Elevator information providing device, elevator information providing method, and learning device

Abstract

The objective of the present invention is to obtain an elevator information providing device enabling a user of the elevator information providing device to consider elevator specifications on the basis of a standard model.　This elevator information providing device comprises: a building data acquisition unit (10) that acquires data relating to a building; and an inference unit (11) that uses a learned model for inferring, from data relating to a building, a standard model of an elevator suitable for installation in the building to infer a standard model of an elevator from the building data input from the building data acquisition unit (10) and outputs data relating to the inferred standard model of the elevator.

Description

Technical Field

[0001] The present invention relates to an elevator information providing device, an elevator information providing method, and a learning device.

Background Art

[0002] An architect who is the ordering side of an elevator uses an elevator information providing device to order an elevator that meets their own requirements.

[0003] The architect inputs the use of the building, the number of floors of the building, the estimated number of residents per floor, and the required specifications for the elevator into the elevator information providing device and orders the elevator. (For example, Patent Document 1)

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In such an elevator information providing device, the user of the elevator information providing device has not been able to consider the specifications of the elevator based on the standard model. The manufacturer, which is the manufacturing side of the elevator, is desirably induced to consider the specifications of the elevator based on the standard model by the user of the elevator information providing device in consideration of the load of the manufacturing process and the like.

[0006] The present invention has been made to solve the above-described problems, and an object thereof is to obtain an elevator information providing device that allows the user of the elevator information providing device to consider the specifications of the elevator based on the standard model.

Means for Solving the Problems

[0007] The elevator information providing device according to the present invention includes a building data acquisition unit that acquires building data, and uses a learned model for inferring a standard model of an elevator suitable for installation in the building from the building data, and infers a standard model of the elevator from the building data input from the building data acquisition unit, and an inference unit that outputs data of the inferred standard model of the elevator. The building data includes data on whether the building is a rental building. If the building is a rental building, the inference unit infers the standard model of the elevator with a larger rated capacity than when the building is not a rental building. 。

Effect of the Invention

[0008] According to the elevator information providing device of the present invention, the user of the elevator information providing device can consider the specifications of the elevator based on the standard model. This is because the inference unit infers the standard model of the elevator from the building data and outputs the data of the inferred standard model of the elevator.

Brief Description of the Drawings

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Embodiments for Carrying Out the Invention

[0010] Embodiment 1. First, an application example of the elevator information providing device 100 according to Embodiment 1 of the present invention will be described. The elevator information providing device 100 according to the present embodiment assumes the user as an architect, but the user is not limited to this, and any person who is considering purchasing or ordering an elevator may be sufficient. In the following, when simply referred to as a user, it refers to a person who is considering purchasing or ordering an elevator, which is a user of the elevator information providing device 100, and the user of the elevator is referred to as a passenger.

[0011] The elevator information providing device 100 according to the present embodiment constitutes a part of a website that provides elevator information. That is, the user of the elevator information providing device 100 is a user of the website created by the elevator information providing device 100. The website created by the elevator information providing device 100 provides elevator information when data on the building where the elevator is to be installed and data on the required specifications for the elevator are input by the user.

[0012] FIG. 1 is a diagram for explaining an application example of the elevator information providing apparatus 100 according to Embodiment 1 of the present invention. The elevator information providing apparatus 100 according to the present embodiment provides elevator information to users via the server 102 and the Internet line 103. FIG. 1 will be described along the data flow. As shown in FIG. 1, the personal computer 104 of the user is connected to the server 102 via the Internet line 103. The building data input by the user to the personal computer 104 is input to the elevator information providing apparatus 100 through the server 102. The elevator information providing apparatus 100 uses the learned model stored in the learned model storage device 101 to infer the standard elevator model from the building data input through the server 102, and outputs the data of the inferred standard elevator model.

[0013] The data output from the elevator information providing apparatus 100 is input to the personal computer 104 of the user through the server 102, and the standard elevator model is displayed on the personal computer 104. That is, the WEB site created by the elevator information providing apparatus 100 displays the standard elevator model when the building data is input by the user, and is a WEB site that recommends the standard elevator model suitable for installation in the building when the building data is input by the user.

[0014] As described above, when the user of the elevator information providing apparatus 100 inputs the building data to the personal computer 104, the standard elevator model is displayed on the personal computer 104. Therefore, based on the displayed standard elevator model, the user will start considering the specifications of the elevator.

[0015] Next, the configuration of the elevator information providing apparatus 100 according to Embodiment 1 of the present invention will be described. FIG. 2 is a configuration diagram of the elevator information providing apparatus 100 according to Embodiment 1 of the present invention. As shown in FIG. 2, the elevator information providing apparatus 100 according to the present embodiment includes a building data acquisition unit 10 that acquires building data, and a learned model for inferring a standard model of an elevator suitable for installation in a building from the building data. Using the learned model, the elevator information providing apparatus 100 infers the standard model of the elevator from the building data input from the building data acquisition unit 10, and outputs data of the inferred standard model of the elevator. The learned model is stored in the learned model storage device 101.

[0016] The building data acquisition unit 10 acquires the building data input by the user of the elevator information providing apparatus 100 to the personal computer 104 of the user through the server 102. For example, when the user is an architect who is about to construct a building, the user inputs the data of the building to be constructed to the personal computer 104. The data of the building to be constructed input to the personal computer 104 is acquired by the building data acquisition unit 10 of the elevator information providing apparatus 100 through the server 102.

[0017] The building data includes, for example, data on the area where the building is to be constructed, data on the type of the building, data on the number of floors of the building, data on the number of people using the elevator, data on the scale of the building, data on whether welfare support is required for the building, and the like. The website created by the elevator information providing apparatus 100 has items for inputting the area where the building is to be constructed, the type of the building, the number of floors of the building, the number of people using the elevator, the scale of the building, whether welfare support is required for the building, and the like. The building data acquisition unit 10 acquires the data input to these items.

[0018] The inference unit 11 uses the learned model stored in the learned model storage device 101 to infer the standard model of the elevator from the building data input from the building data acquisition unit 10, and outputs the data of the inferred standard model of the elevator. The data of the standard model of the elevator output by the inference unit 11 is input to the user's personal computer 104, and the standard model of the elevator is displayed on the personal computer 104.

[0019] Note that the elevator information providing device 100 is realized, for example, by a CPU (Central Processing Unit), but is not limited thereto. The learned model storage device 101 is realized, for example, by a semiconductor memory such as a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), or a flash memory, but is not limited thereto.

[0020] Next, the standard model of the elevator inferred by the inference unit 11 of the elevator information providing device 100 according to the present embodiment will be described with reference to FIG. 3. FIG. 3 is an example of a cross-sectional view of the elevator seen from above, and is generally called a hoistway floor plan. The elevator includes a car and moves up and down the hoistway. The hoistway member 1 forms a hoistway and an opening for an entrance / exit. The hoistway member 1 is made separately from the building structure and has a height corresponding to the number of floors of the building. The hoistway is a space formed by the hoistway member 1 and is the space surrounded by a dotted line in FIG. 3. The opening for the entrance / exit is an opening formed by the hoistway member 1, and a part of the landing is made in the opening for the entrance / exit. The user of the elevator gets on and off the elevator from the landing formed by the landing member 3.

[0021] The elevator car includes an inner wall 2a and an outer wall 2b. The elevator shown in FIG. 3 is provided with two car doors 4, two landing doors 5, and two landing door pockets 6 respectively. The landing door 5 opens and closes by sliding inside the landing door pocket 6. The car door 4 opens and closes by sliding between the inner wall 2a and the outer wall 2b. The inner wall 2a of the car forms a car space and a car opening. The car space is the space where passengers stay when they get on the elevator, and it is the space surrounded by the dashed line in FIG. 3. A car door 4 is installed at the edge of the car opening.

[0022] The elevator shown in FIG. 3 has two entrances and exits, but there are also elevators with one entrance and exit. In this embodiment, the elevator is not limited to having two entrances and exits, and it may have one entrance and exit. An elevator with one entrance and exit is provided with one car door 4, one landing door 5, and one landing door pocket 6 respectively. In the elevator shaft plane, when the elevator has two entrances and exits, the inner wall 2a of the car is divided into two parts, but when the elevator has one entrance and exit, the inner wall 2a of the car is formed integrally and thus becomes one. Also, in the elevator shaft plane, when the elevator has two entrances and exits, the elevator shaft member 1 is divided into two parts, but when the elevator has one entrance and exit, the elevator shaft member 1 is formed integrally and thus becomes one. Other members are appropriately redesigned according to the number of entrances and exits the elevator has.

[0023] As shown in FIG. 3, the inner dimensions of the hoistway are represented by X×Y, and the inner dimensions of the car are represented by A×B. The width through which the elevator user can pass is shown as the width J of the car entrance. X is the distance within the hoistway between the inner walls of the hoistway member 1 in the hoistway plane, which is the distance in the direction parallel to the car entrance width J. Y is the distance within the hoistway between the inner walls of the hoistway member 1 in the hoistway plane, which is the distance in the direction perpendicular to the car entrance width J. That is, X and Y are orthogonal. A is the distance within the car space between the inner walls 2a of the car in the hoistway plane, which is the distance in the direction parallel to the car entrance width J. B is the distance within the car space between the inner walls 2a of the car in the hoistway plane, which is the distance in the direction perpendicular to the car entrance width J. That is, A and B are orthogonal.

[0024] In this embodiment, the standard model of the elevator refers to a model with a lineup in which the inner dimensions A×B of the car, the width J of the car entrance, and the load capacity are the same, but other specifications are different. That is, if the elevator shown in FIG. 3 is the standard model, it means that there are models with the same inner dimensions A×B of the car, the width J of the car entrance, and the load capacity, but other specifications are different from those of the elevator shown in FIG. 3. For example, if there is an elevator with the same inner dimensions A×B of the car, the width J of the car entrance, and the load capacity as the elevator shown in FIG. 3, but with a different conveyance speed, they are the standard models of the elevator.

[0025] Next, an elevator information providing method using the elevator information providing apparatus 100 according to the present embodiment will be described. FIG. 4 is a flowchart showing an elevator information providing method using the elevator information providing apparatus 100 according to Embodiment 1 of the present invention. As shown in FIG. 4, the elevator information providing method using the elevator information providing apparatus 100 includes an acquisition step S1 of acquiring building data, an inference step S2 of inferring a standard model of an elevator from the building data acquired in the acquisition step S1 and outputting the data, a provision step S3 of providing the output data of the standard model of the elevator to a user, and a display step S4 of causing the personal computer 104 of the user to display the provided data of the standard model of the elevator.

[0026] The acquisition step S1 is a step of acquiring building data. In the acquisition step S1, the building data acquisition unit 10 acquires the building data input to the personal computer 104 by the user of the elevator information providing apparatus 100 through the server 102. Then, the building data acquisition unit 10 outputs the acquired building data to the inference unit 11. After the completion of the acquisition step S1, the elevator information providing method using the elevator information providing apparatus 100 according to the present embodiment proceeds to the inference step S2.

[0027] Inference step S2 uses a learned model for inferring a standard model of an elevator suitable for installation in a building from the building data, and infers the standard model of the elevator from the building data acquired in acquisition step S1, and outputs data of the inferred standard model of the elevator. In inference step S2, first, the inference unit 11 acquires the learned model from the learned model storage device 101. Then, the building data output from the building data acquisition unit 10 is input to the learned model acquired by the inference unit 11, and the inference unit 11 infers a standard model of an elevator suitable for installation in the building. When the inference unit 11 infers the standard model of the elevator, it outputs the data to the server 102. The elevator information providing method using the elevator information providing device 100 in the present embodiment proceeds to provision step S3 after inference step S2 is completed.

[0028] Provision step S3 is a step of providing the user with the data of the standard model of the elevator output from the inference unit 11. In provision step S3, the server 102 provides the user with the data of the standard model of the elevator output by the inference unit 11 via the Internet line 103. That is, in provision step S3, the data of the standard model of the elevator output from the elevator information providing device 100 is provided to the user via the server 102 and the Internet line 103. The elevator information providing method using the elevator information providing device 100 in the present embodiment proceeds to display step S4 after provision step S3 is completed.

[0029] The display step S4 is a step of causing the personal computer 104 of the user to display the data of the standard model of the provided elevator. In the display step S4, the personal computer 104 of the user displays the data of the standard model of the elevator provided from the server 102 via the Internet line 103. In the present embodiment, the method of displaying the data of the standard model of the elevator is not particularly limited. For example, an external view of the standard model of the elevator may be displayed, or the product number of the standard model of the elevator may be displayed. It is sufficient that the user can understand which elevator to consider installing.

[0030] Since the standard model of the elevator is displayed on the personal computer 104 of the user, the user can start considering the specifications of the elevator to be installed in the building based on the displayed standard model of the elevator. In the display step S4 of the elevator information providing method using the elevator information providing apparatus 100 in the present embodiment, the processes described below continue, but it is not limited thereto, and the display step S4 may be completed here.

[0031] In the display step S4, when the personal computer 104 displays the data of the standard model of the elevator, the user selects it on the personal computer 104. When the user selects the standard model of the elevator displayed on the personal computer 104, the data of the specifications of the standard model of the elevator is displayed on the personal computer 104. That is, when the user selects the standard model of the elevator displayed on the website, the data of the specifications of the standard model of the elevator is reflected in the content of the elevator specification items on the website. As a result, it becomes easy for the user to customize the specifications of the elevator based on the standard model of the elevator, and when considering the specifications of the elevator based on the standard model of the elevator, the user can easily start the consideration. The elevator information providing method using the elevator information providing apparatus 100 in the present embodiment ends when the display step S4 is completed.

[0032] In this embodiment, the standard model of the elevator inferred by the inference unit 11 in the inference step S2 may be one type or two or more types. When the standard model of the elevator inferred by the inference unit 11 in the inference step S2 is one type, the inference unit 11 infers the standard model of the elevator that is most suitable for installation in the building. When the standard model of the elevator inferred by the inference unit 11 in the inference step S2 is two or more types, the inference unit 11 may infer by ranking the standard models of the elevators suitable for installation in the building, or may infer without ranking. When inferring by ranking the standard models of the elevators suitable for installation in the building, the inference unit 11 outputs the data of the standard models of the elevators together with the ranking. When inferring without ranking the standard models of the elevators suitable for installation in the building, only the data of two or more standard models of the elevators are output.

[0033] In this embodiment, the display method of the data of the standard models of the elevators displayed on the personal computer 104 is not particularly limited. For example, when the inference unit 11 infers by ranking two or more standard models of the elevators suitable for installation in the building, the higher ranking one may be displayed larger than the lower ranking one, or the higher ranking one may display an external view and the lower ranking one may display the product number, etc., and the display method may be devised as appropriate. In addition, when the inference unit 11 infers two or more standard models of the elevators suitable for installation in the building without ranking, the external views may be arranged and displayed in the same size so that the user can easily select the elevator to be considered as a basis.

[0034] Next, a learning device 600 that generates a learned model used by the elevator information providing device 100 according to the present embodiment will be described. FIG. 5 is a configuration diagram of a learning device 600 that generates a learned model used by the elevator information providing device 100 according to Embodiment 1 of the present invention. As shown in FIG. 5, the learning device 600 includes a learning data acquisition unit 60 and a model generation unit 61. The learning data acquisition unit 60 acquires learning data including building data and data on elevator specifications suitable for installation in the building. The model generation unit 61 generates a learned model for inferring a standard elevator model from the building data using the learning data.

[0035] Note that the learning device 600 is realized, for example, by a CPU, but is not limited thereto.

[0036] The learning data acquisition unit 60 acquires, as learning data, building data and data on elevator specifications suitable for installation in the building. The learning data is input to the learning data acquisition unit 60 by, for example, a manufacturer that manufactures elevators or a manufacturer that sells elevators. The learning data is data in which the building data and the data on elevator specifications suitable for installation in the building are associated with each other.

[0037] The model generation unit 61 learns the standard elevator model according to the learning data created based on the combination of the building data output from the learning data acquisition unit 60 and the data on elevator specifications suitable for installation in the building. That is, a learned model for inferring the optimal standard elevator model from the building data and the data on elevator specifications suitable for installation in the building is generated.

[0038] Next, a learning procedure performed by a learning device 600 that generates a learned model used by the elevator information providing device 100 according to the present embodiment will be described. FIG. 6 is a flowchart showing the learning procedure performed by the learning device 600 that generates the learned model used by the elevator information providing device 100 according to Embodiment 1 of the present invention. As shown in FIG. 6, the learning device 600 includes a first learning step T1 of acquiring data, a second learning step T2 of performing learning processing, and a third learning step T3 of storing the learned model.

[0039] The first learning step T1 is a step of acquiring building data and data on the specifications of an elevator suitable for installation in the building. In the first learning step T1, the learning data acquisition unit 60 acquires building data and data on the specifications of an elevator suitable for installation in the building. Note that the learning data acquisition unit 60 may acquire the building data and the data on the specifications of the elevator suitable for installation in the building simultaneously, or may acquire the building data and the data on the specifications of the elevator suitable for installation in the building at different timings. It is sufficient that the learning data acquisition unit 60 can acquire the building data and the data on the specifications of the elevator suitable for installation in the building in association with each other. In the present embodiment, after the completion of the first learning step T1, the learning procedure performed by the learning device 600 that generates the learned model used by the elevator information providing device 100 proceeds to the second learning step T2.

[0040] The second learning step T2 is a step of generating a learned model according to learning data created based on a combination of building data acquired in the second learning step T2 and data on the specifications of an elevator suitable for installation in the building. In the second learning step T2, first, the model generation unit 61 learns the standard model of the elevator according to the learning data created based on a combination of the building data output from the learning data acquisition unit 60 and the data on the specifications of an elevator suitable for installation in the building. Then, the model generation unit 61 generates a learned model. That is, the model generation unit 61 learns the standard model of the elevator by so-called supervised learning and generates a learned model. The learning procedure performed by the learning device 600 that generates the learned model used by the elevator information providing device 100 in the present embodiment proceeds to the third learning step T3 after the second learning step T2 is completed.

[0041] The third learning step T3 is a step of storing the learned model generated in the third learning step T3. In the third learning step T3, the learned model storage device 101 stores the learned model generated by the model generation unit 61 in the second learning step T2. The learning procedure performed by the learning device 600 that generates the learned model used by the elevator information providing device 100 in the present embodiment ends when the third learning step T3 is completed.

[0042] FIG. 7 is a diagram for explaining an example of a learning method performed by a learning device 600 that generates a learned model used by an elevator information providing device 100 according to Embodiment 1 of the present invention. As the learning algorithm used by the model generation unit 61, a known algorithm such as supervised learning, unsupervised learning, or reinforcement learning can be used. As an example, the case where a neural network is applied will be described.

[0043] The model generation unit 61 learns the standard model of the elevator, for example, by so-called supervised learning according to a neural network model. Here, supervised learning refers to a method of giving a learning device a set of input and result (label) data, learning the features in the learning data, and inferring the result from the input. A neural network is composed of an input layer consisting of a plurality of neurons, an intermediate layer (hidden layer) consisting of a plurality of neurons, and an output layer consisting of a plurality of neurons. The intermediate layer may be one layer or two or more layers.

[0044] In the case of a three-layer neural network as shown in FIG. 7, when a plurality of inputs are input to the input layer (X1-X3), the values are multiplied by weights W1 (w11-w16) and input to the intermediate layer (Y1-Y2), and the result is further multiplied by weights W2 (w21-w26) and output from the output layer (Z1-Z3). This output result changes depending on the values of weights W1 and W2.

[0045] In the present embodiment, the neural network learns the standard model of the elevator by so-called supervised learning according to the learning data created based on the combination of the building data acquired by the learning data acquisition unit 60 and the data of the elevator specifications suitable for installation in the building. That is, the neural network learns by adjusting the weights W1 and W2 so that the result output from the output layer when the building data is input to the input layer approaches the data of the elevator specifications suitable for installation in the building.

[0046] The model generation unit 61 generates and outputs a learned model by executing the above learning. The output learned model is stored in the learned model storage device 101.

[0047] Next, a specific example of the learning data required for the model generation unit 61 that generates the learned model used by the elevator information providing apparatus 100 according to the present embodiment to learn will be described. In the present embodiment, a plurality of pieces of learning data are acquired by the learning data acquisition unit 60. The learning data is a set of input data and result (label) data, and will be described one by one below.

[0048] As one specific example, the learning data acquisition unit 60 acquires data on the area where the building is to be constructed and data on the specifications of an elevator suitable for the laws of that area. The data on the area where the building is to be constructed is acquired as building data, and the data on the specifications of an elevator suitable for the laws of that area is acquired as data on the specifications of an elevator suitable for installation in the building. The data on the area where the building is to be constructed and the data on the specifications of an elevator suitable for the laws of that area are acquired in association with each other, and are used by the model generation unit 61 to learn the standard model of the elevator.

[0049] There are a plurality of pieces of data on the area where the building is to be constructed, and the learning data acquisition unit 60 acquires data on the specifications of an elevator suitable for the laws of each area. The data on the area where the building is to be constructed is, for example, the name of the prefecture or the name of the municipality, but the present embodiment is not limited to this. When the elevator information providing apparatus 100 according to the present embodiment is used outside Japan, the method of dividing the area is appropriately changed to the method of dividing local governments in that country. Further, the law of that area is, for example, an ordinance in that area.

[0050] As another example, the learning data acquisition unit 60 acquires data on the area where the building is to be constructed and data on the specifications of elevators that have been used in the past in that area. The data on the area where the building is to be constructed is acquired as building data, and the data on the specifications of elevators that have been used in the past in that area is acquired as data on the specifications of elevators suitable for installation in the building. The data on the area where the building is to be constructed and the data on the specifications of elevators that have been used in the past in that area are acquired in association with each other and are used by the model generation unit 61 to learn the standard models of elevators. Note that there are a plurality of data on the areas where the building is to be constructed, and the learning data acquisition unit 60 acquires data on the specifications of elevators that have been used in the past in each area. The data on the area where the building is to be constructed is, for example, the name of the prefecture or the name of the municipality, but as described above, the present embodiment is not limited to this.

[0051] As another example, the learning data acquisition unit 60 acquires data on the type of the building and data on the specifications of elevators suitable for the type of the building. The data on the type of the building is acquired as building data, and the data on the specifications of elevators suitable for the type of the building is acquired as data on the specifications of elevators suitable for installation in the building. The data on the type of the building and the data on the specifications of elevators suitable for the type of the building are acquired in association with each other and are used by the model generation unit 61 to learn the standard models of elevators. The data on the type of the building is the name of the use of the building, and is, for example, an office, a house, a hospital, a school, or the like.

[0052] As another example, the learning data acquisition unit 60 acquires data on the type of the building and data on the specifications of elevators that have been used in the past in that type. The data on the type of the building is acquired as building data, and the data on the specifications of elevators that have been used in the past in that type is acquired as data on the specifications of elevators suitable for installation in the building. The data on the type of the building and the data on the specifications of elevators that have been used in the past in that type are acquired in association with each other and are used by the model generation unit 61 to learn the standard models of elevators.

[0053] As another example, the learning data acquisition unit 60 acquires data on the number of floors of a building and data on the specifications of an elevator that satisfies the required speed for that building. The data on the number of floors of the building is acquired as building data, and the data on the specifications of an elevator that satisfies the required speed for that building is acquired as data on the specifications of an elevator suitable for installation in that building. The data on the number of floors of the building and the data on the specifications of an elevator that satisfies the required speed for that building are acquired in association with each other and are used by the model generation unit 61 to learn the standard model of the elevator. Generally, a building with a larger number of floors requires a faster elevator speed than a building with a smaller number of floors.

[0054] As another example, the learning data acquisition unit 60 acquires data on the number of people using the elevator and data on the specifications of an elevator that satisfies the required capacity. The data on the number of people using the elevator is acquired as building data, and the data on the specifications of an elevator that satisfies the required capacity is acquired as data on the specifications of an elevator suitable for installation in that building. The data on the number of people using the elevator and the data on the specifications of an elevator that satisfies the required capacity are acquired in association with each other and are used by the model generation unit 61 to learn the standard model of the elevator.

[0055] The data on the number of people using the elevator may be one numerical data such as the data on the estimated population of the entire building, or may be composed of two or more numerical data. For example, the data on the number of people using the elevator may be composed of the data on the population other than the standard floor of the building and the data on the population of the standard floor of the building. In the present embodiment, the standard floor is the floor where the front entrance of the building is located, that is, the floor with a so-called entrance. In the input items of the website created by the elevator information providing device 100, there are items for inputting the population other than the standard floor of the building and the population of the standard floor of the building in order for the building data acquisition unit 10 to acquire the data on the number of people using the elevator. The learning of the model generation unit 61 is performed so as to generate a learned model that can infer the standard model of the elevator from the data input by the user in the items where the population other than the standard floor of the building and the population of the standard floor of the building are input.

[0056] In the above example, when the data on the number of people using the elevator is composed of two or more numerical data, for example, it is assumed to be composed of the data on the population other than the standard floor of the building and the data on the population of the standard floor of the building, but it is not limited to this. For example, the data on the number of people using the elevator may be composed of the data on the estimated population per floor and the data on the number of floors of the building.

[0057] In addition, data on the number of people using the elevator may be associated with data on the number of elevators to be installed and data on the size of the elevator desired by the user of the elevator information providing apparatus 100. This is to provide an input item for the number of elevators to be installed and the size of the elevator desired on the input items of the website created by the elevator information providing apparatus 100. When the learning data acquisition unit 60 acquires data on the number of people using the elevator in association with data on the specifications of the elevator that satisfies the required capacity, it acquires the data on the number of elevators to be installed and the size of the elevator desired by the user of the elevator information providing apparatus 100 in association with the data on the number of people using the elevator. That is, the model generation unit 61 may learn using the learning data in which the data on the number of people using the elevator associated with the data obtained by combining the data on the number of elevators to be installed and the size of the elevator desired by the user of the elevator information providing apparatus 100 and the data on the specifications of the elevator that satisfies the required capacity are paired.

[0058] As another example, the learning data acquisition unit 60 acquires data on whether welfare support is required for a building, data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through, and data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair. The data on whether welfare support is required for the building is acquired as building data, and the data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through and the data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair are acquired as data on the specifications of an elevator suitable for installation in the building. The data on whether welfare support is required for the building, the data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through, and the data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair are acquired in association with each other and used by the model generation unit 61 to learn the standard model of the elevator. At this time, when welfare support is required for the building, the model generation unit 61 learns to output a standard model of an elevator whose car entrance width is wide enough for a wheelchair to pass through and whose car interior size is large enough to accommodate a wheelchair.

[0059] Among the input items of the website created by the elevator information providing device 100, there is an item for inputting whether welfare support is required for the building in order for the building data acquisition unit 10 to acquire data on whether welfare support is required for the building. The learning by the model generation unit 61 is performed to generate a learned model that can infer the standard model of the elevator from the data input by the user in the item in which it is input whether welfare support is required for the building. The item in which it is input whether welfare support is required for the building may be an item that directly asks whether welfare support is required, or may be an item that indirectly asks whether welfare support is required, such as whether the building is a building to which the barrier-free law is applied.

[0060] As another example, the learning data acquisition unit 60 acquires data on the type of building, data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through, and data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair. The data on the type of building is acquired as building data, and the data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through and the data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair are acquired as data on the specifications of an elevator suitable for installation in the building. The data on the type of building is acquired in association with the data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through and the data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair, and is used by the model generation unit 61 to learn the standard model of the elevator. This learning is performed because depending on the type of building, welfare support may be required for that building. For example, when the type of building is a hospital, welfare support is required for that building.

[0061] In the above example, the model generation unit 61 learned using the learning data in which the data on the type of building, the data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through, and the data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair are grouped together, but it is not limited to this. The model generation unit 61 may, for example, associate the data on the type of building with the data on whether welfare support is required for the building, and learn using the learning data in which the data on whether welfare support is required for the building associated with the data on the type of building, the data on the specifications of an elevator whose car entrance width is wide enough for a wheelchair to pass through, and the data on the specifications of an elevator whose car interior size is large enough to accommodate a wheelchair are grouped together.

[0062] As another example, the learning data acquisition unit 60 acquires data on the scale of a building, data on the specifications of an elevator in which the entrance / exit width of the car is wide enough for a wheelchair to pass through, and data on the specifications of an elevator in which the inner dimensions of the car are large enough for a wheelchair to fit. The data on the scale of the building is acquired as building data, and the data on the specifications of an elevator in which the entrance / exit width of the car is wide enough for a wheelchair to pass through and the data on the specifications of an elevator in which the inner dimensions of the car are large enough for a wheelchair to fit are acquired as data on the specifications of an elevator suitable for installation in the building. The data on the scale of the building is acquired in association with the data on the specifications of an elevator in which the entrance / exit width of the car is wide enough for a wheelchair to pass through and the data on the specifications of an elevator in which the inner dimensions of the car are large enough for a wheelchair to fit, and is used by the model generation unit 61 to learn the standard model of the elevator. This learning is performed because a larger building scale requires welfare support. The scale of the building is, for example, the floor area, but it may also be a combination of the number of floors of the building and the area of one floor.

[0063] In the above example, the model generation unit 61 learns using the learning data in which the data on the scale of the building, the data on the specifications of an elevator in which the entrance / exit width of the car is wide enough for a wheelchair to pass through, and the data on the specifications of an elevator in which the inner dimensions of the car are large enough for a wheelchair to fit are combined, but it is not limited to this. For example, the model generation unit 61 may associate the data on the scale of the building with the data on whether welfare support is required for the building, and learn using the learning data in which the data associated with the data on the scale of the building and indicating whether welfare support is required for the building, the data on the specifications of an elevator in which the entrance / exit width of the car is wide enough for a wheelchair to pass through, and the data on the specifications of an elevator in which the inner dimensions of the car are large enough for a wheelchair to fit are combined.

[0064] As another example, the learning data acquisition unit 60 acquires data indicating whether the building is a rental building and data on the specifications of an elevator that satisfies the required number of passengers. The data indicating whether the building is a rental building is acquired as building data, and the data on the specifications of an elevator that satisfies the required number of passengers is acquired as data on the specifications of an elevator suitable for installation in the building. The data indicating whether the building is a rental building and the data on the specifications of an elevator that satisfies the required number of passengers are acquired in association with each other and used by the model generation unit 61 to learn the standard model of the elevator. At this time, when the building is a rental building, the model generation unit 61 learns to output a standard model of an elevator with a larger number of passengers than when the building is not a rental building. That is, when the building is a rental building, the model generation unit 61 generates a learned model so that the inference unit 11 infers a standard model of an elevator with a larger number of passengers than when the building is not a rental building.

[0065] The data indicating whether the building is a rental building is data associated with the data on the type of the building. That is, the learning data acquisition unit 60 acquires learning data in which the data indicating whether the building is a rental building, which is data associated with the data on the type of the building, and the data on the specifications of an elevator that satisfies the required number of passengers are paired. Note that a rental building is a building that is rented out as an office or a store for a usage fee. In the present embodiment, whether the entire building or only one floor is rented out, it is considered a rental building.

[0066] In the present embodiment, when the model generation unit 61 learns the standard model of the elevator using the data on the specifications of the elevator used in the past, the model generation unit 61 may learn to increase the recommendation rank of the standard model of the elevator.

[0067] As described above, according to the elevator information providing apparatus 100 according to the present embodiment, the user of the elevator information providing apparatus 100 can consider the specifications of the elevator based on the standard model. This is because the inference unit 11 infers the standard model of the elevator from the building data and outputs the data on the inferred standard model of the elevator.

[0068] If the user of the elevator information providing apparatus 100 according to the present embodiment can consider the specifications of the elevator based on the standard model, the manufacturer, who is the elevator manufacturing side, can reduce the load of the manufacturing process. This is because the manufacturing process of the standard model is already determined, so the occurrence of new work can be suppressed. Even when the user of the elevator information providing apparatus 100 considers a special model, the load of the manufacturing process can be reduced in the same way. For the manufacturer, considering the special model as a design change based on the standard model results in a lower load on the elevator manufacturing process than considering the special model from the beginning.

[0069] In addition, the elevator information providing apparatus 100 according to the present embodiment is realized by using a learned model for inferring a standard model of an elevator suitable for installation in a building from the building data, which was conventionally performed by salespersons of elevator manufacturers or elevator selling manufacturers. Conventionally, it was sometimes difficult for salespersons of manufacturers to guide those considering elevator purchase or order to consider the elevator specifications based on the standard model, depending on the salespersons. On the other hand, with the elevator information providing apparatus 100 according to the present embodiment, since a learned model for inferring a standard model of an elevator suitable for installation in a building from the building data is used, it can be realized at any time. That is, according to the elevator information providing apparatus 100 according to the present embodiment, it is possible to prevent the elevator information provided to those considering elevator purchase or order from differing depending on the salespersons of elevator manufacturers or elevator selling manufacturers.

[0070] Furthermore, since the user of the elevator information providing apparatus 100 according to the present embodiment does not have to select an elevator while checking the laws of the area where the building is to be constructed, the elevator selection work can be performed easily. The learned model used by the elevator information providing apparatus 100 according to the present embodiment is generated by acquiring and associating data on the area where the building is to be constructed and data on the specifications of elevators suitable for the laws of that area. This is because the elevator information providing apparatus 100 according to the present embodiment outputs data on the standard models of elevators suitable for the laws of the area where the building is to be constructed.

[0071] Furthermore, the user of the elevator information providing apparatus 100 according to the present embodiment can select an elevator preferred in the area where the building is to be constructed. The learned model used by the elevator information providing apparatus 100 according to the present embodiment is generated by acquiring and associating data on the area where the building is to be constructed and data on the specifications of elevators used in the past in that area. This is because the elevator information providing apparatus 100 according to the present embodiment outputs data on the standard models of elevators used in the past in the area where the building is to be constructed.

[0072] Furthermore, the user of the elevator information providing apparatus 100 according to the present embodiment does not have to select an elevator while considering the type of the building. Depending on the type of the building, the user has to select an elevator while checking various laws, and selecting an elevator while considering the type of the building has been a burden on the user. On the other hand, since the user of the elevator information providing apparatus 100 according to the present embodiment does not have to select an elevator while considering the type of the building, the elevator selection work can be performed easily. The learned model used by the elevator information providing apparatus 100 according to the present embodiment is generated by acquiring and associating data on the type of the building and data on the specifications of elevators suitable for that type. This is because the elevator information providing apparatus 100 according to the present embodiment outputs data on the standard models of elevators suitable for that type.

[0073] Furthermore, the user of the elevator information providing apparatus 100 according to the present embodiment can select a preferred elevator for each type of building. The learned model used by the elevator information providing apparatus 100 according to the present embodiment is generated by associating and acquiring data on the type of building and data on the specifications of the elevators used in the past in that type. This is because the elevator information providing apparatus 100 according to the present embodiment outputs data on the standard models of the elevators used in the past in that type.

[0074] In the present embodiment, the case where supervised learning is applied to the learning algorithm used by the model generation unit 61 has been described, but the present invention is not limited to this. As for the learning algorithm, in addition to supervised learning, reinforcement learning, unsupervised learning, semi-supervised learning, or the like can also be applied.

[0075] In the present embodiment, the elevator information providing apparatus 100 and the learning apparatus 600 may be incorporated in the server 102. Further, the elevator information providing apparatus 100 may be made directly usable by the user without passing through the server 102 and the Internet line 103. Further, the elevator information providing apparatus 100 may be connected to the server 102 via the Internet line. The application of the elevator information providing apparatus 100 according to the present embodiment may be appropriately changed within the scope of the present invention.

[0076] In the present embodiment, the type of the Internet line 103 is not limited. Further, the server 102 may be a physical server or a cloud server.

[0077] Embodiment 2. The configuration of the elevator information providing apparatus 200 according to Embodiment 2 of the present invention will be described. The elevator information providing apparatus 200 according to Embodiment 2 of the present invention has the same application example as the elevator information providing apparatus 100 according to Embodiment 1 of the present invention, but includes an inference unit 22 instead of the inference unit 11 of the elevator information providing apparatus 100 according to Embodiment 1 of the present invention. In Embodiment 2 of the present invention, only the differences from Embodiment 1 of the present invention will be described, and the description of the parts that are the same as those in Embodiment 1 of the present invention will be omitted.

[0078] FIG. 8 is a configuration diagram of the elevator information providing apparatus 200 according to Embodiment 2 of the present invention. As shown in FIG. 8, the elevator information providing apparatus 200 according to the present embodiment includes a building data acquisition unit 10 that acquires building data, and uses a learned model for inferring a standard model of an elevator suitable for installation in the building from the building data, and infers the standard model and the number of elevators from the building data input from the building data acquisition unit, and an inference unit 21 that outputs data on the inferred standard model and the number of elevators. The learned model is stored in the learned model storage device 201.

[0079] The inference unit 21 uses the learned model stored in the learned model storage device 201 to infer the standard model and the number of elevators suitable for installation in the building from the building data input from the building data acquisition unit 10, and outputs data on the inferred standard model and the number of elevators. The data on the standard model and the number of elevators output by the inference unit 21 are input to the personal computer 104 of the user and displayed on the personal computer 104.

[0080] Unlike the inference unit 21 of the elevator information providing apparatus 200 according to the present embodiment, the inference unit 21 of the elevator information providing apparatus 200 according to the first embodiment of the present invention uses the learned model stored in the learned model storage device 201 to infer not only the standard model of the elevator suitable for installation in the building but also the number of elevators from the building data input from the building data acquisition unit 10. Therefore, the learned model stored in the learned model storage device 201 is different between the present embodiment and the first embodiment of the present invention.

[0081] Next, a learning device 700 that generates a learned model used by the elevator information providing apparatus 200 according to the present embodiment will be described. FIG. 9 is a configuration diagram of a learning device 700 that generates a learned model used by the elevator information providing apparatus 200 according to the second embodiment of the present invention. As shown in FIG. 9, the learning device 700 includes a learning data acquisition unit 70 that acquires learning data, and a model generation unit 71 that generates a learned model for inferring the standard model of the elevator from the building data using the learning data.

[0082] Next, a specific example of the learning data required for the model generation unit 71 that generates the learned model used by the elevator information providing apparatus 200 according to the present embodiment to learn will be described. In the present embodiment, a plurality of pieces of learning data are acquired by the learning data acquisition unit 70. The learning data acquisition unit 70 acquires the data described below in addition to the data acquired by the learning data acquisition unit 60 of the learning device 600 that generates the learned model used by the elevator information providing apparatus 100 according to the first embodiment of the present invention. The learning data is a set of input data and result (label) data, and specific examples of the data acquired by the learning data acquisition unit 70 in addition to the learning data acquisition unit 60 will be described one by one below.

[0083] As one specific example, the learning data acquisition unit 70 acquires data on the number of floors of a building, data on the number of people using the elevator, and data on the transportation capacity of the elevator. The transportation capacity of the elevator is determined by the combination of the capacity of the elevator and the number of elevator units. The data on the number of floors of the building and the data on the number of people using the elevator are acquired as building data. The data on the number of floors of the building and the data on the number of people using the elevator, and the data on the transportation capacity of the elevator are acquired in association with each other and are used for the model generation unit 72 to learn the standard model of the elevator and the number of its units.

[0084] As another example, the learning data acquisition unit 70 acquires data on whether the building is a rental building or not, and data on the transportation capacity of the elevator. The data on whether the building is a rental building or not is acquired as building data. The data on whether the building is a rental building or not and the data on the transportation capacity of the elevator are acquired in association with each other and are used for the model generation unit 72 to learn the standard model of the elevator and the number of its units. At this time, when the building is a rental building, the model generation unit 72 learns to output the standard model of the elevator and the number of its units such that the transportation capacity of the elevator is higher than when the building is not a rental building. That is, when the building is a rental building, the model generation unit 72 generates a learned model so that the inference unit 21 infers the standard model of the elevator and the number of its units with a higher transportation capacity than when the building is not a rental building.

[0085] As described above, according to the elevator information providing device 200 according to the present embodiment, the user of the elevator information providing device 200 can consider the number of elevator units installed in the building and examine the specifications of the elevator based on the standard model. This is because the inference unit 21 infers the standard model of the elevator and the number of its units from the building data and outputs the inferred data on the standard model of the elevator and the number of its units.

[0086] Embodiment 3. The configuration of the elevator information providing apparatus 300 according to Embodiment 3 of the present invention will be described. The elevator information providing apparatus 300 according to Embodiment 3 of the present invention has the same application example as the elevator information providing apparatuses according to Embodiment 1 and Embodiment 2 of the present invention. In Embodiment 3 of the present invention, only the differences from Embodiment 1 and Embodiment 2 of the present invention will be described, and the description of the parts that are the same as those in Embodiment 1 and Embodiment 2 of the present invention will be omitted.

[0087] FIG. 10 is a configuration diagram of the elevator information providing apparatus 300 according to Embodiment 3 of the present invention. As shown in FIG. 10, the elevator information providing apparatus 300 according to the present embodiment includes a building data acquisition unit 10 that acquires building data, and uses a learned model for inferring a standard model of an elevator suitable for installation in the building from the building data. The elevator information providing apparatus 300 infers the standard model of the elevator from the building data input from the building data acquisition unit 10, and includes an inference unit 11 that outputs data of the inferred standard model of the elevator. The learned model is stored in the learned model storage device 101.

[0088] The elevator information providing apparatus 300 according to the present embodiment further uses the building data input from the building data acquisition unit 10 and the data of the standard model of the elevator input from the inference unit 11, and obtains data of the provisions of the regulations related to the installation of the standard model of the elevator from a plurality of regulations related to the construction of the building. The elevator information providing apparatus 300 includes a regulation acquisition unit 13 that outputs the obtained data of the provisions of the regulations. The plurality of regulations related to the construction of the building are stored in the regulation storage device 301. The data of the provisions of the regulations output from the regulation acquisition unit 13 are provided to the user via the server 102 and the Internet line 103. Then, the data of the provisions of the regulations acquired by the regulation acquisition unit 13 are displayed on the personal computer 104 of the user.

[0089] The elevator information providing device 300 according to the present embodiment enables a user to consider the specifications of an elevator based on a standard model. Since the inference unit 11 infers the standard model of the elevator, the elevator information provided by the elevator information providing device 300 according to the present embodiment is related to the standard model. For manufacturers of elevators or salespersons of elevators, showing the user the provisions of laws and regulations related to the installation of elevators can be achieved without causing complicated processing to the law acquisition unit 13 if the elevator is a standard model. The elevator information providing device 300 according to the present embodiment has realized this.

[0090] Among the plurality of laws and regulations related to the construction of a building, for example, there are various local ordinances, the Building Standards Act, the Enforcement Order of the Building Standards Act, the Enforcement Regulations of the Building Standards Act, the City Planning Act, the Construction Industry Act, the Architect Act, the Fire Service Act, the Act on the Promotion of Improvement of Energy Conservation Performance of Buildings, and the Act on the Promotion of Smooth Movement of the Elderly, Persons with Disabilities, etc. The Act on the Promotion of Improvement of Energy Conservation Performance of Buildings is commonly called the Building Energy Conservation Act. The Act on the Promotion of Smooth Movement of the Elderly, Persons with Disabilities, etc. is commonly called the Barrier-Free Act. In the present embodiment, the provisions of laws and regulations related to the installation of the standard model of the elevator acquired by the law acquisition unit 13 are, for example, the items of laws and regulations such as Article 〇 of the Building Standards Act. When the elevator information providing device 300 according to the present embodiment is used outside Japan, the plurality of laws and regulations related to the construction of the building may be appropriately changed to the relevant laws and regulations in that country.

[0091] In the present embodiment, the display method and display timing of the data of the legal provisions displayed on the personal computer 104 are not particularly limited. As the display method, for example, the text written in the legal provisions may be directly displayed on the personal computer 104, or the document in which the legal provisions are written may be displayed so that it can be downloaded, or a link leading to the website in which the legal provisions are written may be displayed. As the display timing, for example, it may be shown on the personal computer 104 simultaneously with the data of the standard model of the elevator, or the data of the standard model of the elevator may be displayed first, and then displayed on the personal computer 104 after the user has completed all considerations of the specifications of the elevator based on the standard model.

[0092] As described above, according to the elevator information providing apparatus 300 according to the present embodiment, the user of the elevator information providing apparatus 300 can consider the specifications of the elevator based on the standard model, and can also confirm the data of the legal provisions related to the installation of the standard model of the elevator. This is because the legal provision acquisition unit 13 uses the building data input from the building data acquisition unit 10 and the data of the standard model of the elevator input from the inference unit 11 to acquire the data of the legal provisions related to the installation of the standard model of the elevator from a plurality of laws related to the construction of the building, and outputs the acquired data of the legal provisions.

[0093] Embodiment 4. The configuration of the elevator information providing apparatus 400 according to Embodiment 4 of the present invention will be described. The elevator information providing apparatus 400 according to Embodiment 4 of the present invention has the same application example as the elevator information providing apparatus according to Embodiments 1 to 3 of the present invention. In Embodiment 4 of the present invention, only the differences from Embodiments 1 to 3 of the present invention will be described, and the description of the parts that are the same as those in Embodiments 1 to 3 of the present invention will be omitted.

[0094] FIG. 11 is a configuration diagram of an elevator information providing apparatus 400 according to Embodiment 4 of the present invention. As shown in FIG. 11, the elevator information providing apparatus 400 according to the present embodiment includes a building data acquisition unit 10 that acquires building data, and a learned model for inferring a standard model of an elevator suitable for installation in a building from the building data. Using the learned model, an inference unit 11 infers the standard model of the elevator from the building data input from the building data acquisition unit 10 and outputs data of the inferred standard model of the elevator. The learned model is stored in a learned model storage device 101.

[0095] The elevator information providing apparatus 400 according to the present embodiment further includes a drawing acquisition unit 14 that acquires a drawing related to the installation of the standard model of the elevator from a plurality of drawings related to the installation of the elevator using the building data input from the building data acquisition unit 10 and the data of the standard model of the elevator input from the inference unit 11, and outputs the acquired drawing. The plurality of drawings related to the installation of the elevator are stored in a drawing storage device 401. The data of the drawing output from the drawing acquisition unit 14 is provided to the user via a server 102 and an Internet line 103. Then, the data of the drawing acquired by the drawing acquisition unit 14 is displayed on the user's personal computer 104.

[0096] The elevator information providing apparatus 400 according to the present embodiment enables a user to consider the specifications of an elevator based on the standard model. Since the inference unit 11 infers the standard model of the elevator, the elevator information provided by the elevator information providing apparatus 400 according to the present embodiment is related to the standard model. For a manufacturer that manufactures elevators or a salesperson of an elevator manufacturer, showing the drawings related to the installation of the elevator to the user can be realized without causing complicated processing in the drawing acquisition unit 14 if the elevator is a standard model. The elevator information providing apparatus 400 according to the present embodiment realizes this.

[0097] Among the multiple drawings related to the installation of an elevator, for example, there are drawings with a hoistway floor plan, drawings with a hoistway cross-section, drawings with installation drawings, etc. It includes not only drawings created as 2D CAD data, but also drawings created as 3D CAD data, and not only static drawings but also dynamic drawings.

[0098] In this embodiment, the display method and display timing of the drawing data displayed on the personal computer 104 are not particularly limited. As the display method, for example, the drawing data may be directly displayed on the personal computer 104, or the document of the drawing data may be displayed so that it can be downloaded. As the display timing, for example, it may be displayed on the personal computer 104 at the same time as the data of the standard model of the elevator, or the data of the standard model of the elevator may be displayed first, and then displayed on the personal computer 104 after the user has completed all considerations of the elevator specifications based on the standard model.

[0099] As described above, according to the elevator information providing device 400 according to this embodiment, the user of the elevator information providing device 400 can consider the elevator specifications based on the standard model and can also confirm the drawing data related to the installation of the standard model of the elevator. This is because the drawing acquisition unit 14 uses the building data input from the building data acquisition unit 10 and the data of the standard model of the elevator input from the inference unit 11 to acquire the drawing data related to the installation of the standard model of the elevator from a plurality of drawings related to the installation of the elevator, and outputs the acquired drawing data.

[0100] It should be noted that within the scope of the present invention, each embodiment and modification can be freely combined, and each embodiment can be modified and omitted as appropriate.

Explanation of Reference Numerals

[0101] 1 Hoisting path member, 2a Inner wall of the car, 2b Outer wall of the car, 3 Landing member, 4 Car door, 5 Landing door, 6 Pocket for the landing door, 10 Building data acquisition unit, 11, 21 Inference unit, 13 Regulation acquisition unit, 14 Drawing acquisition unit, 60, 70 Learning data acquisition unit, 61, 71 Model generation unit, 100, 200, 300, 400 Elevator information providing device, 101, 201 Learned model storage device, 102 Server, 103 Internet line, 104 Personal computer, 301 Regulation storage device, 401 Drawing storage device, 600, 700 Learning device.

Claims

1. A building data acquisition unit that acquires building data; Using a learned model for inferring a standard model of an elevator suitable for installation in the building from the building data, the standard model of the elevator is inferred from the building data input from the building data acquisition unit, and the data of the inferred standard model of the elevator is output. An inference unit; Comprising: The building data includes data indicating whether the building is a rental building; When the building is a rental building, the inference unit infers a standard model of the elevator having a larger capacity than when the building is not a rental building. An elevator information providing device.

2. The inference unit infers the number of units of the standard model of the elevator from the building data input from the building data acquisition unit, and outputs the data of the inferred number of units of the standard model of the elevator. The elevator information providing device according to claim 1.

3. Using the building data input from the building data acquisition unit and the data of the standard model of the elevator input from the inference unit, data of the provisions of the regulations related to the installation of the standard model of the elevator is obtained from a plurality of regulations related to the construction of the building, and the obtained data of the provisions of the regulations is output. A regulation acquisition unit; The elevator information providing device according to claim 1 or 2, comprising:

4. Using the building data input from the building data acquisition unit and the data of the standard model of the elevator input from the inference unit, data of the drawings related to the installation of the standard model of the elevator is obtained from a plurality of drawings related to the installation of the elevator, and the obtained data of the drawings is output. A drawing acquisition unit; The elevator information providing device according to claim 1 or 2, comprising:

5. The building data includes data of the area where the building is constructed; The inference unit infers the standard model of the elevator from the data of the specifications of the elevator suitable for the laws of the area. The elevator information providing device according to claim 1 or 2.

6. The building data includes data of the area where the building is constructed; The inference unit infers the standard model of the elevator from the data of the specifications of the elevators used in the area in the past. The elevator information providing device according to claim 1 or 2.

7. The building data includes data of the type of the building; The inference unit infers the standard model of the elevator from data on the specifications of the elevator suitable for the type. The elevator information providing device according to claim 1 or 2.

8. The data of the building includes data on the type of the building. The inference unit infers the standard model of the elevator from data on the specifications of the elevator used in the past in the type. The elevator information providing device according to claim 1 or 2.

9. The data of the building includes data on whether the building requires welfare support. When the building requires welfare support, the inference unit infers the standard model of the elevator with the width of the entrance and exit of the car being wide enough for a wheelchair to pass through and the inner size of the car being large enough for a wheelchair to fit inside. The elevator information providing device according to claim 1 or 2.

10. An acquisition step of acquiring building data, An inference step of inferring the standard model of the elevator from the building data acquired in the acquisition step using a learned model for inferring the standard model of the elevator suitable for installation in the building, and outputting data on the inferred standard model of the elevator. Comprising The data of the building includes data on whether the building is a rental building. When the building is a rental building, in the inference step, the standard model of the elevator with a larger capacity than when the building is not a rental building is inferred. Elevator information providing method.

11. A learning data acquisition unit that acquires learning data including building data and data on the specifications of the elevator suitable for installation in the building, A model generation unit that generates a learned model for inferring the standard model of the elevator from the building data using the learning data. Comprising The data of the building includes data on whether the building is a rental building. When the building is a rental building, the model generation unit generates the learned model that infers the standard model of the elevator with a larger capacity than when the building is not a rental building. Learning device.

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