Intelligent Management Method and Platform for VR Headset Charging Cabinet

Abstract

The present invention provides an intelligent management method and platform for a VR headset charging cabinet. A charging twin cabinet corresponding to the VR headset charging cabinet is constructed, the charging position of the headset device and the headset battery level are obtained, the headset model is retrieved and placed at the charging position in the charging twin cabinet, and the headset battery level is bound to the corresponding headset model to obtain a charging display space; project information sent by the experience terminal is received, the recommended removal position in the charging display space is determined according to the project information and the charging position, and the charging display space is prominently displayed based on the recommended removal position to obtain a recommended display space; a placement request from the experience terminal is received, the remaining battery level and charging times of the headset device corresponding to the experience terminal are obtained, and the recommended storage position is determined according to the remaining battery level, charging times and free positions in the charging display space; the selection times of the experience terminal at each selection position are counted, the preferred position of the experience terminal is determined based on the selection times, and a recommended adjustment coefficient is generated according to the preferred position.

Description

Technical Field

[0001] The present invention relates to data processing technologies, and in particular to an intelligent management method and platform for a VR headset charging cabinet. Background Art

[0002] With the rapid development of VR technologies, more and more educational and entertainment venues have started to introduce VR headset devices. However, during peak consumption periods, the frequency of users accessing and storing VR headsets is too high, and it is impossible to effectively schedule and allocate the headset devices in the VR charging cabinet in a timely manner, thus affecting the use by personnel.

[0003] In the prior art, recommendations are usually made based on the full charge status of the headset devices. Therefore, when other users need to use a VR headset but there is no fully charged headset device, they need to wait for a long time, and effective scheduling and allocation cannot be carried out, thereby affecting the experience of personnel. Moreover, since usually only one row of headset devices is placed on each layer in a traditional headset charging cabinet, when the headset device at the corresponding position is fully charged, there is an identification to prompt personnel that the headset device is fully charged and can be taken for use. However, when multiple rows of headset devices are placed on the same layer, personnel cannot accurately determine the specific position of the fully charged device, affecting the efficiency of personnel taking the headset device.

[0004] Therefore, how to automatically analyze according to the actual demand information of users, so as to recommend corresponding headset devices to users, facilitate users to access and store, and improve the scheduling and use efficiency of VR headset devices has become an urgent problem to be solved. Summary of the Invention

[0005] The present invention provides an intelligent management method and platform for a VR headset charging cabinet, which can automatically analyze according to the actual demand information of users, so as to recommend corresponding headset devices to users, facilitate users to access and store, and improve the scheduling and use efficiency of VR headset devices.

[0006] In a first aspect of the present invention, there is provided an intelligent management method for a VR headset charging cabinet, including:

[0007] Construct a charging twin cabinet corresponding to the VR headset charging cabinet, obtain the charging positions of the headset devices and the headset battery levels, retrieve the headset models and place them at the charging positions in the charging twin cabinet, and bind the headset battery levels to the corresponding headset models to obtain a charging display space;

[0008] Receive project information sent by an experience terminal, determine a recommended removal position in the charging display space according to the project information and the charging position, and prominently display the charging display space based on the recommended removal position to obtain a recommended display space and send it to the experience terminal;

[0009] Receive the placement request of the experience terminal, obtain the remaining power and charging times of the corresponding head-mounted device of the experience terminal, and determine the recommended storage location according to the remaining power, charging times and the idle positions in the charging display space, and send it to the experience terminal;

[0010] Count the selection times of the experience terminal at each selection position, determine the preferred position of the experience terminal based on the selection times, and generate a recommended adjustment coefficient according to the preferred position.

[0011] Optionally, in a possible implementation manner of the first aspect, the receiving the item information sent by the experience terminal, determining the recommended removal position in the charging display space according to the item information and the charging position, and prominently displaying the charging display space based on the recommended removal position to obtain the recommended display space and sending it to the experience terminal includes:

[0012] Receive the item information sent by the experience terminal, determine the corresponding item duration based on the item information, and retrieve the restricted power according to the item duration;

[0013] Based on the restricted power, count the head-mounted models corresponding to the head-mounted power greater than or equal to the restricted power as the initial selection models;

[0014] Retrieve the charging positions and charging times corresponding to the initial selection models, and obtain the removal recommendation values of each initial selection model based on the charging positions and the charging times;

[0015] Sort the charging positions of each initial selection model in descending order based on the removal recommendation values to obtain a position selection sequence;

[0016] Receive the required quantity sent by the experience terminal, perform position selection on the position selection sequence according to the required quantity to obtain the recommended removal position corresponding to the recommended head-mounted device;

[0017] Prominently display the charging display space based on the recommended removal position to obtain the recommended display space and send it to the experience terminal.

[0018] Optionally, in a possible implementation manner of the first aspect, the retrieving the charging positions and charging times corresponding to the initial selection models, and obtaining the removal recommendation values of each initial selection model based on the charging positions and the charging times includes:

[0019] Retrieve the charging positions and charging times corresponding to the initial selection models, obtain the corresponding position rows based on the charging positions, and obtain the corresponding position coefficients according to the position rows. The position rows have one-to-one corresponding position coefficients;

[0020] Retrieve the charging reference times, obtain the charging extraction coefficient based on the ratio of the charging reference times to the charging times, and obtain the extraction times coefficient corresponding to each initial selection model according to the product of the charging extraction coefficient and the times weight;

[0021] Obtain the extraction recommendation value corresponding to each initial selection model according to the sum value of the extraction times coefficient and the position coefficient;

[0022] The extraction recommendation value corresponding to each of the initial selection models is obtained through the following formula,

[0023] where, is the extraction recommendation value, is the charging reference times, is the charging times, is the times weight, is the position coefficient corresponding to the row.

[0024] Optionally, in a possible implementation manner of the first aspect, the receiving the placement request of the experience terminal, obtaining the remaining power and charging times of the head-mounted device corresponding to the experience terminal, and determining the recommended storage location according to the remaining power, charging times and the idle position in the charging display space and sending it to the experience terminal includes:

[0025] Receive the placement request of the experience terminal, and retrieve the remaining power and charging times of the placement device corresponding to the experience terminal based on the placement request;

[0026] Retrieve the idle positions in the charging display space, extract the corresponding position rows as idle rows based on the idle positions, and perform ascending sorting on the idle rows to obtain an idle row sequence;

[0027] Retrieve the charging reference times, obtain the charging placement coefficient based on the ratio of the charging times to the charging reference times, and obtain the corresponding placement times coefficient according to the product of the charging placement coefficient and the times weight;

[0028] Determine the corresponding charging duration according to the remaining power, retrieve the reference duration, obtain the placement duration coefficient based on the ratio of the reference duration to the charging duration, and obtain the duration placement coefficient according to the placement duration coefficient and the charging weight;

[0029] Obtain the placement recommendation value corresponding to each of the placement devices based on the placement times coefficient and the duration placement coefficient;

[0030] Perform descending sorting on the placement devices according to the placement recommendation value to obtain a head-mounted device placement sequence;

[0031] Select the first placement device as the outer placement device based on the head-mounted display placement sequence, use the corresponding last placement device as the inner placement device, and use the remaining placement devices as dynamic placement devices;

[0032] Retrieve the placement recommendation value corresponding to the outer placement device as the initial recommendation value, and retrieve the placement recommendation value corresponding to the inner placement device as the end recommendation value;

[0033] Use the first free line number in the free line number sequence as the recommended storage location for the outer placement device, and use the initial recommendation value as the placement comparison value for the first free line number;

[0034] Use the last free line number in the free line number sequence as the recommended storage location for the inner placement device, and use the end recommendation value as the placement comparison value for the last free line number; Obtain the total recommendation difference based on the difference between the initial recommendation value and the end recommendation value, determine the calculation quantity based on the number quantity corresponding to the free line number in the free line number sequence, and determine the recommendation difference based on the total recommendation difference and the calculation quantity;

[0035] Successively decrease the initial recommendation value according to the recommendation difference until it equals the end recommendation value to obtain the placement comparison value corresponding to each free line number;

[0036] Based on the absolute value of the difference between the placement recommendation value corresponding to the dynamic placement device and the placement comparison value, obtain the comparison difference, and determine the free line number corresponding to the smallest comparison difference as the recommended storage location for the corresponding dynamic placement device;

[0037] Send the recommended storage location to the experience terminal.

[0038] Optionally, in a possible implementation manner of the first aspect, the obtaining the placement recommendation value corresponding to each placement device based on the placement times coefficient and the duration placement coefficient includes:

[0039] Obtain the placement recommendation value corresponding to the head-mounted display device through the following formula,

[0040] where, is the placement recommendation value, is the charging reference times, is the charging times, is the times weight, is the reference duration, is the charging duration, is the charging weight.

[0041] Optionally, in a possible implementation of the first aspect, the method of counting the number of selections of the experience terminal at each selected position, determining the preferred position of the experience terminal based on the number of selections, and generating a recommended adjustment coefficient according to the preferred position includes:

[0042] Obtain the charging position selected by the experience terminal as the selected position, accumulate the number of selections of the selected positions corresponding to the same position row number to obtain the row number count;

[0043] Determine the maximum row number count as the preferred position of the corresponding experience terminal, and adjust the corresponding position coefficient according to the preferred position to obtain the recommended adjustment coefficient.

[0044] Optionally, in a possible implementation of the first aspect, the method of determining the maximum row number count as the preferred position of the corresponding experience terminal, adjusting the corresponding position coefficient according to the preferred position, and obtaining the recommended adjustment coefficient includes:

[0045] Obtain the total number of rows of the charging positions in the VR headset charging cabinet, and judge the row number based on half of the total number of rows of the positions;

[0046] Determine the maximum row number count as the preferred position of the corresponding experience terminal, and upwardly adjust the position coefficient corresponding to the preferred position based on the row number judged by the benchmark to obtain the recommended adjustment coefficient;

[0047] The adjusted recommended adjustment coefficient is obtained through the following formula

[0048] where is the recommended adjustment coefficient, is the position coefficient corresponding to the th row, is the preferred position, is the row number judged by the benchmark.

[0049] Optionally, in a possible implementation of the first aspect, it further includes:

[0050] Receive the headset image collected by the acquisition device, retrieve the preset pixel value, and perform stain recognition on the headset image based on OpenCV and the preset pixel value to obtain stain pixel points;

[0051] Obtain multiple stain regions according to adjacent stain pixel points, count the number of the stain regions to obtain the region number, and count the number of pixel points in all the stain regions as the stain pixel number;

[0052] Obtain a region coefficient based on the product of the number of regions and the region weight, obtain a pixel coefficient based on the product of the number of stain pixels and the pixel point number weight, and obtain a stain coefficient according to the sum value of the region coefficient and the pixel coefficient;

[0053] Retrieve the extraction times coefficient, the position coefficient, and the stain coefficient, and obtain an extraction recommendation value corresponding to each initial selection model based on the extraction times coefficient, the position coefficient, and the stain coefficient.

[0054] Optionally, in a possible implementation manner of the first aspect, the retrieving the extraction times coefficient, the position coefficient, and the stain coefficient, and obtaining an extraction recommendation value corresponding to each initial selection model based on the extraction times coefficient, the position coefficient, and the stain coefficient includes:

[0055] Obtain an extraction recommendation value corresponding to each of the initial selection models through the following formula

[0056] where is the extraction recommendation value, is the charging reference number of times, is the number of charging times, is the number of times weight, is the position coefficient corresponding to the row, is the number of regions, is the region weight, is the number of stain pixels, is the stain weight.

[0057] In a second aspect of the present invention, there is provided an intelligent management platform for a VR headset charging cabinet, including:

[0058] A construction module, configured to construct a charging twin cabinet corresponding to the VR headset charging cabinet, obtain the charging position of the headset device and the headset power, retrieve the headset model and place it at the charging position in the charging twin cabinet, and bind the headset power to the corresponding headset model to obtain a charging display space;

[0059] A determination module, configured to receive project information sent by an experience terminal, determine a recommended extraction position in the charging display space according to the project information and the charging position, and perform prominent display on the charging display space based on the recommended extraction position, and send the recommended display space to the experience terminal;

[0060] A sending module, configured to receive the placement request of the experience terminal, obtain the remaining power and charging times of the corresponding head-mounted device of the experience terminal, and determine a recommended storage location according to the remaining power, charging times, and free positions in the charging display space, and send it to the experience terminal;

[0061] An adjustment module, configured to count the selection times of the experience terminal at each selection position, determine the preferred position of the experience terminal based on the selection times, and generate a recommended adjustment coefficient according to the preferred position.

[0062] In a third aspect of the present invention, an electronic device is provided, including: a memory, a processor, and a computer program, where the computer program is stored in the memory, and the processor runs the computer program to execute the method according to the first aspect of the present invention and various possible aspects of the first aspect.

[0063] In a fourth aspect of the present invention, a storage medium is provided, where a computer program is stored in the storage medium, and when the computer program is executed by a processor, it is used to implement the method according to the first aspect of the present invention and various possible aspects of the first aspect.

[0064] The beneficial effects of the present invention are as follows:

[0065] 1. The present invention can automatically analyze according to the actual demand information of the user, so as to recommend corresponding head-mounted devices for the user, facilitate the user to store and retrieve, and improve the scheduling and use efficiency of VR head-mounted devices. The present invention can construct a virtual charging twin cabinet and monitor the power, so that the user can quickly find a VR head-mounted device with a good charging state, thereby significantly improving the use efficiency of the device, realizing efficient management and scheduling. Moreover, the present invention can reduce the user's waiting time. The user no longer needs to manually search and wait for charging, and the system automatically recommends a suitable device, which greatly saves time.

[0066] 2. The present invention can improve the efficiency of personnel selecting head-mounted devices, facilitate personnel to use, and improve the scheduling efficiency of the VR head-mounted charging cabinet for head-mounted devices. Among them, the present invention can determine the corresponding available head-mounted devices according to the items selected by the experience terminal, calculate according to the charging positions of the corresponding head-mounted devices, and prominently display the recommended positions that are convenient for personnel to pick up in the charging display space, and then obtain a recommended display space, so that personnel can intuitively view the positions of the corresponding available head-mounted devices through the recommended display space, reduce the pick-up selection time, and improve the use efficiency.

[0067] 3. The present invention can achieve intelligent management. Through real-time monitoring and data analysis, the system can intelligently manage the use and charging status of VR head-mounted devices, improve the overall operation efficiency, and at the same time improve the personalized experience of users. Among them, the present invention can provide customized recommendations according to the user's usage habits and preferences to enhance the user experience. Brief Description of the Drawings

[0068] Figure 1 It is a flowchart of an intelligent management method for a VR headset charging cabinet provided by the present invention;

[0069] Figure 2 It is a schematic diagram of a VR headset charging cabinet provided by the present invention;

[0070] Figure 3 It is a schematic structural diagram of an intelligent management platform for a VR headset charging cabinet provided by the present invention;

[0071] Figure 4 It is a schematic hardware structure diagram of an electronic device provided by the present invention. Detailed Embodiments

[0072] Hereinafter, the technical solutions of the present invention will be described in detail with specific embodiments. These specific embodiments can be combined with each other, and for the same or similar concepts or processes, they may not be repeated in some embodiments.

[0073] As Figure 1 shown, the present invention provides an intelligent management method for a VR headset charging cabinet, including:

[0074] S1. Construct a charging twin cabinet corresponding to the VR headset charging cabinet, obtain the charging positions and headset battery levels of the headset devices, retrieve the headset models and place them at the charging positions in the charging twin cabinet, and bind the headset battery levels to the corresponding headset models to obtain a charging display space.

[0075] It should be noted that since multiple VR headset devices are placed in the same VR headset charging cabinet, in order to subsequently display and recommend the information of each headset device intuitively, a corresponding virtual charging twin cabinet can be constructed according to the actual VR headset charging cabinet, so as to mark the positions of the corresponding headset devices, and at the same time obtain the charging positions and headset battery levels of the corresponding headset devices and associate and bind them with the headset models at the corresponding positions to obtain a charging display space, so as to facilitate subsequent recommendations for personnel to pick up the headset based on the charging display space, facilitate intuitive viewing by personnel, and thus quickly determine the devices at the corresponding positions, improving the scheduling and utilization rate of the headset.

[0076] It can be understood that the charging twin cabinet is a virtual twin cabinet corresponding to the VR headset charging cabinet, the headset device is a VR headset device, the charging position is the position where each headset device is charged in the charging cabinet, the headset battery level is the available battery level corresponding to each headset, the headset model is a virtual model corresponding to the headset device, and the charging display space is a virtual charging cabinet with headset model display.

[0077] It is not difficult to understand that, according to the positions of the headset devices in the actual VR headset charging cabinet, the corresponding headset models are displayed at the corresponding positions in the charging twin cabinet, which facilitates the association and binding of the corresponding headset power with the headset models at the corresponding positions, enables the experience personnel to intuitively view the power of different headset devices through the twin space, and also facilitates subsequent pick-up and placement recommendations based on the corresponding charging positions and power, making it convenient for personnel to use.

[0078] S2. Receive the project information sent by the experience terminal, determine the recommended removal position in the charging display space according to the project information and the charging position, highlight the charging display space based on the recommended removal position, and send the obtained recommended display space to the experience terminal.

[0079] It should be noted that, in order to improve the efficiency of personnel in selecting headset devices, facilitate personnel use, and improve the scheduling efficiency of the VR headset charging cabinet for headset devices, the corresponding available headset devices can be determined according to the project selected by the experience terminal, and calculations can be made based on the charging positions of the corresponding headset devices to obtain the recommended positions that are convenient for personnel to pick up, highlight the charging display space, and then obtain the recommended display space, so that personnel can intuitively view the positions of the corresponding available headset devices through the recommended display space, reduce the pick-up selection time, and improve the use efficiency.

[0080] It can be understood that the experience terminal is the information terminal of the personnel experiencing the VR project, such as the mobile phone of the personnel picking up the VR headset device. The project information is the project selected by the experience personnel to experience, such as a selected game project, a movie project watched using VR, etc. The recommended removal position is the position where the recommended headset device can be removed, and the recommended display space is the twin space showing the position of the recommended device.

[0081] In some embodiments, the specific implementation manner in step S2 (receiving the project information sent by the experience terminal, determining the recommended removal position in the charging display space according to the project information and the charging position, highlighting the charging display space based on the recommended removal position, and sending the obtained recommended display space to the experience terminal) includes:

[0082] S21. Receive the project information sent by the experience terminal, determine the corresponding project duration based on the project information, and retrieve the limited power according to the project duration.

[0083] It is understandable that different projects have corresponding usage durations. Thus, the corresponding project duration can be determined based on the project information, so as to obtain the corresponding restricted power according to the project duration, which facilitates the selection of a head-mounted display device that meets the restricted power for personnel to directly use. That is, the power of the corresponding head-mounted display device only needs to meet or exceed the restricted power to meet the usage requirements of personnel, without waiting for the head-mounted display device to be fully charged before it can be used by personnel, thereby reducing the waiting time of personnel and improving the scheduling and usage efficiency of the head-mounted display device.

[0084] Among them, the project duration is the usage duration of experiencing the corresponding project. For example, if the requirement of a person is to watch Video A and the playing duration of the corresponding video is 1 hour, then the project duration corresponding to the project information Video A can be determined to be 1 hour. The restricted power is the minimum power of the recommended head-mounted display determined. And the project duration and the restricted power are in one-to-one correspondence. For example, the power corresponding to one hour is 25% of the power of the head-mounted display device. Thus, the minimum power of the recommended device selected subsequently is 25% of the standard full charge of the device.

[0085] S22. Based on the restricted power, count the head-mounted display models whose head-mounted display power is greater than or equal to the restricted power as the initial selection models.

[0086] It is understandable that when the head-mounted display power of the head-mounted display device is greater than or equal to the restricted power, the corresponding head-mounted display device can meet the requirement for the experience personnel to normally complete the project content being experienced. Therefore, the head-mounted display models that meet the condition of being greater than or equal to the restricted power can be used as the initial selection models based on the restricted power, so as to further select from the initial selection models subsequently, thereby determining the corresponding recommended removal positions, so that personnel can quickly obtain the head-mounted display device at the corresponding recommended positions and improve the usage efficiency of personnel.

[0087] Among them, the initial selection model is the head-mounted display model whose head-mounted display power is greater than or equal to the restricted power.

[0088] S23. Retrieve the charging positions and charging times corresponding to the initial selection models, and obtain the recommended removal values of each initial selection model based on the charging positions and the charging times.

[0089] It can be understood that since there can be multiple initial selection models, but the positions of the head-mounted devices corresponding to different initial selection models are different. Some are outside the charging cabinet, and some are inside the charging cabinet. The difference in position will affect the speed at which personnel can pick them up. At the same time, during the repeated charging process of the head-mounted devices, power consumption will occur, and the more times of charging, the greater the degree of device loss. Therefore, it is possible to calculate based on the charging positions and charging times corresponding to multiple initial selection models, so as to recommend to personnel the head-mounted devices with sufficient power and convenient for personnel to pick up in the subsequent process, thereby greatly improving the usage efficiency of personnel.

[0090] Among them, the extraction recommendation value is the recommended evaluation value for extraction corresponding to each initial selection model.

[0091] It is not difficult to understand that the higher the extraction recommendation value, the higher the usability and picking efficiency of the corresponding head-mounted device, thereby greatly improving the usage efficiency of personnel.

[0092] In some embodiments, the specific implementation manner in step S23 (retrieving the charging position and charging times corresponding to the initial selection model, and obtaining the extraction recommendation value of each initial selection model based on the charging position and the charging times) includes:

[0093] S231, retrieving the charging position and charging times corresponding to the initial selection model, obtaining the corresponding position row number based on the charging position, and obtaining the corresponding position coefficient according to the position row number. The position row number has a one-to-one corresponding position coefficient.

[0094] It can be understood that the position row number is the row and column number where the charging position is located. For example, the first row, the second row, etc. The position coefficient is the calculated coefficient value corresponding to different position row numbers, which is set in advance by humans.

[0095] It is not difficult to understand that as Figure 2 described, multiple rows can be placed on one layer of the VR head-mounted device charging cabinet to increase the placement quantity of VR head-mounted devices. Different position row numbers correspond to different positions. For example, when 3 rows are placed from the outside to the inside on the same layer, the convenience of picking up the first row on the outside and the third row on the inside is different. Therefore, a corresponding position coefficient can be set for each row to calculate the corresponding extraction recommendation value in the subsequent process.

[0096] S232, retrieving the charging reference times, obtaining the charging extraction coefficient based on the ratio of the charging reference times to the charging times, and obtaining the extraction times coefficient corresponding to each initial selection model according to the product of the charging extraction coefficient and the times weight.

[0097] It can be understood that the charging reference number is the number of times of charging for the reference loss of the VR headset. For example, 100 times. That is, when the number of charging times reaches a certain number (100 times), the power storage level of the corresponding VR headset may be damaged. Furthermore, the retrieved recommended value of the corresponding initial selection model will also be different. Therefore, the charging extraction coefficient can be obtained by calculating the ratio of the charging reference number to the charging number of the corresponding initial selection model. Then, the extraction number coefficient corresponding to each initial selection model can be obtained by multiplying the charging extraction coefficient by the number weight, so as to subsequently obtain the corresponding retrieved recommended value of the initial selection model according to the position coefficient, facilitating the selection of the headset device at the appropriate position, thereby improving the efficiency of personnel taking.

[0098] Among them, the charging number is the number of times of charging the VR headset device corresponding to the initial selection model in the historical time period. The charging extraction coefficient is the coefficient value calculated corresponding to the charging number of each initial selection model. The number weight is the proportion weight value corresponding to the charging number in calculating the retrieved recommended value, which is preset. The extraction number coefficient is the coefficient value of the retrieved recommendation corresponding to the charging number.

[0099] S233. Obtain the retrieved recommended value corresponding to each initial selection model according to the sum value of the extraction number coefficient and the position coefficient.

[0100] It can be understood that by summing the extraction number coefficient and the position coefficient corresponding to each initial selection model, the recommended value corresponding to each initial selection model can be obtained, so as to subsequently select the initial selection model according to the retrieved recommended value, and then determine the corresponding device position, thereby obtaining the headset device that best meets the needs of personnel, while facilitating personnel taking and improving personnel use efficiency.

[0101] S234. Obtain the retrieved recommended value corresponding to each of the initial selection models through the following formula

[0102] Among them, is the retrieved recommended value, is the charging reference number, is the charging number, is the number weight, is the position coefficient corresponding to the row.

[0103] It can be understood that is the ratio of the charging reference number to the charging number, that is, the charging extraction coefficient. When the charging number is larger, the corresponding charging extraction coefficient is smaller, so that the number coefficient will also become smaller accordingly. Then, when the number coefficient and the position coefficient are smaller, the corresponding retrieved recommended value It will also become smaller, indicating that the corresponding recommended value is lower. When the number of charging times is smaller, the corresponding charging extraction coefficient is larger, indicating that the performance of the corresponding head-mounted device is excellent. Thus the number of times coefficient will also increase accordingly. When the number of times coefficient and the position coefficient are larger, the corresponding extraction recommended value will also become larger, indicating that the recommended value of the corresponding initial selection model is large, the corresponding device function is better, and it is also convenient for personnel to pick up, thus obtaining a relatively high pick-up recommended value.

[0104] It is not difficult to understand that the more rows the head-mounted devices are placed in, the closer the device position is to the inside. For example, when there are 4 rows or 5 rows, it is more inconvenient for personnel to pick up. The device placement position is closer to the outside. For example, when there are 1 row or 2 rows, it is more convenient for personnel to pick up. Thus, the position coefficient corresponding to the outside is higher than that of the inside.

[0105] S24. Based on the extraction recommended value, perform a descending order sorting on the charging positions of each of the initial selection models to obtain a position selection sequence.

[0106] It can be understood that the position selection sequence is the position sequence after the charging positions corresponding to the initial selection models are sorted in descending order according to the extraction recommended value. For example, when the extraction recommended value of the initial selection model corresponding to column 2 in the first row is 10, the extraction recommended value of the initial selection model corresponding to column 3 in the first row is 7, the extraction recommended value of the initial selection model in column 1 of the second row is 8, the extraction recommended value of the initial selection model in column 3 of the third row is 4, and the extraction recommended value of the initial selection model in column 4 of the fifth row is 1, then the corresponding position selection sequence can be (column 2 in the first row, column 1 in the second row, column 3 in the first row, column 3 in the third row, column 4 in the fifth row).

[0107] Through the above implementation manner, the present invention can obtain a position selection sequence, so as to subsequently determine the corresponding number of recommended extraction positions according to the position selection sequence, so as to update the charging display space, facilitate the viewing of personnel, and further improve the pick-up efficiency.

[0108] S25. Receive the required quantity sent by the experience terminal, and perform position selection on the position selection sequence according to the required quantity to obtain the recommended extraction positions corresponding to the recommended head-mounted devices.

[0109] It can be understood that the required quantity is the number of head-mounted devices required by the experience personnel, such as 1, 3, or 5, etc. The recommended head-mounted devices are the head-mounted devices recommended for personnel to pick up.

[0110] It is not difficult to understand that, according to the received demand quantity, selection is made in the position selection sequence to obtain the recommended extraction position corresponding to the recommended head-mounted display, so as to subsequently highlight the corresponding position in the charging display space for easy viewing by personnel, so that the head-mounted display device at the corresponding position can be quickly taken.

[0111] S26. Based on the recommended extraction position, the charging display space is highlighted to obtain a recommended display space and sent to the experience terminal.

[0112] It can be understood that the corresponding recommended extraction position in the charging display space is highlighted. For example, the pixel value of the head-mounted display model at the corresponding position can be changed, so that the corresponding recommended extraction position is more intuitive. When the recommended display space is sent to the experience terminal, it is convenient for personnel to view, so that the position corresponding to the recommended head-mounted display device can be quickly determined.

[0113] Among them, the recommended display space is a twin space where changes occur at the corresponding recommended extraction position.

[0114] It is worth mentioning that in traditional VR head-mounted display devices, only one row is placed on each layer. Thus, when the head-mounted display device at the corresponding position is fully charged, there is an identifier to prompt the personnel that the device's battery is fully charged and can be taken for use. However, when multiple rows of head-mounted display devices are placed on the same layer, the personnel cannot accurately determine the specific position of the fully charged device. In contrast, the present invention can determine the head-mounted display device that meets the personnel's needs among the head-mounted display devices with multiple rows on each layer according to the user's needs, the battery level of the head-mounted display, and the position of the corresponding head-mounted display device, and intuitively display the corresponding position, so that the personnel can quickly take the head-mounted display device that meets the needs according to the recommended position, improving the usage efficiency of the head-mounted display device.

[0115] It should be noted that since the head-mounted display device will be stained with some stains during the use process by personnel, in order to avoid affecting the use experience of the experience personnel, the stain factor on the head-mounted display device can be added to the recommended evaluation. That is, the extraction recommendation value can be adjusted and calculated according to the area or quantity of the stains, so as to improve the use experience of the personnel. Thus, in some embodiments, it further includes:

[0116] A1. Receive the head-mounted display image collected by the acquisition device, retrieve the preset pixel value, and perform stain recognition on the head-mounted display image based on OpenCV and the preset pixel value to obtain stain pixel points.

[0117] It can be understood that the acquisition device is a device for photographing a head-mounted display device. For example, it can be a camera installed in a VR head-mounted display charging cabinet. There can be multiple acquisition devices in one charging cabinet, and the acquisition angle of the acquisition device can be changed so that the surface stains of each head-mounted display device can be clearly acquired for accurate calculation and recommendation. The head-mounted display image is the image of the head-mounted display device acquired, the preset pixel value is a preset pixel value. For example, if the color of the stain is usually black, the corresponding preset pixel value can be black. OpenCV is an existing image recognition technology that can perform pixel recognition, extraction, etc. on the acquired head-mounted display image. The stain pixel points are the pixel points representing stains in the image.

[0118] Through the above embodiments, the present invention can determine the corresponding stain pixel points, so as to subsequently obtain the corresponding number of regions and the number of stain pixels based on the stain pixel points, and further adjust the calculation method of the recommended removal value, so as to determine the recommended removal position corresponding to the head-mounted display device that better meets the needs of the personnel.

[0119] A2. Obtain multiple stain regions according to the adjacent stain pixel points, count the number of the stain regions to obtain the number of regions, and count the number of pixel points in all the stain regions as the number of stain pixels.

[0120] It can be understood that the stain region is the region on the head-mounted display device representing the stain, that is, the region formed by counting adjacent stain pixel points, and the number of stain pixels is the number of pixel points in all stain regions.

[0121] A3. Obtain the region coefficient according to the product of the number of regions and the region weight, obtain the pixel point coefficient based on the product of the number of stain pixels and the pixel point number weight, and obtain the stain coefficient according to the sum value of the region coefficient and the pixel point coefficient.

[0122] It can be understood that the more stain regions there are on the head-mounted display device, the less likely the corresponding head-mounted display device is to be recommended for personnel to pick up and use. Therefore, the region coefficient can be obtained according to the number of regions and the corresponding region weight, so as to comprehensively consider the stain region factor in the subsequent obtained recommended removal value. At the same time, when the number of stain pixels is larger, it can indicate that the total area of the stains on the corresponding head-mounted display device is larger, and the head-mounted display device needs to be cleaned for a longer time. Then the subsequent obtained recommended removal value will become smaller, and the placement positions with more stains need to be arranged later.

[0123] Among them, the area weight is the proportion weight of the stain area in the calculated recommended value, the area coefficient is the coefficient value corresponding to the number of stain areas, that is, the product of the number of areas and the area weight, the pixel point number weight is the proportion weight value of the stain pixel points in the calculation, which can be set in advance manually, the pixel point coefficient is the product of the number of stain pixels and the pixel point number weight, and the stain coefficient is the coefficient value corresponding to the stain factor in the calculated recommended value taken out by the head-mounted device, that is, the sum value of the area coefficient and the pixel point coefficient.

[0124] Through the above implementation manner, the present invention can obtain the corresponding stain coefficient, so as to calculate the corresponding recommended value for taking out together with the taking-out times coefficient and the position coefficient subsequently.

[0125] A4. Retrieve the taking-out times coefficient, the position coefficient and the stain coefficient, and obtain the taking-out recommended value corresponding to each initial selection model based on the taking-out times coefficient, the position coefficient and the stain coefficient.

[0126] It can be understood that by comprehensively calculating the numerical values of various factors such as the taking-out times coefficient, the position coefficient and the stain coefficient, the taking-out recommended value corresponding to each initial selection model can be obtained, which is convenient for subsequently determining the charging position of the best head-mounted device, convenient for personnel to take, and improves the use efficiency and experience of personnel.

[0127] In some embodiments, the specific implementation manner in step A4 (retrieving the taking-out times coefficient, the position coefficient and the stain coefficient, and obtaining the taking-out recommended value corresponding to each initial selection model based on the taking-out times coefficient, the position coefficient and the stain coefficient) includes:

[0128] A41. Obtain the taking-out recommended value corresponding to each initial selection model through the following formula.

[0129] Among them, is the taking-out recommended value. is the charging reference times. is the charging times. is the times weight. is the position coefficient corresponding to the row. is the number of areas. is the area weight. is the number of stain pixels. is the stain weight.

[0130] It can be understood that is the ratio of the charging reference times to the charging times, that is, the charging taking-out coefficient. When the charging times is larger, the corresponding The smaller the charging extraction coefficient, thus the frequency coefficient will also become smaller accordingly. When the frequency coefficient and the position coefficient are smaller, the corresponding extraction recommendation value will also become smaller, which indicates that the corresponding recommendation value is lower. When the number of charging times is smaller, the corresponding the charging extraction coefficient is larger, indicating that the performance of the corresponding head-mounted device is excellent, thus the frequency coefficient will also become larger accordingly. When the frequency coefficient and the position coefficient are larger, the corresponding extraction recommendation value will also become larger, which indicates that the recommendation value of the corresponding initial selection model is large, the corresponding device function is better, and it is also convenient for personnel to pick up, thus obtaining a higher pick-up recommendation value.

[0131] Moreover, since the stain condition on the head-mounted device will affect the user experience of personnel, thus when the number of regions and the number of stain pixels are larger, the region coefficient and the pixel coefficient are larger, it can be explained that the more stains there are on the corresponding head-mounted device. Then, the extraction recommendation value corresponding to the corresponding initial selection model is smaller, and it is less recommended that personnel pick up and use it. When the number of regions and the number of stain pixels are smaller, it can be explained that the fewer stains there are on the corresponding head-mounted device. Then, the extraction recommendation value corresponding to the corresponding initial selection model is larger, and it is more recommended that personnel pick up and use it.

[0132] Among them, the stain weight is the calculation proportion corresponding to the stain in calculating the extraction recommendation value, which is set in advance by humans.

[0133] It should be noted that since different personnel pay attention to different factors, there are certain differences in the selection of devices. For example, some personnel have strong requirements for the cleanliness of the device and need a new head-mounted device with few stains on the appearance, while some personnel have no high requirements for the newness and stain condition of the device. Therefore, in order to improve the scheduling efficiency of the device and recommend devices that meet the requirements for different personnel, thus, the frequency weight and the stain weight for calculating the extraction recommendation value of the corresponding computing device can be adaptively adjusted. Therefore, in some embodiments, it further includes:

[0134] Receiving the device evaluation value sent by the experience terminal, determining that the device evaluation value is greater than the extraction recommendation value, retrieving the frequency weight and the stain weight, performing an increase adjustment based on the frequency weight to obtain a frequency increase adjustment weight, and performing a decrease adjustment on the stain weight to obtain a stain decrease adjustment weight.

[0135] It can be understood that the device evaluation value is the evaluation value of the device recommended for the person to pick up, the increased frequency adjustment weight is the weight value after the increase adjustment of the frequency weight, and the decreased stain adjustment weight is the weight value after the decrease adjustment of the stain weight.

[0136] It is not difficult to understand that when the evaluation value of the device recommended by the person is greater than the recommended value for taking out calculated by the original weight, it can be explained that the person has a high evaluation value for the current device. Therefore, the corresponding frequency weight can be increased and the corresponding stain weight can be decreased, so that when recommending for the person later, the calculated recommended value of the corresponding head-mounted device can be changed to recommend more head-mounted devices to meet the person's needs.

[0137] The increased frequency adjustment weight and the decreased stain adjustment weight are obtained through the following formula.

[0138] Among them, is the increased frequency adjustment weight, is the device evaluation value, is the decreased stain adjustment weight.

[0139] It can be understood that when the device evaluation value is larger, the corresponding value will also increase, and thus the increased value of the increased frequency adjustment weight is larger. Similarly, when the device evaluation value is larger, the corresponding value will also increase, that is, the more the stain weight decreases, and thus the decreased stain adjustment weight is smaller.

[0140] It is determined that the device evaluation value is less than the recommended value for taking out, the frequency weight and the stain weight are retrieved, the frequency weight is decreased based on the frequency weight to obtain the decreased frequency adjustment weight, and the stain weight is increased to obtain the increased stain adjustment weight.

[0141] It can be understood that the device evaluation value is the evaluation value of the device recommended for the person to pick up, the decreased frequency adjustment weight is the weight value after the decrease adjustment of the frequency weight, and the increased stain adjustment weight is the weight value after the increase adjustment of the stain weight.

[0142] It is not difficult to understand that when the evaluation value of the recommended device by the person is less than the extraction recommendation value calculated by the original weight, it can indicate that the person's evaluation value of the current device is low. Thus, it can be shown that the person has higher requirements for the device. In order to improve the person's satisfaction and recommend a suitable head-mounted display device, the corresponding frequency weight can be reduced and adjusted, and the corresponding stain weight can be increased and adjusted, so that when recommending to this person later, the calculated recommendation value of the corresponding head-mounted display device is changed, so as to recommend more head-mounted display devices to meet the person's needs.

[0143] The frequency reduction adjustment weight and the stain increase adjustment weight are obtained through the following formula.

[0144]

[0145] Among them, is the frequency reduction adjustment weight, is the device evaluation value, is the stain increase adjustment weight.

[0146] It can be understood that when the device evaluation value is smaller, the corresponding value will increase, and the more the frequency weight decreases, so that the value of the obtained frequency reduction adjustment weight is smaller. Similarly, when the device evaluation value is smaller, the corresponding value will increase, that is, the more the stain weight increases, so that the obtained stain increase adjustment weight is larger.

[0147] S3. Receive the placement request of the experience terminal, obtain the remaining power and charging times of the head-mounted display device corresponding to the experience terminal, and determine the recommended storage location according to the remaining power, charging times and the free positions in the charging display space, and send it to the experience terminal.

[0148] It should be noted that when the user finishes using the VR headset, the corresponding headset device needs to be placed in the VR headset charging cabinet. Since there can be multiple empty charging positions in the VR headset charging cabinet at the same time for placing the headset devices for charging, and at the same time, the user can also place multiple headset devices simultaneously. However, there are certain differences in the remaining battery power or device performance of the multiple headset devices. For example, some headset devices have more remaining battery power, so relatively speaking, they require less charging time compared to the other placed headset devices. Therefore, the ones with more remaining battery power can be placed in the empty positions on the outer side. Or some devices charge quickly and can be fully charged in a short time, and they can also be placed on the outer side. Therefore, a multi-dimensional analysis can be carried out on the headset devices to be placed, so as to determine the best placement position for each device, which is convenient for the user to place quickly. At the same time, it enables the devices placed on the outer layer in the charging cabinet to be fully charged in a shorter time than those on the inner layer, facilitating the subsequent use by other users, so that other users can quickly obtain fully charged devices, thereby improving the usage efficiency and experience.

[0149] It can be understood that the placement request is the request information for placing the headset device in the charging cabinet, the remaining battery power is the battery power of the headset device to be placed, the idle position is the position in the charging display space where there is no headset model placed, and the recommended storage position is the position recommended for the experience terminal to place the device.

[0150] Through the above embodiments, the present invention can determine the recommended storage position, which is convenient for the user to quickly store the corresponding device, reduces the time for the user to find the charging position, and at the same time, it is also convenient for subsequent users to pick up, improving the scheduling and usage efficiency of the headset device.

[0151] In some embodiments, the specific implementation manner of step S3 (receiving the placement request from the experience terminal, obtaining the remaining battery power and the number of charging times of the headset device corresponding to the experience terminal, and determining the recommended storage position according to the remaining battery power, the number of charging times, and the idle positions in the charging display space, and sending it to the experience terminal) includes:

[0152] S301, receiving the placement request from the experience terminal, and retrieving the remaining battery power and the number of charging times of the placement device corresponding to the experience terminal based on the placement request.

[0153] It can be understood that when receiving the placement request sent by the experience terminal, the remaining battery power and the number of charging times of the corresponding placement device can be retrieved, so as to subsequently determine the recommended storage position corresponding to each placement device.

[0154] Among them, the placement device is the headset device that the experience terminal needs to place.

[0155] S302. Retrieve the idle positions in the charging display space, extract the corresponding row numbers of these positions as idle row numbers, and sort the idle row numbers in ascending order to obtain an idle row number sequence.

[0156] It can be understood that the corresponding idle row numbers are obtained through each idle position, and then the idle row numbers are sorted in ascending order to obtain a space row number sequence, so as to subsequently determine the recommended storage positions corresponding to each placement device according to the idle row number sequence.

[0157] Among them, the idle row number is the row number corresponding to the idle position, and the idle row number sequence is the row number sequence obtained after sorting the idle row numbers in ascending order. For example, when the obtained idle row numbers are 1 row, 3 rows, and 4 rows, the corresponding idle row number sequence is (1 row, 3 rows, 4 rows).

[0158] S303. Retrieve the charging reference times, obtain a charging placement coefficient based on the ratio of the charging times to the charging reference times, and obtain a corresponding placement times coefficient according to the product of the charging placement coefficient and the times weight.

[0159] It can be understood that since the charging times of the device will affect the charging duration of the device. For example, when the charging times of the device are more, the corresponding battery loss is greater, so the chargeable power will become smaller and the corresponding charging duration will become shorter. On the contrary, when the charging times are less, the corresponding full-charge duration is longer. Therefore, in order to determine the placement recommendation values corresponding to each placement device and select corresponding storage positions for each placement device, the charging times and the charging reference times can be retrieved for calculation, the charging placement coefficient and the times weight are obtained for multiplication, and then the placement times coefficient is obtained, which is convenient for obtaining accurate placement recommendation values subsequently.

[0160] Among them, the charging placement coefficient is the ratio of the charging times to the charging reference times, the times weight is the weight ratio corresponding to the charging times, which can be set in advance manually, and the placement times coefficient is the coefficient value corresponding to the influence of the charging times factor on the placement recommendation value, that is, the product of the charging placement coefficient and the times weight.

[0161] S304. Determine the corresponding charging duration according to the remaining power, retrieve the reference duration, obtain a placement duration coefficient based on the ratio of the reference duration to the charging duration, and obtain a duration placement coefficient according to the placement duration coefficient and the charging weight.

[0162] It can be understood that the reference duration is the reference value for determining the charging duration corresponding coefficient of the placement device, which is set artificially in advance. The placement duration coefficient is the ratio of the reference duration to the charging duration. The charging weight is the weight ratio corresponding to the charging duration, which can be set artificially in advance. The duration placement coefficient is the coefficient value of the influence of the charging duration factor on the placement recommendation value, that is, the product of the placement duration coefficient and the charging weight.

[0163] S305. Obtain the placement recommendation value corresponding to each placement device based on the placement times coefficient and the duration placement coefficient.

[0164] It can be understood that by calculating the sum value of the placement times coefficient and the duration placement coefficient, the placement recommendation value corresponding to the placement device is obtained, so as to subsequently determine the recommended placement position corresponding to the corresponding device according to the placement recommendation value, facilitating the personnel to quickly store the placement device at the corresponding position.

[0165] In some embodiments, the specific implementation manner in step S305 (obtaining the placement recommendation value corresponding to each placement device based on the placement times coefficient and the duration placement coefficient) includes:

[0166] S3051. Obtain the placement recommendation value corresponding to the head-mounted display device through the following formula,

[0167] where, is the placement recommendation value, is the charging reference times, is the charging times, is the times weight, is the reference duration, is the charging duration, is the charging weight.

[0168] It can be understood that when the charging times are more, the charging placement coefficient will also increase accordingly, and then the placement times coefficient will also become larger. At the same time, when the charging duration is smaller, the placement duration coefficient will increase accordingly, so that the duration placement coefficient will also increase. Furthermore, the value of the placement recommendation value will also become larger accordingly, which indicates that the corresponding device has more charging times and shorter required charging time, and can reach the full charge state quickly. Therefore, the placement recommendation value obtained for the corresponding placement device is large, and subsequently, the placement device with a large placement recommendation value can be preferentially stored on the outside of the charging cabinet, facilitating quick charging for subsequent personnel to continue using, and improving the scheduling and use efficiency of the head-mounted display device.

[0169] On the contrary, when the charging times are less, the charging placement coefficient will also decrease, and then the placement times coefficient will also become smaller. At the same time, when the charging duration is longer, the placement duration coefficient will become smaller accordingly, so that the duration placement coefficient will also decrease. Furthermore, the placement recommendation value will also become smaller. Then it can be shown that the corresponding device has fewer charging times, requires a longer charging time, and takes a longer time to reach the full charge state. Therefore, the placement recommendation value obtained for the corresponding placement device is small. Subsequently, the placement device with a small placement recommendation value can be stored inside the charging cabinet to leave sufficient time to charge the device.

[0170] S306. Sort the placement devices in descending order according to the placement recommendation value to obtain the headset placement sequence.

[0171] It can be understood that the headset placement sequence is the sequence obtained by sorting the placement devices in descending order according to the size of the placement recommendation value.

[0172] It is not difficult to understand that the placement devices are arranged according to the placement recommendation value to obtain the headset placement sequence, so as to subsequently determine the corresponding recommended storage positions in turn according to the arrangement order of the placement devices in the headset placement sequence, so that the placement devices can be charged at the corresponding positions while being convenient for subsequent personnel to pick up and use, improving the scheduling and allocation of the headset devices.

[0173] S307. Select the first placement device in the headset placement sequence as the outer placement device, select the corresponding last placement device as the inner placement device, and use the remaining placement devices as dynamic placement devices.

[0174] It can be understood that the outer placement device is the first placement device in the headset placement sequence, the inner placement device is the corresponding last placement device in the headset placement sequence, and the dynamic placement device is the placement device whose selected placement position changes dynamically.

[0175] Through the above implementation manners, the present invention can determine the corresponding outer placement device, inner placement device, and dynamic placement device, so as to subsequently determine the corresponding recommended storage positions for the corresponding headset devices.

[0176] S308. Retrieve the placement recommendation value corresponding to the outer placement device as the initial recommendation value, and retrieve the placement recommendation value corresponding to the inner placement device as the end recommendation value.

[0177] It can be understood that the initial recommendation value is the placement recommendation value corresponding to the outer placement device, and the end recommendation value is the placement recommendation value corresponding to the inner placement device.

[0178] Through the above embodiments, the present invention can determine the initial recommended value and the end recommended value, so as to calculate the corresponding recommended difference subsequently, and further determine the recommended storage positions corresponding to each placement device.

[0179] S309. Take the first free row number in the free row number sequence as the recommended storage position of the outer placement device, and take the initial recommended value as the placement comparison value of the first free row number.

[0180] It can be understood that, in order to facilitate the personnel at the experience end to store the placement devices and quickly charge the devices, and facilitate the subsequent use by personnel, the first free row number in the free row number sequence can be taken as the recommended storage position of the outer placement device, so as to facilitate the subsequent selection of the corresponding free position in the corresponding free row numbers for storing the outer placement device. Moreover, in order to determine the placement positions of the remaining devices, the initial recommended value can be taken as the placement comparison value of the first free row number, so as to calculate the corresponding recommended difference in combination with the placement comparison value corresponding to the inner placement device subsequently.

[0181] Among them, the placement comparison value is a value used to compare with the recommended value corresponding to the placement device, so as to calculate the corresponding recommended difference subsequently, and further determine the placement comparison values corresponding to the remaining free row numbers, which is convenient for determining the recommended storage positions corresponding to the dynamic placement devices.

[0182] S310. Take the last free row number in the free row number sequence as the recommended storage position of the inner placement device, and take the end recommended value as the placement comparison value of the last free row number.

[0183] It can be understood that since the placement recommended value corresponding to the inner placement device is the smallest, when determining the recommended storage position corresponding to the inner placement device, the corresponding storage position can be determined among the last free row numbers arranged in the free row number sequence. Therefore, the last free row number in the free row number sequence can be taken as the recommended storage position of the inner placement device, and the end recommended value can be taken as the placement comparison value of the last free row number, so as to determine the recommended difference subsequently, and further determine the recommended storage positions corresponding to the dynamic placement devices.

[0184] S311. Obtain the total recommended difference according to the difference between the initial recommended value and the end recommended value, determine the calculation quantity based on the number of rows corresponding to the free row numbers in the free row number sequence, and determine the recommended difference according to the total recommended difference and the calculation quantity.

[0185] It can be understood that the total recommended difference is the maximum difference for determining the placement recommended value of the device corresponding to the recommended storage location, that is, the difference between the initial recommended value and the end recommended value. The calculation quantity is the number of rows corresponding to the number of idle rows in the idle row sequence. For example, when the idle row sequence is (1 row, 3 rows, 4 rows), the number of rows is 3. Among them, since the difference calculation can only be performed between two adjacent rows, when the number of rows is 3, the corresponding calculation quantity is 3 - 1 = 2. Thus, the corresponding calculation quantity is 2, and the recommended difference is the difference between adjacent idle rows, that is, the ratio of the total recommended difference to the calculation quantity, and the recommended difference is obtained. For example, when the total recommended difference is 8 and the corresponding calculation quantity is 2, the recommended difference can be obtained as 8÷2 = 4.

[0186] It is not difficult to understand that there is a difference of one between the calculation quantity and the number of rows, that is, the number of rows minus 1 is equal to the calculation quantity, which is convenient for subsequent calculation of the accurate recommended difference.

[0187] S312. According to the recommended difference, the initial recommended value is successively decreased until it is equal to the end recommended value, and the placement comparison values corresponding to each of the idle rows are obtained.

[0188] It can be understood that according to the recommended difference, the initial recommended value is successively decreased until the remaining value is equal to the end recommended value, and the placement comparison values corresponding to each of the idle rows can be obtained. Among them, the recommended difference between the placement comparison values corresponding to two adjacent idle rows is the same.

[0189] For example, when the idle row sequence is (1 row, 3 rows, 4 rows), where the initial recommended value is 9 and the end recommended value is 1, the total recommended difference can be obtained as 8, and the calculation quantity is 2. When the recommended difference is 4, after successive decreases, 9 - 4 = 5, 5 - 4 = 1 are obtained. Then, the placement comparison value corresponding to the middle idle row (3 rows) can be obtained as 5, the placement comparison value corresponding to the idle row (1 row) is 10, and the placement comparison value corresponding to the idle row (4 rows) is 1.

[0190] Through the above embodiments, the present invention can determine the placement comparison values corresponding to each of the idle rows, which is convenient for subsequent comparison of the placement recommended values corresponding to each placement device with the placement comparison values to determine the idle row closest to the placement recommended value of the dynamic placement device as the recommended storage location.

[0191] S313. Based on the absolute value of the difference between the placement recommended value corresponding to the dynamic placement device and the placement comparison value, the comparison difference is obtained, and the idle row corresponding to the smallest comparison difference is determined as the recommended storage location of the corresponding dynamic placement device.

[0192] It can be understood that the absolute value of the difference is calculated between the placement recommendation value corresponding to the dynamic placement device and the placement comparison value corresponding to each idle row number, so as to obtain the comparison difference. Then, the idle row number corresponding to the smallest comparison difference can be selected as the recommended storage location for the corresponding dynamic placement device.

[0193] It is not difficult to understand that the smaller the comparison difference, the more matching the corresponding dynamic placement device is with the idle position of the corresponding row number. Furthermore, the idle row number corresponding to the smallest comparison difference can be determined as the recommended storage location for the corresponding dynamic placement device.

[0194] Among them, the comparison difference is the absolute value of the difference between the placement recommendation value and the placement comparison difference.

[0195] S314, send the recommended storage location to the experience terminal.

[0196] It can be understood that the recommended storage location is sent to the experience terminal so that the corresponding personnel can store the placement device at the corresponding location according to the recommended storage location.

[0197] S4, count the selection times of the experience terminal at each selection location, determine the preferred location of the experience terminal based on the selection times, and generate a recommended adjustment coefficient according to the preferred location.

[0198] It should be noted that different personnel have different preferences and habits for taking and placing. Some personnel prefer to store and retrieve the head-mounted device inside the VR head-mounted display charging cabinet, while some personnel prefer to store and retrieve the head-mounted device outside the VR head-mounted display charging cabinet. Therefore, in order to improve the experience of personnel and facilitate the personnel to store and retrieve the corresponding device, the calculation coefficient of the recommended location can be customized and adjusted according to the preferred location corresponding to the experience terminal, so as to conform to the preferred habits corresponding to each experience terminal.

[0199] It can be understood that the selection location is the location where the experience terminal stores and retrieves the head-mounted device, the selection times is the number of times of storage and retrieval corresponding to the selection location, the preferred location is the location where the experience terminal prefers to store and retrieve, and the recommended adjustment coefficient is the adjustment coefficient for calculating the recommended location.

[0200] In some embodiments, the specific implementation manner in step S4 (counting the selection times of the experience terminal at each selection location, determining the preferred location of the experience terminal based on the selection times, and generating a recommended adjustment coefficient according to the preferred location) includes:

[0201] S41, obtain the charging location selected by the experience terminal as the selection location, and accumulate the selection times of the selection locations with the same position row number to obtain the row number times.

[0202] It can be understood that the selected charging positions for access and selection at the experience end are such that the number of rows and times is the sum of the selection times of the selected positions corresponding to the same row numbers of positions.

[0203] S42. Determine the position corresponding to the maximum number of rows and times as the preferred position of the corresponding experience end, and adjust the corresponding position coefficient according to the preferred position to obtain a recommended adjustment coefficient.

[0204] It can be understood that the larger the number of rows and times, the more it indicates that the person is more accustomed to selecting positions in the corresponding rows. Therefore, the position corresponding to the maximum number of rows and times can be taken as the preferred position of the corresponding experience end. For example, when the number of times corresponding to the first row is 20 times, the number of times corresponding to the second row is 3 times, and the number of times corresponding to the third row is 5 times, the position corresponding to the first row can be taken as the preferred position of the experience end, and thus the position coefficient corresponding to the first row can be adjusted so that when making subsequent recommendations, the positions that meet the person's preferences can be recommended preferentially, thereby improving the person's experience.

[0205] In some embodiments, the specific implementation manner in step S42 (determining the position corresponding to the maximum number of rows and times as the preferred position of the corresponding experience end, and adjusting the corresponding position coefficient according to the preferred position to obtain a recommended adjustment coefficient) includes:

[0206] S421. Obtain the total number of rows of the charging positions corresponding in the VR headset charging cabinet, and judge the rows based on half of the total number of rows of positions.

[0207] It can be understood that the total number of rows of positions is the number of arranged rows corresponding to the charging positions in the VR headset charging cabinet. For example, it can be 3 rows or 5 rows, etc. The reference judgment row number is the reference value for determining the adjusted row number coefficient, that is, half of the total number of rows of positions is the reference judgment row number. For example, when the total number of rows of positions is 5, the corresponding reference judgment row number is 2.5.

[0208] S422. Determine the position corresponding to the maximum number of rows and times as the preferred position of the corresponding experience end, and upward-adjust the position coefficient corresponding to the preferred position based on the reference judgment row number to obtain a recommended adjustment coefficient.

[0209] It can be understood that by upward-adjusting the position coefficient corresponding to the preferred position, when making subsequent position recommendations for the corresponding experience end, calculations can be made according to the adjusted coefficient, so that the recommended positions are more in line with the person's selection preferences.

[0210] S423. Obtain the adjusted recommended adjustment coefficient through the following formula

[0211] where is the recommended adjustment coefficient is the position coefficient corresponding to the row, is the preferred position, is the reference judgment row number.

[0212] It can be understood that when the difference between the row number corresponding to the preferred position of the experience end and the reference judgment row number is larger, that is, the absolute value of will also be larger, and thus the corresponding adjustment ratio will become larger accordingly, and then the adjustment degree of the position coefficient of the corresponding row will also increase accordingly, so that the recommended adjustment coefficient becomes larger. When obtaining the recommended value in subsequent calculations, the recommended value corresponding to the corresponding row number will also become larger, and thus the position that meets the personnel's preferences can be recommended preferentially, improving the personnel's experience.

[0213] See Figure 3 , which is a schematic structural diagram of an intelligent management platform for a VR headset charging cabinet provided by an embodiment of the present invention. The intelligent management platform for the VR headset charging cabinet includes:

[0214] A construction module, configured to construct a charging twin cabinet corresponding to the VR headset charging cabinet, obtain the charging position of the headset device and the headset power, retrieve the headset model and place it at the charging position in the charging twin cabinet, and bind the headset power to the corresponding headset model to obtain a charging display space.

[0215] A determination module, configured to receive the project information sent by the experience end, determine the recommended extraction position in the charging display space according to the project information and the charging position, and perform prominent display on the charging display space based on the recommended extraction position, and send the recommended display space to the experience end.

[0216] A sending module, configured to receive the placement request of the experience end, obtain the remaining power and charging times of the headset device corresponding to the experience end, and determine the recommended storage position according to the remaining power, charging times and the free position in the charging display space, and send it to the experience end.

[0217] An adjustment module, configured to count the selection times of the experience end at each selection position, determine the preferred position of the experience end based on the selection times, and generate a recommended adjustment coefficient according to the preferred position.

[0218] See Figure 4 , which is a schematic hardware structure diagram of an electronic device provided by an embodiment of the present invention. The electronic device 40 includes: a processor 41, a memory 42 and a computer program; wherein

[0219] The memory 42 is used to store the computer program, and this memory can also be a flash memory. The computer program is, for example, an application program, a functional module, etc. that implement the above method.

[0220] A processor 41 for executing the computer program stored in the memory to implement each step performed by the device in the above method. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0221] Optionally, the memory 42 can be either independent or integrated with the processor 41.

[0222] When the memory 42 is a device independent of the processor 41, the device may further include:

[0223] A bus 43 for connecting the memory 42 and the processor 41.

[0224] The present invention also provides a readable storage medium storing a computer program, which when executed by a processor is used to implement the methods provided by the above various embodiments.

[0225] Among them, the readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium facilitating the transmission of a computer program from one place to another. The computer storage medium can be any available medium accessible by a general or special purpose computer. For example, the readable storage medium is coupled to the processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Additionally, the ASIC can be located in the user equipment. Of course, the processor and the readable storage medium can also exist as discrete components in the communication device. The readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0226] The present invention also provides a program product including execution instructions stored in a readable storage medium. At least one processor of the device can read the execution instructions from the readable storage medium, and the execution of the execution instructions by at least one processor causes the device to implement the methods provided by the above various embodiments.

[0227] In an embodiment of the above device, it should be understood that the processor may be a central processing unit (CPU for short), or other general-purpose processors, digital signal processors (DSP for short), application specific integrated circuits (ASIC for short), etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in combination with the present invention may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0228] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent management method for a VR headset charging cabinet, characterized in that, Including: Construct a charging twin cabinet corresponding to the VR headset charging cabinet, obtain the charging position of the headset device and the headset power, retrieve the headset model and place it at the charging position in the charging twin cabinet, and bind the headset power to the corresponding headset model to obtain a charging display space; Receive the project information sent by the experience terminal, determine the recommended extraction position in the charging display space according to the project information and the charging position, and prominently display the charging display space based on the recommended extraction position to obtain a recommended display space and send it to the experience terminal; Receive the placement request from the experience terminal, obtain the remaining power and charging times of the headset device corresponding to the experience terminal, and determine the recommended storage position according to the remaining power, charging times and the available positions in the charging display space, and send it to the experience terminal; Count the selection times of the experience terminal at each selection position, determine the preferred position of the experience terminal based on the selection times, and generate a recommended adjustment coefficient according to the preferred position.

2. The method according to claim 1, wherein: The step of receiving the project information sent by the experience terminal, determining the recommended extraction position in the charging display space according to the project information and the charging position, and prominently displaying the charging display space based on the recommended extraction position to obtain a recommended display space and sending it to the experience terminal includes: Receive the project information sent by the experience terminal, determine the corresponding project duration based on the project information, and retrieve the limited power according to the project duration; Based on the limited power, count the headset models corresponding to the headset power greater than or equal to the limited power as the initial selection models; Retrieve the charging position and charging times corresponding to the initial selection model, and obtain the extraction recommendation value of each initial selection model based on the charging position and the charging times; Sort the charging positions of each initial selection model in descending order based on the extraction recommendation value to obtain a position selection sequence; Receive the required quantity sent by the experience terminal, perform position selection on the position selection sequence according to the required quantity to obtain the recommended extraction position corresponding to the recommended headset; Prominently display the charging display space based on the recommended extraction position to obtain a recommended display space and send it to the experience terminal.

3. The method according to claim 2, wherein: The step of retrieving the charging position and charging times corresponding to the initial selection model, and obtaining the extraction recommendation value of each initial selection model based on the charging position and the charging times includes: Retrieve the charging position and charging times corresponding to the initial selection model, obtain the corresponding position row number based on the charging position, and obtain the corresponding position coefficient according to the position row number. The position row number has a one-to-one corresponding position coefficient; Retrieve the charging reference times, obtain the charging extraction coefficient based on the ratio of the charging reference times to the charging times, and obtain the extraction times coefficient corresponding to each initial selection model according to the product of the charging extraction coefficient and the times weight; Obtain the extraction recommendation value corresponding to each initial selection model according to the sum value of the extraction times coefficient and the position coefficient; The removal recommendation values corresponding to each of the initial selection models are obtained through the following formula. Among them, is to extract the recommended value, is the reference number of charging times, is the number of charging times, is the weight of the number of times, is the position coefficient corresponding to the 5. The method according to claim 3, wherein receiving the placement request of the experience terminal, obtaining the remaining power and the number of charging times of the head-mounted device corresponding to the experience terminal, and determining a recommended storage location based on the remaining power, the number of charging times, and the idle positions in the charging display space, and sending the recommended storage location to the experience terminal, includes: Receiving the placement request of the experience terminal, and retrieving the remaining power and the number of charging times of the placement device corresponding to the experience terminal based on the placement request; Retrieving the idle positions in the charging display space, extracting the corresponding row numbers of the positions as idle row numbers based on the idle positions, and arranging the idle row numbers in ascending order to obtain an idle row number sequence; Retrieving a charging reference number of times, obtaining a charging placement coefficient based on the ratio of the number of charging times to the charging reference number of times, and obtaining a corresponding placement number coefficient based on the product of the charging placement coefficient and the number weight; Determining a corresponding charging duration based on the remaining power, retrieving a reference duration, obtaining a placement duration coefficient based on the ratio of the reference duration to the charging duration, and obtaining a duration placement coefficient based on the placement duration coefficient and the charging weight; Obtaining the placement recommendation values corresponding to each of the placement devices based on the placement number coefficient and the duration placement coefficient; Sorting the placement devices in descending order according to the placement recommendation values to obtain a head-mounted device placement sequence; Selecting the first placement device as the outer placement device based on the head-mounted device placement sequence, taking the last corresponding placement device as the inner placement device, and taking the remaining placement devices as dynamic placement devices; Retrieving the placement recommendation value corresponding to the outer placement device as an initial recommendation value, and retrieving the placement recommendation value corresponding to the inner placement device as an end recommendation value; Taking the first idle row number in the idle row number sequence as the recommended storage location of the outer placement device, and taking the initial recommendation value as the placement comparison value of the first idle row number; Taking the last idle row number in the idle row number sequence as the recommended storage location of the inner placement device, and taking the end recommendation value as the placement comparison value of the last idle row number; Obtaining a total recommendation difference based on the difference between the initial recommendation value and the end recommendation value, determining a calculation number based on the number of rows corresponding to the idle row numbers in the idle row number sequence, and determining a recommendation difference based on the total recommendation difference and the calculation number; Performing a sequential decreasing process on the initial recommendation value according to the recommendation difference until it is equal to the end recommendation value to obtain the placement comparison values corresponding to each of the idle row numbers; Obtaining a comparison difference based on the absolute value of the difference between the placement recommendation value corresponding to the dynamic placement device and the placement comparison value, and determining the idle row number corresponding to the smallest comparison difference as the recommended storage location of the corresponding dynamic placement device; Sending the recommended storage location to the experience terminal.

6. The method according to claim 4, wherein obtaining the placement recommendation values corresponding to each of the placement devices based on the placement number coefficient and the duration placement coefficient, includes: The placement recommendation value corresponding to the head-mounted device is obtained through the following formula, Among them, is the placement recommended value, is the charging reference number of times, is the charging number of times, is the number of times weight, is the reference duration, is the charging duration, is the charging weight.

6. The method according to claim 5, wherein the method of counting the selection times of the experience end at each selected position, determining the preferred position of the experience end based on the selection times, and generating a recommended adjustment coefficient according to the preferred position includes: Obtain the charging position selected by the experience end as the selected position, accumulate the selection times of the selected positions corresponding to the same position row number, and obtain the row number times; Determine the maximum row number times as the preferred position of the corresponding experience end, and adjust the corresponding position coefficient according to the preferred position to obtain the recommended adjustment coefficient.

7. The method according to claim 6, wherein the method of determining the maximum row number times as the preferred position of the corresponding experience end, adjusting the corresponding position coefficient according to the preferred position, and obtaining the recommended adjustment coefficient includes: Obtain the total number of rows of the charging positions corresponding to the VR head-mounted display charging cabinet, and judge the row number based on half of the total number of rows of the positions; Determine the maximum row number times as the preferred position of the corresponding experience end, and upwardly adjust the position coefficient corresponding to the preferred position based on the row number judged by the benchmark to obtain the recommended adjustment coefficient; The adjusted recommended adjustment coefficient is obtained through the following formula, Among them, is the recommended adjustment coefficient, is the position coefficient corresponding to the th row, is the preferred position, is the reference judgment row number. It should be noted that there seems to be an error in the original text where the description of "is the reference judgment row number" is not properly connected in the Chinese text. The above translation tries to make sense of the overall context as accurately as possible.

8. The method according to claim 7, wherein It further includes: Receiving the head-mounted display image collected by the acquisition device, retrieving the preset pixel value, and performing stain recognition on the head-mounted display image based on OpenCV and the preset pixel value to obtain stain pixel points; Obtain multiple stain regions according to adjacent stain pixel points, count the number of stain regions to obtain the region number, and count the number of pixel points in all stain regions as the stain pixel number; Obtain the region coefficient according to the product of the region number and the region weight, obtain the pixel point coefficient based on the product of the stain pixel number and the pixel point number weight, and obtain the stain coefficient according to the sum value of the region coefficient and the pixel point coefficient; Retrieve the removal times coefficient, the position coefficient, and the stain coefficient, and obtain the removal recommendation value corresponding to each initial selection model based on the removal times coefficient, the position coefficient, and the stain coefficient.

9. The method according to claim 8, wherein the method of retrieving the removal times coefficient, the position coefficient, and the stain coefficient, and obtaining the removal recommendation value corresponding to each initial selection model based on the removal times coefficient, the position coefficient, and the stain coefficient includes: The removal recommendation value corresponding to each initial selection model is obtained through the following formula, Among them, is to extract the recommended value, is the charging reference number of times, is the charging number of times, is the weight of the number of times, is the position coefficient corresponding to the row, is the number of regions, is the region weight, is the number of stain pixels, is the weight of the number of pixel points, is the stain weight.

10. An intelligent management platform for a VR headset charging cabinet, characterized in that, including: A construction module for constructing a charging twin cabinet corresponding to the VR head-mounted display charging cabinet, obtaining the charging position of the head-mounted device and the head-mounted display power, retrieving the head-mounted display model and placing it at the charging position in the charging twin cabinet, and binding the head-mounted display power to the corresponding head-mounted display model to obtain a charging display space; A determination module, configured to receive project information sent by an experience terminal, determine a recommended removal position in the charging display space according to the project information and the charging position, and perform prominent display on the charging display space based on the recommended removal position, so as to obtain a recommended display space and send it to the experience terminal; A sending module, configured to receive a placement request from the experience terminal, obtain the remaining power and charging times of the corresponding headset device of the experience terminal, and determine a recommended storage position according to the remaining power, charging times and the idle positions in the charging display space, and send it to the experience terminal; An adjustment module, configured to count the selection times of the experience terminal at each selection position, determine the preferred position of the experience terminal based on the selection times, and generate a recommended adjustment coefficient according to the preferred position.

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