A method for displaying a sound and light effect offline

Abstract

The present application relates to a kind of offline sound-light effect display method, based on the orientation of user, the speed of travel, pose action is identified, for user itself or other users, corresponding sound-light effect is shown in the display area by sound-light display equipment, realize user itself or other users in the environment where it is located obtains immersive experience.The sound-light effect of the present application can also be based on the interaction between users, realize corresponding interactive sound-light effect;With the orientation of user, the speed of travel, pose action, it can be realized that sound-light effect is directive, interactive.The present application can also associate online game attribute with offline behavior, online game attribute can be used to determine the style of corresponding sound-light effect shown in user offline behavior, the interaction between users through offline behavior, influence game attribute, then determine online game attribute, realize the linkage of online and offline.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and more specifically, to a method for displaying offline sound and light effects. Background Technology

[0002] While the implementation of intelligent technologies has enabled scenic spots and venues to offer increasingly interactive ways to enhance the visitor experience, existing interactive methods primarily involve individual devices or attractions. These methods present content to users through interactive implementation plans, but the overall visitor experience within the scenic area or venue still involves walking, stopping, and looking, failing to fundamentally address the monotony of the visit. For example, Chinese invention patent application 201910820209.5 provides an AR-based scenic spot experience system. This system employs a scenic spot service module, a gamified tourism experience module, an AR visual display module, and a cultural IP module. Visitors learn about the actual characteristics of the scenic spot through AR visuals and quickly gain an understanding through the gamified tourism experience module. This combines gaming with the popularization of scenic spot knowledge, allowing visitors to quickly learn about the cultural features of the scenic spot while having fun, achieving a positive scenic spot experience.

[0003] However, the technical solutions in the aforementioned invention patent applications inevitably require handheld terminals, including AR devices and smartphones, to display interactive content using AR visuals in order to achieve interaction with users. However, due to the inherent characteristics of AR technology, it cannot achieve a truly immersive experience. Furthermore, the form of AR visual display is limited; visual content is simply overlaid onto the real-world scene using AR devices or smartphones, and users cannot experience any sense of "being there" in their environment.

[0004] Regarding route guidance within scenic areas and venues, Chinese invention patent application 201710576965.9 provides a navigation logic method and its indoor AR navigation system. The navigation system includes an indoor positioning module, a path search module, and a navigation module, and improves the path search algorithm of the path search module and the navigation logic method of the navigation module.

[0005] However, the technical solutions in the aforementioned invention patent applications inevitably require handheld terminals, including AR devices and smartphones, to achieve AR navigation; and indoor positioning is performed based on the handheld terminal. The indoor positioning module uses a positioning method such as WiFi indoor positioning, iBeacon indoor positioning, communication base station indoor positioning, or pseudo-satellite GPS indoor positioning. Clearly, due to inherent defects in the technology itself, the performance limitations of related hardware, or environmental interference factors, different navigation technologies are only suitable for navigation under relatively specific conditions; otherwise, accuracy and real-time performance are poor, lacking versatility. Correspondingly, existing technologies strongly associate users with handheld terminal devices, making it difficult for users to detach from them, resulting in insufficient ease of use.

[0006] On the other hand, traditional navigation requires generating route information first, and then using that information as the basis for navigation. Because of this route information, there is a risk of privacy issues arising from data recording by navigation service providers or local security vulnerabilities. For navigation software that requires users to agree to privacy terms, user privacy is unnecessarily collected if the user ignores or compromises, a problem that is difficult to effectively address at present. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide an offline audio-visual effects display method. The display and guidance process of audio-visual effects are free from dependence on handheld terminal devices; it has high versatility and can be adapted to various different environments; it is implemented based on a peer-to-peer network, eliminating the need to store user perception information or generate route information, thus ensuring user privacy and security.

[0008] The technical solution of the present invention is as follows:

[0009] A method for offline audio-visual effects display involves deploying audio-visual display equipment within a display area; acquiring user orientation data, walking speed data, and posture data; and displaying audio-visual effects corresponding to the user's current orientation, walking speed, and posture based on the user's orientation, walking speed, and posture.

[0010] As a preferred approach, several types of game attributes are set for each user. If the user's current orientation, movement speed, and posture affect the user's own game attributes, then the corresponding sound and light effects are displayed for the user and modify the user's own or other users' game attributes. If the user's current orientation, movement speed, and posture affect other users' game attributes, then the corresponding sound and light effects are displayed for other users and modify the user's own or other users' game attributes.

[0011] As a preferred method, the system reads the user's online game attributes, calculates matching audio-visual effects based on these attributes, and uploads the modified game attributes corresponding to the user's offline influence on their own or other users' game attributes to the online game server according to preset rules, thereby updating the user's online game attributes.

[0012] Preferably, the system obtains the user's route requirements and location information; based on the route requirements and the user's real-time location information, it calculates the guidance information for the user's next step; the guidance information is presented through an audio-visual display device at the location corresponding to the user's real-time location information to guide the user.

[0013] As a preferred method, the system acquires the user's orientation data, walking speed data, and posture data, and uses a prediction model pre-trained with preset conditions or through machine learning to predict the user's next action, including the user's orientation, walking speed, and posture. The system then displays audio-visual effects and guides the user's next action at a location that matches the predicted orientation, walking speed, and posture of the user's next action.

[0014] As a preferred option, if the prediction of the user's audio-visual effects or next action is inaccurate, the audio-visual display device that presents the audio-visual effects and guides the user's next action is corrected based on the user's real-time orientation data, walking speed data, and posture and action data. The density of people around the user, environmental information, orientation data, walking speed data, and posture and action data of people around the user are used as training samples and added to the sample library for further training and adjustment of the prediction model.

[0015] As a preferred method, the user's height, leg length, and cadence data are obtained to calculate the user's walking speed; if the prediction of the user's next action is inaccurate, the calculated walking speed is used instead of the predicted walking speed.

[0016] As a preferred approach, a personalized prediction model is established for different users. After identifying the user, the associated prediction model is used to predict the user's next action.

[0017] Preferably, the audio-visual display equipment includes a visual information display equipment for displaying visual effects and visual guidance information;

[0018] A visual information display device that acquires real-time user orientation, speed, and posture data, follows the user's orientation, speed, and posture, and maintains a certain distance from the user to display visual guidance information for the user's next step; or, corresponding to the current user's or other users' positions, and displays visual effects following the current user's or other users' positions.

[0019] Alternatively, based on the user's route requirements and real-time location information, a peer-to-peer network can be used for collaborative computation to obtain a visual information display device that matches the location where visual guidance information needs to be displayed for each user's next step; and a visual information display device that maintains a certain distance from the user relative to the user's real-time location information, real-time walking speed, and real-time posture and movement can be used to display the visual guidance information for the user's next step; or, the visual effect can be displayed according to the location of the current user or other users and follow the location of the current user or other users.

[0020] As a preferred option, the distance between the visual information display device that displays visual guidance information and the user is calculated based on the user's height and stride length.

[0021] Preferably, the audio-visual display device includes an audio playback device for playing audio effects and audio guidance information; the audio playback device acquires the user's real-time location information, walking speed data, and posture and movement data, follows the user's position, walking speed, and posture and movement, and maintains the sound field covering the user's position, and plays audio effects and audio guidance information for the user's next step.

[0022] Alternatively, based on the user's route requirements and real-time location information, a peer-to-peer network can be used for collaborative computation to obtain an audio playback device that matches the location where audio guidance information needs to be played for each user's next step; and relative to the user's real-time location information, real-time walking speed, and real-time posture and movements, an audio playback device that maintains sound field coverage of the user's location can be used to play audio effects and audio guidance information for the user's next step.

[0023] Preferably, the audio playback device is positioned above the display area and is equipped with a downward-facing sound-focusing shield, which is used to limit the sound field of the audio playback device to a certain range.

[0024] Alternatively, a pan-tilt-zoom (PTZ) speaker can be used, and the transmission angle can be adjusted according to the orientation and speed of the user who needs to listen to the audio effects and audio guidance information.

[0025] As a preferred method, the physical attributes of users within the display area are obtained by deploying corresponding types of sensors that cover the display area, the route requirements of users are obtained by human-computer interaction devices associated with users, and collaborative calculations are performed through a peer-to-peer network to obtain audio-visual effects and guidance information for each user.

[0026] Alternatively, route requirements can be inferred from the play content for the user, which includes a defined or presumed destination, which is the final destination or the next of multiple consecutive destinations.

[0027] As a preferred method, peer-to-peer networks are used to perform non-specific feature identification and location identification of users;

[0028] The peer-to-peer network consists of multiple node devices, and there is no master-slave relationship among all node devices. Each node device is equipped with a data acquisition device and a computing module. The data acquisition device includes at least one type of sensor for collecting different corresponding types of sensing data. Node devices set at different acquisition locations collect at least one point sample from the user, and the point sample is sensing data of the corresponding sensor type.

[0029] For a given node device, the collected sensing data is processed to obtain result data, which is then propagated to other node devices. Other node devices that receive the result data use it as one of the original data collected, and the result data influences the result data of other node devices. Based on this, without needing to obtain user identity information, multiple node devices in the peer-to-peer network perform collaborative computation to determine that each unique user is itself, achieving non-specific feature recognition and user location identification.

[0030] Preferably, the current node device receives the result data output by other node devices; for the current node device, the collected sensing data is combined with the result data from other node devices to calculate the result data of the current node device, and then sent to other node devices; the node devices in the peer-to-peer network perform collaborative calculations as sensing data is collected and result data is calculated.

[0031] Preferably, in a peer-to-peer network, for a specific point sample of a user, in the result data transmitted from the node device that collected the point sample to other node devices, the subsequent node devices adjust their perceptual attention based on the characteristics of the point sample, or report the characteristics of the point sample for subsequent node devices to adjust their perceptual attention; if the subsequent other node devices do not detect the characteristics of the point sample, but can determine from the characteristics of other point samples that the undetected characteristics of the point sample still belong to the user, then the undetected characteristics of the point sample are continued to be represented in the result data of the current node device and transmitted to other node devices.

[0032] As a preferred method, the method of reporting the features of the point sample for subsequent node devices to adjust the perceptual attention is as follows: based on the result data expressing the features of the point sample provided by the preceding node device, or the features of the point sample, the parameters of the data processing model of the subsequent node device are adjusted so that the subsequent node device can improve the computing power of the point sample to identify its features; or, the subsequent node device uses the perceptual attention model to match the features of the received point sample or the result data expressing the features of the point sample to adjust the computing power.

[0033] Preferably, when processing the output data of several preceding node devices, the node device, based on the data processing model, merges the point sample features and other information described by each node device into the same user when the user described by several preceding node devices can be identified as the same user through certain common point sample features.

[0034] Preferably, when the result data received by the node device indicates that the flag used by the current node device to identify the user before the current receipt of result data is different from the flag used by other node devices to identify the user, and the flags assigned to the user by other node devices have been updated, then the flag used by the current node device to identify the user before the current receipt of result data is converted.

[0035] As a preferred method, the method for converting the flag used by the current node device to identify the user before the current reception of result data is as follows:

[0036] Replace the flag used by the current node device to identify the user before the current reception of result data with the latest flag assigned to the user by other node devices;

[0037] Alternatively, record the conversion relationship between the flag used by the current node device to identify the user before the current reception of result data and the updated flag assigned to the user by other node devices, and perform the conversion when it is necessary to reference the result data received by the current node device in the current reception.

[0038] Alternatively, node devices can deploy conversion models to perform corresponding conversions on the identifiers of multiple users based on the input raw data or result data.

[0039] As a preferred option, for one or more point samples collected sequentially by node devices at different collection locations, if the feature values ​​of one or more point samples at different collection locations meet the preset similarity conditions or are determined by a specific model to have a correlation threshold, and are unique at each collection location, then it is determined that the point samples at different collection locations are correlated.

[0040] Preferably, for one or more point samples collected simultaneously by node devices at different collection locations, if the node devices at different collection locations collect data from the same spatial field, and there is only one user in the spatial field, or the collected point sample can correctly point to one of the multiple users, then for a certain user, one or more point samples collected by node devices at different collection locations are correlated.

[0041] Preferably, the data acquisition device of the node device includes one or more of the following: an image acquisition device, an electromagnetic induction device, a temperature measurement device, a vibration frequency sensing device, and a lidar. The data acquired by the above devices and the three-dimensional point cloud acquired by the lidar, or the point cloud generated from images acquired by multiple image acquisition devices, are jointly calculated to obtain three-dimensional points with data. The image color, contour, lines, reflectivity, motion trend, electromagnetic characteristics, temperature, temperature change trend, vibration frequency, and vibration frequency change trend based on two-dimensional perception are used as additional attributes of the corresponding three-dimensional points to form an attributed three-dimensional point cloud. Combining electromagnetic induction, temperature law, vibration frequency change characteristics, motion correlation, and reflectivity, the correspondence between each region of the attributed three-dimensional point cloud and each part or related part of the user's 3D appearance is determined.

[0042] Preferably, when it is necessary to obtain the user's identity information, an identity information acquisition command is triggered. The identity information acquisition command is used as one of the inputs to participate in the calculation of the result data of the node device. By driving the node device in the peer-to-peer network that is connected to the barrier-free data collection conditions that can obtain the user's identity information to respond with the corresponding result data, the user's identity information can be obtained.

[0043] As a preferred approach, the peer-to-peer network verifies the authenticity of the user's identity information to determine their permissions. In this approach, the node device in the peer-to-peer network that can obtain identity information does not provide the identity information itself, but only expresses the verification result in the result data of the node device based on the verification requirements for the authenticity of the identity information in the received result data.

[0044] Preferably, in a peer-to-peer network, the node device capable of obtaining identity information does not provide identity information. Instead, the information source device that drives the provision of identity information establishes an encrypted information transmission channel with the node device input terminal that needs to obtain identity information, or establishes an encrypted information transmission channel using other network communication modes, and uses the identity information as one of the inputs to the node device.

[0045] Preferably, the data acquisition device includes one or more of the following: image acquisition device, audio acquisition device, temperature measurement device, vibration frequency sensing device, lidar, chemical sensor, and electromagnetic induction device.

[0046] Preferably, the human-computer interaction device associated with the user connects to the node device as an access device and submits route requests to the peer-to-peer network; each audio-visual display device joins the peer-to-peer network through one or more node devices; if it is determined based on collaborative computing that the audio-visual display device needs to present based on the corresponding audio-visual effects and the user's next guidance information, the current node device will send instructions to the audio-visual display device connected to the current node device according to the calculated result data, and control the audio-visual display device to complete the presentation of audio-visual effects and guidance information.

[0047] Preferably, the sound and light effects and the user's next step guidance information are represented in the result data; the sound and light display device receives the result data output by the connected node device. If a specific element in the result data indicates that the sound and light display device needs to present sound and light effects and guidance information, or if the result data is used as one of the inputs to the data processing model of the node device, and the corresponding sound and light display device is calculated and determined to present sound and light effects and guidance information, then the sound and light display device presents the corresponding sound and light effects and guidance information.

[0048] As a preferred option, when the audio-visual display device needs to present audio-visual effects and guidance information, the audio-visual display device combines the result data received from other node devices to calculate its own result data, and controls the audio-visual display device to present the corresponding audio-visual effects and guidance information through the obtained result data.

[0049] As a preferred option, for audio-visual display devices, the calculated results include the optimal solution for all situations obtained at the current moment based on collaborative calculations between all users in the display area and the external environment; audio-visual effects and guidance information for the user's next step are presented through audio-visual display devices.

[0050] Preferably, the audio-visual display device receives the result data output by other node devices. The principle is as follows: when the corresponding audio-visual display device needs to present audio-visual effects and guidance information, if the result data calculated by one or more node devices can determine the audio-visual display device that needs to present audio-visual effects and guidance information, then the corresponding audio-visual display device is added to the node list for transmitting the current result data. The one or more node devices directly transmit the result data to the audio-visual display device or the node device connected to the audio-visual display device; or, the audio-visual display device receives the result data output by other node devices in a layer-by-layer transmission manner.

[0051] As a preferred option, based on preset conditions or algorithm output and model output, the corresponding audio-visual display devices are added to the node list for transmitting result data.

[0052] Preferably, the audio-visual display device is a node device with execution components that are set with specific functions. The execution feedback information of the execution components of the audio-visual display device is fed back to the audio-visual display device and participates in the calculation of the subsequent result data of the audio-visual display device.

[0053] Preferably, when the collaborative computing results determine that the orientation and travel speed of multiple users are consistent, the distance between users meets the travel distance standard, and among the multiple users, only one user's route requirement is obtained, or the route requirements of multiple users are the same, then the multiple users are grouped into a team of users.

[0054] As a preferred option, among users in the same user group, based on the results of collaborative computing, if it is determined that the vision and / or hearing of some users are interfered with by other users, then visual guidance information and / or audio guidance information will be displayed to the user whose route needs have been obtained or to the user at the forefront whose next step guidance information is correctly oriented; if the vision and hearing of the user whose route needs have been obtained are both interfered with by other users, then visual guidance information or audio guidance information will be displayed to other users whose vision or hearing has not been interfered with.

[0055] If all users' vision and hearing are not disturbed by other users, then visual guidance information and audio guidance information are displayed to each user.

[0056] The beneficial effects of this invention are as follows:

[0057] The offline sound and light effect display method described in this invention is based on recognizing the user's orientation, walking speed, and posture. For the user or other users, corresponding sound and light effects are displayed within a designated area using sound and light display equipment, enabling the user or other users to obtain an immersive experience in their environment. The sound and light effects display of this invention can also be based on user interaction to achieve corresponding interactive sound and light effects; by combining the user's orientation, walking speed, and posture, the directionality and interactivity of the sound and light effects can be achieved.

[0058] This invention can also link online game attributes with offline behaviors. Online game attributes can be used to determine the style of sound and light effects displayed in the user's offline behavior. Through the interaction of offline behaviors, users can influence game attributes, thereby determining online game attributes and realizing the linkage between online and offline.

[0059] Applying this invention to scenic spots and venues can not only display content information through sound and light effects and achieve immersive tours, but also combine scenic spots and venues with online games. By using immersive sound and light effects to display content, players can engage in games through offline activities. The online games can be linked to the sound and light effects displayed offline, achieving online and offline synergy and increasing the diversity of online games and offline tours.

[0060] This invention is based on user identification and positioning, and guides users through audio-visual display devices deployed in the user's surrounding environment. During the guidance process, users can get rid of their handheld terminal devices. Therefore, it does not have the problems of poor accuracy and real-time performance caused by the inherent defects of the existing technology, the performance impact of the handheld terminal device's hardware, and many environmental interference factors.

[0061] This invention utilizes sensors of corresponding types deployed within and covering the display area to acquire the physical attributes of users within that area, enabling user identification and location. It can construct a purely internal network for navigation, avoiding the data security risks associated with data interaction via public communication platforms. This invention is applicable to any scenario where sensors can be deployed, demonstrating strong versatility.

[0062] This invention utilizes a peer-to-peer network for collaborative computing to perform non-specific feature recognition and location recognition on all users within the display area, thereby completing identity recognition and positioning. In the peer-to-peer network, there is no primary or secondary relationship between all node devices, and there are no fixed connection paths between node devices. Node devices only receive the calculation results of other node devices and send out their own calculation result data. The discovery of events and / or the response of corresponding audio-visual display devices do not rely on the identification and control of a single node device, but are jointly confirmed through collaborative computing by multiple node devices in the peer-to-peer network. Furthermore, this invention can distribute computing functions across the entire network without relying on single-point user identification, reducing the hardware and software requirements of single-point computing, resulting in high execution efficiency and significantly improved anti-attack capabilities. The relatively symmetrical information among node devices prevents illegal data tampering. Even if a single node device is physically compromised and its transmitted data is altered, the network-wide computing involves highly redundant and complex calculations and multi-dimensional verification. Therefore, the alteration of data transmitted by a single node device does not affect the overall network computing results. Moreover, it allows for rapid location of faulty and tampered node devices, ensuring the reliability of the overall network computing results. This, in turn, resolves the conflict between data sharing and information security between departments.

[0063] This invention can identify each unique user without requiring specific features or identity information, achieving non-specific feature recognition. This invention uses non-specific feature recognition for user identification, identity verification, or event monitoring, resulting in high accuracy and precise location identification. This invention can identify and verify users and protect privacy while addressing issues related to transportation, education, healthcare, epidemic prevention, public services, emergency response, community services, market behavior, workplace safety, and civilized behavior.

[0064] This invention employs non-specific feature recognition, effectively preventing risks caused by theft or counterfeiting of specific features, thus significantly enhancing security. It uses a non-contact, passive method for seamless user identification, greatly improving ease of execution. Based on the aforementioned peer-to-peer network, this invention can be easily deployed over coverage areas ranging from hundreds of meters to hundreds of kilometers, making it suitable for various geographical areas.

[0065] In this invention, the peer-to-peer network does not directly control the audio-visual display device as a single machine. The response execution of the audio-visual display device (i.e., the presentation of audio-visual effects and guidance information) is controlled based on the calculation results obtained through collaborative computing. This results in high response efficiency and avoids illegal responses such as false execution or failure to execute when required due to network attacks. To prevent hijacking, this invention can also use multiple node devices to collaboratively control the audio-visual display device, further improving its immunity to hijacking attacks. Detailed Implementation

[0066] The present invention will be further described in detail below with reference to the embodiments.

[0067] To address the shortcomings of existing technologies, such as poor versatility, accuracy, and real-time performance, and reliance on handheld devices, this invention provides an offline audio-visual effects display method. Based on the recognition of user offline behavior (including but not limited to orientation, walking speed, and posture), audio-visual display devices deployed in the user's surrounding environment display audio-visual effects to the user, achieving an immersive experience for the user or other users. Based on user identification and location, audio-visual display devices deployed in the user's surrounding environment provide guidance to the user. During the audio-visual effects display and guidance process, users can be freed from handheld devices, enabling interactivity between users and an immersive audio-visual effects experience. The guidance process achieves high accuracy and real-time performance. This invention uses sensors of corresponding types deployed in and covering the display area to acquire the physical attributes of users within the display area for user identification and location. A pure intranet can be constructed to achieve user-specific audio-visual effects display and navigation, avoiding the data security risks associated with data interaction using public communication platforms. This invention can be implemented in any scenario where sensors can be deployed, demonstrating strong versatility.

[0068] The offline audio-visual effects display method described in this invention deploys audio-visual display equipment within a display area. This equipment targets the user, delivering audio-visual effects at their location and within their environment to achieve an immersive experience. Furthermore, the audio-visual display equipment can also be used to display corresponding information content to the user at desired locations within the display area, serving as an information output function. For example, when implemented in scenic spots or venues, it can be used to display specific information content at specific attractions or locations to achieve the purpose of visiting. Specifically, this invention acquires the user's orientation data, walking speed data, and posture data—that is, it detects and identifies the user's orientation, walking speed, and posture. Then, based on the user's orientation, walking speed, and posture, the audio-visual display equipment displays audio-visual effects corresponding to the user's current orientation, walking speed, and posture. In practice, the user's orientation, walking speed, posture, and combinations thereof, or the user's orientation, walking speed, posture, and combinations thereof at several consecutive moments (i.e., the user's offline behavior), can be exhaustively listed. Corresponding audio-visual effects can be set, triggered by the user's offline behavior, and then displayed through the audio-visual display device at the location where the audio-visual effects need to be displayed. The audio-visual effects can be targeted at the user performing the offline behavior, or at other designated users (based on the identification and location of other users), for example, by identifying other designated users through the user's orientation and posture (pointing direction of fingers or arms).

[0069] Furthermore, this invention sets several types of game attributes for each user (when this invention is applied to offline scenarios, the game attributes may refer solely to offline game attributes; when this invention is applied to the linkage between offline games and offline tourism, the game attributes include online game attributes and offline game attributes, with the categories of online game attributes and offline game attributes corresponding). If a user's current orientation, movement speed, and posture affect their own game attributes, then the corresponding audio-visual effects are displayed for that user, and the game attributes of the user or other users are modified. If a user's current orientation, movement speed, and posture affect the game attributes of other users, then the corresponding audio-visual effects are displayed for those other users, and the game attributes of the user or other users are modified. For example, in team battles, if one or more users trigger an aura effect (corresponding to a skill that affects teammates' game attributes) or release a skill (corresponding to a skill that affects the opponent's game attributes) through offline actions, then the audio-visual display device displays the corresponding audio-visual effects (including visual presentation and sound playback) based on the user's orientation, movement speed, and posture. Correspondingly, the corresponding audio-visual effects are displayed in the environment where teammates or opponents are located. Similarly, for other designated users (e.g., influenced by teammates or opponents), sound and light effects are passively displayed at their location and in their environment. Simultaneously, the game attributes of the relevant users are modified based on the influence received. For example, buffs from teammates increase the attack power (one of the game attributes) of other teammates, while attacks from enemies decrease the health (one of the game attributes) of the attacked user, and so on.

[0070] When it's necessary to link online games with offline tourism, offline tourism can be associated with online games. The user's online game attributes are read, and in practice, online game attributes correspond to or are converted to offline game attributes. Matching audio-visual effects are calculated based on the online game attributes. For example, different levels reflected in online game attributes result in corresponding differences in offline audio-visual effects, thus determining the different impacts of offline behavior on game attributes between users. For instance, higher levels result in higher attack power, a larger range of audio-visual effects, and a greater impact on other users. This invention achieves online-offline linkage. When offline behavior affects a user's game attributes, and during user interaction, modifies the user's game attributes, the modified game attributes corresponding to the user's offline influence on their own or other users' game attributes are uploaded to the online game server according to preset rules, updating the user's online game attributes.

[0071] This invention can be implemented as script-based tourism and immersive travel, guiding users through the entire tourism process via plot progression and game sequences. During the process, users can be guided to complete the tour according to the script's storyline and game plot. In this invention, by identifying (or locking) and locating users, and based on their route requirements (which can be implemented as the starting position corresponding to the script or game plot, multiple transit points, and route requirements such as game difficulty, path length, and terrain complexity), without calculating and generating path information, based on the situation of all users within the data collection range, and while meeting the route requirements, the next action of each user is calculated and output, gradually guiding the user to the destination. When using this invention for navigation (i.e., guiding users according to the script's storyline and game plot), the route requirements for the user are first obtained, and the user's location information is acquired in real time; then, based on the route requirements and the user's real-time location information, the next guidance information for the user is calculated; the guidance information is presented through an audio-visual display device corresponding to the user's real-time location information to guide the user. This invention provides guidance to users in stages. Typically, guidance information is presented to users at locations where route selection is required (not a complete selection of route information; in fact, this invention does not generate complete route information, but rather refers to situations where the user needs to choose one of the roads at intersections), to guide the user in selecting the appropriate direction of travel; and so on, until navigation is completed.

[0072] In this embodiment, the audio-visual display device can be implemented as a visual information display device, an audio playback device, or a combination of both. The specific implementation can be chosen based on the implementation scenario and performance requirements. The visual information display device can be a projection device (projected onto the ground or wall), a dedicated display device (set on the ground or wall), a multi-purpose display device (such as billboards, light boxes, signs, outdoor displays, etc.), or a combination thereof. The audio playback device can be a dedicated playback device, a multi-purpose playback device (such as an advertising terminal with sound playback function, a background music playback device, an information broadcasting device, etc.), or a combination thereof. When there are multiple users and guidance information needs to be presented to multiple users simultaneously, different types of audio-visual display devices can choose a presentation method suitable for their own functional characteristics. For example, a projection device can simultaneously display visual guidance information for each user, while an audio playback device can play audio guidance information for each user one by one. When guidance information and sound and light effects are triggered simultaneously, they can be displayed at the same time. Depending on the settings, guidance information or sound and light effects will be displayed first. For example, if the sound and light effect is a flashbang, guidance information will not be displayed to express the effect of the flashbang. However, if the user has a virtual item that can counteract the flashbang, the display effect of guidance information will be stronger than that of sound and light effects to express the effect of the item.

[0073] To enhance user experience and provide pre-guided navigation without interruption, this invention also acquires user orientation data, walking speed data, and posture data. Using preset conditions (such as preset judgment criteria) or a pre-trained prediction model based on machine learning, it predicts the user's next action, including orientation, walking speed, and posture. For example, a user whose posture data indicates "looking around" will typically slow down or stop walking; a user whose posture data indicates "looking straight ahead" and whose walking speed data indicates "walking quickly" will typically maintain or potentially increase their walking speed. Furthermore, the audio-visual display device, positioned according to the predicted direction, speed, and posture of the user's next move, presents audio-visual effects and guidance information for the user's next step. For example, if the predicted speed of a user is to slow down or stop, the presentation of the audio-visual effects and guidance information can be delayed or not displayed until the user moves to the position where the audio-visual effects and guidance information are needed. The gap time can be used to present other content, including audio-visual effects and guidance information for other users, or other types of content. If the predicted speed of a user is to maintain or increase, the presentation of the audio-visual effects and guidance information can be maintained or advanced accordingly. Therefore, the presentation of audio-visual effects and guidance information is dynamically and proactively adjusted, rather than solely relying on the user's location.

[0074] In addition, the prediction of the user's walking speed can be made through auxiliary means. Specifically, the user's height data, leg length data, and cadence data can be obtained to calculate the user's walking speed. If the prediction of the user's next action is inaccurate, the calculated walking speed will be used instead of the predicted walking speed.

[0075] If the prediction of the user's audio-visual effects or next action is inaccurate, the audio-visual display device for presenting the audio-visual effects and guiding the user's next step is corrected based on the user's real-time orientation data, walking speed data, and posture data. The density of people around the user, environmental information, and the orientation, walking speed, and posture data of people around the user are used as training samples and added to a sample library for further training and adjustment of the prediction model to improve its accuracy. To further improve the accuracy of the prediction model, this invention can establish individual prediction models for different users. After identifying the user, the associated prediction model is used to predict the user's next action.

[0076] When the aforementioned audio-visual display device is implemented as a visual information display device, used to display visual effects and visual guidance information; in order to improve the user's experience in obtaining visual guidance information, in this invention, the visual information display device acquires the user's real-time orientation data, walking speed data, and posture data, and follows the user's orientation, walking speed, and posture, maintaining a position at a certain distance from the user to display the user's next visual guidance information; that is, the display of visual guidance information follows the user's orientation and walking speed, and is displayed in front of the user at a convenient viewing position, with the display effect being that it moves in the same direction and at the same speed as the user. Alternatively, it corresponds to the position of the current user or other users, and displays visual effects according to the position of the current user or other users.

[0077] As another implementation, based on the user's route requirements and real-time location information, the peer-to-peer network provided by this invention performs collaborative computation to obtain a visual information display device that matches the location where visual guidance information needs to be displayed for each user's next step. This visual information display device, positioned at a certain distance from the user's real-time location, speed, and posture, displays the user's next visual guidance information. Alternatively, it can display visual effects corresponding to the current user's or other users' locations and following their positions. The peer-to-peer network provided by this invention, based on collaborative computation, can perform non-specific feature recognition of users and determine their real-time location, orientation, speed, and posture. Furthermore, based on the results of collaborative computation, the visual information display device that needs to display visual effects and guidance information can then display the corresponding visual effects and guidance information.

[0078] The distance between the visual information display device that displays visual guidance information and the user is calculated based on the user's height and stride length.

[0079] When the aforementioned audio-visual display device is implemented as an audio playback device, it is used to play audio effects and audio guidance information. In order to improve the user's experience in obtaining audio guidance information, in this invention, the audio playback device acquires the user's real-time location information, walking speed data, and posture data, and follows the user's position, walking speed, and posture to maintain the sound field covering the user's position, and plays the audio effects and the audio guidance information for the user's next step; that is, the playback of audio effects and audio guidance information follows the user's orientation, walking speed, and posture to be aligned with and cover the user's position in the sound field, and the playback effect is to move and play in the same direction and at the same speed as the user.

[0080] As another implementation, based on the user's route requirements and real-time location information, the peer-to-peer network provided by this invention is used for collaborative computation to obtain an audio playback device that matches the location where audio guidance information needs to be played for each user's next step. This audio playback device maintains sound field coverage of the user's location relative to the user's real-time location, real-time walking speed, and real-time posture, and then plays the audio effects and the user's next audio guidance information. The peer-to-peer network provided by this invention, based on collaborative computation, can perform non-specific feature recognition of users and determine their real-time location, orientation, walking speed, and posture. Simultaneously, based on the results of collaborative computation, the audio playback device that needs to play audio effects and audio guidance information can play the corresponding audio effects and audio guidance information.

[0081] The audio playback device is positioned above the display area and is equipped with a downward-facing sound-focusing shield. The sound-focusing shield is used to limit the sound field of the audio playback device to a certain range, such as ensuring that the sound can be clearly transmitted to the space required for a person to walk below, and to minimize the diffusion to the surrounding area; or, a super-directional speaker with a pan-tilt head is used, and the emission angle is adjusted according to the direction and walking speed of the user who needs to listen to the audio effect and audio guidance information, so as to ensure that the super-directional speaker is aimed at the user.

[0082] To eliminate reliance on handheld terminal devices, this invention uses sensors of corresponding types deployed in and covering the display area to acquire the physical attributes (physical space, sound, appearance, body temperature, odor, etc.) of users within the display area. It then uses a human-computer interaction device associated with the user (which can be a fixed or mobile device, only needed for submitting route requests) to obtain the user's route requirements. Finally, it uses a peer-to-peer network provided by this invention for collaborative computation to obtain audio-visual effects and next-step guidance information tailored to each user.

[0083] In practical implementation, the human-computer interaction device can be omitted. Route requirements are determined based on the user's gameplay content. The gameplay content includes a definite or presumed destination, which may be the final destination or the next of multiple consecutive destinations. The gameplay content can be implemented as the entirety or stages of a scripted storyline or game plot. In this invention, when the peer-to-peer network covers the user's route requirements, the user leaves their home, starting from their initial location. The peer-to-peer network then performs real-time calculations of various states and requirements, including navigation requirements. Through calculations based on laws, regulations, and user agreements, the peer-to-peer network can guide the user from roads to indoor areas, and then from indoor areas to their destination (or the next of multiple consecutive destinations).

[0084] In practical implementation, traditional single-point identification methods can be used to identify users at designated locations to confirm their identities and associate location information. Alternatively, the peer-to-peer network-based collaborative computing provided by this invention can be used for non-specific feature-based identity recognition. The peer-to-peer network of this invention is based on collaborative computing, does not rely on single-point identification, and distributes computational functions across the entire network, reducing the hardware and software requirements of single-point computation, resulting in high execution efficiency and significantly improved anti-attack capabilities. The relatively symmetrical information among node devices prevents illegal data tampering. Even if a single node device is physically compromised and its transmitted data is altered, the network-wide computation is a highly redundant and complex calculation with numerous multi-dimensional verifications. Therefore, the alteration of data transmitted by a single node device does not affect the overall network computation results. Furthermore, it allows for rapid location of faulty and tampered node devices, ensuring the reliability of the overall network computation results. This, in turn, resolves the conflict between data sharing and information security between departments.

[0085] The result data transmitted between node devices can be the processing result of information rather than the information itself. Therefore, the raw data collected (i.e., the perceived data) does not need to be stored. Node devices only receive the calculation results output by other node devices and send out their own calculation results. The amount of information contained in a single calculation result is insufficient to reconstruct any event or target information. A definite result can only be obtained by joint calculation of the calculation results of the entire peer-to-peer network, multi-dimensional data matrix elements, and physical space and facility correspondence. The collaborative calculation has less dependence on the information transmitted by a few node devices, which can fundamentally change the nature of traditional information technology's single-point security sensitivity.

[0086] In this invention, user identity information and location information can be obtained through collaborative computation via a peer-to-peer network provided by this invention. Specifically, the peer-to-peer network is used to perform non-specific feature recognition and location recognition on users. The term "non-specific feature recognition" differs from the common understanding of "recognition" in a strict conceptual definition. Commonly, "recognition" refers to identifying a user's concrete form or specific identity information, such as who they are (including their name and other specific information indicating their identity) or what they are (e.g., a car, a person). However, the "recognition" in this invention refers to identifying each unique user (i.e., the user or other fixed or moving objects besides the user) as itself; that is, for a given object to be identified, its existence is unique. After implementing "non-specific feature recognition," this invention determines that the object to be identified (i.e., the user who has not been identified or whose identity has not been confirmed) is itself, and not other objects to be identified. The result of "non-specific feature recognition" does not require determining the specific characteristics of the object to be identified, nor does it require determining the object's identity information or concrete form. For example, if a person is considered object A to be verified, and an object is considered object B to be verified, then after implementing "non-specific feature recognition," it is not necessary to identify whether object A is a person or what their specific identity is, nor is it necessary to identify whether object B is an object or what kind of object it is; rather, it is necessary to determine that object A is object A itself, and object B is object B itself. Then, corresponding services or controls can be provided for object A or object B.

[0087] The peer-to-peer network comprises multiple node devices, all without a hierarchy, forming a decentralized network and computing architecture. Unlike traditional single-point aggregation computing models, the data transmission direction between node devices in this invention does not have a fixed, preset path relationship. In the peer-to-peer network described in this invention, a particular node device processes the collected raw data to obtain result data, and then propagates the result data to other node devices. Other node devices that receive the result data use it as one of their collected raw data, thus influencing the result data of other node devices. For ease of description, the aforementioned "particular node device" is referred to as the "current node device," and the "other node devices" are referred to as "subsequent node devices." One aspect of this influence is that the result data calculated by subsequent node devices is not entirely determined by the raw data they themselves collected, but rather jointly determined by the result data output by the current node device. Specifically, the result data output by the current node device may change the data processing model and parameters used by subsequent node devices to calculate the result data, thereby affecting the result data of subsequent node devices. For example, if the output data of the current node device is correlated with the raw data collected by subsequent node devices, it is necessary to consider the impact of the output data of the current node device on the accuracy of the output data of the subsequent node devices. Specifically, for the perception of a specific user, if the result data is calculated based solely on the raw data collected by subsequent node devices, it can only reflect the real-time (including real-time location and time) single-point result judgment of that user within the perception range of the subsequent node devices. However, the output data of the current node device reflects the direct perception data and result judgments of that user at other locations and at other times, or other indirectly related perception data and result judgments, which helps to improve the accuracy and comprehensiveness of the result data of the subsequent node devices, including superimposed calculations of the same dimension and correlation references of different dimensions.

[0088] Because there is no master-slave relationship between nodes in a peer-to-peer network, point-to-point transmission is possible. Therefore, for a given user's perceived data reflected in the output data of one node, the information is relatively symmetrical among the other nodes receiving that data. These other nodes use the received data as input, combining it with their own sensor data to calculate their own results. These results naturally encompass both the received data and the information from their own sensors, and are then transmitted to the next layer of nodes. Thus, for a given user's perceived data, information is relatively symmetrical across all nodes. This prevents the impact of tampering or falsification of the calculation process and results of a single node on the overall data. It also serves as a means to detect faulty, tampered, or non-compliant nodes, fundamentally solving the inherent vulnerabilities of traditional information technology: information asymmetry leading to false, forged, or erroneous information, which becomes a point of entry for fraud and cyberattacks. Furthermore, it addresses issues such as poor accuracy, excessive processing time, low reliability, and poor responsiveness in complex applications. Ultimately, it can truly become the information infrastructure for comprehensive management of large areas and the infrastructure for the digital economy. Unlike blockchain technology, which relies on independent computation by each node to determine the result and emphasizes the preservation of original data, this invention focuses on peer-to-peer collaborative computation among node devices. Through this collaborative computation, each node device can adjust its own data processing model (i.e., the algorithm for calculating the result data) and parameters when processing data. This adjustment is a feedback mechanism from all node devices, transforming the computation of all node devices into a unified whole. Instead of individual nodes performing calculations independently, all node devices collaboratively complete the computation. The adjustments to the node device's data processing model are objectively real and will impact subsequent data processing iterations.

[0089] Node devices are equipped with data acquisition devices (in specific implementations, these may include one or more of the following: image acquisition devices, audio acquisition devices, temperature measurement devices, vibration frequency sensing devices, lidar, chemical sensors, and electromagnetic induction devices) and a computing module. The data acquisition devices include at least one type of sensor for collecting sensing data of different corresponding types. The computing module calculates the resulting data based on a data processing model. Node devices located at different acquisition positions (i.e., at different physical installation locations) collect at least one point sample from the user; the point sample is sensing data corresponding to the sensor type. Based on this, without needing to obtain user identity information, multiple node devices in the peer-to-peer network perform collaborative computation to determine that each unique user is themselves, achieving non-specific feature recognition and user location identification.

[0090] Specifically, taking a given node device as the current node device, and considering the data transmission between its preceding and subsequent node devices (in this invention, preceding and subsequent node devices are only used to describe their sequential relationship with the current node device in the current calculation and data transmission process, and do not imply any necessary sequential or priority relationship between them), the current node device receives the result data output by other node devices (including preceding node devices), and subsequent node devices receive the result data output by other node devices (including the current node device). For the current node device, the collected sensing data is combined with the result data from other node devices (including preceding node devices) to calculate the result data of the current node device, and this result data is sent to other node devices (including subsequent node devices). Similarly, the working process of subsequent node devices is the same as that of the current node device, and preceding node devices also receive the result data from the preceding node devices of their predecessors and perform the same working process as the current node device; that is, the node devices in the peer-to-peer network perform the same working process. Furthermore, the node devices in the peer-to-peer network perform collaborative calculations as sensing data is collected and result data is calculated. In this process, the output data of a certain node device is only received and used as input by the subsequent layer of node devices, and the output data of the subsequent layer of node devices will cover the output data of the preceding layer of node devices (including the aforementioned node device).

[0091] In a peer-to-peer network, all events are processed synchronously, and it is not necessarily necessary to explicitly produce phased outputs such as what event was discovered or what the specific content of the event is. In a peer-to-peer network, only the sensor's perception and the corresponding execution device (in this invention, the audio-visual display device)'s response are explicit. All other intermediate processes are processed simultaneously through collaborative computing. That is, during the operation of this invention, the intermediate process of event discovery is imperceptible. As collaborative computing proceeds and the node device obtains the result data, the corresponding execution device automatically responds and executes.

[0092] To further ensure the trustworthiness of the data source and computation process, in this invention, all node devices encrypt their computational results based on an encrypted consensus mechanism, obtaining encrypted results, which are then sent to other node devices. The encrypted consensus mechanism includes one or more consensus mechanisms, with different mechanisms corresponding to changes in the encryption algorithm structure and parameters of the node devices.

[0093] Node devices communicate using standard-sized data packets (i.e., result data or calculation results). In this invention, the node devices in the peer-to-peer network are similar to human neurons. Just as each neuron does not transmit specific data directly describing external events, the node devices do not output raw data. Instead, they process the raw data acquired by connected sensors and data acquisition devices into standard-sized data packets (i.e., result data or calculation results, similar to nerve impulses in neurons) based on their own data processing model (similar to the biological characteristics of nerve cells). The information contained in a single data packet is insufficient to reconstruct any event or target information. A definite result can only be obtained through collaborative computation involving the calculation results across the entire peer-to-peer network, multi-dimensional data matrix elements, and the correspondence between physical space and facilities. Collaborative computation has little dependence on the data output by a few node devices, and it simultaneously processes all requests received or initiated by all node devices. It is a collaborative verification computation of highly multi-dimensional related information, thereby fundamentally changing the traditional single-point security sensitivity of information systems.

[0094] To ensure data integrity and the effective execution of collaborative computing, this invention deploys a QoS mechanism in the peer-to-peer network, which prioritizes the transmission quality of result data between node devices.

[0095] In practical implementation, the peer-to-peer network can be configured using one or a combination of 4G, 5G, or MESH modes to suit different application scenarios. The optimal solution is achieved by considering factors such as feasibility and cost. The MESH mode is based on the LTE standard, communicating at the LTE physical layer. Data is carried by a customized frame structure, and interaction is performed using a dedicated wireless communication protocol. Customizing the frame structure for peer-to-peer network computing and employing a proprietary wireless communication protocol developed for urban cluster peer-to-peer network computing further enhances its security and reliability. Furthermore, the wireless algorithm is fully adaptable to the multipath channel environment controlled by a consensus mechanism required for peer-to-peer network computing. Communication distances range from 100 meters to 10 kilometers within cities, and up to 120 kilometers in the field using omnidirectional antennas. In this embodiment, the Mesh network communication distance is 50-150 meters between indoor nodes and 50 meters to 120 kilometers between outdoor nodes, with each node capable of connecting to 65,535 nodes. In addition, when networking in 4G and 5G modes, there is no limit to the communication distance, and the number of node devices that can be connected depends on the computing power of the computing chip and the communication latency.

[0096] In a peer-to-peer network, for a specific point sample of an object to be identified, the resulting data transmitted from the node that collected the point sample to other nodes allows subsequent nodes to adjust their perceptual attention based on the features of that point sample (it's not necessary for the feature of the point sample to be included in the resulting data; rather, the feature of the point sample participates in the computation of the preceding node, so that the resulting data of the preceding node can be used as input to the data processing model of the subsequent node, allowing the subsequent node's data processing model to adjust the perceptual attention during computation); or, the features of the point sample can be reported for subsequent nodes to adjust their perceptual attention (the feature of the point sample is directly described in the resulting data). If other subsequent nodes do not detect the feature of the point sample, but can determine from the features of other point samples that the undetected feature of the point sample still belongs to the object to be identified, then the undetected feature of the point sample is continued to be described in the resulting data of the current node and transmitted to other nodes. For example, if a preceding node device senses the color of an object A to be identified, but the current node device does not sense the color of the object A to be identified, but it can be determined from the sensing data of other node devices that there is another object A to be identified besides other objects to be identified, then the color of the object A to be identified that has not been sensed will still be represented in the result data of the current node device.

[0097] In this embodiment, the method for reporting the features of the point sample for subsequent node devices to adjust the perceptual attention is as follows: adjusting the parameters of the data processing model of the subsequent node device based on the features of the point sample provided by the preceding node device, so that the subsequent node device can improve the computing power of the point sample to identify its features; or, the subsequent node device uses the perceptual attention model to match the features of the received point sample to adjust the computing power.

[0098] The “feature” mentioned above has a different meaning from the “feature recognition” in the prior art. The “feature recognition” in the prior art usually refers to information that can determine the identity of a user, while the “feature” in this invention represents a kind of perceived data belonging to the object to be identified, such as coordinates, colors belonging to the object to be identified, etc. The “non-specific feature recognition” of the object to be identified cannot be directly completed by the “feature” perceived by a single point.

[0099] In this embodiment, the method for reporting the features of the point sample for subsequent node devices to adjust the perceptual attention is as follows: based on the result data expressing the features of the point sample provided by the preceding node device (in this invention, the features of the point sample are usually not provided themselves, but expressed in the result data), or the features of the point sample (i.e. the features of the point sample itself), the parameters of the data processing model of the subsequent node device are adjusted so that the subsequent node device can improve the computing power of the point sample to identify its features; or, the subsequent node device uses the perceptual attention model to match the features of the received point sample or the result data expressing the features of the point sample to adjust the computing power.

[0100] When a node device processes the output data from several preceding node devices, based on the data processing model, if the objects to be identified described by several preceding node devices can be determined to be the same user through certain common point sample features, the point sample features and other information described by each node device are merged into the same user. For example, point sample features in physical space that almost completely overlap at the same time can be used to determine that they belong to the same user.

[0101] When the result data received by a node device indicates that the flag used by the current node device to identify the object to be identified before the current reception of result data is different from the flags used by other node devices to identify the object to be identified, and the flags assigned to the object by other node devices have been updated, then the flag used by the current node device to identify the object to be identified before the current reception of result data is converted. Specifically, the method for converting the flag used by the current node device to identify the object to be identified before the current reception of result data is as follows:

[0102] The flag used by the current node device to identify the object to be identified before the current reception of result data is replaced with the latest flag assigned to the object by other node devices; this is a simpler implementation of the present invention.

[0103] Alternatively, the conversion relationship between the flag used by the current node device to identify the object to be identified before the current receiving result data and the updated flag assigned to the object by other node devices can be recorded, and the conversion can be performed when the current node device's current receiving result data needs to be referenced; this is a relatively complex implementation method provided by the present invention.

[0104] Alternatively, the node device can deploy a conversion model to perform corresponding conversions on the labels of multiple objects to be identified based on the input raw data or result data; this is a more complex implementation provided by the present invention.

[0105] In this invention, in order to improve the effectiveness of "non-specific feature recognition", for one or more point samples collected successively by node devices at different collection locations, if the feature values ​​of one or more point samples at different collection locations meet the preset similarity conditions or are determined by a specific model to have a correlation threshold, and are unique at each collection location, then it is determined that the point samples at different collection locations are correlated.

[0106] On the other hand, for one or more point samples collected simultaneously by node devices at different collection locations, if the node devices at different collection locations collect data on the same spatial field, and there is only one object to be identified in the spatial field, or the collected point sample can correctly point to one of the multiple objects to be identified, then for a certain object to be identified, one or more point samples collected by node devices at different collection locations are correlated.

[0107] In this invention, the data acquisition device of the node device includes one or more combinations of an image acquisition device, an electromagnetic induction device, a temperature measurement device, and a vibration frequency sensing device, and a lidar. The data acquired by the aforementioned devices (i.e., one or more combinations of the image acquisition device, electromagnetic induction device, temperature measurement device, and vibration frequency sensing device) and the three-dimensional point cloud acquired by the lidar, or the point cloud generated from images acquired by multiple image acquisition devices, are jointly calculated to obtain three-dimensional points with data. The image color, contour, lines, reflectivity, motion trend, electromagnetic characteristics, temperature, temperature change trend, vibration frequency, and vibration frequency change trend based on two-dimensional perception are used as additional attributes of the corresponding three-dimensional points to constitute an attributed three-dimensional point cloud. Combining electromagnetic induction, temperature patterns, vibration frequency change characteristics, motion correlation (different motion correlations exhibited by different materials such as ropes and fabrics), and reflectivity, the correspondence between each region of the attributed three-dimensional point cloud and each part or related part of the 3D appearance of the object to be identified is determined. This embodiment utilizes the attributes and correlations of attributed 3D point clouds to determine the relationships between points, the correspondence between the regions to which each related point belongs and each part or related part of the 3D appearance of the object to be identified, and can more accurately determine the point sample features belonging to the object to be identified, thereby improving the efficiency and accuracy of "non-specific feature recognition".

[0108] In the process of "non-specific feature recognition," this invention can also acquire the identity information of the object to be identified when necessary. Specifically, when it is determined that the identity information of the object to be identified needs to be acquired, an identity information acquisition command is triggered. This command is used as one of the inputs in the calculation of the result data of the node device. By driving the node device connected to the peer-to-peer network with barrier-free data collection conditions capable of acquiring the identity information of the object to be identified to respond with the corresponding result data, the identity information of the object to be identified is acquired. The acquisition of identity information is also the result of collaborative calculation; that is, the determination that identity information needs to be acquired triggers the acquisition of identity information, rather than being additionally triggered by a specific request command. Based on this invention, if permission calculation is triggered by a request command, in most cases, it can be completed without acquiring identity information. Only in a few cases, when it is found that permission calculation cannot be completed without acquiring identity information, is the determination that identity information needs to be acquired generated according to implementation requirements. For example, if collaborative computing reveals that a person's identity information exists in several location-specific QR code registration systems, package pickup registration systems, or consumer registration systems, and prior authorization from the person or legal access to these systems is obtained, then the peer-to-peer network can drive node devices connected to these systems via barrier-free data collection. The obtained information is then transmitted to the peer-to-peer network through each node device for information comparison and to provide accurate identity information. Based on this, the present invention can also minimize the possibility of identity tampering with a system.

[0109] Specifically, the peer-to-peer network determines the permissions of the target by verifying the authenticity of the identity information. Nodes in the peer-to-peer network capable of acquiring identity information may choose not to provide the identity information (or may provide it depending on implementation requirements), but instead express the verification result in their own result data based solely on the verification requirements for the identity information's authenticity found in the received result data. In other words, in this invention, even when a node capable of acquiring identity information does not provide it, the verification result is expressed in its own result data based solely on the verification requirements for the identity information's authenticity found in the received result data.

[0110] When a node device in a peer-to-peer network that can obtain identity information does not provide identity information, the information source device that drives the provision of identity information establishes an encrypted file transmission channel with the input terminal of the node device that needs to obtain identity information, or establishes an encrypted information transmission channel using other network communication modes; and uses the identity information as one of the inputs of the node device.

[0111] When necessary, in order to meet the needs of other traditional computing modes for raw data, such as the need for evidence preservation in traditional evidence presentation, in this embodiment, the node settings can be equipped with a data storage device for storing the raw data sensed by the sensor.

[0112] In practical implementation, the node device can also be equipped with leakage protection and other functions in its power supply. The node device can also provide various communication interfaces, including fiber optic interfaces and wireless communication interfaces; it can also provide a data interface for connecting external storage devices. The node device can be powered by solar energy or mains power. When implemented outdoors, the node device can be installed on poles such as streetlights (without crossarms, mounted on the main pole, or integrated into the lampshade); in pole-less areas, if implemented indoors, it can be wall-mounted or integrated into the ceiling.

[0113] When this invention is implemented indoors and outdoors, the node devices, as artificial intelligence facilities installed in public spaces, can serve as digital economy infrastructure for urban clusters, providing 24 / 7 seamless coverage. Through collaborative computing across node devices, vehicle identification at any location within the coverage area can achieve near 100% accuracy, with location identification accuracy related to sensor accuracy.

[0114] In this invention, the architecture of a peer-to-peer computing network consists of nodes of the same type and function. Each node dynamically adjusts its data processing model in real time according to the network's consensus mechanism. The raw data collected by the data acquisition devices (including sensors, cameras, etc.) connected to each node is processed and encrypted by the node according to its own data processing model, generating byte-level processing and encryption results (i.e., result data). This result data is then sent to other node devices (the computational and encryption results received by the current node from other node devices are also considered part of the raw data collected by the current node). Therefore, the effect of the raw data sensed by each sensor will propagate exponentially among a massive number of peer-to-peer node devices. If each node sends its result data to 100 surrounding node devices, after four units of time, hundreds of millions of node devices will be affected by the event sensed by that sensor. In this computing model, information is relatively symmetrical and immune to tampering and forgery. It fundamentally solves the inherent hidden dangers of traditional information technology, namely, the false, forged, and erroneous information caused by information asymmetry, which in turn become entry points for fraud and cyberattacks, as well as the problems of long cycles, poor accuracy, and poor adaptability in complex and integrated applications. In turn, it truly becomes an information infrastructure for comprehensive management of large areas and a digital economy infrastructure.

[0115] This invention utilizes collaborative computing in a peer-to-peer network. When the results of this collaborative computing can identify an event, the event discovery is complete. In this embodiment, the discovery of an event by the peer-to-peer network includes the content of the event, the location of the event, and the corresponding response. In a peer-to-peer network, all events are processed synchronously; it is not necessarily necessary to explicitly produce staged outputs such as what event was discovered or what its specific content is. In a peer-to-peer network, only the sensor's perception and the corresponding execution device's response are explicitly defined. All other intermediate processes are processed simultaneously through collaborative computing. That is, during the operation of this invention, the intermediate process of event discovery is imperceptible; it is as the collaborative computing progresses, the node devices obtain the result data, and the corresponding execution devices automatically respond and execute.

[0116] In this invention, each audio-visual display device joins a peer-to-peer network through one or more node devices. To prevent hijacking, this invention can use multiple node devices to collaboratively control the audio-visual display device, further improving its immunity to hijacking attacks. A human-computer interaction device associated with the user connects to the node devices as an access device and submits route requests to the peer-to-peer network. In this invention, a route request can be considered a request command, i.e., requesting the user to drive autonomously from one location to another. Responses to the request command include various scenarios such as "request-execution," "request-response," or others. When the result data calculated by one or more node devices in the peer-to-peer network matches the request command, the result corresponding to the request command is represented in the result data output by one or more node devices, according to preset conditions, a pre-deployed program, or a data processing model deployed on the node device. If, based on collaborative computation, it is determined that the current node device needs to respond to the request command, the current node device will send instructions to the execution device connected to the current node device according to the calculated result data, controlling the execution device to complete the response action; this is the "request-execution" scenario. In this invention, if it is determined based on collaborative computing that the audio-visual display device needs to present the corresponding audio-visual effects and the user's next guidance information, the current node device will send instructions to the audio-visual display device connected to the current node device according to the calculated result data, and control the audio-visual display device to complete the presentation of audio-visual effects and guidance information.

[0117] Based on peer-to-peer collaborative computing, the execution device can act as one of the node devices. As collaborative computing progresses, when the result data obtained by the execution device can correspond to the request command and perform the relevant operation, the execution device completes the response to the request command. In this invention, audio-visual effects and user guidance information are represented in the result data. The audio-visual display device receives the result data output by the connected node device. If a specific element in the result data indicates that the audio-visual display device needs to present audio-visual effects and guidance information, or if the result data is used as one of the inputs to the node device's data processing model to calculate and determine that the corresponding audio-visual display device needs to present audio-visual effects and guidance information, then the audio-visual display device presents the corresponding audio-visual effects and guidance information.

[0118] When the audio-visual display device needs to present audio-visual effects and guidance information, it combines the result data received from other node devices to calculate its own result data. Based on this result data, the device controls itself to present the corresponding audio-visual effects and guidance information. In this invention, the audio-visual display device does not need to first determine whether it needs to present audio-visual effects and guidance information. Instead, it combines the result data received from other node devices with the perception data collected by its own sensors, inputs this data into its own data processing model, and outputs the result data indicating whether the device should present audio-visual effects and guidance information, and what content of these effects and guidance information should be presented.

[0119] In this invention, the calculated results include the optimal solutions for all scenarios obtained through collaborative calculations between all users within the display area and the external environment at the current moment. Audiovisual effects and user guidance information are presented through audiovisual display devices. In this invention, the results of calculations for various types of information in the peer-to-peer network are presented as result data. All audiovisual display devices, as node devices, contribute the optimal solutions for all scenarios during collaborative calculations within the peer-to-peer network. Furthermore, all control commands for audiovisual display devices are the optimal solution commands output by the node devices connected to them after collaborative calculations. This invention eliminates the traditional generation and transmission of commands to avoid security vulnerabilities that could make audiovisual display devices a risk point.

[0120] In this embodiment, the audio-visual display device is a node device that connects to the execution components of a specific function. The execution feedback information of the execution components of the audio-visual display device is fed back to the audio-visual display device and participates in the calculation of the subsequent result data of the audio-visual display device.

[0121] In this invention, since the audio-visual display device can be one of the node devices, its response execution is based on the calculation results obtained through collaborative computing, resulting in high response efficiency and avoiding illegal responses such as false execution or failure to execute when required due to network attacks. To prevent hijacking, this invention can also use multiple node devices to collaboratively control the audio-visual display device, further improving its immunity to hijacking attacks.

[0122] In a peer-to-peer network, the result data calculated and output by node devices can be implemented as a representation of the state corresponding to the perceived data (i.e., the raw data). This state value can be used for representation, thus eliminating the need for node devices to store and transmit the raw data. In this embodiment, the data or elements in the multidimensional matrix are related to the installation location, attributes, etc., of each node device. Therefore, when transmitting the result data, what is actually transmitted is the transcoded result after transcoding multiple sets of parameters. A multidimensional matrix is ​​actually a combination of multiple sets of parameters. For example, if a user's path is from abcd, and the physical location of the abcd node device is fixed, then the sequence abcd can be expressed by a single character or a similar concept during the multi-parameter transcoding transmission.

[0123] Based on the technical characteristics of peer-to-peer networks, they can be applied to various use cases that provide targeted services or controls for specific users or events. Since the data transmitted between node devices is the result of information processing, rather than the information itself, the raw data collected (i.e., perceived data) does not need to be stored. Node devices only receive the calculation results output by other node devices and send out their own calculation results. The information contained in a single calculation result is insufficient to reconstruct any event or target information; a definite result can only be obtained through collaborative calculation using the calculation results across the entire peer-to-peer network, multi-dimensional data matrix elements, and the correspondence between physical space and facilities. Collaborative calculation has less dependence on the information transmitted by a few node devices, thus fundamentally changing the traditional single-point security sensitivity of information systems.

[0124] In this invention, since the output data of each node device reflects the state evolution of the output data of the preceding node devices, the user's behavior, attributes, state, or events at the time of being perceived by the preceding node devices can be inferred based on the output data received by the current node device. For example, when it is necessary to find the location of user a 15 minutes ago, the location corresponding to the node device that user a was perceived at the current moment can be obtained, and the location of user a can be inferred. Then, based on the transmission path of the output data, it can be inferred back to 15 minutes ago, and the location of user a 15 minutes ago can be estimated (determined by the node device that user a was perceived). Furthermore, the node device does not need to store the original data about user a. That is, based on this invention, it is not necessary to identify the original data to find user a, but rather to first infer the node device that user a was perceived, and if necessary, obtain the original data about user a at the time when it needs to be found from the storage device connected to the node device.

[0125] In this invention, the audio-visual display device receives result data output from other node devices. The principle is as follows: when a corresponding audio-visual display device needs to present audio-visual effects and guidance information, if the result data calculated by one or more node devices can determine which audio-visual display device needs to present these effects and guidance information, then the corresponding audio-visual display device is added to the node list for transmitting the current result data. The one or more node devices directly transmit the result data to the audio-visual display device or the node device connected to it. This is done based on preset conditions, algorithm output, or model output, adding the corresponding audio-visual display device to the node list for transmitting result data. Alternatively, the audio-visual display device receives result data output from other node devices in a layer-by-layer transmission manner. During the collaborative computing process of the peer-to-peer network, each node device also calculates the node list for receiving result data during each result data calculation. Based on the current result data, it clearly knows which one or more audio-visual display devices need to be added and will be added to the node list. The audio-visual display device or the node device connected to it is directly used as the next layer's subsequent node device to directly receive the current result data, achieving cross-layer transmission and transforming the peer-to-peer network into a three-dimensional architecture. For example, if the result data from the current node device clearly indicates that it needs to be submitted to the public security bureau as evidence, then according to the normal layer-by-layer transmission method, the result data from the current node device would require at least one or more layers of transmission to reach the corresponding node device in the public security bureau. However, if the node device in the public security bureau's network is added to the node list, then the corresponding node device in the public security bureau can directly receive the result data from the current node device when it is transmitted to the next layer, thereby greatly shortening the processing time and improving responsiveness. This invention uses a peer-to-peer network; therefore, this temporary construction is precisely the advantage of this invention. The traditional layer-by-layer aggregation architecture of information systems cannot withstand the complex computing requirements brought about by this temporary network construction.

[0126] To conserve resources and improve the operational efficiency of audio-visual display equipment, enabling it to meet the needs of more users, this invention establishes a user group based on the following: when the collaborative calculation results determine that multiple users share the same orientation and travel speed, the distance between users meets the standard for group travel, and only one user's route requirement is obtained, or the route requirements of multiple users are identical; in this case, the users are grouped together. Furthermore, when providing guidance, only one or a few users within the same user group need to be guided to complete the guidance for the entire group.

[0127] In this invention, the selection of users for guidance within a team of users specifically involves, based on the results of collaborative computation, if it is determined that the vision and / or hearing of some users are interfered with by other users, then visual guidance information and / or audio guidance information are prioritized for the user whose route needs have been obtained or for the user at the front whose next step guidance information is correctly oriented. If both the vision and hearing of the user whose route needs have been obtained are interfered with by other users, then visual guidance information or audio guidance information is displayed or played for other users whose vision or hearing is not interfered with. For example, two users walking side by side do not interfere with each other visually, but they do interfere with each other auditorily; when four users walk in pairs, the users in the front row cause visual interference to the users in the back row, but do not interfere with each other auditorily, while users in the same row cause auditory interference. In specific implementation, the type and presentation method of guidance information can be selected according to the results of collaborative computation.

[0128] If all users' vision and hearing are not disturbed by other users, then visual guidance information and audio guidance information are displayed to each user to meet each user's needs.

[0129] The above embodiments are merely illustrative of the present invention and are not intended to limit the invention. Any changes or modifications to the above embodiments based on the technical essence of the present invention will fall within the scope of the claims of the present invention.

Claims

1. A method for displaying offline sound and light effects, characterized in that, Deploy audio-visual display equipment within the display area; acquire user orientation data, walking speed data, and posture data; based on the user's orientation, walking speed, and posture, display audio-visual effects and guidance information corresponding to the user's current orientation, walking speed, and posture through the audio-visual display equipment; By deploying corresponding types of sensors in and covering the display area, the physical attributes of users in the display area are obtained, the route needs of users are obtained or predicted, and collaborative calculations are performed through a peer-to-peer network to obtain audio-visual effects and guidance information for each user. Among them, peer-to-peer networks are used to perform non-specific feature identification and location identification of users; The peer-to-peer network consists of multiple node devices, and there is no master-slave relationship among all node devices. Each node device is equipped with a data acquisition device and a computing module. The data acquisition device includes at least one type of sensor for collecting different corresponding types of sensing data. Node devices set at different acquisition locations collect at least one point sample from the user, and the point sample is sensing data of the corresponding sensor type. For a given node device, the collected sensing data is processed to obtain result data, which is then propagated to other node devices. Other node devices that receive the result data use it as one of the original data collected, and the result data influences the result data of other node devices. Based on this, without needing to obtain user identity information, multiple node devices in the peer-to-peer network perform collaborative computation to determine that each unique user is itself, achieving non-specific feature recognition and user location identification.

2. The offline sound and light effect display method according to claim 1, characterized in that, Several types of game attributes are set for each user. If a user's current orientation, movement speed, or posture affects their own game attributes, then the corresponding sound and light effects are displayed for that user, and the game attributes of the user or other users are modified. If a user's current orientation, movement speed, or posture affects the game attributes of other users, then the corresponding sound and light effects are displayed for those other users, and the game attributes of the user or other users are modified.

3. The offline sound and light effect display method according to claim 2, characterized in that, The system reads the user's online game attributes, calculates matching audio-visual effects based on these attributes, and uploads the modified game attributes corresponding to the user's offline influence on their own or other users' game attributes to the online game server according to preset rules, thus updating the user's online game attributes.

4. The offline sound and light effect display method according to claim 1, characterized in that, Obtain the user's route requirements and location information; based on the route requirements and the user's real-time location information, calculate the guidance information for the user's next step; The guidance information is presented through an audio-visual display device at the user's real-time location to guide the user.

5. The offline sound and light effect display method according to claim 4, characterized in that, The system acquires user orientation data, walking speed data, and posture data. Using preset conditions or a prediction model pre-trained through machine learning, it predicts the user's next action, including the user's orientation, walking speed, and posture. At the location that matches the predicted user's next orientation, walking speed, and posture, the system presents audio-visual effects and guides the user's next step.

6. The offline sound and light effect display method according to claim 5, characterized in that, If the prediction of the user's audio-visual effects or next action is inaccurate, the audio-visual display device that presents the audio-visual effects and guides the user's next action will be corrected based on the user's real-time orientation data, walking speed data, and posture and action data. The density of people around the user, environmental information, orientation data, walking speed data, and posture and action data of people around the user will be added to the sample library as training samples for further training and adjustment of the prediction model.

7. The offline sound and light effect display method according to claim 5, characterized in that, The system acquires the user's height, leg length, and cadence data to calculate the user's walking speed. If the prediction of the user's next move is inaccurate, the calculated walking speed is used instead of the predicted walking speed.

8. The offline sound and light effect display method according to claim 5, characterized in that, We establish personalized prediction models for different users. After identifying users, we use the associated prediction models to predict the user's next action.

9. The offline sound and light effect display method according to claim 1, characterized in that, The aforementioned audio-visual display equipment includes visual information display equipment, used to display visual effects and visual guidance information; A visual information display device that acquires real-time user orientation, speed, and posture data, follows the user's orientation, speed, and posture, and maintains a certain distance from the user to display visual guidance information for the user's next step; or, corresponding to the current user's or other users' positions, and displays visual effects following the current user's or other users' positions. Alternatively, based on the user's route requirements and real-time location information, a peer-to-peer network can be used for collaborative computation to obtain a visual information display device that matches the location where visual guidance information needs to be displayed for each user's next step; and a visual information display device that maintains a certain distance from the user relative to the user's real-time location information, real-time walking speed, and real-time posture and movement can be used to display the visual guidance information for the user's next step; or, the visual effect can be displayed according to the location of the current user or other users and follow the location of the current user or other users.

10. The offline sound and light effect display method according to claim 9, characterized in that, The distance between the visual information display device that displays visual guidance information and the user is calculated based on the user's height and stride length.

11. The offline sound and light effect display method according to claim 1, characterized in that, The aforementioned audio-visual display device includes an audio playback device for playing audio effects and audio guidance information; an audio playback device that acquires the user's real-time location information, walking speed data, and posture and movement data, follows the user's position, walking speed, and posture and movement, and maintains the sound field covering the user's position, and plays audio effects and audio guidance information for the user's next step; Alternatively, based on the user's route requirements and real-time location information, a peer-to-peer network can be used for collaborative calculations to obtain an audio playback device that matches the location where each user needs to play audio guidance information next. It also plays audio playback devices that maintain sound field coverage of the user's location relative to the user's real-time location information, real-time walking speed, and real-time posture and movements, and plays audio effects and audio guidance information for the user's next step.

12. The offline sound and light effect display method according to claim 11, characterized in that, The audio playback device is positioned above the display area and is equipped with a downward-facing acoustic shield, which is used to limit the sound field of the audio playback device to a certain range. Alternatively, a pan-tilt-zoom (PTZ) speaker can be used, and the launch angle can be adjusted according to the orientation and speed of the user who needs to listen to the audio effects and audio guidance information.

13. The offline sound and light effect display method according to claim 1, characterized in that, Alternatively, route requirements can be inferred from the gameplay content targeted at the user, which includes a defined or presumed destination, which may be the final destination or the next of multiple consecutive destinations.

14. The offline sound and light effect display method according to claim 1, characterized in that, The current node device receives the result data output by other node devices; for the current node device, it combines the collected sensing data with the result data from other node devices to calculate the result data of the current node device, and then sends it to other node devices; In a peer-to-peer network, node devices perform collaborative computation as they collect sensing data and calculate result data.

15. The offline sound and light effect display method according to claim 1, characterized in that, In a peer-to-peer network, for a specific point sample of a user, the resulting data transmitted from the node device that collected the point sample to other node devices allows subsequent node devices to adjust their perceptual attention based on the features of that point sample, or report the features of that point sample for subsequent node devices to adjust their perceptual attention. If other subsequent node devices do not detect the features of that point sample, but can determine from the features of other point samples that the undetected features still belong to that user, then the undetected features of that point sample are continued to be represented in the result data of the current node device and transmitted to other node devices.

16. The offline sound and light effect display method according to claim 14, characterized in that, The method for reporting the features of the point sample to subsequent node devices for adjusting the perceptual attention is as follows: based on the result data expressing the features of the point sample provided by the preceding node device, or the features of the point sample, adjust the parameters of the data processing model of the subsequent node device so that the subsequent node device can improve the computing power of the subsequent node device to identify the features of the point sample; or, the subsequent node device uses the perceptual attention model to match the features of the received point sample or the result data expressing the features of the point sample to adjust the computing power.

17. The offline sound and light effect display method according to claim 16, characterized in that, When a node device processes the output data of several preceding node devices, based on the data processing model, if the users described by several preceding node devices can be identified as the same user through certain common point sample features, the point sample features and other information described by each node device will be merged into the same user.

18. The offline sound and light effect display method according to claim 17, characterized in that, If the result data received by a node device indicates that the flag used by the current node device to identify the user before the current receipt of result data is different from the flag used by other node devices to identify the user, and the flags assigned to the user by other node devices have been updated, then the flag used by the current node device to identify the user before the current receipt of result data is converted.

19. The offline sound and light effect display method according to claim 17, characterized in that, The method for converting the flag used to identify the user by the current node device before the current reception of result data is as follows: Replace the flag used by the current node device to identify the user before the current reception of result data with the latest flag assigned to the user by other node devices; Alternatively, record the conversion relationship between the flag used by the current node device to identify the user before the current reception of result data and the updated flag assigned to the user by other node devices, and perform the conversion when it is necessary to reference the result data received by the current node device in the current reception. Alternatively, node devices can deploy conversion models to perform corresponding conversions on the identifiers of multiple users based on the input raw data or result data.

20. The offline sound and light effect display method according to claim 15, characterized in that, For one or more point samples collected sequentially by node devices at different collection locations, if the feature values ​​of one or more point samples at different collection locations meet the preset similarity conditions or are determined by a specific model to have a correlation threshold, and are unique at each collection location, then it is determined that the point samples at different collection locations are correlated.

21. The offline sound and light effect display method according to claim 15, characterized in that, If node devices at different acquisition locations collect one or more point samples simultaneously, and if the node devices at different acquisition locations collect samples from the same spatial field, and there is only one user in the spatial field, or the collected point sample can correctly point to one of the multiple users to which it belongs, then for a certain user, the one or more point samples collected by node devices at different acquisition locations are correlated.

22. The offline sound and light effect display method according to claim 21, characterized in that, The data acquisition device of the node equipment includes one or more of the following: image acquisition device, electromagnetic induction device, temperature measurement device, vibration frequency sensing device, and lidar. It performs joint calculations on the data acquired by the above devices and the 3D point cloud acquired by the lidar, or on the point cloud generated from images acquired by multiple image acquisition devices, to obtain 3D points with data. It uses image color, contour, lines, reflectivity, motion trend, electromagnetic characteristics, temperature, temperature change trend, vibration frequency, and vibration frequency change trend based on 2D perception as additional attributes of the corresponding 3D points, forming an attributed 3D point cloud. Combining electromagnetic induction, temperature patterns, vibration frequency change characteristics, motion correlation, and reflectivity, it determines the correspondence between each region of the attributed 3D point cloud and each or related part of the user's 3D appearance.

23. The offline sound and light effect display method according to claim 1, characterized in that, When it is necessary to obtain the user's identity information, an identity information acquisition command is triggered. The identity information acquisition command is used as one of the inputs to participate in the calculation of the result data of the node device. By driving the node device in the peer-to-peer network that is connected to the barrier-free data collection conditions that can obtain the user's identity information, the corresponding result data is responded to, thereby realizing the acquisition of the user's identity information.

24. The offline sound and light effect display method according to claim 23, characterized in that, Peer-to-peer networks determine user permissions by verifying the authenticity of user identity information. In a peer-to-peer network, the node device that can obtain identity information does not provide the identity information itself, but only expresses the verification result in the result data of the node device based on the verification requirements for the authenticity of identity information in the received result data.

25. The offline sound and light effect display method according to claim 24, characterized in that, In a peer-to-peer network, the node device capable of obtaining identity information does not provide the identity information itself. Instead, the information source device that drives the provision of identity information establishes an encrypted information transmission channel with the node device input terminal that needs to obtain the identity information, or establishes an encrypted information transmission channel using other network communication modes, and uses the identity information as one of the inputs to the node device.

26. The offline sound and light effect display method according to claim 1, characterized in that, The data acquisition device includes one or more of the following: image acquisition device, audio acquisition device, temperature measurement device, vibration frequency sensing device, lidar, chemical sensor, and electromagnetic induction device.

27. The offline sound and light effect display method according to claim 1, characterized in that, The human-computer interaction device associated with the user connects to the node device as an access device and submits route requests to the peer-to-peer network; each audio-visual display device joins the peer-to-peer network through one or more node devices; If, based on collaborative computing, it is determined that the audio-visual display device needs to present corresponding audio-visual effects and the user's next guidance information, the current node device will send instructions to the audio-visual display device connected to the current node device according to the calculated result data, and control the audio-visual display device to complete the presentation of audio-visual effects and guidance information.

28. The offline sound and light effect display method according to claim 27, characterized in that, The sound and light effects and the user's next step guidance information are represented in the result data; the sound and light display device receives the result data output by the connected node device. If a specific element in the result data indicates that the sound and light display device needs to present sound and light effects and guidance information, or if the result data is used as one of the inputs to the data processing model of the node device, and it is calculated that the corresponding sound and light display device needs to present sound and light effects and guidance information, then the sound and light display device presents the corresponding sound and light effects and guidance information.

29. The offline sound and light effect display method according to claim 28, characterized in that, When the audio-visual display device needs to present audio-visual effects and guidance information, it combines the result data received from other node devices to calculate its own result data, and controls the audio-visual display device to present the corresponding audio-visual effects and guidance information based on the obtained result data.

30. The offline sound and light effect display method according to claim 29, characterized in that, For audio-visual display devices, the calculated results include the optimal solution for all situations obtained at the current moment based on collaborative calculations between all users in the display area and the external environment; audio-visual effects and guidance information for the user's next step are presented through audio-visual display devices.

31. The offline sound and light effect display method according to claim 29, characterized in that, The audio-visual display device receives the result data output by other node devices. The principle is as follows: when the corresponding audio-visual display device needs to present audio-visual effects and guidance information, if the result data calculated by one or more node devices can determine the audio-visual display device that needs to present audio-visual effects and guidance information, then the corresponding audio-visual display device is added to the node list for transmitting the current result data. The one or more node devices directly transmit the result data to the audio-visual display device or the node device connected to the audio-visual display device; or, the audio-visual display device receives the result data output by other node devices in a layer-by-layer transmission manner.

32. The offline sound and light effect display method according to claim 31, characterized in that, Based on preset conditions or algorithm output and model output, the corresponding audio-visual display devices are added to the node list for transmitting result data.

33. The offline sound and light effect display method according to claim 28, characterized in that, The audio-visual display device is a node device with execution components that are set to perform specific functions. The execution feedback information of the execution components of the audio-visual display device is fed back to the audio-visual display device and participates in the calculation of the subsequent result data of the audio-visual display device.

34. The offline sound and light effect display method according to claim 1, characterized in that, If the collaborative computing results determine that multiple users have consistent orientation and travel speed, the distance between users meets the peer distance standard, and among the multiple users, only one user's route requirement is obtained, or the route requirements of multiple users are the same, then the multiple users are grouped into a team of users.

35. The offline sound and light effect display method according to claim 34, characterized in that, Among users in the same user group, based on the results of collaborative computing, if it is determined that the vision and / or hearing of some users are interfered with by other users, then visual guidance information and / or audio guidance information will be displayed to the user whose route needs have been obtained or to the user at the forefront whose next step guidance information is correctly oriented; if the vision and hearing of the user whose route needs have been obtained are both interfered with by other users, then visual guidance information or audio guidance information will be displayed to other users whose vision or hearing has not been interfered with. If all users' vision and hearing are not disturbed by other users, then visual guidance information and audio guidance information are displayed to each user.