WO2020240700A1 - Information processing device, information processing method, and information processing program - Google Patents

Information processing device, information processing method, and information processing program Download PDF

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Publication number
WO2020240700A1
WO2020240700A1 PCT/JP2019/021110 JP2019021110W WO2020240700A1 WO 2020240700 A1 WO2020240700 A1 WO 2020240700A1 JP 2019021110 W JP2019021110 W JP 2019021110W WO 2020240700 A1 WO2020240700 A1 WO 2020240700A1
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point
propagation
fluid
propagation distance
information processing
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PCT/JP2019/021110
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French (fr)
Japanese (ja)
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輔祐太 渡邉
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三菱電機株式会社
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Priority to PCT/JP2019/021110 priority Critical patent/WO2020240700A1/en
Publication of WO2020240700A1 publication Critical patent/WO2020240700A1/en

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/52—Indication arrangements, e.g. displays
    • F24F11/523—Indication arrangements, e.g. displays for displaying temperature data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M9/00—Aerodynamic testing; Arrangements in or on wind tunnels

Definitions

  • the present invention relates to a technique for estimating a fluid state value at an arbitrary point in space.
  • the fluid state value is a fluid value that can be measured using a measuring device.
  • the state value of the fluid includes temperature, humidity, air volume, wind direction, odor, concentration and the like.
  • the fluid state value of the estimated point is estimated by interpolation using the Euclidean distance between the observation point and the estimated point where the fluid state value is known.
  • the spatial distribution estimation technique using the Euclidean distance as described above cannot consider the influence of obstacles and cannot perform highly accurate estimation. Therefore, the spatial distribution estimation technique using the Euclidean distance cannot obtain an accurate estimation result when an obstacle exists.
  • Patent Document 1 discloses a technique for estimating the fluid concentration at an estimated point in a container in which a partition plate that obstructs fluid is installed from the fluid concentration at an observation point.
  • the partition plate corresponds to an obstacle. More specifically, in Patent Document 1, the minimum transfer time between the observation point and the estimation point calculated by the experiment and the fluid simulation and the fluid concentration at the observation point are used to obtain the standard deviation of the Gaussian distribution from the observation point. Estimate the fluid concentration at the estimation point based on this.
  • Patent Document 1 As described above, in the technique of Patent Document 1, it is necessary to calculate the minimum transmission time by an experiment and a fluid simulation, and there is a problem that the workload and the calculation load are large.
  • One of the main purposes of this invention is to solve the above problems. More specifically, the main purpose is to make it possible to estimate the state value of an estimated point in space with a small workload and calculation load.
  • the information processing device is The position of the first point in the space, the position of the second point different from the first point in the space, and the obstacle of the propagation of the fluid from the first point to the second point. Based on the position and size of the obstacle, a path capable of propagating the fluid from the first point to the second point in the space is extracted as a propagation path, and the distance of the extracted propagation path is propagated.
  • Propagation distance calculation unit that calculates as a distance, It has an estimation unit that estimates the state value of the fluid at the second point based on the calculated propagation distance and the state value of the fluid observed at the first point.
  • FIG. 1 The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 1.
  • FIG. The flowchart which shows the operation example of the information processing apparatus which concerns on Embodiment 1.
  • the flowchart which shows the detail of the propagation distance calculation process and the estimated value calculation process which concerns on Embodiment 1.
  • FIG. The figure which shows the example of the calculation formula of the weight and the example of the calculation formula of the estimated value which concerns on Embodiment 1.
  • FIG. The figure which shows the temperature estimation example by Euclidean distance and the temperature estimation example which concerns on Embodiment 1.
  • FIG. The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 2.
  • the flowchart which shows the example of the pre-stage processing which concerns on Embodiment 3.
  • FIG. The flowchart which shows the operation example of the information processing apparatus which concerns on Embodiment 4.
  • FIG. The figure which shows the example of the propagation path which concerns on Embodiment 4.
  • FIG. The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 5.
  • the flowchart which shows the operation example of the information processing apparatus which concerns on Embodiment 5.
  • FIG. 1 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
  • FIG. 2 shows a hardware configuration example of the information processing apparatus 100 according to the present embodiment.
  • the operation procedure of the information processing device 100 corresponds to the information processing method.
  • the program that realizes the operation of the information processing device 100 corresponds to the information processing program.
  • the information processing device 100 includes a processor 901, a main storage device 902, an auxiliary storage device 903, and a communication device 904 as hardware.
  • the auxiliary storage device 903 stores a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 shown in FIG. Details of the propagation distance calculation unit 103 and the estimation unit 104 will be described later. These programs are loaded from the auxiliary storage device 903 into the main storage device 902. Then, the processor 901 executes these programs to operate the propagation distance calculation unit 103 and the estimation unit 104.
  • FIG. 2 schematically shows a state in which the processor 901 is executing a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104. Further, the obstacle information storage unit 101 and the observation point / estimation point information storage unit 102 shown in FIG. 1 are realized by the main storage device 902 or the auxiliary storage device 903.
  • the obstacle information storage unit 101 stores obstacle information.
  • Obstacle information is information on obstacles existing in the space. In the following, the description will be made on the premise of the obstacle 3 shown in FIG. In FIG. 3, the observation point 1 and the estimation point 2 exist in the space 4.
  • Observation point 1 is a point where the state value of the fluid is known.
  • Observation point 1 corresponds to the first point.
  • Estimated point 2 is a point where the state value of the fluid is unknown.
  • Estimated point 2 corresponds to the second point.
  • Obstacle 3 is an obstacle to the propagation of fluid from observation point 1 to estimation point 2. That is, the fluid must detour along the obstacle 3 in order to move from the observation point 1 to the estimation point 2, and cannot move in the shortest distance from the observation point 1 to the estimation point 2.
  • the obstacle information storage unit 101 holds the obstacle position information in which the position of the obstacle 3 is represented in two dimensions and the obstacle size information in which the size of the obstacle 3 is represented in two dimensions as the obstacle information.
  • the observation point / estimation point information storage unit 102 stores the observation point / estimation point information.
  • the observation point / estimation point information is composed of observation point position information in which the position of observation point 1 is represented in two dimensions and estimation point position information in which the position of estimation point 2 is represented in two dimensions.
  • the propagation distance calculation unit 103 calculates the propagation distance.
  • the propagation distance is the distance of the propagation path.
  • the propagation path is a path capable of propagating the fluid from the observation point 1 to the estimation point 2 in the space 4.
  • the propagation distance calculation unit 103 estimates from the observation point 1 in the space 4 based on the position of the observation point 1 and the estimation point 2 in the space 4 and the position and size of the obstacle 3.
  • the shortest path through which the fluid can propagate to 2 is extracted as the propagation path.
  • the propagation distance calculation unit 103 calculates the distance of the extracted propagation path as the propagation distance.
  • the propagation distance calculation unit 103 sets a plurality of observation points 1 for one estimation point 2.
  • the propagation distance calculation unit 103 extracts the propagation path and calculates the propagation distance for each observation point 1. That is, the propagation distance calculation unit 103 extracts a path capable of propagating the fluid to the estimation point 2 in the space 4 as a propagation path for each observation point 1 based on the positions of the plurality of observation points 1. Then, the propagation distance calculation unit 103 calculates the distance of each of the extracted plurality of propagation paths as the propagation distance. The process performed by the propagation distance calculation unit 103 corresponds to the propagation distance calculation process.
  • the estimation unit 104 is based on the propagation distance for each observation point 1 calculated by the propagation distance calculation unit 103 and the state value of the fluid observed at each of the plurality of observation points 1, and the state of the fluid at the estimation point 2. Estimate the value. More specifically, the estimation unit 104 sets a weight for each observation point 1 based on the propagation distance calculated by the propagation distance calculation unit 103. Then, the estimation unit 104 estimates the state value of the fluid at the estimation point 2 based on the weight of each set observation point 1 and the state value of the fluid observed at each of the plurality of observation points 1.
  • the propagation distance calculation unit 103 sets the observation point 1 and the estimation point 2 (step S101). As described above, a plurality of observation points 1 are set for one estimation point 2. Further, the propagation distance calculation unit 103 may set a plurality of estimation points 2. In this case, the propagation distance calculation unit 103 sets a plurality of observation points 1 for each of the plurality of estimation points 2. In the following, for the sake of simplification of the description, an example of setting one estimation point 2 will be described.
  • the propagation distance calculation unit 103 calculates the propagation distance (step S102). More specifically, the propagation distance calculation unit 103 acquires obstacle information (position and size of the obstacle 3) from the obstacle information storage unit 101, and observes / measures from the observation point / estimation point information storage unit 102. The point information (the position of the observation point 1 and the position of the estimation point 2) is acquired. Then, the propagation distance calculation unit 103 extracts the propagation path based on the acquired obstacle information and the observation point / measurement point information. As described above, the propagation path is the shortest path capable of propagating the fluid from the observation point 1 to the estimation point 2. In the case of the observation point 1 and the estimation point 2 in FIG. 3, the path 5 shown in FIG. 6 corresponds to the propagation path. Then, the propagation distance calculation unit 103 extracts such a propagation path and calculates the distance of the extracted propagation path. The propagation distance calculation unit 103 outputs the calculated propagation distance to the estimation unit 104.
  • obstacle information position and size of the obstacle 3
  • the estimation unit 104 calculates the estimated value (step S103).
  • the propagation distance calculation unit 103 calculates the propagation distance (step S102) for each of the plurality of observation points 1 set in step S101. Further, the estimation unit 104 calculates an estimated value (step S103) using the propagation distance calculated for each of the plurality of observation points 1. When a plurality of estimated points 2 are set in step S101, the estimation unit 104 calculates an estimated value for each of the plurality of estimated points 2 (step S103).
  • FIG. 5 shows the details of step S102 and step S103 of FIG.
  • step S101 is the same as that shown in FIG. 4, so the description thereof will be omitted.
  • Step S1020 shows the details of step S102 of FIG. Specifically, the propagation distance calculation unit 103 calculates the distance (shortest distance) of the shortest path between the observation point and the estimation point as the propagation distance by using an A * search algorithm, Dijkstra's algorithm, or the like.
  • Step S1030 shows the details of step S103 of FIG. Specifically, the estimation unit 104 calculates the weight from the propagation distance calculated in step S1020, and calculates the estimated value by the weighted average. The estimation unit 104 calculates the weight using, for example, the calculation formula shown in FIG. 7A. Further, the estimation unit 104 calculates the estimated value using, for example, the calculation formula shown in FIG. 7 (b).
  • FIG. 8 shows a method of estimating the temperature at the estimation point 2 when the temperature of the air (the temperature in the space 4) is taken as an example of the state value of the fluid.
  • FIG. 8A the floor surface of the space 4 is divided into rectangular virtual subregions. Further, in FIG. 8A, there are two observation points 1. That is, in FIG. 8A, the observation point 1a and the observation point 1b exist. It shows that the temperature observed in the partial region where the observation point 1a is located is 20 ° C. It also indicates that the temperature observed in the partial region where the observation point 1b is located is 30 ° C. For example, the region where the observation point 1a is located (the region on the left side of the obstacle 3) is cooled by an air conditioner. on the other hand. The area where the observation point 1b is located (the area on the right side of the obstacle 3) is not cooled.
  • FIG. 8B shows an example of temperature estimation based on the Euclidean distance.
  • FIG. 8B shows the temperature is estimated only depending on the distances from the observation points 1a and the observation points 1b.
  • FIG. 8C shows an example of temperature estimation by the information processing apparatus 100 according to the present embodiment. That is, (c) of FIG. 8 shows the temperature of each partial region estimated by the procedure shown in FIGS. 4 and 5.
  • the partial region where the observation point 1a is located and the partial region other than the partial region where the observation point 1b is located are designated as the estimation points 2 and the procedure shown in FIGS. 4 and 5 is performed. Shows the temperature distribution.
  • 28 ° C. is estimated as the temperature of the partial region 41. Since the partial region 41 is close to the partial region of the observation point 1b, it is estimated that the temperature is 28 ° C., which is close to the temperature of the partial region of the observation point 1b, which is 30 ° C.
  • 22 ° C. is estimated as the temperature of the partial region 41.
  • the obstacle 3 exists between the partial region 41 and the partial region of the observation point 1b, while the obstacle 3 does not exist between the partial region 41 and the partial region of the observation point 1a. Therefore, 22 ° C., which is a temperature close to 20 ° C., which is the temperature of the partial region of the observation point 1a, is estimated. Further, in FIG.
  • the temperature of the partial region 42 is estimated to be 21 ° C. Since the partial region 42 is close to the partial region of the observation point 1a, it is estimated that the temperature is 21 ° C., which is close to the temperature of the partial region of the observation point 1a, which is 20 ° C.
  • 29 ° C. is estimated as the temperature of the partial region 42.
  • the obstacle 3 exists between the partial region 42 and the partial region of the observation point 1a, while the obstacle 3 does not exist between the partial region 42 and the partial region of the observation point 1b. Therefore, 29 ° C., which is a temperature close to 30 ° C., which is the temperature of the partial region of the observation point 1b, is estimated.
  • 29 ° C. is estimated as the temperature of the partial region 43.
  • the obstacle 3 exists between the partial region 43 and the partial region of the observation point 1a, while the obstacle 3 does not exist between the partial region 43 and the partial region of the observation point 1b. Therefore, 29 ° C., which is a temperature close to 30 ° C., which is the temperature of the partial region of the observation point 1b, is estimated.
  • estimation unit 104 may display the temperature distribution for each partial region in the space 4 on the display as shown in FIG. 8C. By doing so, the user of the information processing apparatus 100 can visually grasp the temperature distribution in the space 4.
  • the spatial distribution estimation technique using the Euclidean distance cannot obtain an accurate estimation result when an obstacle exists in the space.
  • the state value of the estimated point in the space can be estimated without performing an experiment and a fluid simulation. Therefore, according to the present embodiment, the state value of the estimated point in the space can be estimated with a small workload and a calculation load.
  • Embodiment 2 In the present embodiment, the difference from the first embodiment will be mainly described. The matters not explained below are the same as those in the first embodiment.
  • the propagation distance calculation unit 103 calculates the propagation distance based on the position of the observation point 1 in two dimensions, the position of the estimation point 2, and the position and size of the obstacle 3. In the present embodiment, the propagation distance calculation unit 103 calculates the propagation distance based on the position of the observation point 1 in three dimensions, the position of the estimation point 2, and the position and size of the obstacle 3.
  • FIG. 9 shows an example of the functional configuration of the information processing apparatus 100 according to the present embodiment.
  • the obstacle information and the observation point / estimation point information are different from the configuration of FIG. That is, in FIG. 1, the obstacle position information and the obstacle size information of the obstacle information are two-dimensional information (horizontal and vertical), but in FIG. 9, the obstacle position information and the obstacle size of the obstacle information are shown. Information is three-dimensional information (horizontal, vertical, height). Further, in FIG. 1, the observation point position information and the estimation point position information of the observation point / estimation point information are two-dimensional information, but in FIG. 9, the observation point position information and the estimation point of the observation point / estimation point information are The position information is three-dimensional information. In FIG. 9, the obstacle position information of the obstacle information is represented in three dimensions, but the obstacle position information may be represented in two dimensions as in the first embodiment. Since the other elements of FIG. 9 are the same as those shown in FIG. 1, the description thereof will be omitted.
  • FIG. 10 shows an operation example of the information processing apparatus 100 according to the present embodiment.
  • FIG. 10A is a view of the observation point 1, the estimation point 2, and the obstacle 3 from the side.
  • FIG. 10B is a view of the observation point 1, the estimation point 2, and the obstacle 3 from above.
  • the wall 6 exists behind the obstacle 3.
  • the observation point 1 and the estimation point 2 are arranged at positions higher than the height of the obstacle 3. If the heights of the observation point 1, the estimation point 2, and the obstacle 3 are not considered, the propagation distance calculation unit 103 recognizes that the propagation of the fluid is hindered by the obstacle 3, and follows the path indicated by reference numeral 12. Will be extracted as.
  • the propagation distance calculation unit 103 indicates that the observation point 1 and the estimation point 2 are higher than the obstacle 3, so that the reference numeral 11 It is recognized that the fluid can propagate even in the path of. As a result, the propagation distance calculation unit 103 extracts the path of reference numeral 11 as the propagation path. The propagation distance calculation unit 103 calculates the propagation distance of the route of reference numeral 11 extracted in this way. Then, the estimation unit 104 estimates the state value of the estimation point 2 based on the propagation distance of the path of reference numeral 11.
  • the propagation path is extracted in consideration of the observation point, the estimation point, and the height of the obstacle. Therefore, the state value of the fluid in the room can be estimated with higher accuracy than in the first embodiment.
  • Embodiment 3 In the present embodiment, the difference from the first embodiment will be mainly described. The matters not explained below are the same as those in the first embodiment.
  • the propagation distance calculation unit 103 calculates the propagation distance in advance and stores the calculated propagation distance in the storage area. Then, when estimating the state value, the estimation unit 104 acquires the propagation distance from the storage area and estimates the state value using the acquired propagation distance.
  • FIG. 11 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
  • the propagation distance storage unit 105 is added as compared with the configuration of FIG.
  • the propagation distance storage unit 105 stores the propagation distance calculated by the propagation distance calculation unit 103.
  • the propagation distance storage unit 105 is realized by the main storage device 902 or the auxiliary storage device 903.
  • the elements other than the propagation distance storage unit 105 are the same as those shown in FIG.
  • the estimation unit 104 acquires the propagation distance from the propagation distance storage unit 105, and estimates the state value using the acquired propagation distance.
  • FIG. 12 shows the pre-stage processing.
  • FIG. 13 shows the post-stage processing.
  • steps S101 and S102 are the same as those described in the first embodiment, and thus the description thereof will be omitted.
  • step S104 the propagation distance calculation unit 103 stores the propagation distance calculated in step S102 in the propagation distance storage unit 105, and the propagation distance storage unit 105 stores the propagation distance.
  • the propagation distance calculation unit 103 stores the propagation distance in the propagation distance storage unit 105 in association with the combination of the observation point 1 and the estimation point 2 set in step S101.
  • step S101 is the same as that described in the first embodiment, and thus the description thereof will be omitted.
  • step S105 the estimation unit 104 acquires the propagation distance corresponding to the combination of the observation point 1 and the estimation point 2 set in step S101 from the propagation distance storage unit 105.
  • step S103 the estimation unit 104 calculates an estimated value using the propagation distance acquired in step S105.
  • the operation of the estimation unit 104 in step S103 is the same as that described in the first embodiment.
  • the estimation unit 104 calculates the estimated value using the propagation distance calculated by the propagation distance calculation unit 103.
  • the estimation unit 104 calculates the estimated value using the propagation distance acquired from the propagation distance storage unit 105.
  • the estimation value calculation algorithm itself is the same as that described in the first embodiment.
  • the calculated propagation distance is stored in the storage area. Therefore, when the calculation of the estimated value is repeated, the stored propagation distance can be reused, so that the propagation distance does not need to be recalculated. As a result, an estimated value can be obtained with a small calculation load.
  • Embodiment 4 In the present embodiment, the difference from the first embodiment will be mainly described. The matters not explained below are the same as those in the first embodiment.
  • the propagation distance calculation unit 103 extracts the propagation path in consideration of the wind direction in the space 4. That is, in the present embodiment, the propagation distance calculation unit 103 uses the wind direction information to select a route in which various particles existing in the space 4 are likely to be transported as the propagation route. Therefore, in the present embodiment, the propagation distance calculation unit 103 may select a path that is not the shortest as the propagation path depending on the wind direction in the space 4.
  • FIG. 14 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
  • the wind direction information storage unit 106 is added as compared with the configuration of FIG.
  • the wind direction information storage unit 106 stores the wind direction information.
  • the wind direction information indicates the wind direction in the space 4.
  • wind direction sensors provided at a plurality of locations in the space 4 can obtain wind directions at a plurality of locations in the space 4.
  • the wind direction information storage unit 106 is realized by the main storage device 902 or the auxiliary storage device 903.
  • the elements other than the wind direction information storage unit 106 are the same as those shown in FIG.
  • the propagation distance calculation unit 103 acquires wind direction information from the wind direction information storage unit 106, and selects a propagation path using the acquired wind direction information.
  • FIG. 15 shows an operation example of the information processing apparatus 100 according to the present embodiment.
  • step S101 is the same as that described in the first embodiment, and thus the description thereof will be omitted.
  • step S106 the propagation distance calculation unit 103 acquires the wind direction information from the wind direction information storage unit 106.
  • step S102 the propagation distance calculation unit 103 extracts the propagation path using the wind direction information.
  • FIG. 16 shows the extraction principle of the propagation path of the propagation distance calculation unit 103 according to the present embodiment.
  • FIG. 16A shows an example of a propagation path extracted without considering the wind direction. That is, the propagation distance calculation unit 103 selects the shortest route 15 from the observation point 1 to the estimation point 2 as the propagation route when the wind direction is not taken into consideration.
  • FIG. 16B shows an example of a propagation path extracted in consideration of the wind direction. That is, the propagation distance calculation unit 103 selects, among the shortest route 15 and the other route 16, the route having a large amount of fluid propagation as the propagation route.
  • FIG. 16A shows an example of a propagation path extracted without considering the wind direction. That is, the propagation distance calculation unit 103 selects the shortest route 15 from the observation point 1 to the estimation point 2 as the propagation route when the wind direction is not taken into consideration.
  • FIG. 16B shows an example of a propagation path extracted in consideration of the wind direction. That is, the propagation distance calculation unit
  • the propagation distance calculation unit 103 selects the path 16 as the propagation path. For example, the propagation distance calculation unit 103 applies the wind direction in the space 4 to the air propagation model, determines in which route the air propagation amount is large, and selects the propagation path. Then, the propagation distance calculation unit 103 calculates the propagation distance in step S102. The method of calculating the propagation distance is the same as that described in the first embodiment.
  • step S103 the estimation unit 104 calculates the estimated value using the propagation distance.
  • the method of calculating the estimated value is the same as that described in the first embodiment.
  • Embodiment 5 the differences between the first embodiment and the fourth embodiment will be mainly described. The matters not explained below are the same as those in the first embodiment and the fourth embodiment.
  • the propagation distance calculation unit 103 acquires the set wind direction information indicating the set wind direction set in the air conditioner provided in the space 4. Then, the propagation distance calculation unit 103 extracts the propagation path using the set wind direction shown in the set wind direction information.
  • FIG. 17 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
  • the air conditioner setting information storage unit 107 is added as compared with the configuration of FIG.
  • the air conditioner setting information storage unit 107 stores the setting information of the air conditioner provided in the space 4.
  • the air conditioner setting information storage unit 107 stores the temperature, wind direction, etc. set by the user of the space 4 using the remote controller as setting information.
  • the air conditioner setting information storage unit 107 is realized by the main storage device 902 or the auxiliary storage device 903.
  • the elements other than the air conditioner setting information storage unit 107 are the same as those shown in FIG.
  • the propagation distance calculation unit 103 acquires the set wind direction information indicating the set wind direction from the set information from the air conditioner setting information storage unit 107, and uses the acquired set wind direction information to propagate the propagation path. Select.
  • FIG. 18 shows an operation example of the information processing apparatus 100 according to the present embodiment.
  • step S101 is the same as that described in the first embodiment, and thus the description thereof will be omitted.
  • step S107 the propagation distance calculation unit 103 acquires the set wind direction information from the air conditioner setting information storage unit 107.
  • the propagation distance calculation unit 103 extracts the propagation path using the set wind direction information. Similar to the fourth embodiment, the propagation distance calculation unit 103 selects a path having a large amount of fluid propagation as a propagation path from a plurality of paths in consideration of the set wind direction.
  • the propagation distance calculation unit 103 applies, for example, a set wind direction to an air propagation model, determines in which route the amount of air propagation is large, and selects a propagation path.
  • the propagation distance calculation unit 103 selects a propagation path using the set wind direction instead of the wind direction obtained by the wind direction sensor of the fourth embodiment.
  • the propagation distance calculation unit 103 calculates the propagation distance in step S102.
  • the method of calculating the propagation distance is the same as that described in the first embodiment.
  • step S103 the estimation unit 104 calculates the estimated value using the propagation distance.
  • the method of calculating the estimated value is the same as that described in the first embodiment.
  • the propagation path is extracted in consideration of the set wind direction. Therefore, the state value of the fluid in the room can be estimated with higher accuracy than in the first embodiment. Further, in the present embodiment, the wind direction sensor required in the fourth embodiment can be eliminated.
  • the processor 901 shown in FIG. 2 is an IC (Integrated Circuit) that performs processing.
  • the processor 901 is a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or the like.
  • the main storage device 902 shown in FIG. 2 is a RAM (Random Access Memory).
  • the auxiliary storage device 903 shown in FIG. 2 is a ROM (Read Only Memory), a flash memory, an HDD (Hard Disk Drive), or the like.
  • the communication device 904 shown in FIG. 2 is an electronic circuit that executes data communication processing.
  • the communication device 904 is, for example, a communication chip or a NIC (Network Interface Card).
  • the OS (Operating System) is also stored in the auxiliary storage device 903. Then, at least a part of the OS is executed by the processor 901.
  • the processor 901 executes a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 while executing at least a part of the OS.
  • the processor 901 executes the OS, task management, memory management, file management, communication control, and the like are performed.
  • at least one of the information, data, signal value, and variable value indicating the processing result of the propagation distance calculation unit 103 and the estimation unit 104 is the main storage device 902, the auxiliary storage device 903, and the registers and cache memory in the processor 901. It is stored in at least one of.
  • a portable recording medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. Good. Then, a portable recording medium in which a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 is stored may be commercially distributed.
  • the "unit" of the propagation distance calculation unit 103 and the estimation unit 104 may be read as “circuit” or “process” or “procedure” or “processing”.
  • the information processing device 100 may be realized by a processing circuit.
  • the processing circuit is, for example, a logic IC (Integrated Circuit), a GA (Gate Array), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field-Programmable Gate Array).
  • the propagation distance calculation unit 103 and the estimation unit 104 are each realized as a part of the processing circuit.
  • the superordinate concept of the processor and the processing circuit is referred to as "processing circuit Lee". That is, the processor and the processing circuit are specific examples of the "processing circuit Lee", respectively.

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Abstract

On the basis of the position of a first point in a space, the position of a second point in the space different from the first point, and the position and size of an obstacle impeding the propagation of a fluid from the first point to the second point, a propagation distance calculation unit (103) extracts, as a propagation route, a route in the space through which the fluid is capable of propagating from the first point to the second point and calculates the distance of the extracted propagation route as a propagation distance. An estimation unit (104) estimates a state value for the fluid at the second point on the basis of the calculated propagation distance and a state value for the fluid observed at the first point.

Description

情報処理装置、情報処理方法及び情報処理プログラムInformation processing equipment, information processing methods and information processing programs
　本発明は、空間内の任意の点における流体の状態値を推定する技術に関する。 The present invention relates to a technique for estimating a fluid state value at an arbitrary point in space.
　空間内の任意の点における流体の状態値を推定する技術として空間分布推定技術がある。以下では、流体の状態値の推定対象となる点を推定点という。また、流体は、静止状態においてせん断応力が発生しない連続体である。具体的には、流体は、液体、気体及びプラズマである。流体の状態値は、計測装置を用いて計測可能な流体の値である。流体の状態値には、温度、湿度、風量、風向、臭度、濃度等が含まれる。空間分布推定技術では、例えば、流体の状態値が既知の観測点と推定点間のユークリッド距離を用いた補間により、推定点の流体の状態値が推定される。 There is a space distribution estimation technology as a technology for estimating the state value of a fluid at an arbitrary point in space. Hereinafter, the point at which the state value of the fluid is estimated is referred to as an estimation point. Further, the fluid is a continuum in which shear stress does not occur in a stationary state. Specifically, the fluids are liquids, gases and plasmas. The fluid state value is a fluid value that can be measured using a measuring device. The state value of the fluid includes temperature, humidity, air volume, wind direction, odor, concentration and the like. In the spatial distribution estimation technique, for example, the fluid state value of the estimated point is estimated by interpolation using the Euclidean distance between the observation point and the estimated point where the fluid state value is known.
　観測点と推定点との間に壁等の物理的な障害物が存在する場合には、障害物によって流体の伝搬が妨げられる。上述のようなユークリッド距離を用いた空間分布推定技術では、障害物の影響を考慮することができず、高精度な推定を行うことができない。このため、ユークリッド距離を用いた空間分布推定技術では、障害物が存在する場合には、正確な推定結果が得られない。 If there is a physical obstacle such as a wall between the observation point and the estimated point, the obstacle prevents the fluid from propagating. The spatial distribution estimation technique using the Euclidean distance as described above cannot consider the influence of obstacles and cannot perform highly accurate estimation. Therefore, the spatial distribution estimation technique using the Euclidean distance cannot obtain an accurate estimation result when an obstacle exists.
　この点、特許文献１では、流体を妨げる仕切り板が設置されている容器内の推定点の流体濃度を、観測点の流体濃度から推定する技術が開示されている。特許文献１では、仕切り板が障害物に相当する。より具体的には、特許文献１では、実験及び流体シミュレーションにより算出した観測点と推定点との最小伝達時間と、観測点での流体濃度とを用い、観測点からのガウス分布の標準偏差に基づいて推定点の流体濃度を推定する。 In this regard, Patent Document 1 discloses a technique for estimating the fluid concentration at an estimated point in a container in which a partition plate that obstructs fluid is installed from the fluid concentration at an observation point. In Patent Document 1, the partition plate corresponds to an obstacle. More specifically, in Patent Document 1, the minimum transfer time between the observation point and the estimation point calculated by the experiment and the fluid simulation and the fluid concentration at the observation point are used to obtain the standard deviation of the Gaussian distribution from the observation point. Estimate the fluid concentration at the estimation point based on this.
特開２０１１－１７９１１１号公報Japanese Unexamined Patent Publication No. 2011-179111
　以上のように、特許文献１の技術では、最小伝達時間を実験及び流体シミュレーションにより算出する必要があり、作業負荷及び計算負荷が大きいという課題がある。 As described above, in the technique of Patent Document 1, it is necessary to calculate the minimum transmission time by an experiment and a fluid simulation, and there is a problem that the workload and the calculation load are large.
　この発明は、上記のような課題を解決することを主な目的の一つとしている。より具体的には、少ない作業負荷及び計算負荷により、空間内の推定点の状態値を推定できるようにすることを主な目的とする。 One of the main purposes of this invention is to solve the above problems. More specifically, the main purpose is to make it possible to estimate the state value of an estimated point in space with a small workload and calculation load.
　本発明に係る情報処理装置は、
　空間内の第１の点の位置と、前記空間内の前記第１の点とは異なる第２の点の位置と、前記第１の点から前記第２の点への流体の伝搬の障害になる障害物の位置及びサイズとに基づき、前記空間内で前記第１の点から前記第２の点への流体の伝搬が可能な経路を伝搬経路として抽出し、抽出した伝搬経路の距離を伝搬距離として算出する伝搬距離算出部と、
　算出された前記伝搬距離と、前記第１の点で観測された流体の状態値とに基づき、前記第２の点での流体の状態値を推定する推定部とを有する。 The information processing device according to the present invention is
The position of the first point in the space, the position of the second point different from the first point in the space, and the obstacle of the propagation of the fluid from the first point to the second point. Based on the position and size of the obstacle, a path capable of propagating the fluid from the first point to the second point in the space is extracted as a propagation path, and the distance of the extracted propagation path is propagated. Propagation distance calculation unit that calculates as a distance,
It has an estimation unit that estimates the state value of the fluid at the second point based on the calculated propagation distance and the state value of the fluid observed at the first point.
　本発明によれば、少ない作業負荷及び計算負荷により、空間内の推定点の状態値を推定することができる。 According to the present invention, it is possible to estimate the state value of an estimated point in space with a small workload and a calculation load.
実施の形態１に係る情報処理装置の機能構成例を示す図。The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 1. FIG. 実施の形態１に係る情報処理装置のハードウェア構成例を示す図。The figure which shows the hardware configuration example of the information processing apparatus which concerns on Embodiment 1. FIG. 実施の形態１に係る空間、観測点、推定点及び障害物の例を示す図。The figure which shows the example of the space, the observation point, the estimation point and the obstacle which concerns on Embodiment 1. FIG. 実施の形態１に係る情報処理装置の動作例を示すフローチャート。The flowchart which shows the operation example of the information processing apparatus which concerns on Embodiment 1. 実施の形態１に係る伝搬距離算出処理及び推定値算出処理の詳細を示すフローチャート。The flowchart which shows the detail of the propagation distance calculation process and the estimated value calculation process which concerns on Embodiment 1. 実施の形態１に係る伝搬経路の例を示す図。The figure which shows the example of the propagation path which concerns on Embodiment 1. FIG. 実施の形態１に係る重みの算出式の例及び推定値の算出式の例を示す図。The figure which shows the example of the calculation formula of the weight and the example of the calculation formula of the estimated value which concerns on Embodiment 1. FIG. ユークリッド距離による温度推定例及び実施の形態１に係る温度推定例を示す図。The figure which shows the temperature estimation example by Euclidean distance and the temperature estimation example which concerns on Embodiment 1. FIG. 実施の形態２に係る情報処理装置の機能構成例を示す図。The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 2. 実施の形態２に係る観測点、推定点及び障害物の高さを考慮した伝搬経路の例を示す図。The figure which shows the example of the propagation path which considered the observation point, the estimation point and the height of an obstacle which concerns on Embodiment 2. 実施の形態３に係る情報処理装置の機能構成例を示す図。The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 3. 実施の形態３に係る前段処理の例を示すフローチャート。The flowchart which shows the example of the pre-stage processing which concerns on Embodiment 3. 実施の形態３に係る後段処理を示すフローチャート。The flowchart which shows the post-stage processing which concerns on Embodiment 3. 実施の形態４に係る情報処理装置の機能構成例を示す図。The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 4. FIG. 実施の形態４に係る情報処理装置の動作例を示すフローチャート。The flowchart which shows the operation example of the information processing apparatus which concerns on Embodiment 4. 実施の形態４に係る伝搬経路の例を示す図。The figure which shows the example of the propagation path which concerns on Embodiment 4. FIG. 実施の形態５に係る情報処理装置の機能構成例を示す図。The figure which shows the functional structure example of the information processing apparatus which concerns on Embodiment 5. 実施の形態５に係る情報処理装置の動作例を示すフローチャート。The flowchart which shows the operation example of the information processing apparatus which concerns on Embodiment 5.
　以下、本発明の実施の形態について、図を用いて説明する。以下の実施の形態の説明及び図面において、同一の符号を付したものは、同一の部分又は相当する部分を示す。 Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description and drawings of the embodiments, those having the same reference numerals indicate the same parts or corresponding parts.
　実施の形態１．
＊＊＊構成の説明＊＊＊
　図１は、本実施の形態に係る情報処理装置１００の機能構成例を示す。
　また、図２は、本実施の形態に係る情報処理装置１００のハードウェア構成例を示す。
　情報処理装置１００の動作手順は、情報処理方法に相当する。また、情報処理装置１００の動作を実現するプログラムは、情報処理プログラムに相当する。 Embodiment 1.
*** Explanation of configuration ***
FIG. 1 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
Further, FIG. 2 shows a hardware configuration example of the information processing apparatus 100 according to the present embodiment.
The operation procedure of the information processing device 100 corresponds to the information processing method. Further, the program that realizes the operation of the information processing device 100 corresponds to the information processing program.
　まず、図２を参照して情報処理装置１００のハードウェア構成例を説明する。 First, a hardware configuration example of the information processing device 100 will be described with reference to FIG.
　情報処理装置１００は、ハードウェアとして、プロセッサ９０１、主記憶装置９０２、補助記憶装置９０３及び通信装置９０４を備える。
　補助記憶装置９０３には、図１に示す伝搬距離算出部１０３及び推定部１０４の機能を実現するプログラムが記憶されている。伝搬距離算出部１０３及び推定部１０４の詳細は後述する。
　これらプログラムは、補助記憶装置９０３から主記憶装置９０２にロードされる。そして、プロセッサ９０１がこれらプログラムを実行して、伝搬距離算出部１０３及び推定部１０４の動作を行う。
　図２では、プロセッサ９０１が伝搬距離算出部１０３及び推定部１０４の機能を実現するプログラムを実行している状態を模式的に表している。
　また、図１に示す障害物情報記憶部１０１及び観測点／推定点情報記憶部１０２は、主記憶装置９０２又は補助記憶装置９０３により実現される。 The information processing device 100 includes a processor 901, a main storage device 902, an auxiliary storage device 903, and a communication device 904 as hardware.
The auxiliary storage device 903 stores a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 shown in FIG. Details of the propagation distance calculation unit 103 and the estimation unit 104 will be described later.
These programs are loaded from the auxiliary storage device 903 into the main storage device 902. Then, the processor 901 executes these programs to operate the propagation distance calculation unit 103 and the estimation unit 104.
FIG. 2 schematically shows a state in which the processor 901 is executing a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104.
Further, the obstacle information storage unit 101 and the observation point / estimation point information storage unit 102 shown in FIG. 1 are realized by the main storage device 902 or the auxiliary storage device 903.
　次に、図１を参照して情報処理装置１００の機能構成例を説明する。 Next, an example of the functional configuration of the information processing apparatus 100 will be described with reference to FIG.
　障害物情報記憶部１０１は、障害物情報を記憶する。障害物情報は、空間内に存在する障害物の情報である。
　以下では、図３に示す障害物３を前提にして説明を行う。
　図３では、空間４内に観測点１と推定点２とが存在する。観測点１は流体の状態値が既知の点である。観測点１は第１の点に相当する。推定点２は流体の状態値が未知の点である。推定点２は第２の点に相当する。
　障害物３は観測点１から推定点２への流体の伝搬の障害となる。つまり、流体は観測点１から推定点２まで移動するためには障害物３に沿って迂回しなければならず、観測点１から推定点２までの最短距離で移動することができない。
　障害物情報記憶部１０１は、障害物３の位置が二次元で表された障害物位置情報と、障害物３のサイズが二次元で表された障害物サイズ情報を障害物情報として保持する。 The obstacle information storage unit 101 stores obstacle information. Obstacle information is information on obstacles existing in the space.
In the following, the description will be made on the premise of the obstacle 3 shown in FIG.
In FIG. 3, the observation point 1 and the estimation point 2 exist in the space 4. Observation point 1 is a point where the state value of the fluid is known. Observation point 1 corresponds to the first point. Estimated point 2 is a point where the state value of the fluid is unknown. Estimated point 2 corresponds to the second point.
Obstacle 3 is an obstacle to the propagation of fluid from observation point 1 to estimation point 2. That is, the fluid must detour along the obstacle 3 in order to move from the observation point 1 to the estimation point 2, and cannot move in the shortest distance from the observation point 1 to the estimation point 2.
The obstacle information storage unit 101 holds the obstacle position information in which the position of the obstacle 3 is represented in two dimensions and the obstacle size information in which the size of the obstacle 3 is represented in two dimensions as the obstacle information.
　観測点／推定点情報記憶部１０２は、観測点／推定点情報を記憶する。
　観測点／推定点情報は、観測点１の位置が二次元で表された観測点位置情報及び推定点２の位置が二次元で表された推定点位置情報で構成される。 The observation point / estimation point information storage unit 102 stores the observation point / estimation point information.
The observation point / estimation point information is composed of observation point position information in which the position of observation point 1 is represented in two dimensions and estimation point position information in which the position of estimation point 2 is represented in two dimensions.
　伝搬距離算出部１０３は、伝搬距離を算出する。伝搬距離は、伝搬経路の距離である。伝搬経路は、空間４内で観測点１から推定点２への流体の伝搬が可能な経路である。
　本実施の形態では、伝搬距離算出部１０３は、空間４内の観測点１の位置と推定点２の位置と、障害物３の位置及びサイズに基づき、空間４内で観測点１から推定点２への流体の伝搬が可能な最短の経路を伝搬経路として抽出する。そして、伝搬距離算出部１０３は、抽出した伝搬経路の距離を伝搬距離として算出する。
　伝搬距離算出部１０３は、１つの推定点２に対して複数の観測点１を設定する。そして、伝搬距離算出部１０３は、観測点１ごとに、伝搬経路の抽出及び伝搬距離の算出を行う。
　つまり、伝搬距離算出部１０３は、複数の観測点１の位置に基づき、観測点１ごとに、空間４内で推定点２への流体の伝搬が可能な経路を伝搬経路として抽出する。そして、伝搬距離算出部１０３は、抽出した複数の伝搬経路の各々の距離を伝搬距離として算出する。
　なお、伝搬距離算出部１０３により行われる処理は、伝搬距離算出処理に相当する。 The propagation distance calculation unit 103 calculates the propagation distance. The propagation distance is the distance of the propagation path. The propagation path is a path capable of propagating the fluid from the observation point 1 to the estimation point 2 in the space 4.
In the present embodiment, the propagation distance calculation unit 103 estimates from the observation point 1 in the space 4 based on the position of the observation point 1 and the estimation point 2 in the space 4 and the position and size of the obstacle 3. The shortest path through which the fluid can propagate to 2 is extracted as the propagation path. Then, the propagation distance calculation unit 103 calculates the distance of the extracted propagation path as the propagation distance.
The propagation distance calculation unit 103 sets a plurality of observation points 1 for one estimation point 2. Then, the propagation distance calculation unit 103 extracts the propagation path and calculates the propagation distance for each observation point 1.
That is, the propagation distance calculation unit 103 extracts a path capable of propagating the fluid to the estimation point 2 in the space 4 as a propagation path for each observation point 1 based on the positions of the plurality of observation points 1. Then, the propagation distance calculation unit 103 calculates the distance of each of the extracted plurality of propagation paths as the propagation distance.
The process performed by the propagation distance calculation unit 103 corresponds to the propagation distance calculation process.
　推定部１０４は、伝搬距離算出部１０３により算出された観測点１ごとの伝搬距離と、複数の観測点１の各々で観測された流体の状態値とに基づき、推定点２での流体の状態値を推定する。
　より具体的には、推定部１０４は、観測点１ごとに、伝搬距離算出部１０３により算出された伝搬距離に基づいて重みを設定する。そして、推定部１０４は、設定した観測点１ごとの重みと、複数の観測点１の各々で観測された流体の状態値とに基づき、推定点２での流体の状態値を推定する。 The estimation unit 104 is based on the propagation distance for each observation point 1 calculated by the propagation distance calculation unit 103 and the state value of the fluid observed at each of the plurality of observation points 1, and the state of the fluid at the estimation point 2. Estimate the value.
More specifically, the estimation unit 104 sets a weight for each observation point 1 based on the propagation distance calculated by the propagation distance calculation unit 103. Then, the estimation unit 104 estimates the state value of the fluid at the estimation point 2 based on the weight of each set observation point 1 and the state value of the fluid observed at each of the plurality of observation points 1.
＊＊＊動作の説明＊＊＊
　次に、情報処理装置１００の動作例を説明する。 *** Explanation of operation ***
Next, an operation example of the information processing device 100 will be described.
　図４を用いて、情報処理装置１００の動作の概要を説明する。 The outline of the operation of the information processing apparatus 100 will be described with reference to FIG.
　先ず、伝搬距離算出部１０３が、観測点１と推定点２とを設定する（ステップＳ１０１）。
　前述のように、１つの推定点２に対して複数の観測点１を設定する。また、伝搬距離算出部１０３は、複数の推定点２を設定してもよい。この場合は、伝搬距離算出部１０３は、複数の推定点２の各々に対して複数の観測点１を設定する。
　以下では、説明の簡明化のために、１つの推定点２を設定する例を説明する。 First, the propagation distance calculation unit 103 sets the observation point 1 and the estimation point 2 (step S101).
As described above, a plurality of observation points 1 are set for one estimation point 2. Further, the propagation distance calculation unit 103 may set a plurality of estimation points 2. In this case, the propagation distance calculation unit 103 sets a plurality of observation points 1 for each of the plurality of estimation points 2.
In the following, for the sake of simplification of the description, an example of setting one estimation point 2 will be described.
　次に、伝搬距離算出部１０３は、伝搬距離を算出する（ステップＳ１０２）。
　より具体的には、伝搬距離算出部１０３は、障害物情報記憶部１０１から障害物情報（障害物３の位置及びサイズ）を取得し、観測点／推定点情報記憶部１０２から観測点／計測点情報（観測点１の位置と推定点２の位置）を取得する。そして、伝搬距離算出部１０３は、取得した障害物情報と観測点／計測点情報に基づいて伝搬経路を抽出する。
　前述したように、伝搬経路は、観測点１から推定点２への流体の伝搬が可能な最短の経路である。
　図３の観測点１と推定点２の場合は、図６に示す経路５が伝搬経路に相当する。
　そして、伝搬距離算出部１０３は、このような伝搬経路を抽出し、抽出した伝搬経路の距離を算出する。
　伝搬距離算出部１０３は、算出した伝搬距離を推定部１０４に出力する。 Next, the propagation distance calculation unit 103 calculates the propagation distance (step S102).
More specifically, the propagation distance calculation unit 103 acquires obstacle information (position and size of the obstacle 3) from the obstacle information storage unit 101, and observes / measures from the observation point / estimation point information storage unit 102. The point information (the position of the observation point 1 and the position of the estimation point 2) is acquired. Then, the propagation distance calculation unit 103 extracts the propagation path based on the acquired obstacle information and the observation point / measurement point information.
As described above, the propagation path is the shortest path capable of propagating the fluid from the observation point 1 to the estimation point 2.
In the case of the observation point 1 and the estimation point 2 in FIG. 3, the path 5 shown in FIG. 6 corresponds to the propagation path.
Then, the propagation distance calculation unit 103 extracts such a propagation path and calculates the distance of the extracted propagation path.
The propagation distance calculation unit 103 outputs the calculated propagation distance to the estimation unit 104.
　次に、推定部１０４が推定値を算出する（ステップＳ１０３）。 Next, the estimation unit 104 calculates the estimated value (step S103).
　伝搬距離算出部１０３は伝搬距離の算出（ステップＳ１０２）をステップＳ１０１で設定された複数の観測点１の各々について行う。また、推定部１０４は、複数の観測点１の各々に対して算出された伝搬距離を用いて推定値の算出（ステップＳ１０３）を行う。
　また、ステップＳ１０１で複数の推定点２が設定されている場合は、推定部１０４は、複数の推定点２の各々について推定値の算出（ステップＳ１０３）を行う。 The propagation distance calculation unit 103 calculates the propagation distance (step S102) for each of the plurality of observation points 1 set in step S101. Further, the estimation unit 104 calculates an estimated value (step S103) using the propagation distance calculated for each of the plurality of observation points 1.
When a plurality of estimated points 2 are set in step S101, the estimation unit 104 calculates an estimated value for each of the plurality of estimated points 2 (step S103).
　図５は、図４のステップＳ１０２及びステップＳ１０３の詳細を示す。 FIG. 5 shows the details of step S102 and step S103 of FIG.
　図５において、ステップＳ１０１は図４に示したものと同じであるため、説明を省略する。 In FIG. 5, step S101 is the same as that shown in FIG. 4, so the description thereof will be omitted.
　ステップＳ１０２０は、図４のステップＳ１０２の詳細を示す。
　具体的には、伝搬距離算出部１０３は、Ａ＊探索アルゴリズム、ダイクストラ法等を用いて観測点と推定点間の最短経路の距離（最短距離）を伝搬距離として算出する。 Step S1020 shows the details of step S102 of FIG.
Specifically, the propagation distance calculation unit 103 calculates the distance (shortest distance) of the shortest path between the observation point and the estimation point as the propagation distance by using an A * search algorithm, Dijkstra's algorithm, or the like.
　ステップＳ１０３０は、図４のステップＳ１０３の詳細を示す。
　具体的には、推定部１０４は、ステップＳ１０２０で算出された伝搬距離から重みを計算し、加重平均により推定値を算出する。
　推定部１０４は、例えば、図７の（ａ）に示す算出式を用いて重みを算出する。また、推定部１０４は、例えば、図７の（ｂ）に示す算出式を用いて推定値を算出する。 Step S1030 shows the details of step S103 of FIG.
Specifically, the estimation unit 104 calculates the weight from the propagation distance calculated in step S1020, and calculates the estimated value by the weighted average.
The estimation unit 104 calculates the weight using, for example, the calculation formula shown in FIG. 7A. Further, the estimation unit 104 calculates the estimated value using, for example, the calculation formula shown in FIG. 7 (b).
　図８は、空気の温度（空間４内の温度）を流体の状態値の例とする場合の推定点２での温度の推定方法を示す。 FIG. 8 shows a method of estimating the temperature at the estimation point 2 when the temperature of the air (the temperature in the space 4) is taken as an example of the state value of the fluid.
　図８の（ａ）では、空間４の床面が矩形の仮想的な部分領域に分割されている。また、図８の（ａ）では、２つの観測点１が存在する。つまり、図８の（ａ）では、観測点１ａと観測点１ｂが存在する。観測点１ａの所在する部分領域で観測された温度は２０℃であることを示している。また、観測点１ｂの所在する部分領域で観測された温度は３０℃であることを示している。例えば、観測点１ａが所在する領域（障害物３の左側の領域）は空気調和機により冷房運転が行われている。一方。観測点１ｂが所在する領域（障害物３の右側の領域）は冷房運転が行われていない。
　図８の（ｂ）は、ユークリッド距離による温度推定例を示す。つまり、図８の（ｂ）では、観測点１ａ及び観測点１ｂの位置からの距離にのみ依存して温度が推定されている。
　図８の（ｃ）は、本実施の形態に係る情報処理装置１００による温度推定例を示す。つまり、図８の（ｃ）は、図４及び図５に示す手順により推定された各部分領域の温度を示す。図８の（ｃ）では、観測点１ａが所在する部分領域及び観測点１ｂが所在する部分領域以外の部分領域を推定点２に指定して図４及び図５に示す手順を実施して得られた温度分布を示す。 In FIG. 8A, the floor surface of the space 4 is divided into rectangular virtual subregions. Further, in FIG. 8A, there are two observation points 1. That is, in FIG. 8A, the observation point 1a and the observation point 1b exist. It shows that the temperature observed in the partial region where the observation point 1a is located is 20 ° C. It also indicates that the temperature observed in the partial region where the observation point 1b is located is 30 ° C. For example, the region where the observation point 1a is located (the region on the left side of the obstacle 3) is cooled by an air conditioner. on the other hand. The area where the observation point 1b is located (the area on the right side of the obstacle 3) is not cooled.
FIG. 8B shows an example of temperature estimation based on the Euclidean distance. That is, in FIG. 8B, the temperature is estimated only depending on the distances from the observation points 1a and the observation points 1b.
FIG. 8C shows an example of temperature estimation by the information processing apparatus 100 according to the present embodiment. That is, (c) of FIG. 8 shows the temperature of each partial region estimated by the procedure shown in FIGS. 4 and 5. In FIG. 8C, the partial region where the observation point 1a is located and the partial region other than the partial region where the observation point 1b is located are designated as the estimation points 2 and the procedure shown in FIGS. 4 and 5 is performed. Shows the temperature distribution.
　例えば、図８の（ｂ）では、部分領域４１の温度として２８℃が推定される。部分領域４１は観測点１ｂの部分領域に近いので、観測点１ｂの部分領域の温度である３０℃に近い温度である２８℃が推定される。図８の（ｃ）では、部分領域４１の温度として２２℃が推定される。部分領域４１と観測点１ｂの部分領域との間に障害物３が存在する一方で部分領域４１と観測点１ａの部分領域との間には障害物３が存在しない。このため、観測点１ａの部分領域の温度である２０℃に近い温度である２２℃が推定される。
　また、図８の（ｂ）では、部分領域４２の温度として２１℃が推定される。部分領域４２は観測点１ａの部分領域に近いので、観測点１ａの部分領域の温度である２０℃に近い温度である２１℃が推定される。図８の（ｃ）では、部分領域４２の温度として２９℃が推定される。部分領域４２と観測点１ａの部分領域との間に障害物３が存在する一方で部分領域４２と観測点１ｂの部分領域との間には障害物３が存在しない。このため、観測点１ｂの部分領域の温度である３０℃に近い温度である２９℃が推定される。
　同様に、図８の（ｂ）では、部分領域４３の温度として２２℃が推定される。部分領域４３は観測点１ａの部分領域に近いので、観測点１ａの部分領域の温度である２０℃に近い温度である２２℃が推定される。図８の（ｃ）では、部分領域４３の温度として２９℃が推定される。部分領域４３と観測点１ａの部分領域との間に障害物３が存在する一方で部分領域４３と観測点１ｂの部分領域との間には障害物３が存在しない。このため、観測点１ｂの部分領域の温度である３０℃に近い温度である２９℃が推定される。 For example, in FIG. 8B, 28 ° C. is estimated as the temperature of the partial region 41. Since the partial region 41 is close to the partial region of the observation point 1b, it is estimated that the temperature is 28 ° C., which is close to the temperature of the partial region of the observation point 1b, which is 30 ° C. In FIG. 8C, 22 ° C. is estimated as the temperature of the partial region 41. The obstacle 3 exists between the partial region 41 and the partial region of the observation point 1b, while the obstacle 3 does not exist between the partial region 41 and the partial region of the observation point 1a. Therefore, 22 ° C., which is a temperature close to 20 ° C., which is the temperature of the partial region of the observation point 1a, is estimated.
Further, in FIG. 8B, the temperature of the partial region 42 is estimated to be 21 ° C. Since the partial region 42 is close to the partial region of the observation point 1a, it is estimated that the temperature is 21 ° C., which is close to the temperature of the partial region of the observation point 1a, which is 20 ° C. In FIG. 8C, 29 ° C. is estimated as the temperature of the partial region 42. The obstacle 3 exists between the partial region 42 and the partial region of the observation point 1a, while the obstacle 3 does not exist between the partial region 42 and the partial region of the observation point 1b. Therefore, 29 ° C., which is a temperature close to 30 ° C., which is the temperature of the partial region of the observation point 1b, is estimated.
Similarly, in FIG. 8B, 22 ° C. is estimated as the temperature of the partial region 43. Since the partial region 43 is close to the partial region of the observation point 1a, 22 ° C., which is a temperature close to 20 ° C., which is the temperature of the partial region of the observation point 1a, is estimated. In FIG. 8C, 29 ° C. is estimated as the temperature of the partial region 43. The obstacle 3 exists between the partial region 43 and the partial region of the observation point 1a, while the obstacle 3 does not exist between the partial region 43 and the partial region of the observation point 1b. Therefore, 29 ° C., which is a temperature close to 30 ° C., which is the temperature of the partial region of the observation point 1b, is estimated.
　なお、推定部１０４は、図８の（ｃ）のように、空間４内の部分領域ごとの温度分布をディスプレイに表示してもよい。このようにすることで、情報処理装置１００のユーザは、視覚的に空間４内の温度分布を把握することができる。 Note that the estimation unit 104 may display the temperature distribution for each partial region in the space 4 on the display as shown in FIG. 8C. By doing so, the user of the information processing apparatus 100 can visually grasp the temperature distribution in the space 4.
＊＊＊実施の形態の効果の説明＊＊＊
　図８に示すように、ユークリッド距離を用いた空間分布推定技術では、空間内に障害物が存在する場合には、正確な推定結果が得られない。一方、本実施の形態によれば、障害物の影響を考慮した高精度な状態値の推定を行うことができる。
　また、本実施の形態では、実験及び流体シミュレーションを行うことなく、空間内の推定点の状態値を推定することができる。このため、本実施の形態によれば、少ない作業負荷及び計算負荷により空間内の推定点の状態値を推定することができる。 *** Explanation of the effect of the embodiment ***
As shown in FIG. 8, the spatial distribution estimation technique using the Euclidean distance cannot obtain an accurate estimation result when an obstacle exists in the space. On the other hand, according to the present embodiment, it is possible to estimate the state value with high accuracy in consideration of the influence of obstacles.
Further, in the present embodiment, the state value of the estimated point in the space can be estimated without performing an experiment and a fluid simulation. Therefore, according to the present embodiment, the state value of the estimated point in the space can be estimated with a small workload and a calculation load.
　実施の形態２．
　本実施の形態では、主に実施の形態１との差異を説明する。
　なお、以下で説明していない事項は、実施の形態１と同様である。 Embodiment 2.
In the present embodiment, the difference from the first embodiment will be mainly described.
The matters not explained below are the same as those in the first embodiment.
　実施の形態１では、伝搬距離算出部１０３は、二次元での観測点１の位置と推定点２の位置と障害物３の位置及びサイズに基づき、伝搬距離を算出している。
　本実施の形態では、伝搬距離算出部１０３は、三次元での観測点１の位置と推定点２の位置と障害物３の位置及びサイズに基づき、伝搬距離を算出する。 In the first embodiment, the propagation distance calculation unit 103 calculates the propagation distance based on the position of the observation point 1 in two dimensions, the position of the estimation point 2, and the position and size of the obstacle 3.
In the present embodiment, the propagation distance calculation unit 103 calculates the propagation distance based on the position of the observation point 1 in three dimensions, the position of the estimation point 2, and the position and size of the obstacle 3.
＊＊＊構成の説明＊＊＊
　図９は、本実施の形態に係る情報処理装置１００の機能構成例を示す。
　図９では、図１の構成と比較して、障害物情報及び観測点／推定点情報が異なる。
　つまり、図１では、障害物情報の障害物位置情報及び障害物サイズ情報は二次元の情報（横、縦）であったが、図９では、障害物情報の障害物位置情報及び障害物サイズ情報は三次元の情報（横、縦、高さ）である。
　また、図１では、観測点／推定点情報の観測点位置情報及び推定点位置情報は二次元の情報であったが、図９では、観測点／推定点情報の観測点位置情報及び推定点位置情報は三次元の情報である。図９では、障害物情報の障害物位置情報は三次元で表されているが、障害物位置情報は実施の形態１と同様に二次元で表されてもよい。
　図９の他の要素は図１に示したものと同じであるため、説明を省略する。 *** Explanation of configuration ***
FIG. 9 shows an example of the functional configuration of the information processing apparatus 100 according to the present embodiment.
In FIG. 9, the obstacle information and the observation point / estimation point information are different from the configuration of FIG.
That is, in FIG. 1, the obstacle position information and the obstacle size information of the obstacle information are two-dimensional information (horizontal and vertical), but in FIG. 9, the obstacle position information and the obstacle size of the obstacle information are shown. Information is three-dimensional information (horizontal, vertical, height).
Further, in FIG. 1, the observation point position information and the estimation point position information of the observation point / estimation point information are two-dimensional information, but in FIG. 9, the observation point position information and the estimation point of the observation point / estimation point information are The position information is three-dimensional information. In FIG. 9, the obstacle position information of the obstacle information is represented in three dimensions, but the obstacle position information may be represented in two dimensions as in the first embodiment.
Since the other elements of FIG. 9 are the same as those shown in FIG. 1, the description thereof will be omitted.
＊＊＊動作の説明＊＊＊
　図１０は、本実施の形態に係る情報処理装置１００の動作例を示す。 *** Explanation of operation ***
FIG. 10 shows an operation example of the information processing apparatus 100 according to the present embodiment.
　図１０の（ａ）は、側方から観測点１、推定点２及び障害物３を見た図である。図１０の（ｂ）は、上方から観測点１、推定点２及び障害物３を見た図である。
　なお、図１０では、障害物３の背後に壁６が存在するものとする。
　また、図１０では、観測点１及び推定点２は、障害物３の高さよりも高い位置に配置されている。
　観測点１、推定点２及び障害物３の高さを考量しなければ、伝搬距離算出部１０３は、流体の伝搬は障害物３により妨げられると認識し、符号１２で示される経路を伝搬経路として抽出することになる。一方、観測点１、推定点２及び障害物３の高さを考量した場合は、伝搬距離算出部１０３は、観測点１と推定点２は障害物３よりも高い位置にあるため、符号１１の経路でも流体は伝搬可能と認識する。この結果、伝搬距離算出部１０３は、符号１１の経路を伝搬経路として抽出する。
　伝搬距離算出部１０３は、このようにして抽出した符号１１の経路の伝搬距離を算出する。
　そして、推定部１０４は、符号１１の経路の伝搬距離に基づいて、推定点２の状態値を推定する。 FIG. 10A is a view of the observation point 1, the estimation point 2, and the obstacle 3 from the side. FIG. 10B is a view of the observation point 1, the estimation point 2, and the obstacle 3 from above.
In FIG. 10, it is assumed that the wall 6 exists behind the obstacle 3.
Further, in FIG. 10, the observation point 1 and the estimation point 2 are arranged at positions higher than the height of the obstacle 3.
If the heights of the observation point 1, the estimation point 2, and the obstacle 3 are not considered, the propagation distance calculation unit 103 recognizes that the propagation of the fluid is hindered by the obstacle 3, and follows the path indicated by reference numeral 12. Will be extracted as. On the other hand, when the heights of the observation point 1, the estimation point 2 and the obstacle 3 are considered, the propagation distance calculation unit 103 indicates that the observation point 1 and the estimation point 2 are higher than the obstacle 3, so that the reference numeral 11 It is recognized that the fluid can propagate even in the path of. As a result, the propagation distance calculation unit 103 extracts the path of reference numeral 11 as the propagation path.
The propagation distance calculation unit 103 calculates the propagation distance of the route of reference numeral 11 extracted in this way.
Then, the estimation unit 104 estimates the state value of the estimation point 2 based on the propagation distance of the path of reference numeral 11.
＊＊＊実施の形態の効果の説明＊＊＊
　本実施の形態では、観測点、推定点及び障害物の高さも考慮して伝搬経路を抽出する。このため、実施の形態１よりも高精度に室内の流体の状態値を推定することができる。 *** Explanation of the effect of the embodiment ***
In the present embodiment, the propagation path is extracted in consideration of the observation point, the estimation point, and the height of the obstacle. Therefore, the state value of the fluid in the room can be estimated with higher accuracy than in the first embodiment.
　実施の形態３．
　本実施の形態では、主に実施の形態１との差異を説明する。
　なお、以下で説明していない事項は、実施の形態１と同様である。 Embodiment 3.
In the present embodiment, the difference from the first embodiment will be mainly described.
The matters not explained below are the same as those in the first embodiment.
　本実施の形態では、伝搬距離算出部１０３が、事前に伝搬距離を算出し、算出した伝搬距離を記憶領域に格納する。そして、状態値を推定する際に、推定部１０４が、記憶領域から伝搬距離を取得し、取得した伝搬距離を用いて状態値を推定する。 In the present embodiment, the propagation distance calculation unit 103 calculates the propagation distance in advance and stores the calculated propagation distance in the storage area. Then, when estimating the state value, the estimation unit 104 acquires the propagation distance from the storage area and estimates the state value using the acquired propagation distance.
＊＊＊構成の説明＊＊＊
　図１１は、本実施の形態に係る情報処理装置１００の機能構成例を示す。
　図１１では、図１の構成と比較して、伝搬距離記憶部１０５が追加されている。
　伝搬距離記憶部１０５は、伝搬距離算出部１０３により算出された伝搬距離を記憶する。
　伝搬距離記憶部１０５は、主記憶装置９０２又は補助記憶装置９０３により実現される。
　伝搬距離記憶部１０５以外の要素は図１に示したものと同じである。
　なお、本実施の形態では、推定部１０４は、伝搬距離記憶部１０５から伝搬距離を取得し、取得した伝搬距離を用いて状態値を推定する。 *** Explanation of configuration ***
FIG. 11 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
In FIG. 11, the propagation distance storage unit 105 is added as compared with the configuration of FIG.
The propagation distance storage unit 105 stores the propagation distance calculated by the propagation distance calculation unit 103.
The propagation distance storage unit 105 is realized by the main storage device 902 or the auxiliary storage device 903.
The elements other than the propagation distance storage unit 105 are the same as those shown in FIG.
In the present embodiment, the estimation unit 104 acquires the propagation distance from the propagation distance storage unit 105, and estimates the state value using the acquired propagation distance.
＊＊＊動作の説明＊＊＊
　図１２及び図１３は、本実施の形態に係る情報処理装置１００の動作例を示す。
　図１２は、前段処理を示す。図１３は、後段処理を示す。 *** Explanation of operation ***
12 and 13 show an operation example of the information processing apparatus 100 according to the present embodiment.
FIG. 12 shows the pre-stage processing. FIG. 13 shows the post-stage processing.
　図１２において、ステップＳ１０１及びステップＳ１０２は、実施の形態１で説明したものと同じであるため、説明を省略する。 In FIG. 12, steps S101 and S102 are the same as those described in the first embodiment, and thus the description thereof will be omitted.
　ステップＳ１０４では、伝搬距離算出部１０３は、ステップＳ１０２で算出した伝搬距離を伝搬距離記憶部１０５に格納し、伝搬距離記憶部１０５が伝搬距離を記憶する。伝搬距離算出部１０３は、ステップＳ１０１で設定された観測点１と推定点２の組合せと対応付けて伝搬距離を伝搬距離記憶部１０５に格納する。 In step S104, the propagation distance calculation unit 103 stores the propagation distance calculated in step S102 in the propagation distance storage unit 105, and the propagation distance storage unit 105 stores the propagation distance. The propagation distance calculation unit 103 stores the propagation distance in the propagation distance storage unit 105 in association with the combination of the observation point 1 and the estimation point 2 set in step S101.
　図１３において、ステップＳ１０１は実施の形態１で説明したものと同じであるため、説明を省略する。 In FIG. 13, step S101 is the same as that described in the first embodiment, and thus the description thereof will be omitted.
　ステップＳ１０５では、推定部１０４は、ステップＳ１０１で設定された観測点１と推定点２の組合せに対応する伝搬距離を伝搬距離記憶部１０５から取得する。 In step S105, the estimation unit 104 acquires the propagation distance corresponding to the combination of the observation point 1 and the estimation point 2 set in step S101 from the propagation distance storage unit 105.
　次に、推定部１０４は、ステップＳ１０３において、ステップＳ１０５で取得した伝搬距離を用いて推定値を算出する。ステップＳ１０３における推定部１０４の動作は、実施の形態１で説明したものと同じである。実施の形態１では、推定部１０４は、伝搬距離算出部１０３が算出した伝搬距離を用いて推定値を算出する。これに対して、本実施の形態では、推定部１０４は、伝搬距離記憶部１０５から取得した伝搬距離を用いて推定値を算出する。推定値の算出アルゴリズム自体は、実施の形態１で説明したものと同じである。 Next, in step S103, the estimation unit 104 calculates an estimated value using the propagation distance acquired in step S105. The operation of the estimation unit 104 in step S103 is the same as that described in the first embodiment. In the first embodiment, the estimation unit 104 calculates the estimated value using the propagation distance calculated by the propagation distance calculation unit 103. On the other hand, in the present embodiment, the estimation unit 104 calculates the estimated value using the propagation distance acquired from the propagation distance storage unit 105. The estimation value calculation algorithm itself is the same as that described in the first embodiment.
＊＊＊実施の形態の効果の説明＊＊＊
　本実施の形態では、算出した伝搬距離を記憶領域で保管する。このため、推定値の算出を繰り返し行う場合には、保管されている伝搬距離を再利用することができるため、伝搬距離の再計算を行わずに済む。この結果、少ない計算負荷により推定値を得ることができる。 *** Explanation of the effect of the embodiment ***
In the present embodiment, the calculated propagation distance is stored in the storage area. Therefore, when the calculation of the estimated value is repeated, the stored propagation distance can be reused, so that the propagation distance does not need to be recalculated. As a result, an estimated value can be obtained with a small calculation load.
　実施の形態４．
　本実施の形態では、主に実施の形態１との差異を説明する。
　なお、以下で説明していない事項は、実施の形態１と同様である。 Embodiment 4.
In the present embodiment, the difference from the first embodiment will be mainly described.
The matters not explained below are the same as those in the first embodiment.
　本実施の形態では、伝搬距離算出部１０３が、空間４内の風向を考慮して伝搬経路を抽出する。つまり、本実施の形態では、伝搬距離算出部１０３は、風向情報を用いることで、空間４に存在する各種粒子の輸送が起こりやすい経路を伝搬経路として選択する。このため、本実施の形態では、伝搬距離算出部１０３は、空間４内の風向によっては、最短ではない経路を伝搬経路として選択することがある。 In the present embodiment, the propagation distance calculation unit 103 extracts the propagation path in consideration of the wind direction in the space 4. That is, in the present embodiment, the propagation distance calculation unit 103 uses the wind direction information to select a route in which various particles existing in the space 4 are likely to be transported as the propagation route. Therefore, in the present embodiment, the propagation distance calculation unit 103 may select a path that is not the shortest as the propagation path depending on the wind direction in the space 4.
＊＊＊構成の説明＊＊＊
　図１４は、本実施の形態に係る情報処理装置１００の機能構成例を示す。
　図１４では、図１の構成と比較して、風向情報記憶部１０６が追加されている。
　風向情報記憶部１０６は、風向情報を記憶する。風向情報には、空間４内の風向が示される。例えば、空間４内の複数の箇所に設けられた風向センサにより空間４内の複数の箇所の風向を得ることができる。
　風向情報記憶部１０６は、主記憶装置９０２又は補助記憶装置９０３により実現される。
　風向情報記憶部１０６以外の要素は図１に示したものと同じである。
　なお、本実施の形態では、伝搬距離算出部１０３は、風向情報記憶部１０６から風向情報を取得し、取得した風向情報を用いて伝搬経路を選択する。 *** Explanation of configuration ***
FIG. 14 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
In FIG. 14, the wind direction information storage unit 106 is added as compared with the configuration of FIG.
The wind direction information storage unit 106 stores the wind direction information. The wind direction information indicates the wind direction in the space 4. For example, wind direction sensors provided at a plurality of locations in the space 4 can obtain wind directions at a plurality of locations in the space 4.
The wind direction information storage unit 106 is realized by the main storage device 902 or the auxiliary storage device 903.
The elements other than the wind direction information storage unit 106 are the same as those shown in FIG.
In the present embodiment, the propagation distance calculation unit 103 acquires wind direction information from the wind direction information storage unit 106, and selects a propagation path using the acquired wind direction information.
＊＊＊動作の説明＊＊＊
　図１５は、本実施の形態に係る情報処理装置１００の動作例を示す。 *** Explanation of operation ***
FIG. 15 shows an operation example of the information processing apparatus 100 according to the present embodiment.
　図１５において、ステップＳ１０１は、実施の形態１で説明したものと同じであるため、説明を省略する。 In FIG. 15, step S101 is the same as that described in the first embodiment, and thus the description thereof will be omitted.
　ステップＳ１０６では、伝搬距離算出部１０３は、風向情報記憶部１０６から風向情報を取得する。 In step S106, the propagation distance calculation unit 103 acquires the wind direction information from the wind direction information storage unit 106.
　ステップＳ１０２では、伝搬距離算出部１０３は、風向情報を用いて伝搬経路を抽出する。 In step S102, the propagation distance calculation unit 103 extracts the propagation path using the wind direction information.
　図１６は、本実施の形態に係る伝搬距離算出部１０３の伝搬経路の抽出原理を示す。
　図１６の（ａ）は、風向を考慮せずに抽出された伝搬経路の例を示す。つまり、伝搬距離算出部１０３は、風向を考慮しない場合は、観測点１から推定点２への最短の経路１５を伝搬経路として選択する。
　図１６の（ｂ）は、風向を考慮して抽出された伝搬経路の例を示す。つまり、伝搬距離算出部１０３は、最短の経路１５と他の経路１６とのうち、流体の伝搬量が多い経路を伝搬経路として選択する。図１６の（ｂ）では、前段部分が風向に沿っている経路１６が流体の伝搬量が多いと考えられるので、伝搬距離算出部１０３は、経路１６を伝搬経路として選択する。
　伝搬距離算出部１０３は、例えば、空気の伝搬モデルに空間４内の風向を適用して、いずれの経路で空気の伝搬量が多いかを判定して、伝搬経路を選択する。
　そして、伝搬距離算出部１０３は、ステップＳ１０２において、伝搬距離を算出する。伝搬距離の算出方法は実施の形態１で説明したものと同じである。 FIG. 16 shows the extraction principle of the propagation path of the propagation distance calculation unit 103 according to the present embodiment.
FIG. 16A shows an example of a propagation path extracted without considering the wind direction. That is, the propagation distance calculation unit 103 selects the shortest route 15 from the observation point 1 to the estimation point 2 as the propagation route when the wind direction is not taken into consideration.
FIG. 16B shows an example of a propagation path extracted in consideration of the wind direction. That is, the propagation distance calculation unit 103 selects, among the shortest route 15 and the other route 16, the route having a large amount of fluid propagation as the propagation route. In FIG. 16B, since it is considered that the path 16 whose front stage portion is along the wind direction has a large amount of fluid propagation, the propagation distance calculation unit 103 selects the path 16 as the propagation path.
For example, the propagation distance calculation unit 103 applies the wind direction in the space 4 to the air propagation model, determines in which route the air propagation amount is large, and selects the propagation path.
Then, the propagation distance calculation unit 103 calculates the propagation distance in step S102. The method of calculating the propagation distance is the same as that described in the first embodiment.
　次に、ステップＳ１０３において、推定部１０４が伝搬距離を用いて推定値を算出する。推定値の算出方法は、実施の形態１で説明したものと同じである。 Next, in step S103, the estimation unit 104 calculates the estimated value using the propagation distance. The method of calculating the estimated value is the same as that described in the first embodiment.
＊＊＊実施の形態の効果の説明＊＊＊
　本実施の形態では、風向も考慮して伝搬経路を抽出する。このため、実施の形態１よりも高精度に室内の流体の状態値を推定することができる。 *** Explanation of the effect of the embodiment ***
In the present embodiment, the propagation path is extracted in consideration of the wind direction. Therefore, the state value of the fluid in the room can be estimated with higher accuracy than in the first embodiment.
　実施の形態５．
　本実施の形態では、主に実施の形態１及び実施の形態４との差異を説明する。
　なお、以下で説明していない事項は、実施の形態１及び実施の形態４と同様である。 Embodiment 5.
In the present embodiment, the differences between the first embodiment and the fourth embodiment will be mainly described.
The matters not explained below are the same as those in the first embodiment and the fourth embodiment.
　本実施の形態では、伝搬距離算出部１０３が、空間４に設けられた空気調和機に設定された設定風向が示される設定風向情報を取得する。そして、伝搬距離算出部１０３は、設定風向情報に示される設定風向を用いて伝搬経路を抽出する。 In the present embodiment, the propagation distance calculation unit 103 acquires the set wind direction information indicating the set wind direction set in the air conditioner provided in the space 4. Then, the propagation distance calculation unit 103 extracts the propagation path using the set wind direction shown in the set wind direction information.
＊＊＊構成の説明＊＊＊
　図１７は、本実施の形態に係る情報処理装置１００の機能構成例を示す。
　図１７では、図１の構成と比較して、空気調和機設定情報記憶部１０７が追加されている。
　空気調和機設定情報記憶部１０７は、空間４に設けられた空気調和機の設定情報を記憶する。例えば、空気調和機設定情報記憶部１０７は、空間４の利用者がリモートコントローラを用いて設定した温度、風向等を設定情報として記憶する。
　空気調和機設定情報記憶部１０７は、主記憶装置９０２又は補助記憶装置９０３により実現される。
　空気調和機設定情報記憶部１０７以外の要素は図１に示したものと同じである。
　なお、本実施の形態では、伝搬距離算出部１０３は、空気調和機設定情報記憶部１０７から設定情報のうち設定風向が示される設定風向情報を取得し、取得した設定風向情報を用いて伝搬経路を選択する。 *** Explanation of configuration ***
FIG. 17 shows an example of a functional configuration of the information processing apparatus 100 according to the present embodiment.
In FIG. 17, the air conditioner setting information storage unit 107 is added as compared with the configuration of FIG.
The air conditioner setting information storage unit 107 stores the setting information of the air conditioner provided in the space 4. For example, the air conditioner setting information storage unit 107 stores the temperature, wind direction, etc. set by the user of the space 4 using the remote controller as setting information.
The air conditioner setting information storage unit 107 is realized by the main storage device 902 or the auxiliary storage device 903.
The elements other than the air conditioner setting information storage unit 107 are the same as those shown in FIG.
In the present embodiment, the propagation distance calculation unit 103 acquires the set wind direction information indicating the set wind direction from the set information from the air conditioner setting information storage unit 107, and uses the acquired set wind direction information to propagate the propagation path. Select.
＊＊＊動作の説明＊＊＊
　図１８は、本実施の形態に係る情報処理装置１００の動作例を示す。 *** Explanation of operation ***
FIG. 18 shows an operation example of the information processing apparatus 100 according to the present embodiment.
　図１８において、ステップＳ１０１は、実施の形態１で説明したものと同じであるため、説明を省略する。 In FIG. 18, step S101 is the same as that described in the first embodiment, and thus the description thereof will be omitted.
　ステップＳ１０７では、伝搬距離算出部１０３は、空気調和機設定情報記憶部１０７から設定風向情報を取得する。 In step S107, the propagation distance calculation unit 103 acquires the set wind direction information from the air conditioner setting information storage unit 107.
　ステップＳ１０２では、伝搬距離算出部１０３は、設定風向情報を用いて伝搬経路を抽出する。
　伝搬距離算出部１０３は、実施の形態４と同様に、設定風向を考慮し、複数の経路の中から、流体の伝搬量が多い経路を伝搬経路として選択する。
　伝搬距離算出部１０３は、例えば、空気の伝搬モデルに設定風向を適用して、いずれの経路で空気の伝搬量が多いかを判定して、伝搬経路を選択する。
　本実施の形態では、伝搬距離算出部１０３は、実施の形態４の風向センサにより得られた風向の代わりに、設定風向を用いて伝搬経路を選択する。 In step S102, the propagation distance calculation unit 103 extracts the propagation path using the set wind direction information.
Similar to the fourth embodiment, the propagation distance calculation unit 103 selects a path having a large amount of fluid propagation as a propagation path from a plurality of paths in consideration of the set wind direction.
The propagation distance calculation unit 103 applies, for example, a set wind direction to an air propagation model, determines in which route the amount of air propagation is large, and selects a propagation path.
In the present embodiment, the propagation distance calculation unit 103 selects a propagation path using the set wind direction instead of the wind direction obtained by the wind direction sensor of the fourth embodiment.
　そして、伝搬距離算出部１０３は、ステップＳ１０２において、伝搬距離を算出する。伝搬距離の算出方法は実施の形態１で説明したものと同じである。 Then, the propagation distance calculation unit 103 calculates the propagation distance in step S102. The method of calculating the propagation distance is the same as that described in the first embodiment.
　次に、ステップＳ１０３において、推定部１０４が伝搬距離を用いて推定値を算出する。推定値の算出方法は、実施の形態１で説明したものと同じである。 Next, in step S103, the estimation unit 104 calculates the estimated value using the propagation distance. The method of calculating the estimated value is the same as that described in the first embodiment.
＊＊＊実施の形態の効果の説明＊＊＊
　本実施の形態では、設定風向も考慮して伝搬経路を抽出する。このため、実施の形態１よりも高精度に室内の流体の状態値を推定することができる。また、本実施の形態では、実施の形態４で必要であった風向センサを不要とすることができる。 *** Explanation of the effect of the embodiment ***
In the present embodiment, the propagation path is extracted in consideration of the set wind direction. Therefore, the state value of the fluid in the room can be estimated with higher accuracy than in the first embodiment. Further, in the present embodiment, the wind direction sensor required in the fourth embodiment can be eliminated.
　以上、本発明の実施の形態について説明したが、これらの実施の形態のうち、２つ以上を組み合わせて実施しても構わない。
　あるいは、これらの実施の形態のうち、１つを部分的に実施しても構わない。
　あるいは、これらの実施の形態のうち、２つ以上を部分的に組み合わせて実施しても構わない。
　なお、本発明は、これらの実施の形態に限定されるものではなく、必要に応じて種々の変更が可能である。 Although the embodiments of the present invention have been described above, two or more of these embodiments may be combined and implemented.
Alternatively, one of these embodiments may be partially implemented.
Alternatively, two or more of these embodiments may be partially combined and implemented.
The present invention is not limited to these embodiments, and various modifications can be made as needed.
＊＊＊ハードウェア構成の説明＊＊＊
　最後に、情報処理装置１００のハードウェア構成の補足説明を行う。
　図２に示すプロセッサ９０１は、プロセッシングを行うＩＣ（Ｉｎｔｅｇｒａｔｅｄ　Ｃｉｒｃｕｉｔ）である。
　プロセッサ９０１は、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、ＤＳＰ（Ｄｉｇｉｔａｌ　Ｓｉｇｎａｌ　Ｐｒｏｃｅｓｓｏｒ）等である。
　図２に示す主記憶装置９０２は、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）である。
　図２に示す補助記憶装置９０３は、ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、フラッシュメモリ、ＨＤＤ（Ｈａｒｄ　Ｄｉｓｋ　Ｄｒｉｖｅ）等である。
　図２に示す通信装置９０４は、データの通信処理を実行する電子回路である。
　通信装置９０４は、例えば、通信チップ又はＮＩＣ（Ｎｅｔｗｏｒｋ　Ｉｎｔｅｒｆａｃｅ　Ｃａｒｄ）である。 *** Explanation of hardware configuration ***
Finally, a supplementary explanation of the hardware configuration of the information processing apparatus 100 will be given.
The processor 901 shown in FIG. 2 is an IC (Integrated Circuit) that performs processing.
The processor 901 is a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or the like.
The main storage device 902 shown in FIG. 2 is a RAM (Random Access Memory).
The auxiliary storage device 903 shown in FIG. 2 is a ROM (Read Only Memory), a flash memory, an HDD (Hard Disk Drive), or the like.
The communication device 904 shown in FIG. 2 is an electronic circuit that executes data communication processing.
The communication device 904 is, for example, a communication chip or a NIC (Network Interface Card).
　また、補助記憶装置９０３には、ＯＳ（Ｏｐｅｒａｔｉｎｇ　Ｓｙｓｔｅｍ）も記憶されている。
　そして、ＯＳの少なくとも一部がプロセッサ９０１により実行される。
　プロセッサ９０１はＯＳの少なくとも一部を実行しながら、伝搬距離算出部１０３及び推定部１０４の機能を実現するプログラムを実行する。
　プロセッサ９０１がＯＳを実行することで、タスク管理、メモリ管理、ファイル管理、通信制御等が行われる。
　また、伝搬距離算出部１０３及び推定部１０４の処理の結果を示す情報、データ、信号値及び変数値の少なくともいずれかが、主記憶装置９０２、補助記憶装置９０３、プロセッサ９０１内のレジスタ及びキャッシュメモリの少なくともいずれかに記憶される。
　また、伝搬距離算出部１０３及び推定部１０４の機能を実現するプログラムは、磁気ディスク、フレキシブルディスク、光ディスク、コンパクトディスク、ブルーレイ（登録商標）ディスク、ＤＶＤ等の可搬記録媒体に格納されていてもよい。そして、伝搬距離算出部１０３及び推定部１０４の機能を実現するプログラムが格納された可搬記録媒体を商業的に流通させてもよい。 In addition, the OS (Operating System) is also stored in the auxiliary storage device 903.
Then, at least a part of the OS is executed by the processor 901.
The processor 901 executes a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 while executing at least a part of the OS.
When the processor 901 executes the OS, task management, memory management, file management, communication control, and the like are performed.
Further, at least one of the information, data, signal value, and variable value indicating the processing result of the propagation distance calculation unit 103 and the estimation unit 104 is the main storage device 902, the auxiliary storage device 903, and the registers and cache memory in the processor 901. It is stored in at least one of.
Further, even if the program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 is stored in a portable recording medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. Good. Then, a portable recording medium in which a program that realizes the functions of the propagation distance calculation unit 103 and the estimation unit 104 is stored may be commercially distributed.
　また、伝搬距離算出部１０３及び推定部１０４の「部」を、「回路」又は「工程」又は「手順」又は「処理」に読み替えてもよい。
　また、情報処理装置１００は、処理回路により実現されてもよい。処理回路は、例えば、ロジックＩＣ（Ｉｎｔｅｇｒａｔｅｄ　Ｃｉｒｃｕｉｔ）、ＧＡ（Ｇａｔｅ　Ａｒｒａｙ）、ＡＳＩＣ（Ａｐｐｌｉｃａｔｉｏｎ　Ｓｐｅｃｉｆｉｃ　Ｉｎｔｅｇｒａｔｅｄ　Ｃｉｒｃｕｉｔ）、ＦＰＧＡ（Ｆｉｅｌｄ－Ｐｒｏｇｒａｍｍａｂｌｅ　Ｇａｔｅ　Ａｒｒａｙ）である。
　この場合は、伝搬距離算出部１０３及び推定部１０４は、それぞれ処理回路の一部として実現される。
　なお、本明細書では、プロセッサと処理回路との上位概念を、「プロセッシングサーキットリー」という。
　つまり、プロセッサと処理回路とは、それぞれ「プロセッシングサーキットリー」の具体例である。 Further, the "unit" of the propagation distance calculation unit 103 and the estimation unit 104 may be read as "circuit" or "process" or "procedure" or "processing".
Further, the information processing device 100 may be realized by a processing circuit. The processing circuit is, for example, a logic IC (Integrated Circuit), a GA (Gate Array), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field-Programmable Gate Array).
In this case, the propagation distance calculation unit 103 and the estimation unit 104 are each realized as a part of the processing circuit.
In this specification, the superordinate concept of the processor and the processing circuit is referred to as "processing circuit Lee".
That is, the processor and the processing circuit are specific examples of the "processing circuit Lee", respectively.
　１　観測点、２　推定点、３　障害物、４　空間、５　経路、６　壁、１５　経路、１６　経路、１００　情報処理装置、１０１　障害物情報記憶部、１０２　観測点／推定点情報記憶部、１０３　伝搬距離算出部、１０４　推定部、１０５　伝搬距離記憶部、１０６　風向情報記憶部、１０７　空気調和機設定情報記憶部、９０１　プロセッサ、９０２　主記憶装置、９０３　補助記憶装置、９０４　通信装置。 1 observation point, 2 estimation point, 3 obstacle, 4 space, 5 route, 6 wall, 15 route, 16 route, 100 information processing device, 101 obstacle information storage unit, 102 observation point / estimation point information storage unit, 103 Propagation distance calculation unit, 104 estimation unit, 105 propagation distance storage unit, 106 wind direction information storage unit, 107 air conditioner setting information storage unit, 901 processor, 902 main storage device, 903 auxiliary storage device, 904 communication device.

Claims (11)

  1. 　空間内の第１の点の位置と、前記空間内の前記第１の点とは異なる第２の点の位置と、前記第１の点から前記第２の点への流体の伝搬の障害になる障害物の位置及びサイズとに基づき、前記空間内で前記第１の点から前記第２の点への流体の伝搬が可能な経路を伝搬経路として抽出し、抽出した伝搬経路の距離を伝搬距離として算出する伝搬距離算出部と、
    　算出された前記伝搬距離と、前記第１の点で観測された流体の状態値とに基づき、前記第２の点での流体の状態値を推定する推定部とを有する情報処理装置。     The position of the first point in the space, the position of the second point different from the first point in the space, and the obstacle of the propagation of the fluid from the first point to the second point. Based on the position and size of the obstacle, a path capable of propagating the fluid from the first point to the second point in the space is extracted as a propagation path, and the distance of the extracted propagation path is propagated. Propagation distance calculation unit that calculates as a distance,
    An information processing device having an estimation unit that estimates a fluid state value at the second point based on the calculated propagation distance and the fluid state value observed at the first point.
  2. 　前記伝搬距離算出部は、
    　前記空間内で前記第１の点から前記第２の点への流体の伝搬が可能な最短の経路を前記伝搬経路として抽出する請求項１に記載の情報処理装置。     The propagation distance calculation unit
    The information processing apparatus according to claim 1, wherein the shortest path in which the fluid can propagate from the first point to the second point in the space is extracted as the propagation path.
  3. 　前記伝搬距離算出部は、
    　複数の第１の点の位置に基づき、第１の点ごとに、前記空間内で前記第２の点への流体の伝搬が可能な経路を伝搬経路として抽出し、抽出した複数の伝搬経路の各々の距離を伝搬距離として算出し、
    　前記推定部は、
    　算出された第１の点ごとの伝搬距離と、前記複数の第１の点の各々で観測された流体の状態値とに基づき、前記第２の点での流体の状態値を推定する請求項１に記載の情報処理装置。     The propagation distance calculation unit
    Based on the positions of the plurality of first points, for each first point, a path capable of propagating the fluid to the second point in the space is extracted as a propagation path, and the extracted plurality of propagation paths Calculate each distance as the propagation distance,
    The estimation unit
    Claim to estimate the fluid state value at the second point based on the calculated propagation distance for each first point and the fluid state value observed at each of the plurality of first points. The information processing apparatus according to 1.
  4. 　前記推定部は、
    　第１の点ごとに、算出された伝搬距離に基づいて重みを設定し、
    　設定した第１の点ごとの重みと、前記複数の第１の点の各々で観測された流体の状態値とに基づき、前記第２の点での流体の状態値を推定する請求項３に記載の情報処理装置。     The estimation unit
    For each first point, set the weight based on the calculated propagation distance,
    According to claim 3, the state value of the fluid at the second point is estimated based on the set weight for each first point and the state value of the fluid observed at each of the plurality of first points. The information processing device described.
  5. 　前記伝搬距離算出部は、
    　二次元で表された前記第１の点の位置と、二次元で表された前記第２の点の位置と、二次元で表された前記障害物の位置及びサイズとに基づき、前記伝搬経路を抽出する請求項１に記載の情報処理装置。     The propagation distance calculation unit
    The propagation path is based on the position of the first point represented in two dimensions, the position of the second point represented in two dimensions, and the position and size of the obstacle represented in two dimensions. The information processing apparatus according to claim 1.
  6. 　前記伝搬距離算出部は、
    　三次元で表された前記第１の点の位置と、三次元で表された前記第２の点の位置と、三次元で表された前記障害物の位置及びサイズとに基づき、前記伝搬経路を抽出する請求項１に記載の情報処理装置。     The propagation distance calculation unit
    The propagation path is based on the position of the first point represented in three dimensions, the position of the second point represented in three dimensions, and the position and size of the obstacle represented in three dimensions. The information processing apparatus according to claim 1.
  7. 　前記情報処理装置は、更に、
    　前記伝搬距離算出部により算出された前記伝搬距離を記憶する伝搬距離記憶部を有し、
    　前記推定部は、
    　前記伝搬距離記憶部に記憶されている前記伝搬距離に基づき、前記第２の点での流体の状態値を推定する請求項１に記載の情報処理装置。     The information processing device further
    It has a propagation distance storage unit that stores the propagation distance calculated by the propagation distance calculation unit.
    The estimation unit
    The information processing apparatus according to claim 1, wherein the state value of the fluid at the second point is estimated based on the propagation distance stored in the propagation distance storage unit.
  8. 　前記伝搬距離算出部は、
    　前記空間での風向に基づき、前記空間内で前記第１の点から前記第２の点への流体の伝搬量が多い経路を前記伝搬経路として抽出する請求項１に記載の情報処理装置。     The propagation distance calculation unit
    The information processing apparatus according to claim 1, wherein a path in which a large amount of fluid propagates from the first point to the second point in the space is extracted as the propagation path based on the wind direction in the space.
  9. 　前記空間には空気調和機が設置されており、
    　前記伝搬距離算出部は、
    　前記空気調和機に設定されている風向に基づき、前記伝搬経路を抽出する請求項８に記載の情報処理装置。     An air conditioner is installed in the space.
    The propagation distance calculation unit
    The information processing device according to claim 8, wherein the propagation path is extracted based on the wind direction set in the air conditioner.
  10. 　コンピュータが、空間内の第１の点の位置と、前記空間内の前記第１の点とは異なる第２の点の位置と、前記第１の点から前記第２の点への流体の伝搬の障害になる障害物の位置及びサイズとに基づき、前記空間内で前記第１の点から前記第２の点への流体の伝搬が可能な経路を伝搬経路として抽出し、抽出した伝搬経路の距離を伝搬距離として算出し、
    　前記コンピュータが、算出された前記伝搬距離と、前記第１の点で観測された流体の状態値とに基づき、前記第２の点での流体の状態値を推定する情報処理方法。     The computer uses the position of a first point in space, the position of a second point different from the first point in space, and the propagation of fluid from the first point to the second point. Based on the position and size of the obstacle that becomes an obstacle, a path capable of propagating the fluid from the first point to the second point in the space is extracted as a propagation path, and the extracted propagation path Calculate the distance as the propagation distance
    An information processing method in which the computer estimates the fluid state value at the second point based on the calculated propagation distance and the fluid state value observed at the first point.
  11. 　空間内の第１の点の位置と、前記空間内の前記第１の点とは異なる第２の点の位置と、前記第１の点から前記第２の点への流体の伝搬の障害になる障害物の位置及びサイズとに基づき、前記空間内で前記第１の点から前記第２の点への流体の伝搬が可能な経路を伝搬経路として抽出し、抽出した伝搬経路の距離を伝搬距離として算出する伝搬距離算出処理と、
    　算出された前記伝搬距離と、前記第１の点で観測された流体の状態値とに基づき、前記第２の点での流体の状態値を推定する推定処理とをコンピュータに実行させる情報処理プログラム。     The position of the first point in the space, the position of the second point different from the first point in the space, and the obstacle of the propagation of the fluid from the first point to the second point. Based on the position and size of the obstacle, a path capable of propagating the fluid from the first point to the second point in the space is extracted as a propagation path, and the distance of the extracted propagation path is propagated. Propagation distance calculation processing calculated as distance and
    An information processing program that causes a computer to execute an estimation process for estimating the fluid state value at the second point based on the calculated propagation distance and the fluid state value observed at the first point. ..
PCT/JP2019/021110 2019-05-28 2019-05-28 Information processing device, information processing method, and information processing program WO2020240700A1 (en)

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