked up by an image sensor included in the sensor unit 23 .

The stay time data are data of the length of time the user stays at the green roof shading installation site after reaching the target time. The residence time differs depending on the user and is accordingly defined as an average residence time per user. In addition, this data is generated using data provided by an external system, such as activity data generated by analyzing location information from a device such as a smartphone carried by the user; or they are generated through the analysis of images or videos of the vegetation shading installation site repeatedly captured by an image sensor included in the sensor unit 23 .

The machine learning device 80 receives the above learning data and then learns the relationships between the pieces of data included in the learning data. An operation of each component when the machine learning device 80 performs the learning will be described next.

The state observation unit 81 observes, as state variables, the above-described operation state data, the crowd density forecast data, the air temperature forecast data, the wind forecast data, the actual environment data, the crowd density situation data, and the above-described residence time data as state variables.

The learning unit 82 learns the timing to start spraying mist and the amount of mist to be sprayed based on a data set generated based on the state variables observed by the state observation unit 81 .

The learning unit 82 can potentially use any learning algorithm. As an example, a use case of reinforcement learning is described. The reinforcement learning is performed such that an agent (acting entity) in a certain environment observes the current state and determines an action to be taken. The agent chooses an action to receive a reward from the environment, thus learning a strategy that allows maximum reward to be obtained through a sequence of actions. Typical well-known reinforcement learning techniques are Q-learning and TD-learning. For example, in Q learning, a general update formula (action value table) of an action value function Q(s, a) is expressed as formula (1) below.
[Formula 1] $$Q\left(s_t,a_t\right)\leftarrow Q\left(s_t,a_t\right)+a\left({\mathrm{right}}_{t+1}+g\underset{a}{{\displaystyle \text{Max}}}Q\left(s_{t+1},a\right)-Q\left(s_t,a_t\right)\right)$$

In formula (1), s _t stands for the environment at time t and a _t for the action at time t. The Action a _t changes the environment to s _t+1 . Furthermore, r _t+1 stands for the reward obtained by this change in environment, γ for the discounting factor and α for the learning rate. Note that γ has a range of 0<γ≦1 and α has a range of 0<α≦1. Using Q-learning, determining when to start mist spraying and the amount of mist to spray is equivalent to action a _t .

The update formula expressed by formula (1) increases the action value Q when the action value of the best action a _t+1 at time t+1 is greater than the action value Q of the action a t performed at time _t , and decreases the action value Q otherwise. In other words, the action value function Q(s,a) is updated to bring the action value Q of action a _t , at time t closer to the best action value at time t+1. This causes the best action value in a given environment to be sequentially transferred to the action values in the environment before that point in time.

The learning unit 82 comprises in particular a reward calculation unit 821 and a function update unit 822.

The reward calculation unit 821 calculates the reward based on a state variable. Specifically, the reward calculation unit 821 calculates the reward r based on the residence time data. The reward calculation unit 821 increases the reward r (for example, gives a reward of “1”) when, for example, the residence time of people at the greenery shading installation site has increased. The expression “people's residence time increases” means that the residence time is, for example, longer than the previous average residence time of users of a green covering. Alternatively, when the residence time of people at the greenery shading installation site has decreased, the reward calculation unit 821 decreases the reward r (for example, gives a reward of "-1").

The function update unit 822 updates the function for determining the timing to start spraying mist and the amount of mist to be sprayed according to the reward calculated by the reward calculation unit 821 . For example, in Q learning, the action value function Q(s _t , a _t ) expressed by formula (1) is used as the function for calculating the fog operating state.

The learned model, which is generated by the learning unit 82 by training with the aforesaid learning data, receives the crowding forecast data, the air temperature forecasting data, the wind forecasting data, the actual environment data and the crowded situation data described above, and outputs the fog operating state, i. H. the timing to start mist spraying and the amount of mist to be sprayed.

The refrigerated island control device 4 will be described next. The refrigerated island control device 4 according to the second embodiment includes an in 13 Fig. 1 shows the greenery shade installation site selection function unit 41a instead of the greenery shade installation site selection function unit 41 of the refrigerated island control device 4 according to the first embodiment. It should be noted that 13 12 is a diagram illustrating an example configuration of the greenery shade installation site selection functional unit 41a included in the refrigerated island control device 4 according to the second embodiment.

The vegetation shade installation site selection function unit 41a includes a machine learning device 90 . The device 90 for machine learning comprises a state observation unit 91 and a learning unit 92.

The greenery shade installation site selection function unit 41a supports the decision-making of the cold island system planning personnel regarding the installation sites and the number of greenery shade installations using a result of reinforcement learning performed by the machine learning device 90 .

Learning data input to the machine learning device 90 when the machine learning device 90 is to perform machine learning includes data of the installation location of each of the plurality of green shading systems 1, city planning data, the operating state data of each of the plurality of green shading systems 1, the crowd density prediction data of each of the plural green roof shading system 1, the air temperature forecast data of each of the plurality of green roof shading systems 1, the wind forecast data of each of the plurality of green roof shading systems 1, heat island situation data, the actual environmental data of each of the plurality of green roof shading systems 1, the crowding situation data of each of the plurality of green roof shading systems 1, and the residence time data of each of the plurality of green roof shading systems 1.

Among the data included in the learning data to be input into the machine learning device 90 are the operating condition data, the crowd density forecast data, the air temperature forecast data, the wind forecast data, the actual environment data, the crowded situation data, and the residence time data data corresponding to the operating condition data , the crowd density forecast data, the air temperature forecast data, the wind forecast data, the actual environment data, the crowd density situation data and the residence time data included in the learning data described above input to the machine learning device 80 are similar.

The city planning data is data showing an arrangement of buildings in an area, for example, which building is located where in the area where the green shade is installed.

The heat island situation data is data representing the air temperature at each applicable location in the area where the green cover is installed.

The machine learning device 90 receives the above learning data and then learns relationships between the pieces of data included in the learning data. The operation of each component when the machine learning device 90 performs the learning will be described below.

The state observation unit 91 observes, as state variables, the above-described data of the installation site of each green shade, urban planning data, operation state data, crowding forecast data, air temperature forecasting data, wind forecasting data, heat island situation data, actual environment data, crowding situation data and residence time.

The learning unit 92 learns a place where installation of a green shade is advantageous based on a data set generated based on the state variables observed by the state observation unit 91 . The place where it is beneficial to install a green shade includes a place where the installation of a green shade allows the air temperature to drop below the ambient temperature and a wind to blow.

The learning unit 92 of the machine learning device 90 includes a reward calculation unit 921 and a function updating unit 922. The learning unit 92 performs machine learning through an operation similar to the aforementioned operation of the learning unit 82 of the machine learning device 80. That is, the learning unit 92 of the machine learning device 90 differs from the learning unit 82 of the machine learning device 80 in the structure of the learning data used. It should be noted that the method used by the reward calculation unit 921 of the learning unit 92 to calculate the reward differs from the method used by the reward calculation unit 821 of the learning unit 82 to calculate the reward. For example, the reward calculation unit 921 increases the reward r when the installation of a green shade has caused the air temperature in the area to reach a target value, and decreases the reward r when the target value has not been reached.

Note that the present embodiment has been described with respect to the case of using the reinforcement learning as the learning algorithm used by the learning unit, but the learning algorithm is not limited to this. As far as the learning algorithm is concerned, supervised learning, unsupervised learning, semi-supervised learning, or the like can be used instead of reinforcement learning.

The aforementioned learning algorithm may also be deep learning that learns the extraction of a feature set per se, and the machine learning may also be performed using a known method such as neural network, genetic programming, functional logic programming, support vector machine, or the like .

In addition, the machine learning device 80 is used to learn the timing to start mist spraying performed by the spraying unit 16 of the green cover shading unit 10 under the control of the mist control unit 26a of the environment control device 20, but the machine learning device 80 can be configured to be located outside of the mist control unit 26a. Furthermore, the machine learning device 80 may be configured to be connected to the environmental control device 20 via a network, i. H. a device that implements the fog controller 26a and the machine learning device 80 may be separate devices. In addition, the machine learning device 80 may be installed in a cloud server.

Further, the machine learning device 80 may learn the fog operating state based on a data set generated for multiple environmental control devices 20 . It should be noted that the machine learning device 80 may obtain datasets from multiple environmental control devices 20 used at a single location, or learn the fog operating state using datasets collected from multiple environmental control devices 20 independently at different locations locations work. Furthermore, an environmental control device 20 for maintaining a data set during operation can be added to or conversely removed from a group of data set acquisition sources. Further, a machine learning device 80 that has learned the fog operating states for a particular environmental control device 20 can be connected to another environmental control device 20 to cause that machine learning device 80 to re-learn the fog operating states for the other environmental control device 20 and to To update.

The machine learning device 80 included in the fog control unit 26a of the environment control device 20 has already been described, and a similar description also applies to the machine learning device 90 included in the greenery shade installation site selection function unit 41a of the cooling island control device 4 .

As described above, the fog control unit 26a of the green plant shade system 1 according to the present embodiment learns the fog operation state and determines the timing to start spraying fog and the amount of fog to be sprayed based on a learning result. In this way, the setting of the environmental conditions can be reliably completed before a target time. Further, the refrigerated island control device 4 learns the installation location of each greenery shade and determines the installation location of each greenery shade based on a learning result. In this way, a suitable installation location for each green shading can be efficiently determined.

Third embodiment

The second embodiment has been described with respect to a configuration in which the fog control unit 26a of the grass shade system 1 learns the fog operation state using the reinforcement learning. The present embodiment will be described with respect to a configuration in which the fog operating state is learned using supervised learning. It should be noted that the cooling island system and the green roof system according to a third embodiment are configured similarly to those of the first and second embodiments. The present embodiment will be described below in terms of differences from the first and second embodiments.

The environmental control device 20 according to the third embodiment includes an in 14 shown fog control unit 26b instead of the fog control unit 26a of the environment control device 20 according to the second embodiment. It should be noted that 14 12 is a diagram showing an example configuration of the mist control unit 26b included in the environment control device 20 according to the third embodiment.

The fog controller 26b includes a machine learning device 80b. The device 80b for machine learning comprises a data acquisition unit 85, a state observation unit 86 and a learning unit 87.

The fog control unit 26b controls the environment of the environment control area using a result of supervised learning performed by the machine learning device 80b. Specifically, the fog control unit 26b determines the fog operation state based on a result of machine learning, similarly to the fog control unit 26a described in the second embodiment.

Learning data that is input to the machine learning device 80b when the machine learning device 80b is to perform machine learning includes the operating state data, the crowd density forecast data, the air temperature forecast data, the wind forecast data, the actual environment data, the crowd density situation data, and the residence time data that in the second embodiment, and the surrounding state evaluation data made by the user of the greenery shade (hereinafter referred to as user evaluation data).

The user evaluation data is data representing, for example, a result of evaluating the feeling of refreshment felt by the user. The user evaluation data are, for example, using the user terminal 5 or by filling out a questionnaire gens by a user using the green cover.

The machine learning device 80b receives the aforementioned learning data and then learns relationships between the pieces of data included in the learning data. The following describes the operation of each component when the machine learning device 80b performs the learning.

The data acquisition unit 85 obtains the residence time data and the user evaluation data described above as decision data.

The state observation unit 86 observes the operational state data, the crowding forecast data, the air temperature forecasting data, the wind forecasting data, the actual environment data, and the crowded situation data described above as state variables.

The learning unit 87 learns the fog operation state (the timing to start spraying fog and the amount of fog to be sprayed) based on a data set obtained based on a combination of the state variables observed by the state observation unit 86 and the decision data acquired by the data acquisition unit 85 is produced. In this operation, the data set is a data set that links the state variable and the decision data.

The learning unit 87 learns the fog operating state based on, for example, a neural network model using so-called supervised learning. In this context, supervised learning refers to a model that, when given a large number of data pairs of specific inputs and results (labels) to a learning device, learns a feature present in those data sets and predicts a result from an input.

A neural network comprises an input layer composed of a plurality of neurons, an intermediate layer (hidden layer) composed of a plurality of neurons, and an output layer composed of a plurality of neurons. There may be one interlayer or two or more interlayers.

For example, when multiple inputs are fed into the input layer (X1 to X3), a three-layer neural network multiplies, as in 15 shown, these values with a weight W1 (w 11 to w16), inputs the resulting products into the intermediate layer (Y1 to Y2), further multiplies these results by a weight W2 (w21 to w26) and outputs the resulting products from the output layer (Z1 to Z3) off. These output results vary depending on the values of the weights W1 and W2. It should be noted that 15 Fig. 12 is a diagram showing an example configuration of a neural network.

In the present embodiment, the neural network learns the fog operating state using so-called supervised learning based on a data set generated based on a combination of the state variables observed by the state observation unit 86 and the decision data acquired by the data acquisition unit 85.

That is, the neural network performs learning such that the weights W1 and W2 are adjusted to bring the results output from the output layer closer to the decision data when the operating condition data, the crowd density forecast data, the air temperature forecast data, the wind forecast data, the actual -environment data and the crowd density situation data are inputted into the input layer.

Further, a neural network can also learn the timing to start mist spraying and the amount of mist to be sprayed through so-called unsupervised learning. Unsupervised learning is a technique for learning a device that performs compression, classification, rendering, and the like on input data without providing corresponding tagged output data. This is achieved by learning how the input data is distributed, just providing the machine learning system with a large amount of input data. For example, unsupervised learning allows features of these datasets to be clustered into groups based on similarity. By specifying a specific criterion and allocating outputs to optimize the criterion using the learning outcome, an output can be predicted. A technique for solving a problem that lies between unsupervised and supervised learning is called semi-supervised learning. This corresponds to the cases where only some data sets have data pairs from inputs and outputs and the other data sets only have data from inputs.

Furthermore, the machine learning device 80b can learn the fog operating state based on a data set that is stored for a plurality of environmental control devices 20 was generated. It should be noted that the machine learning device 80b can collect datasets from multiple environmental control devices 20 used at a single location, or learn the fog operating state using datasets collected from multiple environmental control devices 20 independently at different locations locations work. Additionally, an environmental control device 20 for acquiring a dataset may be added to or, conversely, removed from a set of dataset acquisition sources during operation. In addition, a machine learning device 80b that has learned the timing to start spraying mist and the amount of mist to be sprayed for a particular environment control device 20 can be connected to another environment control device 20 to prompt that machine learning device 80b to re-learn and update the fog operating conditions for the other environmental control device 20 .

As described above, the fog control unit 26b of the green plant shade system 1 according to the present embodiment performs supervised learning about the fog operation state, and determines the timing to start spraying fog and the amount of fog to be sprayed based on a learning result. The plant shade system 1 according to the present embodiment can provide an advantage similar to the advantage of the plant shade system 1 according to the second embodiment.

It should be noted that the shade frame 11 of the grass shade unit 10 described in the first embodiment may have a variety of shapes and arrangements. In particular, there can be variations in ceiling design, including flat design, corrugated design, and triangular roof, as well as variations in side surface. The cultivation area of the passion flower bush 12 can be increased by the design of the ceiling design and by planting plants on the side surface, which in turn can increase the intensity of the cooling by the evaporation heat of the passion flower bush 12 and thus the cooling effect in the green shading. Further, cultivating the passion flower bush 12 on the side surface can reduce the discharge of the air cooled in the shade.

There may also be variations for the passionflower shrub 12 included in the cover shading unit 10, including the use of a different plant than that of the passionflower shrub 12. In particular, a plant that grows in a subtropical region, such as a plant from the Passiflora family. In short, instead of the plant of the passion flower bush 12, a plant that does not die from boiling water, for example, can be used even if the plant is watered in a high air temperature environment such as a summer day.

The installation position of the pipeline of the fog unit 13 of the green covering shading unit 10 can also vary. Specifically, for example, the duct can be installed above the greenery shading, the ducting can be installed under the greenery shading (in this case, the mist is sprayed from below), or the ducting can be installed inside the greenery shading (in this case, the mist is discharged from the sprayed inside the green cover to cause evaporation through more natural evaporation). The selection of these variants depends on the ambient temperature, such as in the summer.

Other variations related to the vegetation shade unit 10 include variations in lighting control, variations in air curtain, and variations in dry fog.

There are variations in lighting control related to providing different types of indoor lighting control to support the growth of the passionflower bush 12 .

There are variations of the air curtain in terms of installing an air curtain to maintain the temperature inside the green cover.

There are variations of dry fog relating to the use of dry fog to increase the cooling effect by creating negative ions inside the green cover.

There are also different variations of the user terminal 5 in relation to the individual applications offered as the user application 51 . Detailed examples are a tourist guide service for summer resorts and an electronic commerce service (sale of passion flowers, green plants, tables, etc.). As the user application 51, various service applications can be installed that are for the Systems of the first to third embodiments are provided.

In another embodiment, the spraying of fog can be adjusted based on a mixed situation, so that an image capturing unit such as a camera is installed in the grass shading unit 10 to capture information about the situation of crowding in the grass shading, and the fog control unit 26 then recognizes the situation of the crowd density based on the image captured by the image capturing unit. In particular, the fog control unit 26 can predict a temperature rise in the plant shading and predict the situation of temperature exchange between inside and outside the plant shading caused by the movement of people, also based on the situation of human density, and then the timing for spraying Set fog that has already been planned based on the temperature schedule and/or the like.

The configurations described in the foregoing are just examples. These configurations can be combined with another known technology, and configurations of different embodiments can be combined with each other. In addition, part of the configurations may be omitted and/or modified without departing from the gist of the configurations.

Reference List

1

green shading system;

3

data management device;

4

refrigerated island control device;

5

user terminal;

6

management terminal for maintenance purposes;

7

management terminal operated by planning personnel;

10

green cover shading unit;

11

shading frame;

12

passion flower bush;

13

fog unit;

14

irrigation unit;

15

Pump;

16

spray unit;

17

fog unit tap;

20

environmental control device;

21

cloud interface unit;

22

device interface unit;

23

sensor unit;

24

actual data acquisition unit;

25

control unit;

26, 26a, 26b

fog control unit;

27

irrigation control unit;

28

fog operation time management unit;

29

temperature plan management unit;

31, 511, 611

interface unit;

32

temperature change prediction unit;

33

actual data acquisition unit;

34

service application;

35, 612

fog operation time setting unit;

36, 613

temperature schedule setting unit;

41, 41a

Greening shading installation site selection engine;

42

refrigerated island control engine;

43

heat island situation management unit;

44

wind data acquisition unit;

51

user application;

61

remote maintenance application;

71

Greening shading installation site selection evaluation unit;

72

heat island situation review unit;

80, 80b, 90

machine learning device;

81, 86, 91

condition observation unit;

82, 87, 92

learning unit;

85

data acquisition unit;

100

refrigerated island system;

341

user service;

342

remote control service;

512

Greening shading search and status display unit;

513

heat exhaustion warning information display unit;

514

other functional unit;

614

remote maintenance unit;

821, 921

reward calculation unit;

822, 922

feature update unit.

QUOTES INCLUDED IN DESCRIPTION

This list of documents cited by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent Literature Cited

• JP2005237261 [0004]

Claims (10)

Green roof shading system, comprising: a greenery shade unit for creating a shaded space by a greenery shade formed using a plant; a spray unit for converting water into mist and spraying the mist onto the plant; and a mist control unit for controlling a mist spraying operation performed by the spray unit based on an air temperature of an environmental control area including the shaded space and a temperature map representing a target temperature of the environmental control area in each time range. Greening shading system claim 1 , the plant being a plant of the passionflower family. Greening shading system claim 1 or 2 wherein the mist control unit controls the spraying operation based on the air temperature and a humidity of the environment control area, the temperature schedule, and the growth state of the plant. Greening shading system claim 3 , wherein the growth condition includes an upper limit for an amount of water supplied to the plant, and wherein the mist control unit controls the spraying operation so that the amount of water converted into the mist and supplied to the plant by the spray unit is maintained at or below the upper limit. Greening shading system according to one of the Claims 1 until 4 wherein the mist control unit adjusts an amount of mist to be sprayed by the spray unit based on the lighting and a wind speed detected in the environmental control area. Greening shading system according to one of the Claims 1 until 5 wherein the mist control unit adjusts an amount of mist to be sprayed by the spray unit based on a density of people in the environmental control area. Greening shading system according to one of the Claims 1 until 6 wherein notification of air temperature, humidity and wind speed of the environmental control area is provided to a user carried terminal. Greening shading system according to one of the Claims 1 until 7 , comprising: a machine learning device for performing learning of a timing to start spraying operation based on operational status data, crowding forecast data, air temperature forecasting data, wind forecasting data, actual environmental data and crowded situation data, the operational status data indicating the timing to start spraying operation and a through the spraying operation amount of mist to be sprayed, wherein the crowding forecast data represents a degree of crowding at a target time point at an installation site of the green roof shading unit, the air temperature forecast data represents a predicted value of an air temperature at the target time point at the installation site, the wind forecast data representing predicted values of a wind direction and a wind speed at the Represent the target time at the installation site, the actual environmental data being an air temperature, an air humidity, a Wi nd direction and a wind speed at an actual time at the installation site, the crowding situation data representing the degree of crowding at the actual time at the installation site, and the mist control unit a timing to start controlling the spray unit using a result of the from the device for learning performed by machine learning. A refrigerated island system, comprising: the green roof shading system according to any one of Claims 1 until 8th ; and a refrigerated island controller for controlling an operation of the green roof system, wherein the refrigerated island system includes a plurality of green roof systems, and wherein the cold island controller includes a machine learning device for learning installation locations and the number of installations of the green roof systems based on urban planning data, operational status data , crowding forecast data, air temperature forecasting data, wind forecasting data, heat island situation data, actual environment data and crowding situation data, wherein the urban planning data represents an arrangement of buildings in an area where the green area shading unit of each of the green area shading systems is installed, wherein the operating condition data indicates a timing for starting the spraying operation by the spraying unit of each of the grass shading systems and an amount of mist to be sprayed by the spraying operation, the crowd density prediction data representing a degree of crowding at a target time point at an installation site of the grass shading unit of each of the grass shading systems, the air temperature forecast data representing a predicted value of an air temperature at the target time point at the installation site of the grass shading unit represent each of the greenery shading systems, wherein the wind forecast data represents predicted values of a wind direction and a wind speed at the target time point at the installation site of the greenery shading unit of each of the greenery shading systems, wherein the heat island situation data represents air temperatures at respective locations in the area where the greenery shading unit of each of the greenery shading systems is installed, where the actual environmental data is a Lu ft temperature, a humidity, a wind direction and a wind speed at an actual point in time at the installation site of the plant shading unit of each of the plant shading systems, and wherein the crowding situation data represents the degree of crowding at the actual point in time at the installation site of the plant shading unit of each of the plant shading systems, and determining the Installation places and the number of installations of the green cover shading systems using a result of the learning performed by the machine learning device. Refrigerated island system comprising: a variety of greenery shade systems each creating a shady space by a greenery shade formed using a plant, wherein the vegetation shade systems each have functionality for spraying atomized water onto the plant; and a refrigerated island control device for controlling an operation of the green cover shading systems, wherein the cooling island control device controls a spray operation of mist of each of the plurality of vegetation shade systems to cause air cooled by vaporization heat resulting from wetting of branches and leaves of the plant to move toward the heated air, and wherein air is caused to move by the installation of multiple vegetation shade systems to cause a wind to blow through an opening of the vegetation shade.

Images