KR102121778B1 - Method of controlling exhibition lighting - Google Patents

Abstract

Disclosed is a method of controlling exhibition lighting. The method of controlling exhibition lighting includes the step of: establishing a correspondence relationship between at least one exhibition rental and a selected exhibition production, which is a basis for setting the display location of the selected exhibition production by specifying each exhibition production in a predetermined order; detecting whether or not visitors are gathered above a predetermined threshold in an area corresponding to the popularity of at least one exhibition rental having a corresponding relationship with the selected exhibition production; and turning on the lighting illuminating the pointed exhibition production, if it is detected that the visitors gather above the threshold.

Description

METHOD OF CONTROLLING EXHIBITION LIGHTING

The embodiments below relate to a technique for controlling lights that illuminate exhibits displayed in an exhibition hall.

Recently, with the increase in leisure time and interest in cultural life, people's interest in art/history/science/nature is increasing, and various exhibitions are held. In particular, restrictions on outdoor activities due to fine dust problems and thus the rise of indoor contents; Providing a diversified viewing experience through convergence with the Internet and smart technologies; And thanks to the quantitative and qualitative improvement of the exhibition as the cultural level increases, the exhibitions are gradually becoming specialized and diversified.

As the topics covered in the exhibition are specialized and diversified, it becomes difficult for the organizer of the exhibition to grasp the detailed information of all exhibits. Accordingly, technical efforts have been confirmed to grasp the characteristics of the exhibition centering on popular exhibits and derive the characteristics of the exhibition.

As an example, Republic of Korea Patent Publication KR 10-1412505 B1 discloses a method and system for providing a visitor's activity-based exhibition service in an IoT environment. In the IoT environment of the prior literature, a method for providing an exhibition service includes receiving sensor access time information and sensor departure time information from a user terminal; Calculating a viewing time of a work corresponding to a corresponding sensor signal based on the sensor connection time information and the sensor departure time information; And determining the audience's interest in the work based on the calculated viewing time. By this method, it is possible to provide a user's movement guidance and advertisement service based on the importance or interest of the work, and provide a personalized viewing history of the user based on the user's interest in the work or the exhibits to be displayed in the exhibition hall. It is possible to provide a service for providing a user's personalized viewing experience.

Prior literature extracts the interest level of works exhibited at the exhibition for each spectator, and when it is determined that a specific spectator is interested in a specific work, provides personalized viewing information for works belonging to a category similar to the corresponding work to the spectator can do. However, beyond the level of providing personalized information on the works of the exhibition already in progress, how to decide how to display each exhibit efficiently by using the popularity of exhibits as a measure in the stage of preparing for the exhibition. Prior literature has not been confirmed.

As the exhibitions are specialized and diversified, it is difficult for the organizer of the exhibition to grasp the detailed information of all the exhibitions, and thus, depending on the knowledge of some curators or directors, determine the exhibition location of exhibition rentals to be exhibited at the exhibition; Produce exhibits to be used in the exhibition; When determining how to arrange and control the lighting of an exhibition, a problem that may cause inconvenience to visitors may occur.

For example, if other exhibition rentals are placed near the popular exhibition rentals, a lot of people will be attracted to the corresponding part of the exhibition hall, and the high density of visitors will hinder visitors from seeing the entire exhibition. At this time, if there are no suitable exhibition products and lighting means to induce visitors to the exhibition productions, the visitors may feel discomfort due to the high density of visitors.

Therefore, there is a need for a method of determining how to display exhibits efficiently in the preparation stage for holding the exhibition, beyond providing personalized information on the works of the exhibition already in progress. In short, there is a demand for a method of determining the exhibition location of exhibition rentals so that there is no specific section crowded with visitors. Furthermore, when a certain section in which a large number of visitors inevitably occurs during the process of arranging exhibits, a method for dispersing the visitors from the section through the exhibition production is required. To this end, it is time to discuss the lighting control method of the exhibition hall, which can disperse the audience from the crowded section.

Republic of Korea Registered Patent Publication KR 10-1933279 B1

The embodiments are intended to provide a method of setting a display location of an exhibition that can help visitors to view an exhibition held in an exhibition hall without blocking a section by minimizing a section in which the viewers are concentrated at a high density.

The embodiments are intended to provide an artificial neural network capable of outputting an exhibition location of exhibition rentals so that there is no specific section crowded by visitors and a method of learning such an artificial neural network.

Embodiments provide a method of controlling exhibition hall lighting so that visitors who have gathered to view exhibition rentals are distributed to view exhibition productions, and accordingly, a phenomenon in which a large number of visitors are attracted to a specific part is reduced, so that a smooth exhibition can be achieved. I want to.

Furthermore, the embodiments are intended to provide an exhibition hall lighting control method for solving the problems mentioned in the background art and the problems in the technical field revealed in this specification.

The lighting control method of an exhibition hall according to an embodiment includes exhibition rentals rented for an exhibition held in the exhibition hall-each exhibition rental has a popularity expressed in an area according to a preset method-and the exhibition hall Acquiring floor plan data of the exhibition hall and copper wire data of the exhibition hall in order to display the exhibition productions produced for the exhibition in the exhibition hall; Determining the display location of the exhibit rentals based on the output of the artificial neural network by applying the top view, the movement data, and the popularity of each exhibit rental to an artificial neural network; And determining the number of exhibition productions and the exhibition location based on the exhibition location of the exhibition rentals, in which the popularity of the exhibition rentals having the exhibition location is overlapped with each other. Among the areas, the number of the intersection areas exceeding a preset area value is determined as the number of exhibition productions, and the exhibition positions of the exhibition productions include one exhibition production for each intersection area exceeding the preset area value. After determining a, in the method of controlling the lighting of the exhibition hall, each exhibition production is designated in a predetermined order, and at least one exhibition rental and the selected exhibition are used as a basis for setting the exhibition location of the selected exhibition production. Establishing a corresponding relationship of the product; Detecting through a means for detecting whether or not visitors are gathered above a predetermined threshold in an area corresponding to the popularity of the at least one exhibition rental having a corresponding relationship with the indicated exhibition production; When it is sensed that the viewers are gathered above the threshold, the step of turning on the light illuminating the pointed exhibition production may be included.

According to an embodiment, the popularity of an exhibition rental is measured by a predetermined number of times or a predetermined time through a measuring means capable of measuring the floor area and the number of visitors in the floor space of the exhibition rental space being exhibited. Obtaining a measurement area and the number of visitors within the measurement area; ii) determining the number of spectators in the measurement area per unit number or unit time as the spectator density of exhibition rentals; iii) determining whether the visitor density of the exhibition rental and a predetermined reference density are within a predetermined error range; iv) repeating steps i) to iii) after adjusting the floor area measured by the measuring means when the density of the visitors of the exhibition rental and the reference density are outside the error range; v) If the visitor density of the exhibition rental and the reference density are within the error range, it may be determined by a method including determining the measurement area as the popularity of the exhibition rental.

According to an embodiment, a method for controlling lighting in an exhibition hall may include determining whether lighting illuminating the indicated exhibition production is turned on when it is sensed that the visitors are gathered above a threshold value; And when the lighting illuminating the pointed exhibition production is turned on, increasing the illuminance of the lighting.

According to an embodiment, a method for controlling lighting in an exhibition hall may include determining whether the lighting for illuminating the selected exhibition product is turned on when it is sensed that the visitors are gathered above a threshold value; And lowering the illuminance of the light illuminating at least one or more exhibition rentals having the corresponding relationship with the indicated exhibition production when the lighting illuminating the indicated exhibition production is turned on.

According to an embodiment, a method for controlling lighting in an exhibition hall may include determining whether lighting illuminating the indicated exhibition production is turned on when it is sensed that the visitors are gathered above a threshold value; And when the lighting illuminating the indicated exhibit is turned on, further increasing the illuminance of the lighting and lowering the illuminance of the lighting illuminating at least one exhibit rental having the corresponding relationship with the indicated exhibit. You can.

Embodiments can provide a method for setting a display location of an exhibition that can help visitors to view an exhibition held in an exhibition hall without blocking a section by minimizing a section in which the viewers are concentrated at a high density.

Embodiments can provide an artificial neural network capable of outputting an exhibition location of exhibition rentals so that there is no specific section crowded by visitors, and a method of learning such an artificial neural network.

The embodiments provide a method of controlling the lighting of the exhibition hall so that the spectators who gathered to view the exhibition rentals are distributed to view the exhibition productions, thereby reducing the phenomenon that many spectators are attracted to a specific part, so that a smooth exhibition can be achieved. can do.

Meanwhile, the effects according to the embodiments are not limited to those mentioned above, and other effects not mentioned may be clearly understood by those having ordinary knowledge in the relevant technical field from the following description.

1 is an exemplary view of a configuration of an apparatus according to an embodiment.
2 is a view for explaining an exhibit according to an embodiment.
3 is a flowchart illustrating a method of determining an exhibition location of an exhibition object according to an embodiment.
4 is a view for explaining a plan view and copper wire data of an exhibition hall according to an embodiment.
5 is a view for explaining the display location setting of the exhibition rental according to an embodiment.
FIG. 6 is a view for explaining the number of exhibition productions and setting the exhibition location of the exhibition productions according to an embodiment.
7 is a flow chart for explaining a method for determining the popularity of an exhibition rental according to an embodiment.
8 to 10 are diagrams for explaining learning of an artificial neural network according to an embodiment.
11 is a view for explaining the lighting and monitoring means of the exhibition hall according to an embodiment.
12 is a flowchart illustrating a method for controlling lighting in an exhibition hall according to an embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, various changes may be made to the embodiments, and the scope of the patent application right is not limited or limited by these embodiments. It should be understood that all modifications, equivalents, or substitutes for the embodiments are included in the scope of rights.

Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only, and may be implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosure form, and the scope of the present specification includes modifications, equivalents, or substitutes included in the technical spirit.

Terms such as first or second may be used to describe various components, but these terms should be interpreted only for the purpose of distinguishing one component from other components. For example, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component.

When an element is said to be "connected" to another element, it should be understood that other elements may be present, either directly connected to or connected to the other element.

The terms used in the examples are used for illustrative purposes only and should not be construed as limiting. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, the terms "include" or "have" are intended to indicate the presence of features, numbers, steps, actions, components, parts or combinations thereof described herein, one or more other features. It should be understood that the existence or addition possibilities of fields or numbers, steps, operations, components, parts or combinations thereof are not excluded in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person skilled in the art to which the embodiment belongs. Terms, such as those defined in a commonly used dictionary, should be interpreted as having meanings consistent with meanings in the context of related technologies, and should not be interpreted as ideal or excessively formal meanings unless explicitly defined in the present application. Does not.

The spatially relative terms “below”, “beneath”, “lower”, “above”, “upper”, etc., are as shown in the figure. It can be used to easily describe a correlation between a component and other components. The spatially relative terms should be understood as terms including different directions of components in use or operation in addition to the directions shown in the drawings. For example, if a component shown in the drawing is flipped over, the component described as "below" or "beneath" the other component will be placed "above" the other component. Can be. Accordingly, the exemplary term “below” can include both the directions below and above. The component can also be oriented in other directions, so that spatially relative terms can be interpreted according to the orientation.

In addition, in the description with reference to the accompanying drawings, the same reference numerals are assigned to the same components regardless of reference numerals, and redundant descriptions thereof will be omitted. In describing the embodiments, when it is determined that detailed descriptions of related known technologies may unnecessarily obscure the subject matter of the embodiments, detailed descriptions thereof will be omitted.

1 is an exemplary view of a configuration of an apparatus according to an embodiment.

The device 101 according to an embodiment includes a processor 102 and a memory 103. The processor 102 may include at least one device described below through FIGS. 2 to 12, or may perform at least one method described below through FIGS. 2 to 12. The memory 103 may store information related to methods described below or a program implemented with methods described below. The memory 103 may be a volatile memory or a nonvolatile memory.

A person or organization using the device 101 may provide a service related to some or all of the methods described below through FIGS. 2 to 12. The device 101 may be a single server or computer, or may refer to a combination of a plurality of servers or nodes. One device 101 may store and perform all methods described below through FIGS. 2 to 12, and individual devices 101 may share and store methods described below through FIGS. 2 to 12. have. For example, the device 101 for learning the artificial neural network described below and the device 101 using the learned artificial neural network may be the same or may be individual. In addition, the apparatus 101 for determining the popularity of the exhibition rentals, which will be described later, and the apparatus 101 for determining the location of the exhibition rentals for which the popularity is determined may be the same or may be individual. In addition, the apparatus 10 for determining the exhibition location of the exhibition rentals 210 described later and the apparatus 101 for determining the exhibition location of the exhibition productions 220 may be the same or may be individual. In addition, the apparatus 10 for determining the display position of the exhibits 200 described later and the apparatus 101 for controlling the lighting of the exhibition hall may be the same or may be individual.

The processor 102 can execute a program and control the device 101. The code of the program executed by the processor 102 may be stored in the memory 103. The device 101 may be connected to an external device (for example, a personal computer or network) through an input/output device (not shown), and exchange data through wired or wireless communication.

Device 101 may be used to train an artificial neural network. The memory 103 may include a learned artificial neural network. The processor 102 may execute an artificial neural network algorithm stored in the memory 103. The device 101 for training the artificial neural network and the device 101 using the learned artificial neural network may be the same or may be individual.

2 is a view for explaining an exhibit according to an embodiment.

The exhibition 200 for an exhibition held in the exhibition hall may include an exhibition rental 210 and an exhibition production 220. For example, there may be a traditional agricultural exhibition held at the agricultural equipment exhibition hall in Pyeongtaek-si, and there may be an exhibition rental 210 and an exhibition production 220 shown in FIG. 2 as an exhibition 200 for this.

The exhibition rental 210 is a rental exhibition for an exhibition held in an exhibition hall, and may be an exhibition that cannot be manufactured directly or indirectly by a person who uses the device 101. For example, the exhibition rental 210 for a traditional agricultural exhibition held in the agricultural equipment exhibition hall of Pyeongtaek City includes galpans and galdols 211; Comb-shaped earthenware 212; Half moon stone knife (213); Pyeongtaek Tojinri ruins sarcophagus (214); And a home hat 215. If the exhibition rental 210 is suitable for the nature of the exhibition hall or exhibition, the number, type, size, etc. are not limited. For example, if the exhibition is an art exhibition of impressionist artists, the exhibition rental may be a picture of impressionist artists.

Each exhibition rental 210 may have a popularity expressed in area. The more popular the exhibition rental 210, the more visitors would like to see it, so more visitors are attracted to the exhibition compared to the less popular exhibition rental 210. Therefore, in order to ensure that the entire exhibition hall has a uniform audience density, a popular exhibition rental can have a wide area of popularity, and a less popular exhibition rental can have a small area of popularity.

To this end, the device 101 i) a measurement area and measurement measured a predetermined number of times or a predetermined time through a measuring means capable of measuring the floor area of the exhibition rental space and the number of visitors within the floor area Acquire the number of visitors within the area; ii) the number of visitors within the measurement area per unit number or unit time is determined as the density of visitors in the exhibition rental; iii) determining whether the visitor density of the exhibition rental and the predetermined reference density are within a predetermined error range; iv) if the visitor density and the reference density of the exhibition rental are outside the error range, after adjusting the floor area measured by the measuring means, repeat steps i) to iii); v) If the visitor density and reference density of the exhibition rental are within the error range, the measurement area can be determined as the popularity of the exhibition rental.

The device 101 for determining the popularity of the exhibition rental 210 may be the same device as the device 101 for determining the exhibition location of the exhibition 200 or may be a separate device. A detailed method of determining the popularity of the exhibition rentals 210 will be described later with reference to FIG. 7.

The device 101 can determine the display location of the exhibition rental 210. To this end, the device 101 acquires the floor plan 410 of the exhibition hall and the moving line data 420 of the exhibition hall; By applying the popularity of the floor plan 410, the copper wire data 420, and each exhibition rental 210 to the learned artificial neural network, the exhibition location of the exhibition rentals 210 may be determined based on the output of the artificial neural network.

The artificial neural network may output the exhibition positions of exhibition rentals in which the sum of the intersection area where the popularitys expressed by the area of the exhibition rentals 210 overlap each other is minimized. The area where the popularity overlaps with each other has a high density of visitors, so as the area where the popularity of exhibition rentals overlaps with each other is minimized, a specific section that attracts a lot of visitors disappears, and accordingly, a smooth exhibition can be achieved. That is, the device 101 can determine the display location of the exhibition rentals so that there is no specific section crowded with visitors through the output of the artificial neural network.

In addition, the device 101 may output the exhibition positions of exhibition rentals such that exhibition rentals classified as having high popularity according to a preset classification are positioned at regular intervals along the circulation of the movement data 420. In this case, the preset classification may be a criterion for classifying that the popularity is high if the popularity is a specific area or more, for example, 4 m ² or more. Since the exhibition rentals with high popularity cause visitors' interest, the more the exhibition rentals classified as highly popular in the exhibition rentals are located at regular intervals along the circulation of the exhibition hall, the more interesting the audience is in the rest of the exhibition. Rather than feeling bored, you can watch the entire exhibition with interest.

A more specific method of determining the display position of the artificial neural network by the exhibition rentals 210 will be described later with reference to FIGS. 3 to 5. In addition, a specific method for learning the artificial neural network will be described later with reference to FIGS. 8 to 10.

The exhibition production 220 may be an exhibition produced by a person using the device 101 through a direct or indirect method to meet the purpose of the exhibition hall or exhibition. For example, an exhibition product 220 for a traditional agricultural exhibition held at the agricultural equipment exhibition hall in Pyeongtaek-si may include a farmhouse model 221 and a sarcophagus diorama 222. Alternatively, if the exhibition is an art exhibition of impressionist painters, the exhibition production may be a poster explaining the history of the impressionist style.

The device 101 may determine an exhibition location of the exhibition production 220. Specifically, the device 101 may set a predetermined area value, for example, the number of intersection areas exceeding 1 m ² or more, among the intersection areas in which the popularity of exhibition rentals for which the exhibition location is determined overlap with each other, as the number of exhibition productions. You can. In addition, it is possible to determine an exhibition location of exhibition productions so that one exhibition production is included for each intersection area exceeding a preset area value.

The apparatus 101 for determining the exhibition location of the exhibition production 220 may be the same apparatus as the apparatus 101 for determining the exhibition location of the exhibition rental 210 or may be a separate apparatus. A specific method for the apparatus 101 to determine the number and location of the exhibition productions 220 will be described later with reference to FIGS. 3 and 6.

3 is a flowchart illustrating a method of determining an exhibition location of an exhibition object according to an embodiment.

First, the device 101 may acquire the floor plan data of the exhibition hall and the copper wire data of the exhibition hall (310). Acquisition may be made from ROM to RAM; May be achieved by physical insertion of an external device; It may be achieved through a wired or wireless network such as the Internet. Examples of the plan view and copper wire data will be described later with reference to FIG. 4.

The device 101 may generate an input to be applied to an artificial neural network based on the obtained floor plan 410 and the copper wire data 420 and the popularity expressed as the area of the exhibition rental 210. The popularity of the exhibition rentals 210 may be determined through a method described below with reference to FIG. 7.

Next, the apparatus 101 may determine the display location of the display rentals based on the output of the artificial neural network by applying the top view 410, the copper wire data 420, and the popularity of each display rental to the artificial neural network. (320). Here, the artificial neural network may be an algorithm for outputting the exhibition location of the exhibition rentals along the exhibition circulation of the exhibition hall after receiving the floor plan and the movement data of the exhibition hall and the popularity expressed as the area of the exhibition rentals. The artificial neural network may be learned through a method described below with reference to FIGS. 8 to 10.

The artificial neural network may be trained to output the exhibition positions of the exhibition rentals 210 in which the sum of the intersection areas where the popularitys represented by the area of the exhibition rentals 210 overlap each other is minimized. Through this, the artificial neural network can output the exhibition location of exhibition rentals so that there is no specific section crowded with visitors.

In addition, the artificial neural network may be trained to output the display positions of the display rentals 210, which are displayed at regular intervals along the moving line of the moving line data 420, according to the preset classification. Through this, the artificial neural network can output the exhibition positions of exhibition rentals where the viewers can watch the entire exhibition with interest, rather than having only a certain part of the exhibition fun and bored by the rest of the exhibition.

In addition, the artificial neural network minimizes the total sum of intersection areas where the popularity of the exhibition rentals 210 is overlapped with each other, while the exhibition rentals classified as high in popularity according to the preset classification are moving data 420 ) Can be learned to output the exhibition location of exhibition rentals located at regular intervals along the copper line.

In addition, artificial neural networks are given priority as minimizing the total sum of intersection areas in which the popularity expressed by the area of the exhibition rentals 210 overlaps each other, and the exhibition rental classified as high in popularity according to a preset classification. It can be learned that the water is positioned at a constant cycle along the copper line of the copper line data 420 as the next highest priority.

In addition, the artificial neural network has a priority in minimizing the total sum of the intersection areas where the popularity expressed by the area of the exhibition rentals 210 overlaps each other, and the exhibition rental classified as high in popularity according to a preset classification. It can be learned to prioritize that the water is positioned at regular intervals along the copper line of the copper line data 420.

Subsequently, the apparatus 101 may determine the number of exhibition productions and the exhibition location based on the exhibition location of the exhibition rentals (330).

Specifically, the device 101 may set a predetermined area value, for example, the number of intersection areas exceeding 1 m ² or more, among the intersection areas in which the popularity of exhibition rentals for which the exhibition location is determined overlap with each other, as the number of exhibition productions. You can. In addition, it is possible to determine an exhibition location of exhibition productions so that one exhibition production is included for each intersection area exceeding a preset area value.

The apparatus 101 for determining the exhibition location of the exhibition production 220 may be the same apparatus as the apparatus 101 for determining the exhibition location of the exhibition rental 210 or may be a separate apparatus. A specific example in which the device 101 determines the number and location of the exhibition productions 220 will be described later with reference to FIG. 6.

4 is a view for explaining a plan view and copper wire data of an exhibition hall according to an embodiment.

The device 101 may acquire the floor plan 410 and the copper wire data 420 of the exhibition hall where the exhibition is held. The floor plan 410 and the copper wire data 420 may be a basis for input to be applied to an artificial neural network, along with the popularity expressed as the area of the exhibition rentals 210.

The floor plan 410 is marked with an entrance and an exit, and as long as it represents a place where the exhibition is held, there are no restrictions on the type, size, and format of the floor plan 410 file. For example, the floor plan 410 is a CAD file; A vector (SVR) file; An illustration (AI) file; It can be a TIF file.

The moving line data 420 also expresses a starting point and an ending point, and there is no limitation in the type, size, format, etc. of the file, as long as it represents the moving line of the exhibition hall. For example, the floor plan 410 is a CAD file; A vector (SVR) file; An illustration (AI) file; It can be a TIF file.

The device 101 may generate an input of an artificial neural network by performing pre-processing on the floor plan 410 and the copper wire data 420. Specifically, the device 101 unifies the obtained floor plan 410 and the extension format of the copper wire data 420; Accumulate accumulation; Uniform resolution; Pre-processing such as leaving only the minimum color required in the color information may be performed. In addition, the device 101, after making the background area of the floor plan 410 and the copper wire data 420 transparent, layer the layer of the floor plan 410 and the copper wire data 420 to enter the copper wire data 420. And pre-processing to adjust the exit to match the entrance and exit of the exhibition hall or exhibition shown in the floor plan 410.

5 is a view for explaining the display location setting of the exhibition rental according to an embodiment.

The device 101 may set the exhibition location of the exhibition rental 210 along the movement line of the exhibition hall through the learned artificial neural network. The artificial neural network can output the exhibition location of exhibition rentals so that there is no specific section crowded with visitors. Alternatively, the artificial neural network can output the exhibition locations of exhibition rentals that allow the viewers to watch the entire exhibition with interest, rather than having a particular part of the exhibition interesting and not bored with the rest.

For example, the exhibition rental 210 for a traditional agricultural exhibition held on the first floor of the agricultural equipment exhibition hall in Pyeongtaek-si includes a brown plate and a reed 211; Comb-shaped earthenware 212; Half moon stone knife (213); Pyeongtaek Tojinri ruins sarcophagus (214); And a home hat 215. Each of the exhibition rentals 211, 212, 213, 214, and 215 may have a popularity expressed as an area. As shown in Fig. 6, the popularity 611 of galpan and galdol is the smallest; The popularity (612) of comb-shaped earthenware is in the middle of five exhibition rentals; The popularity 613 of the Bandal Stone Knife is greater than the popularity 612 of the comb-shaped earthenware and less than the popularity 614 of the Pyeongtaek Tojinri ruins sarcophagus; Pyeongtaek Tojinri Ruins The highest popularity (614) of sarcophagus was; The popularity 615 of the home hat is less than the popularity 612 of the comb-shaped earthenware, but may be greater than the popularity 611 of the galpan and the stone. The popularity of the exhibition rentals 210 may be determined through a method described below with reference to FIG. 7.

Referring back to FIG. 5, the device 101 may determine the display position of each exhibition rental 211, 212, 213, 214, 215 through the learned artificial neural network.

Specifically, the device 101 includes a plan view of the first floor where a traditional agricultural exhibition is held at the agricultural equipment exhibition hall in Pyeongtaek City; Data of visits to traditional agricultural exhibitions; And an input of an artificial neural network based on the popularity of each exhibition rental 211, 212, 213, 214, and 215.

Next, the device 101 may apply input to the artificial neural network. The artificial neural network may be an artificial neural network learned according to reinforcement learning. The artificial neural network may be a Q-Network, a Depp Q-Network (DQN), or a relational network (RL) structure suitable for outputting abstract reasoning through reinforcement learning.

Subsequently, the device 101 may acquire an output from the artificial neural network (830 ). The artificial neural network can output the exhibition location of exhibition rentals so that there is no specific section crowded by visitors according to the learning result. In addition, the artificial neural network can output the exhibition positions of exhibition rentals that allow the viewers to watch the entire exhibition with interest, rather than having a certain part of the exhibition interesting and bored by the rest of the exhibition according to the learning result. In FIG. 5, the galpan and galdol 211 so that there is no specific section where a large number of visitors are gathered; Comb-shaped earthenware 212; Half moon stone knife (213); Pyeongtaek Tojinri ruins sarcophagus (214); And the output position of the home hat 215 is output.

The device 101 may use the output of the artificial neural network as it is, or through a process of post-processing the output of the artificial neural network, the display location of the exhibition rentals 210 may be determined. The post-treatment process may include post-treatment according to humidity and post-treatment according to the ceiling height of the exhibition hall.

Specifically, the exhibition location of the exhibition rentals 210 may be corrected according to the geographical location and the humidity of the time when the exhibition is currently held. Since high humidity causes discomfort, if the geographical location and timing of the current exhibition is high, the distance between exhibition rentals should be corrected to be wider than if the humidity is low.

To this end, the device 101 determines the popularity of the exhibition rental through the method described below with reference to FIG. 7 and the geographic location of the previous exhibition halls where the visitor density of the exhibition rental was measured and humidity information at the time when the exhibition was opened in each exhibition hall. Can be obtained.

Subsequently, the device 101 obtains the average humidity of the previous exhibition halls as a representative value of humidity, compares the representative humidity values of the previous exhibition halls with the humidity of the exhibition hall where the current exhibition rental is displayed, and then displays the current exhibition rental. When the humidity of the exhibition hall is higher, the distance between the exhibition rentals can be set to be wider at the exhibition location of the exhibition rentals output by the artificial neural network. Through this, the device 101 can reduce the situation in which the viewers feel unpleasant when concentrated in a specific part of the exhibition hall in a high humidity situation.

In addition, the exhibition location of the exhibition rentals 210 may be corrected according to the ceiling height of the exhibition hall where the current exhibition is held. In general, people tend to feel more comfortable when the floor-to-ceiling height is higher on one floor in the building, and less likely to feel uncomfortable when the floor-to-ceiling height is lower on one floor in the building. Therefore, if the height of the ceiling of the corresponding floor of the exhibition hall where the exhibition is held is low, the gap between the exhibition rentals should be corrected to be wider than the height of the ceiling.

To this end, with reference to FIG. 7, ceiling height information of previous exhibition halls in which the visitor density of the exhibition rental was measured is obtained to determine the popularity of the exhibition rental through a method described below.

Subsequently, the device 101 obtains the average of the ceiling height of the previous exhibition halls as a representative value of the ceiling height, compares the representative value of the ceiling heights of the previous exhibition halls with the ceiling height of the exhibition hall where the current exhibition rental is displayed, and then displays the current exhibition hall. When the height of the ceiling of the exhibition hall where the trough is exhibited is lower, it is possible to set the interval between the exhibition rentals wider at the exhibition location of the exhibition rentals output by the artificial neural network. Through this, the device 101 can reduce the situation in which the viewers feel unpleasant when crowded to a specific part of the exhibition hall in a situation where the ceiling height is low.

Through the above process, the device 101 may output the location of exhibitions of exhibition rentals so that there is no specific section crowded by visitors. In addition, the device 101 can output the exhibition location of exhibition rentals that allow the viewers to watch the entire exhibition with interest, rather than having a particular part of the exhibition interesting and feeling bored with the rest of the exhibition. In addition, the device 101 may post-process the output of the artificial neural network using the humidity information and the ceiling height information, thereby reducing a situation in which visitors feel uncomfortable when they are concentrated in a specific part of the exhibition hall.

FIG. 6 is a view for explaining the number of exhibition productions and setting the exhibition location of the exhibition productions according to an embodiment.

First, the popularity expressed as the area of each exhibition rental 211, 212, 213, 214, 215 may be as shown in FIG. The popularity (611) of galpan and galdol is the smallest; The popularity (612) of comb-shaped earthenware is in the middle of five exhibition rentals; The popularity 613 of the Bandal Stone Knife is greater than the popularity 612 of the comb-shaped earthenware and less than the popularity 614 of the Pyeongtaek Tojinri ruins sarcophagus; Pyeongtaek Tojinri Ruins The highest popularity (614) of sarcophagus was; The popularity 615 of the home hat is less than the popularity 612 of the comb-shaped earthenware, but may be greater than the popularity 611 of the galpan and the stone. A specific method of determining the popularity of the exhibition rentals 210 will be described later with reference to FIG. 7.

The area where the popularity overlaps with each other is a high-density area, so if an exhibition production is placed in an area where the popularity of the exhibition rentals overlaps, the visitors gathered to view the exhibition rentals are distributed to see the exhibition production, Accordingly, a phenomenon in which a large number of visitors are attracted to a specific portion is reduced, so that a smooth exhibition can be achieved.

In order to place the exhibition production in an area where the popularity of the exhibition rentals overlaps each other, the device 101 sets a predetermined area value among intersection areas where the popularitys expressed as the area of the exhibition rentals having the exhibition location overlap each other. The number of intersection areas exceeding may be determined as the number of exhibits. The preset area value may be, for example, 1 m ² .

For example, the small square intersection area where the popularity 611 of the galpan and the reed stone overlaps with the popularity 612 of the comb-patterned earthenware may exceed a preset area value. In addition, the popularity of the bandaldol knife (613); The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And a large non-square intersection area where the popularity 615 of the groove is overlapped with each other may also exceed a preset area value. In this case, the device 101 may determine the number of exhibition products to be produced in two.

In order to place the exhibition productions in an area where the popularity of the exhibition rentals overlap with each other, the apparatus 101 may determine the exhibition location of the exhibition productions to include one exhibition production for each intersection area exceeding a preset area value. .

For example, the small square intersection area where the popularity 611 of the galpan and the reed stone and the popularity 612 of the comb-patterned earth overlap each other exceeds a preset area value, so the small square intersection area includes the farmhouse model 221 Can be. In addition, the popularity of the bandaldol knife (613); The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And a large non-square intersection area where the popularity 615 of the grooves overlaps with each other exceeds a preset area value, so the large non-square intersection area may include a sarcophagus diorama 222.

As such, among the intersection areas where the popularitys expressed by the area of the exhibition rentals where the exhibition location is determined overlap with each other, the number of intersection areas exceeding a preset area value is determined as the number of exhibition productions, and the intersection area exceeds a preset area value. By setting the exhibition location of exhibition productions so that one exhibition production is included in each area, it is possible to place the exhibition productions in an area where the popularity of exhibition rentals overlap with each other, that is, an area where there are many visitors. Through this, visitors who were gathered to view the exhibition rentals are distributed to view the exhibition productions, and accordingly, a phenomenon in which a large number of visitors are attracted to a specific part is reduced, so that a smooth exhibition can be achieved.

7 is a flow chart for explaining a method of determining the popularity of an exhibition rental according to an embodiment.

The apparatus 101 for determining the popularity of an exhibition rental may be the same apparatus 101 as the apparatus 101 for determining how to display the exhibitions by pre-processing the exhibition rentals having a predetermined popularity as an input of an artificial neural network, or a separate apparatus 101 ). Hereinafter, the process of determining the popularity of the exhibition rental will be described.

First, the device 101 is a measuring area capable of measuring the floor area and the number of visitors in the floor space of the exhibition rental space being exhibited, and the measuring area and the measuring area are measured by a predetermined number of times. A number may be obtained (710).

The device 101 may be interlocked with measurement means (not shown). Measurement means include a general camera; Thermal imaging camera; It may be a pressure to a weight sensor, or a combination including at least one of them. The measuring means is not limited in its type and characteristics as long as it can measure the floor area of the exhibition rental space and the number of visitors in the floor area. The measuring means may be fixed to measure the floor area of a specific space where the exhibition rental can be viewed for a predetermined number of times or for a predetermined time.

The predetermined number of times may be to measure the floor area and the number of visitors in the floor area of the specific space where the exhibition rental can be viewed once per hour during the exhibition. The predetermined time may be to continuously measure the floor area and the number of visitors in the floor area of the specific space where the exhibition rental can be viewed during the exhibition. The predetermined number of times and the predetermined time are not limited thereto, and may be set as many times as necessary and desired.

Next, the apparatus 101 may determine the number of visitors within the measurement area per unit number or unit time as the density of visitors in the exhibition rental (720 ). The unit of visitor density of exhibition rentals may be [person/m ² ].

Specifically, when the number of visitors in the measurement area per unit number of times is determined as the audience density of the exhibition rental, the device 101 may determine a predetermined number of times, for example, within the floor area and floor area of a specific space where the exhibition rental can be viewed during the exhibition. Based on the measured number of visitors per hour, the average number of visitors in the floor area can be calculated to obtain the density of visitors in the exhibition rental.

In addition, if the number of visitors within the measurement area per unit time is determined as the density of visitors in the exhibition rental, the device 101 may be set at a predetermined time, for example, the number of visitors in the floor area and floor area of a specific space where the exhibition rental can be viewed during the exhibition. Based on continuously measured data, the average number of visitors in the floor area can be calculated to obtain the density of visitors in the exhibition rental.

Subsequently, the apparatus 101 may determine whether the audience density of the exhibition rental and the predetermined reference density are within a predetermined error range (730). The predetermined reference density may be, for example, 2 people/m ² . The predetermined error range may be, for example, 0.1 persons/m ² . The predetermined reference density and the predetermined error range are not limited thereto, and may be set differently according to needs and purposes.

The apparatus 101 may adjust the floor area measured by the measuring means when the spectator density and the reference density of the exhibition rental are outside the error range (735). Specifically, when the density of visitors in the exhibition rental is greater than the reference density, the device 101 may be controlled to increase the floor area measured by the measuring means. Conversely, when the density of visitors in the exhibition rental is smaller than the reference density, the device 101 may control the measuring means to reduce the floor area measured.

Thereafter, the device 101 may repeat steps 710 to 730. By repeating steps 710 to 730, the density of visitors to the exhibition rental can be gradually narrowed within a predetermined reference density and a predetermined error range.

The apparatus 101 may determine the measurement area measured by the measurement means as the popularity of the exhibition rental when the visitor density and the reference density of the exhibition rental are narrowed within the error range (740). Through this, the most popular exhibition rentals have a large area popularity, and the less popular exhibition rentals have a small area popularity.

On the other hand, the artificial neural network learned by the method described below with reference to FIG. 8 determines the display position of the exhibition rentals in which the sum of the intersection areas where the popularitys expressed by the area of the exhibition rentals 210 overlap each other is minimized. Can print Therefore, if the popularity of the exhibition rentals described with reference to FIG. 7 is applied to an artificial neural network, the artificial neural network allocates a wide exhibition space for a popular exhibition rental, and a less popular exhibition rental allocates a small exhibition space, The area where the popularity of the exhibition rentals overlap with each other is minimized, so that the exhibition location of the exhibition rentals is minimized so that a specific section where the audience is driven to a standard density, for example, 2 people/m ² or more, is minimized.

8 is a diagram for explaining learning of an artificial neural network according to an embodiment.

The artificial neural network may be an algorithm that outputs the location of the exhibition rentals along the exhibition circulation of the exhibition hall after receiving the floor plan and the movement data of the exhibition hall and the popularity expressed as the area of the exhibition rentals. The device 101 in which the learning of the artificial neural network is performed may be the same device 101 as the device 101 for determining a method for displaying an exhibition using the learned artificial neural network, or may be a separate device 101. Hereinafter, a process of learning an artificial neural network will be described.

First, the device 101 may generate an input based on the floor plan and copper wire data of the exhibition hall and the popularity expressed as the area of the exhibition rentals (810). Specifically, the device 101 unifies the obtained floor plan 410 and the extension format of the copper wire data 420; Accumulate accumulation; Uniform resolution; Pre-processing such as leaving only the minimum color required in the color information may be performed. In addition, the device 101, after making the background area of the floor plan 410 and the copper wire data 420 transparent, layer the layer of the floor plan 410 and the copper wire data 420 to enter the copper wire data 420. And pre-processing to adjust the exit to match the entrance and exit of the exhibition hall or exhibition shown in the floor plan 410.

In addition, the popularity of the exhibition rentals 210 also unifies the extension format with the floor plan 410 and the moving data 420; Accumulate accumulation; Uniform resolution; Pre-processing such as leaving only the minimum color required in the color information may be performed. The floor plan 410 and the copper wire data 420 of the exhibition hall on which the pre-processing has been performed, and the popularity of the exhibition rentals 210 are used as the input of the artificial neural network, or the input is generated through normal processing to remove unnecessary information. Can be.

Next, the device 101 may apply input to the artificial neural network (820 ). The artificial neural network may be an artificial neural network learned according to reinforcement learning. The artificial neural network may be a Q-Network, a Depp Q-Network (DQN), or a relational network (RL) structure suitable for outputting abstract reasoning through reinforcement learning.

The artificial neural network learned according to reinforcement learning may be updated and optimized by reflecting the evaluation on the first compensation and the second compensation. The first reward can be increased as the popularity of exhibition rentals is minimized. The second reward may be increased as exhibition rentals classified as having high popularity according to a predetermined classification are positioned at regular intervals along the moving line of the moving data. A detailed description related to the first compensation will be described later with reference to FIG. 9. A detailed description related to the second compensation will be described later with reference to FIG. 10.

Subsequently, the device 101 may acquire an output from the artificial neural network (830 ). The output of the artificial neural network may be an exhibition location of exhibition rentals arranged along the exhibition line of the exhibition hall. At this time, the artificial neural network can determine the exhibition location of the exhibition rentals so that there is no specific section crowded with visitors. In addition, the artificial neural network can determine the location of exhibition rentals that allow visitors to watch the entire exhibition with interest, rather than having fun with only certain parts of the exhibition and feeling bored with the rest of the exhibition.

Thereafter, the device 101 may evaluate the output of the artificial neural network and pay the reward (840 ). The evaluation of the output can be divided into a first compensation and a second compensation. The first reward is that the artificial neural network can be increased as the popularity of exhibition rentals is minimized. The second reward may be increased as exhibition rentals classified as having high popularity according to a predetermined classification are positioned at regular intervals along the moving line of the moving data.

When the first compensation and the second compensation have the same staged compensation system, when the first compensation and the second compensation correspond to the same compensation phase, the compensation value given as the first compensation and the compensation value given as the second compensation This may be the same; The compensation value given as the first compensation may be greater than the compensation value given as the second compensation; The compensation value given as the first compensation may be smaller than the compensation value given as the second compensation.

For example, when the first compensation and the second compensation have a reward system of 10 steps, when the first compensation and the second compensation correspond to the same compensation step 6, the compensation value given as the first compensation and the second compensation The given compensation value may be equally 60; The compensation value given as the first compensation may be 60, and the compensation value given as the second compensation may be 48; The compensation value given as the first compensation may be 48, and the compensation value given as the second compensation may be 60. The reward system may be more subdivided or simpler depending on needs and objectives.

Next, the device 101 may update the artificial neural network based on the evaluation (850 ). Specifically, the device 101, in an environment in which an artificial neural network arranges exhibition rentals 210 having a popularity expressed as an area along the moving line data 420 on the floor plan 410 of the exhibition hall, rewards the reward. The artificial neural network can be updated through a process of optimizing a policy of determining actions to be taken in specific states so that the expected value of consensus is maximized.

Meanwhile, the process of optimizing the policy may be performed through the process of estimating the maximum value of the expected value of the sum of rewards or the maximum value of the Q-function, or the minimum value of the loss function of the Q-function. Estimation of the minimum value of the loss function can be made through stochastic gradient descent (SGD). The process of optimizing the policy is not limited to this, and various optimization algorithms used in reinforcement learning may be used.

The device 101 may gradually update the artificial neural network by repeating the learning process of the artificial neural network as described above. Through this, the device 101 can learn an artificial neural network that outputs the exhibition positions of the exhibition rentals 210 in accordance with the purpose along the movement line of the exhibition hall.

Specifically, when the first compensation and the second compensation have the same phased compensation system, when the first compensation and the second compensation correspond to the same compensation phase, the compensation value and the second compensation given as the first compensation If the given reward value is the same, the artificial neural network will be updated to equally increase the first and second rewards so that the expected expectation of the rewards is maximized.

Through this, the artificial neural network considers the task of minimizing the area where the popularity of exhibition rentals overlap with each other and the positioning of exhibition rentals classified as high in popularity at regular intervals along the circulation of the movement data with the same importance. 210) of the display location can be output. Through this, the artificial neural network determines the exhibition location of exhibition rentals so that there is no specific section crowded by visitors, and, to an equal extent, the audience is interested in rather than being bored in the rest of the exhibition and having fun with only certain parts of the exhibition. You can decide the location of the exhibition rentals so that you can see the entire exhibition with you.

Alternatively, when the first compensation and the second compensation have the same staged compensation system, when the first compensation and the second compensation correspond to the same compensation phase, the compensation value given as the first compensation is given as the second compensation If it is higher than the compensation value, the artificial neural network will be updated in such a way that the first compensation can be obtained more than the second compensation, so that the expectation of the sum of the compensation values is maximized.

Through this, the artificial neural network considers that the task of minimizing the area where the popularity of exhibition rentals overlap with each other is more important than the task of positioning the exhibition rentals classified as high in popularity at regular intervals along the circulation of the movement data ( 210) of the display location can be output. Through this, the artificial neural network, first of all, determines the location of the exhibition rentals so that there is no specific section crowded with visitors, and, in the next order, the viewers are only interested in the specific part of the exhibition and feel bored in the rest of the exhibition. Rather, it is possible to determine the location of the exhibition rentals, which allows you to watch the entire exhibition with interest.

Alternatively, when the first compensation and the second compensation have the same leveled compensation system, when the first compensation and the second compensation correspond to the same compensation phase, the compensation value given as the second compensation is given as the first compensation If it is higher than the compensation value, the artificial neural network will be updated in such a way that the second compensation can be obtained more than the first compensation, so that the expectation of the sum of the compensation values is maximized.

Through this, the artificial neural network considers the display loans classified as highly popular as a higher priority than the task of minimizing the area where the popularity of the exhibition rentals overlaps with each other along the movement line of the movement data. 210) of the display location can be output. Through this, the artificial neural network preferentially determines the exhibition location of exhibition rentals, which allows visitors to watch the entire exhibition with interest, rather than having fun with only certain parts of the exhibition and feeling bored with the rest of the exhibition. In the second order, the exhibition location of exhibition rentals can be determined so that there is no specific section with a lot of visitors.

9 is a view for explaining a first compensation in the learning of an artificial neural network according to an embodiment.

With respect to the output of the artificial neural network learned through reinforcement learning, the first reward may be increased as the popularity of exhibit rentals is minimized to minimize the overlapping area. The area where the popularity overlaps with each other has a high density of visitors, so as the area where the popularity of exhibition rentals overlaps with each other is minimized, a specific section that attracts a lot of visitors disappears, and accordingly, a smooth exhibition can be achieved.

Since the artificial neural network is updated so that the expected expectation of the rewards is maximized, the output of the artificial neural network gradually maximizes the first compensation during learning, that is, the area where the popularity of exhibition rentals overlap each other gradually. Can be minimized. Through this, the artificial neural network can output the exhibition location of exhibition rentals so that there is no specific section crowded with visitors.

Specifically, the vandal stone knife 213 output through an artificial neural network that has undergone a first learning cycle; Pyeongtaek Tojinri ruins sarcophagus (214); And the display position of the groove 215 may be the same as the first output 901. That is, the first popularity 613 of the vandal stone knife; Pyeongtaek Tojinri Ruins 1st popularity of sarcophagus (614); The area occupied by the first popularity 615 of the groove may be the same as the first output 901 shown on the left side of FIG. 9.

On the other hand, the vandal stone knife 213 output through an artificial neural network that has undergone a second learning cycle; Pyeongtaek Tojinri ruins sarcophagus (214); And the display position of the home hat 215 may be the same as the second output (902). That is, the second popularity 913 of the vandal stone knife; The second popularity of the sarcophagus of the Tojinri ruins in Pyeongtaek (914); The area occupied by the second popularity 915 of the groove may be the same as the second output 902 shown on the right side of FIG. 9.

When the first output 901 and the second output 902 are compared, the area where the popularity of the display rentals 213, 214, and 215 of the second output 902 overlap each other is displayed in the first output 901. The popularity of rental items 213, 214, and 215 is smaller than the area overlapping each other. Therefore, the apparatus 101 provides more compensation values of the first compensation in the case of the second output 902 than in the case of the first output 901 in learning the artificial neural network. Through this, the artificial neural network may be updated so that the artificial neural network can calculate an output closer to the second output 902 than the first output 901. Through this, the artificial neural network can infer the output in which the area where the popularity of exhibition rentals overlap each other is gradually minimized. Through this, the artificial neural network can gradually output the exhibition positions of exhibition rentals so that there are no specific sections crowded by visitors.

10 is a view for explaining a second compensation in the learning of an artificial neural network according to an embodiment.

With respect to the output of the artificial neural network learned through reinforcement learning, the second compensation may be increased as the exhibition rentals classified as having high popularity according to a preset classification are positioned at regular intervals along the circulation of the moving data. In this case, the preset classification may be a criterion for classifying that the popularity is high if the popularity is a specific area or more, for example, 4 m ² or more. Since the exhibition rentals with high popularity cause visitors' interest, the more the exhibition rentals classified as highly popular in the exhibition rentals are located at regular intervals along the circulation of the exhibition hall, the more interesting the audience is in the rest of the exhibition. Rather than feeling bored, you can watch the entire exhibition with interest.

Since the artificial neural network is updated so that the expected expectation of the rewards is maximized, the output of the artificial neural network during the learning is gradually maximized by the second compensation, that is, exhibition rentals classified as highly popular are exhibited. It can be arranged gradually and gradually. Through this, the artificial neural network can output the exhibition positions of exhibition rentals where the viewers can watch the entire exhibition with interest, rather than having only a certain part of the exhibition fun and bored by the rest of the exhibition.

Specifically, the exhibition rental 1 11010 output through an artificial neural network that has undergone a first learning cycle; Exhibition Rental 2 (1020); Exhibition Rental 3 (1030); Exhibition Rental 4 (1040); Exhibition Rental 5 (1050); And the exhibition location of the exhibition rental 6 (1060) may be the same as the first output (1001). The first output 1001 includes a highly popular exhibition rental 1 1010; Exhibition Rental 3 (1030); And it can be seen that the exhibition rental 5 (1050) is arranged at a relatively constant cycle along the movement line of the exhibition hall.

On the other hand, the vandal stone knife 213 output through an artificial neural network that has undergone a second learning cycle; Pyeongtaek Tojinri ruins sarcophagus (214); And the display position of the home hat 215 may be the same as the second output 1002. The second output 1002 includes a highly popular exhibition rental 1 1010; Exhibition Rental 3 (1030); And it can be seen that the exhibition rental 5 (1050) is arranged in a relatively irregular cycle along the movement line of the exhibition hall.

When the first output 1001 and the second output 1002 are compared, the arrangement of the exhibition rentals 1010, 1030, 1050 classified as having high popularity of the first output 1001 is the popularity of the second output 1002. Has a certain periodicity than the arrangement of exhibition rentals 1010, 1030, 1050 classified as high. Therefore, the apparatus 101 provides more compensation values of the second compensation in the case of the first output 1001 than in the case of the second output 1002 in learning the artificial neural network. Through this, the artificial neural network can be updated so that the artificial neural network can calculate an output closer to the first output 1001 than the second output 1002. Through this, the artificial neural network can infer the output in which exhibition rentals classified as highly popular are arranged at regular intervals along the circulation of the exhibition hall. Through this, the artificial neural network is able to output the exhibition locations of exhibit rentals that allow the viewers to watch the entire exhibition with interest, rather than having only a certain part of the exhibition interesting and bored by the rest of the exhibition.

11 is a view for explaining the lighting and monitoring means of the exhibition hall according to an embodiment.

The device 101 may be linked with a sensing means 1110 that can detect in real time the number of visitors in the floor area and the floor area of the space where the lighting corresponding to each exhibition object 200 and the exhibition rental being displayed can be viewed. .

Each lighting illuminates the corresponding exhibit 200, so that the exhibit can be seen or attracted attention. For example, the lighting 1120 for the sarcophagus diorama may illuminate the sarcophagus diorama 222; The half moon stone knife lighting 1123 may illuminate the half moon stone knife 213; Pyeongtaek Tojinri historic site sarcophagus lighting 1124 may illuminate the Pyeongtaek Tojinri historic site sarcophagus 214; The lighting 1125 for the grooves may illuminate the grooves 215. In addition, although not shown, there may be lighting for the galpan and the reed 211; There may be lighting for the comb-shaped earthenware 212; There may be lighting for the farmhouse model 221.

Each light may be composed of a single lamp, or a combination of a plurality of lamps, as long as it is advantageous to illuminate the exhibit. Each light has a ceiling; Around the exhibits; It can be located in a suitable location to illuminate exhibits such as the floor.

The device 101 may turn off or turn on all or some lights according to needs and purposes, or control the illuminance of each light. A method of controlling the lighting of the exhibition hall through the device 101 will be described later with reference to FIG. 12.

The detection means 1110 may detect in real time the floor area of the exhibition rental space and the number of visitors within the floor area. The detection means 1110 includes a general camera; Thermal imaging camera; It may be a pressure to a weight sensor, or a combination including at least one of them. As long as the sensing means 1110 can detect in real time the floor area of the exhibition rental space and the number of visitors in the floor area, there is no limitation on its type and characteristics. The sensing means 1110 may be fixed in real time to detect the floor area of a specific space in which an exhibition rental can be viewed. One or more sensing means 1110 may be disposed in the exhibition hall depending on the size of the exhibition hall and the relationship between the exhibition locations of the exhibition objects 200.

The device 101 may turn off or turn on all or some lights or control the illuminance of each light when it is sensed that the viewers are gathered over a predetermined threshold in a specific area through the sensing means 1110. A method of controlling exhibition hall lighting through the device 101 will be described later with reference to FIG. 12.

12 is a flowchart illustrating a method for controlling lighting in an exhibition hall according to an embodiment.

First, as described above with reference to FIGS. 3 and 6, the device 101 sets the number of intersection areas exceeding a preset area value among intersection areas where the popularitys of the exhibition rentals 220 where the exhibition location is determined overlap each other. The number of exhibition productions may be determined, and the exhibition location of exhibition productions may be determined to include one exhibition production for each intersection area exceeding a preset area value. The preset area value may be, for example, 1 m ² .

For example, the small square intersection area where the popularity 611 of the galpan and the reed stone overlaps with the popularity 612 of the comb-patterned earthenware may exceed a preset area value. In addition, the popularity of the bandaldol knife (613); The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And a large non-square intersection area where the popularity 615 of the groove is overlapped with each other may also exceed a preset area value. In this case, the device 101 may determine the number of exhibition products to be produced in two. In addition, the device 101 includes a small square intersection area and a popularity 613 of a half-moon stone knife in which the popularity 611 of the brown plate and the stone and the popularity 612 of the comb-shaped earthenware overlap each other; The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And the display location of the exhibition productions so that one of the exhibition productions is included in a large non-square intersection area where the popularity 615 of the home hat overlaps with each other. Through this, a small square intersecting area where the popularity 611 of galpans and galdols and the popularity 612 of comb-shaped earthenware overlap with each other includes a farmhouse model 221 as an exhibition product, and a popularity 613 of a vandal stone knife; The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And the number and location of the exhibition productions so that the sarcophagus diorama 222, which is an exhibition production, is included in a large non-square intersection area where the popularity 615 of the home hat overlaps with each other.

Hereinafter, a method of controlling the lighting of the exhibition hall by the device 101 will be described in earnest. The apparatus 10 for determining the exhibition location of the exhibits 200 and the apparatus 101 for controlling the lighting of the exhibition hall may be the same or may be individual.

The device 101 may designate a corresponding relationship between at least one exhibition rental and a selected exhibition production, which is a basis for setting the display location of the selected exhibition production, by pointing each exhibition production in a predetermined order (1210) . The predetermined order may be an order in which the exhibition productions are arranged along the movement line of the exhibition hall. Alternatively, the predetermined order may be an order in which the volume or price of exhibits is large or small. In addition, various predetermined sequences can be determined, and there are no restrictions on the rules of the predetermined sequence as long as each exhibition product can be classified and pointed out.

For example, referring to FIG. 6, a farmhouse model 221 and a sarcophagus diorama 222, which are exhibition products 220, may be displayed along the copper line of the exhibition hall. The apparatus 101 first points to the farmhouse model 221, and the galvans and galls 211 and the comb-shaped earthenware 212, which are the exhibition rentals 210, which are the basis for setting the display location of the farmhouse model 221, Correspondence relations between the farmhouse models 221 may be established. In the following order, the device 101 points to the sarcophagus grave diorama 222, the vandal stone sword 213, which is an exhibition rental 210 based on setting the exhibition location of the sarcophagus grave diorama 222; Pyeongtaek Tojinri ruins sarcophagus (214); And a corresponding relationship between the home hat 215 and the sarcophagus diorama 222.

Subsequently, the device 101 may detect whether or not visitors are gathered above a predetermined threshold in an area corresponding to the popularity of at least one exhibition rental having a corresponding relationship with the indicated exhibition production (1220). The popularity of the exhibition rental can be determined by the method described above with reference to FIG. 7. The predetermined threshold may be, for example, 2 persons/m ² , which is the reference density described with reference to FIG. 7.

For example, referring to FIGS. 6 and 11, the device 101 includes a half moon stone knife 213 having a corresponding relationship with the indicated sarcophagus diorama 222; Pyeongtaek Tojinri ruins sarcophagus (214); And the popularity 613 of the vandal stone knife, which is the popularity of the home hat 215. The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And it is possible to detect through the detection means whether or not the audience gathered in the area corresponding to the popularity 615 of the home hatch over a predetermined threshold of 2 people/m ² .

Next, the device 101 turns on the light illuminating the selected exhibition production when it is detected that the viewers are gathered above the threshold in an area corresponding to the popularity of at least one exhibition rental having a corresponding relationship with the indicated exhibition production. Can (1230).

For example, referring to FIGS. 6 and 11, the device 101 includes a half moon stone knife 213 having a corresponding relationship with the indicated sarcophagus diorama 222; Pyeongtaek Tojinri ruins sarcophagus (214); And the popularity 613 of the vandal stone knife, which is the popularity of the home hat 215. Pyeongtaek Tojinri Ruins Popularity of the sarcophagus (614); And if it is detected that the visitors gathered in more than 2 people / m ² in the area corresponding to the popularity (615) of the home hat, the lighting for the sarcophagus diorama 1120 can be turned on.

As such, half moon stone knife (213); Pyeongtaek Tojinri ruins sarcophagus (214); And when the viewers gather around the home hat 215 at a predetermined threshold value, for example, more than 2 people/m ² , by turning on the lighting 1120 for the sarcophagus diorama that was turned off, the sarcophagus diorama 222 pays attention to the spectators It becomes easy to receive. Through this, visitors who were gathered to view the exhibition rentals are distributed to view the exhibition productions, and accordingly, a phenomenon in which a large number of visitors are attracted to a specific part is reduced, so that a smooth exhibition can be achieved.

Or, if the device 101 is detected that the viewers are gathered above the threshold in an area corresponding to the popularity of at least one exhibition rental having a corresponding relationship with the indicated exhibition production, is the lighting illuminating the indicated exhibition production turned on? If it is determined, and the lighting illuminating the pointed exhibit is turned on, the illuminance of the light illuminating the pointed exhibit can be increased.

For example, referring to FIGS. 6 and 11, the device 101 includes a half moon stone knife 213 having a corresponding relationship with the indicated sarcophagus diorama 222; Pyeongtaek Tojinri ruins sarcophagus (214); And the popularity 613 of the vandal stone knife, which is the popularity of the home hat 215. The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And if the visitor is detected to gather more than 2 people/m ² in an area corresponding to the popularity 615 of the home hat, it is determined whether the lighting for the sarcophagus diorama 1120 is turned on, and the lighting for the sarcophagus diorama 1120 is If it is already on, the illumination of the sarcophagus diorama lighting 1120 can be increased.

As such, half moon stone knife (213); Pyeongtaek Tojinri ruins sarcophagus (214); And when the viewers gather around the home hat 215 at a predetermined threshold value, for example, more than 2 people/m ² , by increasing the illuminance of the lighting 1120 for the sarcophagus grave, the sarcophagus grave diorama 222 pays attention to the visitors. It is easier to receive. Through this, visitors who were gathered to view the exhibition rentals are distributed to view the exhibition productions, and accordingly, the phenomenon of attracting many visitors to a specific part is reduced, so that a smooth exhibition can be achieved.

Alternatively, if the device 101 is detected that the viewers are gathered above the threshold in an area corresponding to the popularity of at least one exhibition rental having a corresponding relationship with the indicated exhibition production, is the lighting illuminating the indicated exhibition production turned on? If it is determined, and the lighting that illuminates the indicated exhibition production is turned on, the illuminance of the illumination that illuminates at least one exhibition rental having a corresponding relationship with the indicated exhibition production can be lowered.

For example, referring to FIGS. 6 and 11, the device 101 includes a half moon stone knife 213 having a corresponding relationship with the indicated sarcophagus diorama 222; Pyeongtaek Tojinri ruins sarcophagus (214); And the popularity 613 of the vandal stone knife, which is the popularity of the home hat 215. The popularity of the sarcophagus in the Tojinri ruins of Pyeongtaek (614); And if the visitor is detected to have gathered more than 2 people/m ² in an area corresponding to the popularity 615 of the home hat, it is determined whether the lighting for the sarcophagus diorama 1120 is turned on, and the lighting for the sarcophagus diorama 1120 is If it is already on, half moon stone knife 1123; Pyeongtaek Tojinri Ruins Lighting for sarcophagus (1124); And it is possible to lower the illuminance of the lighting 1125 for the home hat.

As such, half moon stone knife (213); Pyeongtaek Tojinri ruins sarcophagus (214); And when the audience gathers around the home hat 215 with a predetermined threshold value, for example, more than 2 people/m ² , lighting for a vandal stone knife 1123; Pyeongtaek Tojinri Ruins Lighting for sarcophagus (1124); And by lowering the illuminance of the lighting 1125 for the home hat, the sarcophagus grave diorama 222 is in an easier state to get attention from the audience. Through this, visitors who were gathered to view the exhibition rentals are distributed to view the exhibition productions, and accordingly, the phenomenon of attracting many visitors to a specific part is reduced, so that a smooth exhibition can be achieved.

Or, if the device 101 is detected that the viewers are gathered above the threshold in an area corresponding to the popularity of at least one exhibition rental having a corresponding relationship with the indicated exhibition production, is the lighting illuminating the indicated exhibition production turned on? If the lighting that illuminates the selected exhibit is turned on, the illuminance of the illumination that illuminates the indicated exhibit is increased, and the illuminance of the illumination that illuminates at least one exhibit rental having a corresponding relationship with the indicated exhibit is reduced. have. Through this, for the same reason as described above, visitors who were gathered to view exhibition rentals are distributed to view the exhibition productions, and accordingly, a phenomenon in which a large number of visitors are attracted to a specific portion is reduced, so that a smooth exhibition can be achieved.

The embodiments described above may be implemented as hardware components, software components, and/or combinations of hardware components and software components. For example, the devices, methods, and components described in the embodiments include, for example, processors, controllers, arithmetic logic units (ALUs), digital signal processors (micro signal processors), microcomputers, and field programmable gates (FPGAs). It can be implemented using one or more general purpose computers or special purpose computers, such as arrays, programmable logic units (PLUs), microprocessors, or any other device capable of executing and responding to instructions. The processing device may run an operating system (OS) and one or more software applications running on the operating system. In addition, the processing device may access, store, manipulate, process, and generate data in response to the execution of the software. For convenience of understanding, a processing device may be described as one being used, but a person having ordinary skill in the art, the processing device may include a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include. For example, the processing device may include a plurality of processors or a processor and a controller. In addition, other processing configurations, such as parallel processors, are possible.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, or the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiments or may be known and usable by those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs, DVDs, and magnetic media such as floptical disks. Includes hardware devices specifically configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language code that can be executed by a computer using an interpreter, etc., as well as machine language codes produced by a compiler. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The software may include a computer program, code, instruction, or a combination of one or more of these, and configure the processing device to operate as desired, or process independently or collectively You can command the device. Software and/or data may be interpreted by a processing device, or to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. , Or may be permanently or temporarily embodied in the transmitted signal wave. The software may be distributed over networked computer systems, and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

As described above, although the embodiments have been described with limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order than the described method, and/or the components of the described system, structure, device, circuit, etc. are combined or combined in a different form from the described method, or other components Alternatively, even if substituted or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (5)

Exhibit rentals rented for exhibitions held in the exhibition hall-each exhibit rental has a popularity expressed in area according to a preset method-and
Exhibits produced for the exhibition held at the exhibition hall
In order to exhibit in the exhibition hall,
Obtaining a plan view of the exhibition hall and copper wire data of the exhibition hall;
Determining the exhibition location of the exhibition rentals based on the output of the artificial neural network by applying the top view, the movement data, and the popularity of each exhibition rental to an artificial neural network; And
Determining the number and location of exhibits based on the location of the exhibit rentals.
It includes,
The floor plan includes an entrance and an exit of the exhibition hall,
The copper wire data includes a start point and an end point,
The starting point of the moving line data coincides with the entrance of the exhibition hall,
The end point of the copper wire data coincides with the exit of the exhibition hall,
The exhibition location of the exhibition rentals, while minimizing the total number of intersection areas where the popularitys of the exhibition rentals overlap each other, exhibit rentals classified as high in popularity according to a preset classification, end points at the starting point of the moving data. According to the output of the artificial neural network learned according to reinforcement learning, so as to be positioned at a constant cycle,
The exhibition location of the exhibition productions is determined to include one exhibition production for each intersection area exceeding a preset area value among intersection areas where the popularity of the exhibition rentals overlap each other,
The number of exhibition productions is determined by the number of intersection areas exceeding the preset area value, among intersection areas where the popularity of exhibition rentals for which an exhibition location is determined overlap each other.
After setting the exhibition rentals and the exhibition locations of the exhibition productions as a method of setting the exhibition location,
In the method of controlling the lighting of the exhibition hall,
Establishing a corresponding relationship between the at least one exhibition rental and the named exhibition production, which are based on setting the display location of the selected exhibition production by specifying each exhibition production in a predetermined order;
Detecting through a means for detecting whether or not visitors are gathered above a predetermined threshold in an area corresponding to the popularity of the at least one exhibition rental having a corresponding relationship with the indicated exhibition production;
When it is sensed that the audiences are gathered above the threshold, turning on the light illuminating the pointed exhibition production.
Containing
How to control exhibition hall lighting.
According to claim 1,
The popularity of exhibit rentals is
i) acquiring the number of visitors in the measurement area and the measurement area measured for a predetermined number of times or a predetermined time through a measuring means capable of measuring the floor area and the number of visitors in the floor space of the exhibition rental space being exhibited. ;
ii) determining the number of spectators within the measurement area per unit number or unit time as the spectator density of exhibition rentals;
iii) determining whether the visitor density of the exhibition rental and a predetermined reference density are within a predetermined error range;
iv) repeating the steps of i) to iii) after adjusting the floor area measured by the measuring means when the density of the visitors of the exhibition rental and the reference density are out of the error range;
v) determining the measured area as the popularity of the exhibition rental when the density of the visitors of the exhibition rental and the reference density are within the error range.
Determined in a way that includes,
How to control exhibition hall lighting.
According to claim 2,
If it is sensed that the spectators are gathered above a threshold value, determining whether the light illuminating the pointed exhibit is turned on; And
Increasing the illuminance of the lighting, if the lighting illuminating the indicated exhibit is turned on
Containing more
How to control exhibition hall lighting.
According to claim 2,
If it is sensed that the spectators are gathered above a threshold, determining whether the lighting illuminating the pointed exhibition production is turned on; And
Lowering the illuminance of light illuminating at least one or more exhibition rentals having the corresponding relationship with the indicated exhibition production, when lighting illuminating the indicated exhibition production is turned on,
How to control exhibition hall lighting.
The method of claim 3,
Lowering the illuminance of light illuminating at least one or more exhibition rentals having the corresponding relationship with the indicated exhibition production, when lighting illuminating the indicated exhibition production is turned on,
How to control exhibition hall lighting.

Images