A lighting control method and system for exhibition hall design

Abstract

The present invention discloses a lighting control method and system for exhibition hall design, including obtaining historical exhibition data of the exhibition hall within a preset time period, analyzing the historical exposure rate of each exhibit, and obtaining the historical position information of the display cabinet where each exhibit is located; inputting the historical exposure rate and position information into the target traffic density prediction model, outputting the expected traffic density within the preset range of each display cabinet in this exhibition, so as to determine the initial lighting plan of this exhibition; monitoring the real-time traffic density of each display cabinet, and adaptively adjusting the initial lighting plan; analyzing the display cabinet congestion rate and exhibit exposure rate in this exhibition, adjusting the historical placement of the display cabinet, and optimizing the initial lighting control plan of the next exhibition. The present invention can provide scientific guidance for the planning plan of the current exhibition with reference to the historical exhibition data, and optimize the placement of exhibits, which can not only meet the viewing needs of the audience, but also reduce energy consumption and achieve energy-saving and environmentally friendly lighting effects.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting control, and in particular to a lighting control method and system for exhibition hall design. Background Art

[0002] Lighting control in exhibition hall design is an important means to create atmosphere, highlight exhibits and guide the audience's sight. With the development of technology, lighting control systems have evolved from traditional manual switches to intelligent and automated stages. These systems usually combine lighting equipment, sensors, microprocessors and network communication technology to achieve multi-dimensional control of light intensity, color and direction.

[0003] At present, the lighting control of exhibition halls usually only represents the subjective will of designers in the initial planning. For example, if you want to highlight a certain exhibit, you will control its light differently from other exhibits. However, this planning and design method ignores objective factors, lacks linkage with the audience's viewing intention, and lacks linkage between exhibition data of different exhibition sessions, which makes the lighting control plan unreasonable, increases lighting costs, and fails to meet the audience's viewing needs. Summary of the invention

[0004] In order to solve at least one of the above-mentioned technical problems, the present invention provides a lighting control method and system for exhibition hall design.

[0005] In a first aspect, the present invention provides a lighting control method for exhibition hall design, the method comprising:

[0006] Obtain the historical exhibition data of the exhibition hall within a preset period of time, analyze the historical exposure rate of each exhibit based on the historical exhibition data, and obtain the historical location information of the display cabinet where each exhibit is located;

[0007] Input the historical exposure rate and the historical location information of the showcase into the target traffic density prediction model, output the expected traffic density within the preset range of each showcase in this exhibition, and determine the initial lighting control plan for this exhibition based on the expected traffic density;

[0008] Monitor the real-time traffic density of each showcase within a preset range, and adaptively adjust the initial lighting control plan according to the real-time traffic density;

[0009] Obtain the data of this exhibition and analyze the display cabinet congestion rate and exhibit exposure rate in this exhibition; adjust the historical placement of the display cabinets according to the display cabinet congestion rate and exhibit exposure rate in this exhibition, and optimize the initial lighting control plan for the next exhibition.

[0010] Preferably, before acquiring the historical location information of the display cabinet where each exhibit is located, the method further includes:

[0011] Based on the booth information and the display cabinet information, a first matching relationship between the display cabinet and the booth is established according to the exhibition planning scheme;

[0012] Determine the aisle width between the showcases according to the first matching relationship, select a first target showcase whose aisle width is less than a first preset threshold, re-plan the booth for the first target showcase to update the first matching relationship, and generate a second matching relationship;

[0013] Based on the second matching relationship, the congestion rate of the showcase within the preset range is calculated, a second target showcase having a congestion rate greater than a second preset threshold is screened out, and a booth is replanned for the second target showcase to update the second matching relationship, thereby generating a third matching relationship;

[0014] Each display cabinet is placed on a corresponding booth according to the third matching relationship.

[0015] Preferably, the calculating the congestion rate of the showcase within a preset range includes:

[0016]

[0017] In the formula, C R represents the congestion rate, m represents the number of people staying within the preset time range, S y It indicates the space area within the preset range of the showcase, S n It represents the inaccessible area within the preset range of the showcase, L represents the safe distance between people, and k represents the adjustment factor, satisfying k>1.

[0018] Preferably, before inputting the historical exposure rate and the historical location information of the showcase into the target traffic density prediction model, the method further includes:

[0019] Establish an initial crowd density prediction model:

[0020]

[0021] In the formula, E f represents the density of human traffic, H i represents the historical exposure rate of the i-th showcase, P i represents the grade score of the i-th showcase, D i represents the distance from the ith showcase to the entrance, δ represents the decay rate factor, and α, β, and γ represent weight factors;

[0022] Collect historical exhibition data, including the historical exposure rate of exhibits in each showcase, location information and the corresponding actual traffic density; clean, encode and convert the collected data to obtain a training set;

[0023] The parameters α, β, γ, and δ of the initial pedestrian flow density prediction model are fitted using the training set. After fitting, the prediction accuracy of the model is evaluated using the evaluation index. When the prediction accuracy does not meet the preset conditions, the parameters are adjusted until the prediction accuracy meets the preset conditions, and the target values ​​of the trained parameters α, β, γ, and δ are obtained.

[0024] Substitute the target values ​​of parameters α, β, γ, and δ into the initial pedestrian flow density prediction model to generate a target pedestrian flow density prediction model.

[0025] Preferably, the mean square error is used as an evaluation indicator to evaluate the prediction accuracy of the model.

[0026] Preferably, the method of adaptively adjusting the initial lighting control scheme according to the real-time crowd density includes:

[0027] Collect real-time video images to identify the real-time density of human traffic and vision data within a preset range of each showcase; the vision data is the ratio of the number of people wearing glasses to the total number of people;

[0028] Input the real-time traffic density and vision conditions into the preset lighting control compensation model, and output the compensated color temperature and compensated illumination;

[0029] Adaptively adjust the initial lighting control scheme according to the compensated color temperature and compensated illumination.

[0030] In a second aspect, the present invention further provides a lighting control system for exhibition hall design, the system comprising:

[0031] A data acquisition unit is used to acquire the historical exhibition data of the exhibition hall within a preset period of time, analyze the historical exposure rate of each exhibit based on the historical exhibition data, and acquire the historical location information of the display cabinet where each exhibit is located;

[0032] An initial scheme determination unit is used to input the historical exposure rate and the historical position information of the showcase into the target crowd density prediction model, output the expected crowd density within the preset range of each showcase in this exhibition, and determine the initial lighting control scheme of this exhibition according to the expected crowd density;

[0033] The adaptive adjustment unit is used to monitor the real-time density of human traffic in each showcase within a preset range, and adaptively adjust the initial lighting control plan according to the real-time density of human traffic;

[0034] The initial plan optimization unit is used to obtain the data of this exhibition, analyze the display cabinet congestion rate and exhibit exposure rate in this exhibition; adjust the historical placement of the display cabinet according to the display cabinet congestion rate and exhibit exposure rate in this exhibition, and optimize the initial lighting control plan for the next exhibition.

[0035] In a third aspect, the present invention further provides an electronic device comprising a processor and a memory, wherein the memory is used to store computer program code, and the computer program code comprises computer instructions. When the processor executes the computer instructions, the electronic device executes the method as described in the first aspect above and any possible implementation thereof.

[0036] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, wherein the computer program includes program instructions, and when the program instructions are executed by a processor of an electronic device, the processor executes the method as described in the first aspect above and any possible implementation thereof.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1) The present invention first obtains the historical exhibition data of the exhibition hall within a preset time period, analyzes the historical exposure rate of each exhibit based on the historical exhibition data, and obtains the historical location information of the display cabinet where each exhibit is located; the historical exposure rate and the historical location information of the display cabinet are input into the target traffic density prediction model, and the expected traffic density within the preset range of each display cabinet in this exhibition is output, and the initial lighting control plan for this exhibition is determined according to the expected traffic density. When designing the initial lighting control plan for the exhibition hall before the audience enters, the present invention analyzes the exposure rate and location information of the exhibits in the historical exhibition data, so as to first estimate the expected traffic density within the preset range of each display cabinet, thereby providing a scientific basis for planning the initial lighting plan. Compared with the subjective intention of the designer, this method can better meet the viewing needs of the audience.

[0039] 2) When the initial lighting control scheme is adopted to perform lighting control first, the present invention will also monitor the real-time traffic density of each display cabinet within a preset range, and adaptively adjust the initial lighting control scheme according to the real-time traffic density. For example, in places with many people, the illumination will be increased and the color temperature will be adjusted with reference to the vision of the people, while in places with few people, the lights can be adjusted to energy-saving mode for energy-saving and environmental protection. Therefore, the present invention takes into account the actual distribution of people on the basis of the initial scheme, and adaptively adjusts the lighting. This can not only improve the utilization rate of lighting resources and reduce lighting costs, but also achieve energy saving and environmental protection, and make the lighting more in line with the actual situation, thereby improving the audience's viewing experience.

[0040] 3) After the exhibition is over, the present invention will also obtain the exhibition data, analyze the display cabinet congestion rate and exhibit exposure rate in this exhibition; adjust the historical placement of the display cabinet according to the display cabinet congestion rate and exhibit exposure rate in this exhibition, and optimize the initial lighting control plan for the next exhibition. The present invention analyzes the unreasonable placement of exhibits in this exhibition according to the display cabinet congestion rate and exhibit exposure rate by analyzing the current exhibition data, thereby optimizing the initial lighting control plan for the next exhibition, including the optimization of booth placement and lighting control. It can not only improve the space utilization rate of the exhibition hall and further ensure the rationality of lighting control, but also reduce the safety hazards caused by overcrowding of spectators around the display cabinets, and improve the management efficiency of the exhibition hall security work.

[0041] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0043] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0044] Figure 1 A flowchart of a lighting control method for exhibition hall design provided by an embodiment of the present invention;

[0045] Figure 2 A schematic diagram of the structure of a lighting control system for exhibition hall design provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0048] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0049] In addition, in order to better illustrate the present invention, numerous specific details are provided in the following specific embodiments. It should be understood by those skilled in the art that the present invention can be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present invention.

[0050] Most of the current exhibition hall lighting control planning schemes rely on the subjective will of designers, lack linkage with the audience's viewing intention, and lack sharing and linkage analysis between data of different exhibition sessions, which makes the lighting control scheme unreasonable and unable to meet the audience's viewing needs, and the lighting cost and energy saving and environmental protection efficiency need to be improved. To this end, the present invention provides a lighting control method for exhibition hall design, which can refer to historical exhibition data to provide scientific guidance for the planning scheme of the current exhibition, and adjust the placement of exhibits according to the exhibition data after the current exhibition ends, and optimize the next initial lighting control scheme, which can not only meet the audience's viewing needs, but also reduce energy consumption, improve the utilization rate of lighting resources, and achieve energy saving and environmental protection effects.

[0051] See also Figure 1 , Figure 1 The following is a flow chart of a lighting control method for exhibition hall design provided by an embodiment of the present invention. Figure 1 As shown, the lighting control method includes:

[0052] S10, obtaining historical exhibition data of the exhibition hall within a preset period of time, analyzing the historical exposure rate of each exhibit based on the historical exhibition data, and obtaining historical location information of the display cabinet where each exhibit is located;

[0053] S20, inputting the historical exposure rate and the historical position information of the showcase into the target crowd density prediction model, outputting the expected crowd density within the preset range of each showcase in this exhibition, and determining the initial lighting control plan for this exhibition according to the expected crowd density;

[0054] S30, monitoring the real-time density of human traffic in each display cabinet within a preset range, and adaptively adjusting the initial lighting control scheme according to the real-time density of human traffic;

[0055] S40, obtaining data of this exhibition, analyzing the display cabinet congestion rate and the exhibit exposure rate in this exhibition; adjusting the historical placement position of the display cabinet according to the display cabinet congestion rate and the exhibit exposure rate in this exhibition, and optimizing the initial lighting control plan for the next exhibition.

[0056] Historical exhibition data usually includes the following:

[0057] Visitor flow and behavior patterns: It can provide valuable information about visitor flow trends, peak hours, average visitor duration and visitor flow routes. This data helps predict and plan the flow management, safety measures and guidance system of this exhibition.

[0058] Popularity of exhibits: Which types of exhibits or display methods were most popular in previous exhibitions can be used as a reference for the planning and layout of this exhibition content.

[0059] Sales and transaction data: For commercial exhibitions, analysis of past exhibition sales, transaction rates and visitor purchasing behavior is crucial for predicting sales potential, pricing strategies and promotional activity design. Recent data can more accurately reflect market conditions.

[0060] Feedback and evaluation: Instant feedback from past visitors and subsequent satisfaction surveys can reveal the strengths and weaknesses of services, facilities, and exhibition content.

[0061] The historical exhibition data within the preset time period is usually the historical exhibition data within one year from the current exhibition. For example, the historical data of the same quarter or the historical data of the same month can be selected as a reference.

[0062] The calculation of historical exposure rate usually involves the analysis of past exhibition data to assess the extent to which each exhibit was noticed by the audience. If referring to some common standards, exposure can be defined as at least 50% of the content of the advertisement or exhibit is in the audience's visual area for at least 1 second. However, in a physical exhibition hall environment, it is difficult to directly measure the audience's sight line, so some alternative indicators are usually used to evaluate exposure rate, such as estimated pass-by frequency, time spent in front of the exhibit, etc.

[0063] Specifically, when calculating the historical exposure rate in step S10, the total number of visitors during the exhibition, the estimated flow or actual count of each exhibit location (through entrance / exit counters, heat map analysis, etc.), the average time the audience stays in front of the exhibits, or the number and duration of views indirectly estimated by technologies such as cameras, the layout of the exhibition area, and the relative position of each exhibit (which may affect the distribution of natural flow) can be collected based on historical exhibition data. After the data is collected, for each exhibit, based on the flow and audience behavior data at its location, estimate how many people actually "saw" the exhibit to obtain the actual exposure. Further, determine the theoretical maximum number of exposures for all visitors to "ideally" come into contact with each exhibit, and obtain the total exposure opportunity. Finally, calculate the exposure rate according to the following formula: Exposure rate = (actual exposure / total exposure opportunities) × 100%.

[0064] Usually, the density of human traffic is related to both location information and exposure rate. Location information affects the distribution of natural traffic. For example, without considering the influence of audience viewing preferences, the flow of people in wide aisles is usually greater than that in narrow aisles. The exposure rate reflects audience preferences. The flow of people around the showcases with more popular exhibits is usually greater than the flow of people around unpopular showcases. Therefore, step S20 mainly obtains the expected flow density based on these two parameters, wherein the target flow density prediction model is usually trained in advance. When predicting, it is only necessary to input the historical exposure rate and the historical location information of the showcase into the target flow density prediction model, and the expected flow density within the preset range of each showcase in this exhibition can be quickly output. Then, the initial lighting control scheme of this exhibition is determined according to the expected flow density; for example, a brighter lighting environment can be provided for some showcases with a large expected flow of people, while for showcases with less flow of people, the light can be darker, or even enter the energy-saving mode first.

[0065] Therefore, when designing the initial lighting control plan for the exhibition hall before the audience enters, this embodiment analyzes the exposure rate and location information of the exhibits in the historical exhibition data, so as to first estimate the expected traffic density within the preset range of each showcase, thereby providing a scientific basis for planning the initial lighting plan. Compared with the subjective intention of the designer, this method can better meet the viewing needs of the audience. In addition, providing different lighting for different traffic distributions according to the expected traffic density can also reduce energy consumption and further improve the utilization rate of lighting resources.

[0066] The initial plan is an effective plan before the exhibition begins. After the exhibition begins, as the number of visitors enter and the number of people increases, the real-time density of people flow in each showcase within a preset range is monitored in step S30, and the initial lighting control plan is adaptively adjusted according to the real-time density of people flow, which may include the following aspects:

[0067] Dynamic adjustment strategy: Use dimmable lamps and intelligent control systems, such as those based on the Internet of Things, to adjust lighting intensity in real time according to actual traffic flow. During peak traffic periods, increase lighting brightness to ensure overall brightness and safety of the exhibition area while avoiding visual blind spots in crowded areas. When traffic is low, reduce brightness appropriately to save energy.

[0068] Focus lighting design: For areas with high traffic volume (such as entrances, near popular exhibits, rest areas, etc.), focus lighting design is used to enhance the light intensity and visual appeal of these areas. For areas with low traffic volume, basic lighting is used to maintain moderate brightness.

[0069] Sensor control: Infrared or radar sensors are installed in front of specific channels or exhibits. When they sense the approach of visitors, local lighting is automatically increased, which not only improves the interactive experience but also effectively saves energy.

[0070] Preset scene modes: Preset different lighting scene modes based on the peak and trough periods of visitor traffic predicted by historical data and exhibition arrangements. For example, a soft welcome mode is used when the museum opens in the morning, an efficient display mode is switched to during the day when the crowds are dense, and a warm low-light mode is switched to at night or before closing.

[0071] Balance between safety and comfort: Ensure that all areas, especially key locations such as stairs and emergency exits, are adequately lit and not affected by the flow of people, always maintaining safety standards. At the same time, by adjusting the color temperature and brightness, create a comfortable exhibition environment and reduce visitors' visual fatigue.

[0072] Therefore, this embodiment takes into account the actual distribution of personnel on the basis of the initial plan, and adaptively adjusts the lighting. This not only reduces the lighting cost, but also makes the lighting more in line with the actual situation, provides a high-quality exhibition experience, realizes effective energy management, and achieves energy-saving and environmental protection effects.

[0073] When designing the initial display cabinet positions, popular exhibits may be placed in a relatively narrow viewing area, which will cause congestion around such display cabinets during actual viewing, thus posing a greater safety hazard. Therefore, in step S40, the display cabinet congestion rate and exhibit exposure rate in this exhibition will also be analyzed; the historical placement of the display cabinets will be adjusted according to the display cabinet congestion rate and exhibit exposure rate in this exhibition. By replanning and adjusting the display cabinet booths, the probability of safety accidents caused by this congestion can be reduced. After the placement of the display cabinet is adjusted, since the display position of the display cabinet and the exhibits has changed, the initial lighting control plan also needs to be further optimized to ensure that the lighting control can adapt to changes in the exhibit position.

[0074] In summary, this embodiment analyzes the problem of unreasonable placement of exhibits in this exhibition according to the display cabinet congestion rate and the exhibit exposure rate by analyzing the current exhibition data, so as to optimize the initial lighting control plan for the next exhibition, including the optimization of booth placement and the optimization of lighting control. It can not only improve the space utilization rate of the exhibition hall and further ensure the rationality of lighting control, but also reduce the safety hazards caused by excessive crowding of spectators around the display cabinets, and improve the management efficiency of the security work in the exhibition hall.

[0075] In one embodiment, before acquiring the historical position information of the display cabinet where each exhibit is located, the method further includes:

[0076] 1) Based on the booth information and the display cabinet information, a first matching relationship between the display cabinet and the booth is established according to the exhibition planning scheme.

[0077] First, booths need to be classified, including by location (such as entrance, central area, corner), size, and theme (such as history and culture, technological innovation, art appreciation, etc.). Then, showcase evaluation is conducted based on the size, structure (open, closed, hanging, etc.), and display requirements (whether special lighting, temperature and humidity control, etc.) of the showcases. When establishing a matching relationship, the following points should be considered:

[0078] Theme consistency: Ensure that the exhibits in the display cabinets are consistent with the theme of the booth to enhance the overall coherence and logic of the exhibition.

[0079] Spatial adaptability: The size of the display cabinet must be suitable for the booth space. It should not be too large to waste space, nor too small to appear cramped, while leaving enough space for audience circulation.

[0080] Crowd flow guidance: Use important or attractive display cabinets to guide the flow of people, such as placing featured exhibits in booths with large traffic, or setting up highlight display cabinets at the turning points of the path to attract attention.

[0081] Security arrangement: For precious or fragile exhibits, priority should be given to booths with good surveillance vision and relatively controllable traffic flow, and appropriate security measures should be provided.

[0082] 2) Determine the aisle width between the showcases according to the first matching relationship, select a first target showcase whose aisle width is less than a first preset threshold, re-plan the booth for the first target showcase to update the first matching relationship, and generate a second matching relationship.

[0083] The rationality of the aisle width design can affect the natural flow distribution and improve the safety of the viewing process. Generally speaking, the width of the main aisle of the exhibition hall should not be less than 3 meters to ensure that people can be evacuated quickly in an emergency. The width of the secondary aisle should be at least 1.4 meters, and in some cases, such as venues over 10,000 square meters, the width of the aisle should not be less than 2.4 meters. In addition, all buildings should have a fire passage of not less than 3.5 meters to meet the needs of fire trucks. In some cases, the width of the aisle can also be determined based on the expected passenger flow. The main aisle should allow 8 to 10 people to pass through at the same time, which is equivalent to a width of 4.8 to 6 meters; the secondary aisle should ensure the passage of 2 to 4 people, that is, a width of about 2.4 to 3.6 meters.

[0084] When calculating the aisle width, the length of the edge connection line of each display cabinet can be identified, and the ratio of the length of the connection line to the number of aisles it connects can be calculated. Then, the minimum value can be identified from multiple ratios to calculate the average aisle width. When the average aisle width is greater than or equal to the first preset threshold, it means that the aisle widths of other display cabinets can meet the requirements. On the contrary, if the average aisle width is less than the first preset threshold, it means that the aisle width between the corresponding display cabinets is too narrow and the display cabinets need to be replanned. Therefore, the identified display cabinets can be marked, and then all display cabinets that need to be replanned can be identified in the same way to obtain the first target display cabinet. After replanning the display cabinet for the first target display cabinet to update the first matching relationship, the optimized second matching relationship can be generated.

[0085] 3) Based on the second matching relationship, the congestion rate of the showcase within the preset range is calculated, a second target showcase having a congestion rate greater than a second preset threshold is selected, and booths are replanned for the second target showcase to update the second matching relationship and generate a third matching relationship.

[0086] The second matching relationship is mainly the natural aisle distribution without considering the audience's viewing preferences. First, the basic aisle width should be guaranteed when the popularity of each exhibit is the same. However, in actual exhibitions, due to the different popularity of exhibits, there may still be a high probability of congestion around such showcases under the second matching relationship. In order to solve this problem, this step will screen out the second target showcase with a congestion rate greater than the second preset threshold, re-plan the booth for the second target showcase to update the second matching relationship, and generate a third matching relationship. The third matching relationship can not only meet the basic aisle width requirements, but also perform targeted aisle expansion processing for showcases with high popularity and high exposure, thereby reducing the probability of congestion events.

[0087] In one embodiment, the calculating the congestion rate of the showcase within a preset range includes:

[0088]

[0089] In the formula, C R represents the congestion rate, m represents the number of people staying within the preset time range, S y It indicates the space area within the preset range of the showcase, S n It represents the inaccessible area within the preset range of the showcase, L represents the safe distance between people, and k represents the adjustment factor, satisfying k>1.

[0090] In the above formula, Reflecting the actual population density, the number of people staying can be estimated based on the length of stay, for example, the number of people staying in the same period of time can be estimated by the average length of stay and the total flow of people; It reflects the safe personnel density, which depends on the safe distance between personnel and can be set according to industry safety standards. For example, it is recommended not to exceed 4 people per square meter. k is a coefficient greater than 1, reflecting the gap between the maximum comfort boundary and the safety boundary.

[0091] 4) Placing each display cabinet on a corresponding booth according to the third matching relationship.

[0092] In summary, this embodiment has made multiple adjustments and optimizations to the matching relationship between the display cabinets and the booths by taking into account the basic safety aisle width of the display cabinets and the influence of the audience's viewing preferences, thereby ensuring that the display cabinets can be reasonably placed on the corresponding booths, that is, the display cabinets are arranged scientifically, which can meet the audience's viewing preferences and enhance the audience's viewing experience, while also improving safety during the exhibition.

[0093] In one embodiment, before inputting the historical exposure rate and the historical location information of the showcase into the target traffic density prediction model, the method further includes:

[0094] Establish an initial crowd density prediction model:

[0095]

[0096] In the formula, E f represents the density of human traffic, H i represents the historical exposure rate of the i-th showcase, P i represents the grade score of the i-th showcase, D i represents the distance from the ith showcase to the entrance, δ represents the decay rate factor, and α, β, and γ represent weight factors. Among them, α is used to measure the influence of historical exposure rate on the density of human traffic, β is used to measure the importance of showcase level, and γ is used to measure the importance of location factors. It is used to represent the negative impact of distance on the flow of people, and δ represents the decay rate factor. Usually, the parameters α, β, γ, and β need to be fitted and solved by the training set data.

[0097] Specifically, historical exhibition data is collected, including the historical exposure rate of exhibits in each display cabinet, location information and the corresponding actual traffic density; the collected data is cleaned, encoded and formatted to obtain a training set;

[0098] The parameters α, β, γ, and δ of the initial pedestrian flow density prediction model are fitted using the training set. After fitting, the prediction accuracy of the model is evaluated using evaluation indicators. When the prediction accuracy does not meet the preset conditions, the parameters are adjusted until the prediction accuracy meets the preset conditions, and the target values ​​of the trained parameters α, β, γ, and δ are obtained. Preferably, the mean square error is used as the evaluation indicator to evaluate the prediction accuracy of the model.

[0099] Finally, the target values ​​of parameters α, β, γ, and δ are substituted into the initial pedestrian flow density prediction model to generate the target pedestrian flow density prediction model.

[0100] Therefore, this embodiment uses an initial crowd flow density prediction model and solves the unknown parameters in the model through model training and fitting, thereby obtaining a target crowd flow density prediction model. The model can quickly and accurately evaluate the crowd flow density in the medium, providing a basis for achieving reasonable lighting control.

[0101] In one embodiment, the adaptively adjusting the initial lighting control scheme according to the real-time crowd density includes:

[0102] 1) Collect real-time video images to identify the real-time traffic density and vision data within a preset range of each showcase; the vision data is the ratio of the number of people wearing glasses to the total number of people.

[0103] In terms of hardware equipment, high-definition cameras are deployed to cover the entire exhibition hall, especially the key areas around each display cabinet, to ensure high resolution and good light adaptability. In terms of software processing, image segmentation and target detection algorithms can be deployed to identify individuals in real time from video streams by using deep learning algorithms such as YOLO and Mask R-CNN algorithms to distinguish between people and other objects. Target detection also includes identifying individuals wearing glasses on their faces and counting their proportion of the total flow of people as vision data. At the same time, for real-time crowd density calculation, crowd counting and density estimation algorithms should be deployed, such as density-based map estimation and deep learning counting networks to estimate the density of people within the preset range of each display cabinet.

[0104] 2) Input the real-time crowd density and vision conditions into the preset lighting control compensation model, and output the compensated color temperature and compensated illumination.

[0105] The lighting control compensation model is usually built and trained based on machine learning. The model can predict the most suitable compensation color temperature and compensation illumination according to the traffic density and vision conditions (such as the proportion of people wearing glasses). When training the model, it includes:

[0106] Feature selection: Crowd density and vision (proportion of people wearing glasses) are used as the main input features.

[0107] Target variables: Compensated color temperature and compensated illuminance.

[0108] Training data: The model is trained based on historical data or simulation data. The data should include the optimal lighting settings for different traffic flows and different vision conditions.

[0109] Model output: The model outputs the compensated color temperature and compensated illumination values ​​for the current scene based on real-time input data.

[0110] 3) Adaptively adjust the initial lighting control scheme according to the compensated color temperature and compensated illumination.

[0111] Through control system integration, the model output is integrated with the exhibition hall's intelligent lighting control system to support dynamic adjustment of color temperature and illumination. When the command is issued, according to the model output, the system will automatically send instructions to the corresponding LED lamps in the exhibition area to adjust their color temperature and brightness. At the same time, the system should have a real-time feedback mechanism to monitor the adjusted lighting effect and make fine adjustments as needed to achieve the best viewing experience.

[0112] Preferably, in the process of exhibition hall lighting control, the illumination uniformity and blue light damage factor of the exhibition hall lighting can also be considered, and the lighting control plan can be optimized according to these parameters, so that the illumination, uniformity and color temperature of the lighting are more in line with the comfort requirements of the human eye.

[0113] In summary, this embodiment takes into account the actual distribution of people and adaptively adjusts the lighting, which can not only improve the utilization rate of lighting resources and reduce lighting costs, but also achieve energy-saving and environmental protection effects, making the lighting more suitable for the actual situation, thereby improving the audience's viewing experience. In addition, by considering the uniformity of illumination and the blue light damage factor, the lighting control scheme can be further optimized to meet the comfort requirements of the human eye.

[0114] See also Figure 2 In one embodiment, the present invention further provides a lighting control system for exhibition hall design, the system comprising:

[0115] The data acquisition unit 100 is used to acquire the historical exhibition data of the exhibition hall within a preset period of time, analyze the historical exposure rate of each exhibit based on the historical exhibition data, and acquire the historical location information of the display cabinet where each exhibit is located;

[0116] The initial scheme determination unit 200 is used to input the historical exposure rate and the historical position information of the showcase into the target crowd flow density prediction model, output the expected crowd flow density within the preset range of each showcase in this exhibition, and determine the initial lighting control scheme of this exhibition according to the expected crowd flow density;

[0117] The adaptive adjustment unit 300 is used to monitor the real-time density of human traffic in each showcase within a preset range, and adaptively adjust the initial lighting control scheme according to the real-time density of human traffic;

[0118] The initial scheme optimization unit 400 is used to obtain the exhibition data, analyze the display cabinet congestion rate and the exhibit exposure rate in this exhibition; adjust the historical placement position of the display cabinet according to the display cabinet congestion rate and the exhibit exposure rate in this exhibition, and optimize the initial lighting control scheme for the next exhibition.

[0119] It can be understood that the functions or modules included in the system provided in this embodiment can be used to execute the method described in the above method embodiment. Its specific implementation can refer to the description of the above method embodiment. For the sake of brevity, it will not be repeated here.

[0120] The present invention also provides an electronic device, including a processor and a memory, wherein the memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes a method as described in any possible implementation manner.

[0121] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes a method as described in any possible implementation manner.

[0122] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0123] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

[0124] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0126] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0127] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0128] A person skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by a computer program to instruct the relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The aforementioned storage medium includes: a read-only memory (ROM) or a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

Claims

1. A lighting control method for exhibition hall design, characterized in that: The method comprises: Obtain the historical exhibition data of the exhibition hall within a preset period of time, analyze the historical exposure rate of each exhibit based on the historical exhibition data, and obtain the historical location information of the display cabinet where each exhibit is located; Input the historical exposure rate and the historical location information of the showcase into the target traffic density prediction model, output the expected traffic density within the preset range of each showcase in this exhibition, and determine the initial lighting control plan for this exhibition based on the expected traffic density; Before inputting the historical exposure rate and the historical location information of the showcase into the target traffic density prediction model, the method further includes: Establish an initial crowd density prediction model: In the formula, E f represents the density of human traffic, H i represents the historical exposure rate of the i-th showcase, P i represents the grade score of the i-th showcase, D i represents the distance from the ith showcase to the entrance, δ represents the decay rate factor, and α, β, and γ represent weight factors; Collect historical exhibition data, including the historical exposure rate of exhibits in each showcase, location information and the corresponding actual traffic density; clean, encode and convert the collected data to obtain a training set; The parameters α, β, γ, and δ of the initial pedestrian flow density prediction model are fitted using the training set. After fitting, the prediction accuracy of the model is evaluated using the evaluation index. When the prediction accuracy does not meet the preset conditions, the parameters are adjusted until the prediction accuracy meets the preset conditions, and the target values ​​of the trained parameters α, β, γ, and δ are obtained. Substitute the target values ​​of parameters α, β, γ, and δ into the initial pedestrian flow density prediction model to generate a target pedestrian flow density prediction model; Monitor the real-time traffic density of each showcase within a preset range, and adaptively adjust the initial lighting control plan according to the real-time traffic density; Obtain the data of this exhibition and analyze the display cabinet congestion rate and exhibit exposure rate in this exhibition; adjust the historical placement of the display cabinets according to the display cabinet congestion rate and exhibit exposure rate in this exhibition, and optimize the initial lighting control plan for the next exhibition.

2. The lighting control method for exhibition hall design according to claim 1, characterized in that: Before obtaining the historical position information of the display cabinet where each exhibit is located, the method further includes: Based on the booth information and the display cabinet information, a first matching relationship between the display cabinet and the booth is established according to the exhibition planning scheme; Determine the aisle width between the showcases according to the first matching relationship, select a first target showcase whose aisle width is less than a first preset threshold, re-plan the booth for the first target showcase to update the first matching relationship, and generate a second matching relationship; Based on the second matching relationship, the congestion rate of the showcase within the preset range is calculated, a second target showcase having a congestion rate greater than a second preset threshold is screened out, and a booth is replanned for the second target showcase to update the second matching relationship, thereby generating a third matching relationship; Each display cabinet is placed on a corresponding booth according to the third matching relationship.

3. The lighting control method for exhibition hall design according to claim 2, characterized in that: The calculating the congestion rate of the showcase within a preset range includes: In the formula, C R represents the congestion rate, m represents the number of people staying within the preset time range, S y It indicates the space area within the preset range of the showcase, S n It represents the inaccessible area within the preset range of the showcase, L represents the safe distance between people, and k represents the adjustment factor, satisfying k>1.

4. The lighting control method for exhibition hall design according to claim 1, characterized in that: The mean square error is used as the evaluation indicator to evaluate the prediction accuracy of the model.

5. The lighting control method for exhibition hall design according to claim 1, characterized in that: The method of adaptively adjusting the initial lighting control scheme according to the real-time crowd density includes: Collect real-time video images to identify the real-time density of human traffic and vision data within a preset range of each showcase; the vision data is the ratio of the number of people wearing glasses to the total number of people; Input the real-time traffic density and vision conditions into the preset lighting control compensation model, and output the compensated color temperature and compensated illumination; Adaptively adjust the initial lighting control scheme according to the compensated color temperature and compensated illumination.

6. A lighting control system for exhibition hall design, characterized in that: The system comprises: A data acquisition unit is used to acquire the historical exhibition data of the exhibition hall within a preset period of time, analyze the historical exposure rate of each exhibit based on the historical exhibition data, and acquire the historical location information of the display cabinet where each exhibit is located; An initial plan determination unit is used to input the historical exposure rate and the historical position information of the showcase into the target crowd density prediction model, output the expected crowd density within the preset range of each showcase in this exhibition, and determine the initial lighting control plan of this exhibition according to the expected crowd density; Before inputting the historical exposure rate and the historical location information of the showcase into the target traffic density prediction model, the method further includes: Establish an initial crowd density prediction model: In the formula, E f represents the density of human traffic, H i represents the historical exposure rate of the i-th showcase, P i represents the grade score of the i-th showcase, D i represents the distance from the ith showcase to the entrance, δ represents the decay rate factor, and α, β, and θ represent weight factors; Collect historical exhibition data, including the historical exposure rate of exhibits in each showcase, location information and the corresponding actual traffic density; clean, encode and convert the collected data to obtain a training set; The parameters α, β, γ, and δ of the initial pedestrian flow density prediction model are fitted using the training set. After fitting, the prediction accuracy of the model is evaluated using the evaluation index. When the prediction accuracy does not meet the preset conditions, the parameters are adjusted until the prediction accuracy meets the preset conditions, and the target values ​​of the trained parameters α, β, γ, and δ are obtained. Substitute the target values ​​of parameters α, β, γ, and δ into the initial pedestrian flow density prediction model to generate a target pedestrian flow density prediction model; The adaptive adjustment unit is used to monitor the real-time density of human traffic in each showcase within a preset range, and adaptively adjust the initial lighting control plan according to the real-time density of human traffic; The initial plan optimization unit is used to obtain the data of this exhibition, analyze the display cabinet congestion rate and exhibit exposure rate in this exhibition; adjust the historical placement of the display cabinet according to the display cabinet congestion rate and exhibit exposure rate in this exhibition, and optimize the initial lighting control plan for the next exhibition.

7. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and when the processor executes the computer instructions, the electronic device executes the lighting control method for exhibition hall design as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the lighting control method for exhibition hall design according to any one of claims 1 to 5.

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