Smart library guide system based on VR

Abstract

The invention discloses a smart library guide system based on VR, and relates to the technical field of library guide, the core architecture of the smart library guide system based on VR is formed through the mutual cooperation of three groups of algorithm units, and the system optimization value So is calculated in a database through the combination of the three algorithm units. The intelligent library guide system can feed back and dynamically adjust parameters such as rendering precision and frame rate of the VR equipment in real time through the system optimization value So, find an optimal balance point between energy consumption and performance, pay attention to energy efficiency ratio while pursuing user experience, effectively reduce system energy consumption on the premise of ensuring that the user experience is not reduced or improved, and improve the user experience. According to the intelligent library navigation system, the equipment endurance time is prolonged, the energy consumption is reduced, long-time use of the VR equipment is ensured when many people exist in a library, so that normal use of the intelligent library navigation system is ensured, and the system can more flexibly adapt to changes of different users and environments through the real-time feedback mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of library navigation, and specifically provides a VR-based intelligent library navigation system. Background Art

[0002] A library is an institution that collects, collates, and stores books and materials for people to read and refer to. Libraries have existed since 3000 BC. Libraries have functions such as preserving human cultural heritage, developing information resources, and participating in social education. In some larger libraries, there are multiple book areas. To facilitate the people entering to find the corresponding books, a library navigation device is set at the entrance of the library to help people entering the library find the route and the corresponding book area information. However, most of the existing library navigation devices are flat maps with relatively simple information.

[0003] VR refers to virtual reality technology, which is a brand-new practical technology developed in the 20th century. Virtual reality technology encompasses computer, electronic information, and simulation technologies. Its basic implementation method is mainly based on computer technology, using and integrating the latest development results of various high-techs such as three-dimensional graphics technology, multimedia technology, and simulation technology, and generating a virtual world with a realistic three-dimensional visual, tactile, olfactory, and other sensory experiences through devices such as computers.

[0004] After processing the image information of the library through 3D modeling and importing it into the VR device, users can conduct 3D stereoscopic navigation by wearing the VR device. However, the current VR-based intelligent library navigation system still has the following problems during use:

[0005] 1. Due to the high cost of VR devices, it is difficult for a library to equip multiple VR devices. As a mobile device, in order to improve the performance of the existing VR devices in the calculation, the power consumption of the devices is ignored, and it is difficult to find the best balance between the power consumption and performance of the devices. When there are many people in the library, the low battery life of the VR device is difficult to ensure the normal use of the intelligent library navigation system.

[0006] 2. For the existing VR devices, it is difficult to adjust the image quality and frame rate of the VR device when the user deviates from the navigation route during the navigation process, and it is difficult to help the user return to the correct navigation path by increasing the frame rate.

[0007] Therefore, there is an urgent need for a VR-based intelligent library navigation system to solve the above problems. Summary of the Invention

[0008] The purpose of the present invention is to provide a VR-based intelligent library navigation system to solve the problems raised in the above background art.

[0009] To achieve the above object, the present invention provides the following technical solutions: A VR-based intelligent library navigation system, comprising:

[0010] A data collection module for collecting data of VR devices;

[0011] A data preprocessing module for decoding and preprocessing the data information in the database to obtain the parameters participating in the calculation in the calculation processing module;

[0012] A calculation processing module for inputting the parameters obtained after decoding and preprocessing into the VR image quality value algorithm unit to calculate the VR image quality value VRiq;

[0013] Input the VR image quality value VRiq into the user experience value algorithm unit in the calculation processing module to calculate the user experience value Ue;

[0014] Input the user experience value U into the system optimization value algorithm unit in the calculation processing module to calculate the system optimization value So and upload it to the database;

[0015] Adjust the parameter values in the calculation processing module through the feedback adjustment unit.

[0016] Optionally, the data collection of the VR device specifically includes: obtaining the monocular resolution Mr, maximum frame rate Fps max , minimum frame rate Fps min , total system energy consumption Ec max ;

[0017] Obtaining the frame rate Fps and latency Lat through the built-in performance monitoring tool of the VR device;

[0018] Obtaining the number of polygons Pc, field of view angle Fov, and optimal navigation path length Toup from the built-in 3D modeling software of the VR device;

[0019] Obtaining the system energy consumption Ec, user stay time St, and user path deviation △T through the built-in sensor of the VR device;

[0020] Upload them to the database together.

[0021] Optionally, adjusting the parameter values in the calculation processing module through the feedback adjustment unit specifically includes:

[0022] Setting the good threshold Y of the system optimization value So in the database to 1.8 times And comparing the system optimization value So with the good threshold Y:

[0023] When the system optimization value So > the good threshold Y, it is considered that the system needs to perform energy efficiency optimization, and the values of the image adjustment coefficient α in the VR image quality value algorithm unit and the frame rate adjustment coefficient β in the user experience value algorithm unit are adjusted.

[0024] Optionally, the calculation and processing module includes a VR image quality value algorithm unit, a user experience value algorithm unit, a system optimization value algorithm unit, and a feedback adjustment unit.

[0025] Optionally, the VR image quality value algorithm unit is as follows:

[0026]

[0027] Where:

[0028] VRiq represents the VR image quality value;

[0029] Mr represents the monocular resolution:

[0030] Pc represents the number of polygons;

[0031] Fov represents the field of view angle;

[0032] α is the image adjustment coefficient, with a preset value of 1, which can be self-adjusted in the intelligent library navigation system;

[0033] In the formula calculation:

[0034] Mr -0.8 This part is used as the denominator of the formula calculation. As the monocular resolution Mr increases, Mr -0.8 This part of the value decreases, thereby increasing the calculated VR image quality value Mr. The non-linear influence of the resolution on the calculation of the VR image quality value VRiq is reflected by the power function. As the monocular resolution Mr increases, the VR image quality value will increase, but the growth rate will slow down, meaning that the higher the resolution, the greater the marginal quality improvement will be, but the enhancement effect will gradually weaken;

[0035] The number of polygons Pc measures the fineness of the scene model through the logarithmic function. As the number of polygons Pc increases, a more realistic and complex VR scene is formed, thereby improving the calculated VR image quality value VRiq. The logarithmic function can avoid the excessive influence on the calculation of the VR image quality value caused by simply stacking polygons;

[0036] This part sin(Fov - 30°) quantifies the impact of the wide-angle change on the immersion by taking the sine value after subtracting 30° from the field of view angle Fov. The normal human visual field range is 120°. Specifically:

[0037] When the field of view angle Fov is 120°, sin(Fov - 30°) has π / 2 inside the parentheses, and sin(Fov - 30°) reaches the maximum value of the sine function, which is 1, indicating that the field of view angle at this time is the most suitable angle for the human body;

[0038] When the field of view angle Fov decreases from 120°, the field of view range becomes smaller and the immersion decreases. The value of sin(Fov - 30°) decreases, thereby reducing the calculated VR image quality value VRiq;

[0039] When the field of view angle Fov increases from 120°, although the field of view range becomes larger, it has exceeded the visual angle range familiar to normal people, which will increase the visual fatigue of the user. The value of sin(Fov - 30°) decreases, thereby reducing the calculated VR image quality value VRi.

[0040] Optionally, the user experience value algorithm unit is as follows:

[0041]

[0042] Among them:

[0043] Ue represents the user experience value;

[0044] VRiq represents the VR image quality value;

[0045] Fps represents the frame rate;

[0046] Fps max represents the maximum frame rate;

[0047] Fps min represents the minimum frame rate;

[0048] Lat represents the latency;

[0049] β represents the frame rate adjustment coefficient, with a preset value of 1.2, which can be self-adjusted in the intelligent library navigation system;

[0050] In the formula calculation:

[0051] This part is through the difference between the frame rate Fps and the minimum frame rate Fps max and the ratio of the difference between the maximum frame rate Fps max and the minimum frame rate Fps min to normalize the influence degree of the frame rate Fps on the user experience value to the numerical range of (0, 1). Specifically:

[0052] As the frame rate Fps increases, the frame rate Fps gets closer to Fps max , The closer the value of this part is to 1, it represents that the frame rate Fps at this time is at the maximum value of the device. The increase in the value of this part will have a positive impact on the calculation of the user experience value Ue.

[0053] As the frame rate Fps decreases The value of this part decreases. The decrease in the value of this part represents that the device is in a frame drop state, reducing the calculated user experience value Ue.

[0054] This part, as the exponential part of the natural constant e, compares the latency Lat with the reference value of 20ms. Specifically:

[0055] When the latency Lat > 20, based on the reference value of 20ms, for every 10 increase in the latency Lat, the exponential part increases by 1. The increase in the denominator of this part reduces the calculated user experience value Ue:

[0056] When the latency Lat < 20, The value of this exponential term is negative. The decrease in this part increases the calculated user experience value Ue.

[0057] Optionally, the system optimization value algorithm unit is as follows:

[0058]

[0059] Where:

[0060] So represents the system optimization value;

[0061] Ue represents the user experience value;

[0062] Ec represents the system energy consumption;

[0063] St represents the user stay time;

[0064] △T represents the user path deviation;

[0065] Toup represents the optimal navigation path length;

[0066] In the formula calculation:

[0067] When the system energy consumption Ec of the VR device is high, the device will have problems such as slow response and overheating. As the numerator in the formula, by taking the square root of the system energy consumption Ec, while maintaining the positive impact of the system energy consumption Ec on the system optimization value So, it reduces the excessive impact of the system energy consumption Ec on the calculation result;

[0068] Dividing the user experience value Ue by the square root of the system energy consumption Ec represents the user experience efficiency per unit energy consumption. This part, as the reciprocal of the user experience efficiency per unit energy consumption, indicates that as the user experience value Ue increases, the VR device is operating effectively and does not require system optimization, thus reducing the calculated system optimization value So.

[0069] The larger the user stay time St, the less clear the user's path to find the target book, and the user needs to stop and think about the path. This part is processed by taking the square root of the quotient of the maximum stay time 5 that the system can tolerate divided by the difference between the maximum stay time 5 and the user stay time St to reflect the non-linear impact of the user stay time St on the system optimization value So. Specifically:

[0070] When the user stay time St is 0, it means the user's path to find the target book is clear. This part has a value of 1, and at this time, the user stay time St will not affect the calculation of the system optimization value So.

[0071] As the user stay time St increases, This part has an increasing value, thus increasing the calculated system optimization value So.

[0072] This part standardizes the system optimization value So with respect to the user path deviation △T through the optimal navigation path length Toup to reflect the linear impact of the user path deviation △T on the system optimization value So. Specifically:

[0073] When the user path deviation △T is 0, This part has a value of 1, indicating that at this time the user does not deviate from the optimal navigation path and no system optimization is required.

[0074] When the user path deviation △T increases, This part has an increasing value, indicating that at this time the user deviates from the optimal navigation path, increasing the calculated system optimization value So.

[0075] Optionally, the specific adjustment formulas for the image adjustment coefficient α and the frame rate adjustment coefficient β are as follows:

[0076]

[0077] Where:

[0078] Ec represents the system energy consumption, which is the current system energy consumption of the VR device.

[0079] Ec max Represents the total system energy consumption, which is the total system energy consumption that the VR device has when fully charged.

[0080] Fps represents the frame rate;

[0081] Fps max represents the maximum frame rate;

[0082] After adjustment, α new <α, β new >β.

[0083] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0084] First, through the mutual cooperation of three groups of algorithm units, the present invention jointly constitutes the core architecture of a VR-based intelligent library navigation system. By calculating the system optimization value So in the database, the intelligent library navigation system can dynamically adjust parameters such as the rendering precision and frame rate of the VR device in real time through the system optimization value So, and can find the best balance between energy consumption and performance. Thus, while pursuing the user experience, it pays attention to the energy efficiency ratio, can effectively reduce the system energy consumption, extend the device battery life, reduce energy consumption, ensure the long-term use of the VR device when there are many people in the library, and ensure the normal use of the intelligent library navigation system.

[0085] Second, by comparing the system optimization value So with the good threshold Y in the database, when the system optimization value So is relatively large, it means that the user deviates from the navigation route. At this time, the system can automatically adjust the values of the image adjustment coefficient α and the frame rate adjustment coefficient β to reduce the VR device image quality and increase the frame rate, making it easier for the user to return to the correct navigation path. This real-time feedback mechanism enables the intelligent library navigation system to more flexibly adapt to the changes of different users and environments, and improves the performance and user experience of the intelligent library navigation system. Description of the Drawings

[0086] Figure 1 is a flowchart of a VR-based intelligent library navigation system;

[0087] Figure 2 is an overall structural schematic diagram of a VR-based intelligent library navigation system. Detailed Embodiments

[0088] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0089] Example 1, please refer to Figures 1 to 2, the present invention provides a VR-based intelligent library navigation system, including:

[0090] A data collection module for collecting data of VR devices, specifically including: obtaining the monocular resolution Mr, maximum frame rate Fps from the specifications of VR devices max , minimum frame rate Fps min , total system energy consumption Ec max ;

[0091] Obtaining the frame rate Fps and latency Lat through the built-in performance monitoring tool of the VR device;

[0092] Obtaining the number of polygons Pc, field of view angle Fov, and optimal navigation path length Toup from the built-in 3D modeling software of the VR device;

[0093] Obtaining the system energy consumption Ec, user stay time St, and user path deviation △T through the built-in sensor of the VR device;

[0094] Uploading them to the database together;

[0095] A data preprocessing module for decoding and preprocessing the data information in the database to obtain the parameters participating in the calculation in the calculation processing module;

[0096] A calculation processing module for inputting the parameters obtained after decoding and preprocessing into the VR image quality value algorithm unit to calculate the VR image quality value VRiq;

[0097] Inputting the VR image quality value VRiq into the user experience value algorithm unit in the calculation processing module to calculate the user experience value Ue;

[0098] Inputting the user experience value U into the system optimization value algorithm unit in the calculation processing module to calculate the system optimization value So and uploading it to the database;

[0099] Adjusting the parameter values in the calculation processing module through the feedback adjustment unit, specifically including:

[0100] Setting the good threshold Y of the system optimization value So in the database to 1.8 times And comparing the system optimization value So with the good threshold Y:

[0101] When the system optimization value So > the good threshold Y, it is considered that the system needs energy efficiency optimization, and adjust the image adjustment coefficient α in the VR image quality value algorithm unit and the frame rate adjustment coefficient β in the user experience value algorithm unit.

[0102] After 3D modeling the image information of the library and importing it into the VR device, users can conduct 3D stereoscopic guided tours by wearing the VR device. This is a relatively mature existing technology in the VR field and will not be elaborated here.

[0103] Through the mutual cooperation of three algorithm units, the present invention constitutes the core architecture of a VR-based intelligent library guided tour system. By comprehensively considering multiple influencing factors such as the user experience value Ue, the system energy consumption Ec, and the user path deviation △T, the system optimization value So is calculated. On the one hand, the intelligent library guided tour system can, through the system optimization value So, real-time feedback and dynamically adjust parameters such as the rendering accuracy and frame rate of the VR device, so as to find the best balance point between energy consumption and performance, pay attention to the energy efficiency ratio while pursuing the user experience, effectively reduce the system energy consumption, extend the device battery life, reduce energy consumption, ensure the long-term use of the VR device when there are many people in the library, and ensure the normal use of the intelligent library guided tour system;

[0104] On the other hand, in the database, the system optimization value So is compared with the good threshold Y. When the system optimization value So is larger, it means that the user deviates from the best route. At this time, the system can automatically adjust the values of the image adjustment coefficient α and the frame rate adjustment coefficient β to reduce the VR device image quality and increase the frame rate, making it easier for the user to return to the correct guided tour path. That is, the system optimization value So, as a comprehensive index of system optimization, can be real-time fed back to the VR image quality value algorithm unit and the user experience value algorithm unit for parameter adjustment. This real-time feedback mechanism enables the intelligent library guided tour system to more flexibly adapt to the changes of different users and environments, improving the user experience and the performance of the intelligent library guided tour system.

[0105] In this embodiment:

[0106] The present invention comprehensively considers multiple influencing factors and calculates the estimated value of resource input Er, which can accurately predict the resource input volume on the (t + 1)th day, providing scientific and reliable data support for the informatization management of the construction progress of the construction project and the decision-making of resource allocation.

[0107] Please refer to Figures 1 to 2 , the VR image quality value algorithm unit is as follows:

[0108]

[0109] Among them:

[0110] VRiq represents the VR image quality value;

[0111] Mr represents the monocular resolution, which refers to the image resolution actually rendered by each eye in the VR headset and is obtained from the specifications of the VR device. The unit is K, and 1K = 1024 pixels:

[0112] Pc represents the number of polygons, which is the number of polygons rendered by the VR device in the virtual reality scene and is obtained from the built-in 3D modeling software of the VR device;

[0113] Fov represents the field of view angle, which refers to the field of vision that the user can see when wearing the VR headset. The larger the field of view angle, the wider the field of vision the user feels and the stronger the immersion;

[0114] α is the image adjustment coefficient, with a preset value of 1, which can be self-adjusted in the intelligent library navigation system;

[0115] In the formula calculation:

[0116] The monocular resolution Mr is the cornerstone of image clarity. As the monocular resolution Mr increases, Mr -0.8 This part serves as the denominator of the formula calculation. As the value decreases, the calculated VR image quality value Mr increases. The resolution's non-linear impact on the calculation of the VR image quality value VRiq is reflected through a power function. As the monocular resolution Mr increases, the VR image quality value will increase, but the growth rate will slow down, meaning that the higher the resolution, the greater the marginal quality improvement, but the enhancement effect will gradually weaken;

[0117] The number of polygons Pc measures the fineness of the scene model through a logarithmic function. As the number of polygons Pc increases, a more realistic and complex VR scene is formed, thereby increasing the calculated VR image quality value VRiq. The logarithmic function can avoid the excessive impact on the calculation of the VR image quality value caused by simply piling up polygons;

[0118] This part of sin(Fov - 30°) is obtained by taking the sine value after subtracting 30° from the field of view angle Fov, and is used to quantify the impact of the wide-angle change on the immersion. The normal field of vision range of a person is 120°. Specifically:

[0119] When the field of view angle Fov is 120°, the value inside the parentheses of sin(Fov - 30°) is π / 2, and sin(Fov - 30°) reaches the maximum value of 1 of the sine function, representing that the field of view angle at this time is the most suitable angle for the human body;

[0120] When the field of view angle Fov decreases from 120°, the field of vision range becomes smaller, the immersion decreases, and the value of this part of sin(Fov - 30°) decreases, thereby reducing the calculated VR image quality value VRiq;

[0121] When the field of view Fov increases from 120°, although the field of view becomes larger, it has exceeded the viewing angle range that normal people are familiar with, which will increase the user's visual fatigue. The value of sin (Fov-30°) decreases, thereby reducing the calculated VR image quality value VRiq.

[0122] In this embodiment:

[0123] The VR image quality value algorithm unit determines whether the image the user sees in the VR environment is clear and delicate by incorporating the monocular resolution Mr into the formula calculation. High-resolution images can reduce pixelation, making the details of the books, bookshelves, decorations, etc. in the library more realistic and recognizable, thereby enhancing the user's reading experience and exploration fun. The number of polygons Pc and the field of view Fov are key factors affecting immersion. More polygons can build more complex and realistic scenes, while a wide field of view makes users feel as if they are in a real library environment. By optimizing these parameters and calculating VRiq, the user's sense of immersion can be significantly enhanced, making the user more engaged in VR images.

[0124] And by calculating the VR image quality value VRiq in the database, the smart library navigation system can understand the image rendering capabilities of the current VR device and reasonably allocate computing resources and storage resources based on this indicator. For example, for areas with higher image quality requirements (areas with denser books), the system can allocate more GPU resources to render polygons and textures to ensure the best image quality, thereby ensuring that users get the best navigation experience in the smart library.

[0125] See also Figures 1 to 2 , the user experience value algorithm unit is as follows:

[0126]

[0127] in:

[0128] Ue represents the user experience value;

[0129] VRiq stands for VR image quality value;

[0130] Fps stands for frame rate, which is the display frame rate of the VR headset obtained through the performance monitoring tool built into the VR device;

[0131] Fps max It stands for maximum frame rate, which is the maximum frame rate that a VR headset can display. It is obtained from the specifications of the VR device.

[0132] Fps min Represents the minimum frame rate, which is the minimum frame rate that the VR headset can display, obtained from the specifications of the VR device;

[0133] Lat represents the latency in ms, which is obtained through the performance monitoring tool built into the VR device;

[0134] β represents the frame rate adjustment coefficient, with a preset value of 1.2, which can be self-adjusted in the intelligent library navigation system;

[0135] In the formula calculation:

[0136] This part is calculated by the ratio of the difference between the frame rate Fps and the minimum frame rate Fps max to the difference between the maximum frame rate Fps max and the minimum frame rate Fps min This normalizes the influence degree of the frame rate Fps on the user experience value to the numerical range of (0, 1). Specifically:

[0137] As the frame rate Fps increases, the closer the frame rate Fps is to Fps max , the closer the value of this part is to 1, indicating that the frame rate Fps at this time is at the maximum value of the device. The increase in the value of this part has a positive impact on the calculation of the user experience value Ue;

[0138] As the frame rate Fps decreases the value of this part decreases, and the decrease in the value of this part indicates that the device is in a frame drop state, reducing the calculated user experience value Ue;

[0139] This part is used as the exponential part of the natural constant e, comparing the latency Lat with the reference value of 20 ms. Specifically:

[0140] When the latency Lat > 20, based on the reference value of 20 ms, for every 10 increase in Lat, the exponential part increases by 1. The increase in the denominator of this part reduces the calculated user experience value Ue:

[0141] When the latency Lat < 20, the value of the exponential term of this part is negative, and the decrease in this part increases the calculated user experience value Ue.

[0142] In this embodiment:

[0143] The VR image quality value VRiq reflects the clarity and fineness of the images of VR headset devices, the frame rate Fps embodies the smoothness of the VR headset device's screen, and the latency lst is directly related to the response speed of user operations. The user experience value algorithm unit comprehensively considers these three key influencing parameters: the VR image quality value VRiq, the frame rate Fps, and the latency lst, and calculates the user experience value Ue, which can more comprehensively evaluate the actual experience of users in the VR navigation system.

[0144] In the database of the VR-based intelligent library navigation system, the user experience value Ue can be used as a reference index for system performance optimization. The settings of VR devices and the allocation of system resources can be adjusted according to the user experience value Ue. Specifically:

[0145] The intelligent library navigation system can, based on the calculated user experience value Ue, provide real-time feedback and dynamically adjust parameters. For example, when detecting an increase in latency, it can automatically reduce the rendering precision, or when the user is stationary, it can improve the image quality to achieve a dynamic balance among image quality, frame rate, and latency, enhancing the overall performance of the intelligent library navigation system and thus achieving the best user experience.

[0146] When upgrading the intelligent library navigation system, the user experience value Ue can be one of the important bases for selecting VR devices. By comparing the user experience values Ue of different devices under the same conditions, the most suitable VR device for the current intelligent library navigation system can be selected to ensure that users obtain the best navigation experience. Moreover, with the progress of technology and the emergence of new VR devices, regularly calculating and comparing the user experience values Ue of different devices can provide scientific and reliable data support for the upgrade decision of the intelligent library navigation system.

[0147] Please refer to Figures 1 to 2 , the system optimization value algorithm unit is as follows:

[0148]

[0149] Among them:

[0150] So represents the system optimization value;

[0151] Ue represents the user experience value;

[0152] Ec represents the system energy consumption, which is the current system energy consumption of the VR device;

[0153] St represents the user stay time, with the unit of minutes, St ∈ [0, 4]. When the user stay time St is greater than 4, the value is taken as 4;

[0154] △T represents the user path deviation, with the unit of meters, △T ∈ [0, 5];

[0155] Toup represents the optimal navigation path length, in meters;

[0156] In the formula calculation:

[0157] When the system energy consumption Ec of the VR device is high, the device will have problems of slow response and overheating, As the numerator in the formula, by taking the square root of the system energy consumption Ec, while maintaining the positive impact of the system energy consumption Ec on the system optimization value So, the excessive impact of the system energy consumption Ec on the calculation result is reduced;

[0158] By dividing the user experience value Ue by the square root of the system energy consumption Ec, the user experience efficiency under unit energy consumption is obtained, This part is the reciprocal of the user experience efficiency under unit energy consumption. As the user experience value Ue increases, it means that the VR device is operating effectively and does not require system optimization, thus reducing the calculated system optimization value So;

[0159] The larger the user stay time St, the less clear the path for the user to find the target book, and the user needs to stop and think about the path, This part is processed by taking the square root of the whole after dividing the maximum stay time 5 that the system can tolerate by the difference between the maximum stay time 5 and the user stay time St, to reflect the non-linear impact of the user stay time St on the system optimization value So. Specifically:

[0160] When the user stay time St is 0, it means that the path for the user to find the target book is clear, The value of this part is 1, and at this time, the user stay time St will not affect the calculation of the system optimization value So;

[0161] As the user stay time St increases, The value of this part increases, thus increasing the calculated system optimization value So;

[0162] This part standardizes the system optimization value So by the optimal navigation path length Toup with respect to the user path deviation △T, to reflect the linear impact of the user path deviation △T on the system optimization value So. Specifically:

[0163] When the user path deviation △T is 0, The value of this part is 1, representing that the user does not deviate from the optimal navigation path at this time and does not require system optimization;

[0164] When the user path deviation △T increases, The value of this part increases, representing that the user deviates from the optimal navigation path at this time and increases the calculated system optimization value So;

[0165] Set the good threshold Y of the system optimization value So in the database to 1.8 times And compare the system optimization value So with the good threshold Y:

[0166] When the system optimization value So > the good threshold Y, it is considered that the system needs to optimize energy efficiency, and adjust the values of the image adjustment coefficient α in the VR image quality value algorithm unit and the frame rate adjustment coefficient β in the user experience value algorithm unit. The specific adjustment formulas are as follows:

[0167]

[0168] Where:

[0169] Ec represents the system energy consumption, which is the current system energy consumption of the VR device;

[0170] Ec max Represents the total system energy consumption, which is the total system energy consumption of the VR device in a fully charged state;

[0171] Fps represents the frame rate;

[0172] Fps max Represents the maximum frame rate;

[0173] After adjustment, α new < α, β new > β, reduce the rendering load of the VR device to reduce the image quality, improve the frame rate stability of the VR device. By reducing the image quality and increasing the frame rate, it is easier for users to return to the correct path;

[0174] In this embodiment:

[0175] The system optimization value algorithm unit comprehensively considers multiple influencing factors such as the user experience value Ue, the system energy consumption Ec, the user stay time St, and the user path deviation △T, and calculates the system optimization value So. On the one hand, the intelligent library navigation system can dynamically adjust parameters such as rendering accuracy and frame rate according to the real-time feedback of the system optimization value So, so as to find the best balance point between energy consumption and performance, thereby paying attention to the energy efficiency ratio while pursuing the user experience, so as to effectively reduce the system energy consumption, extend the device battery life, and reduce energy consumption on the premise of ensuring that the user experience is not reduced or improved;

[0176] On the other hand, by comparing the system optimization value So with the good threshold Y in the database, when the system optimization value So is larger, it means that the user deviates from the optimal route. The values of the image adjustment coefficient α and the frame rate adjustment coefficient β can be adjusted to reduce the image quality of the VR device and increase the frame rate, making it easier for the user to return to the correct guiding path. That is, the system optimization value So, as a comprehensive indicator of system optimization, can be fed back to the VR image quality value algorithm unit and the user experience value algorithm unit in real time and adjust their calculation parameters. This real-time feedback mechanism enables the intelligent library guiding system to more flexibly adapt to the changes of different users and environments, and continuously improve the user experience and system performance.

[0177] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A VR-based intelligent library navigation system, characterized in that, Including: A data collection module for collecting data of VR devices; A data preprocessing module for decoding and preprocessing data information in the database to obtain parameters for calculation in the calculation processing module; A calculation processing module for inputting the parameters obtained after decoding and preprocessing into the VR image quality value algorithm unit to calculate the VR image quality value VRiq, inputting the VR image quality value VRiq into the user experience value algorithm unit in the calculation processing module to calculate the user experience value Ue, inputting the user experience value U into the system optimization value algorithm unit in the calculation processing module to calculate the system optimization value So and uploading it to the database; Adjust the parameter values in the calculation processing module through the feedback adjustment unit.

2. The intelligent library navigation system based on VR according to claim 1, wherein: The data collection of the VR device specifically includes: obtaining the monocular resolution Mr, maximum frame rate Fps from the specification of the VR device max , minimum frame rate Fps min , total system power consumption Ec max ; Obtain the frame rate Fps and latency Lat through the performance monitoring tool built in the VR device; Obtain the number of polygons Pc, field of view angle Fov, and optimal navigation path length Toup from the 3D modeling software built in the VR device; Obtain the system energy consumption Ec, user stay time St, and user path deviation △T through the sensors built in the VR device; Upload them to the database together.

3. A VR-based intelligent library navigation system according to claim 1, characterized in that: Adjust the parameter values in the calculation processing module through the feedback adjustment unit, specifically including: Set the good threshold Y of the system optimization value So in the database to 1.8 times And compare the system optimization value So with the good threshold Y: When the system optimization value So > good threshold Y, it is considered that the system needs to perform energy efficiency optimization, and adjust the image adjustment coefficient α in the VR image quality value algorithm unit and the frame rate adjustment coefficient β in the user experience value algorithm unit.

4. The intelligent library navigation system based on VR according to claim 1, characterized in that: The calculation processing module includes a VR image quality value algorithm unit, a user experience value algorithm unit, a system optimization value algorithm unit, and a feedback adjustment unit.

5. The intelligent library navigation system based on VR according to claim 4, characterized in that: The VR image quality value algorithm unit is as follows: Where: VRiq represents the VR image quality value; Mr represents the monocular resolution: Pc represents the number of polygons; Fov represents the field of view angle; α is the image adjustment coefficient, with a preset value of 1, which can be self-adjusted in the intelligent library navigation system; In the formula calculation: Mr -0.8 This part serves as the denominator of the formula calculation. As the monocular resolution Mr increases, Mr -0.8 The value of this part decreases. By increasing the calculated VR image quality value Mr, the non-linear influence of resolution on the calculation of the VR image quality value VRiq is reflected through a power function. As the monocular resolution Mr increases, the VR image quality value will increase, but the growth rate will slow down, meaning that the higher the resolution, the greater the marginal quality improvement, but the enhancement effect will gradually weaken; The number of polygons Pc measures the fineness of the scene model through a logarithmic function. As the number of polygons Pc increases, a more realistic and complex VR scene is formed, thereby improving the calculated VR image quality value VRiq. The logarithmic function can avoid the excessive influence on the calculation of the VR image quality value caused by simply piling up polygons; This part of sin(Fov - 30°) quantifies the impact of the wide-angle change on the immersion by taking the sine value after subtracting 30° from the field of view angle Fov. The normal field of view range of a person is 120°; When the field of view angle Fov is 120°, the value inside the parentheses of sin(Fov - 30°) is π / 2, and sin(Fov - 30°) reaches the maximum value of 1 of the sine function, representing that the field of view angle at this time is the most suitable angle for the human body; When the field of view angle Fov decreases from 120°, the field of view range becomes smaller, the immersion decreases, and the value of this part of sin(Fov - 30°) decreases, thereby reducing the calculated VR image quality value VRiq; When the field of view angle Fov increases from 120°, although the field of view range becomes larger, it has exceeded the perspective range familiar to normal people, increasing the visual fatigue of the user. The value of sin(Fov - 30°) decreases, thereby reducing the calculated VR image quality value VRiq.

6. The intelligent library navigation system based on VR according to claim 5, characterized in that: The user experience value algorithm unit is as follows: Where: Ue represents the user experience value; VRiq represents the VR image quality value; Fps represents the frame rate; Fps max Represents the maximum frame rate; Fps min Represents the minimum frame rate; Lat represents the latency; β represents the frame rate adjustment coefficient, with a preset value of 1.2, which can be self-adjusted in the intelligent library navigation system; In the formula calculation: This part normalizes the influence degree of the frame rate Fps on the user experience value to the numerical range of (0, 1) through the ratio of the difference between the frame rate Fps and the minimum frame rate Fps max to the difference between the maximum frame rate Fps max and the minimum frame rate Fps min ; As the frame rate Fps increases, the frame rate Fps gets closer to Fps max , the value of this part gets closer to 1, indicating that the frame rate Fps at this time is at the maximum value of the device, the increase in the value of this part will have a positive impact on the calculation of the user experience value Ue; As the frame rate Fps decreases The value of this part decreases, The decrease in the value of this part indicates that the device is in a frame-drop state, reducing the calculated user experience value Ue; This part, as the exponential part of the natural constant e, compares the delay Lat with a reference value of 20 ms. Specifically: When the latency Lat > 20, based on the reference value of 20 ms, for every 10 increase in the latency Lat, the exponential part increases by 1. This increases the denominator of this part, reducing the calculated user experience value Ue: When the latency Lat < 20, the value of this exponential term is negative, this part decreases, increasing the calculated user experience value Ue.

7. A VR-based intelligent library navigation system according to claim 6, characterized in that: The system optimization value algorithm unit is as follows: Where: So represents the system optimization value; Ue represents the user experience value; Ec represents the system energy consumption; St represents the user stay time; △T represents the user path deviation; Toup represents the optimal navigation path length; In the formula calculation: When the system energy consumption Ec of the VR device is high, the device will have problems of slow response and overheating. As the numerator in the formula, by taking the square root of the system energy consumption Ec, while maintaining the positive impact of the system energy consumption Ec on the system optimization value So, the excessive impact of the system energy consumption Ec on the calculation result is reduced. Dividing the user experience value Ue by the square root of the system energy consumption Ec represents the user experience efficiency per unit energy consumption. This part, as the reciprocal of the user experience efficiency per unit energy consumption, indicates that as the user experience value Ue increases, the VR device is operating effectively and does not require system optimization, thereby reducing the calculated system optimization value So. The larger the user's stay time St is, it means that the path for the user to find the target book is not clear, and the user needs to stop and think about the path. This part is processed by taking the square root of the quotient of the maximum stay time 5 that the system can tolerate divided by the difference between the maximum stay time 5 and the user's stay time St, so as to reflect the non-linear influence of the user's stay time St on the system optimization value So. When the user stay time St is 0, it means that the path for the user to find the target book is clear, This part of the value is 1, and at this time, the user stay time St will not affect the calculation of the system optimization value So; As the user stay time St increases, this part of the value increases, thus increasing the calculated system optimization value So; This part standardizes the system optimization value So with respect to the user path deviation △T through the optimal navigation path length Toup to reflect the linear influence of the user path deviation △T on the system optimization value So; When the user path deviation △T is 0, This part of the value is 1, indicating that the user does not deviate from the optimal navigation path at this time and no system optimization is required; When the user path deviation △T increases, This part of the value increases, indicating that the user deviates from the optimal navigation path at this time, and the calculated system optimization value So increases.

8. The intelligent library navigation system based on VR according to claim 3, wherein, The specific adjustment formulas for the image adjustment coefficient α and the frame rate adjustment coefficient β are as follows: Where: Ec represents the system energy consumption, which is the current system energy consumption of the VR device; Ec max Represents the total system energy consumption, which is the total system energy consumption when the VR device is fully charged; Fps represents the frame rate; Fps max Represents the maximum frame rate; After adjustment, α new <α, β new >β.

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