Non-contact intelligent navigation system and interaction method

Abstract

The invention relates to a non-contact intelligent navigation system and an interaction method, and the system comprises an identifier identification module which is used for triggering a navigation service through two-dimensional code scanning, RFID tag reading or Bluetooth beacon matching; the content management module is used for storing multi-language guide content and supporting cloud synchronization and dynamic updating; the voice explanation module is integrated with a TTS technology module and supports voice instruction control and offline caching; the AR module is used for superposing virtual contents to a real scene based on an SLAM (Simultaneous Localization and Mapping) algorithm module or an ARCore / ARKit framework, and supporting gesture interaction; the user interaction module supports gesture operation, voice control and screen touch interaction; and the data analysis module is used for collecting user behavior data and optimizing a guide recommendation path through a machine learning algorithm. According to the non-contact intelligent navigation system, the sanitation safety is improved, the user experience is enhanced, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent tour guide technology, and in particular to a contactless intelligent tour guide system and an interaction method. Background Art

[0002] Traditional guided tour systems typically rely on manual explanations or user contact with shared devices (such as handheld guides and touchscreen terminals). This approach presents issues such as sanitation risks, low interaction efficiency, and limited functionality. Some existing contactless guided tour systems use QR codes or Bluetooth technology to trigger guided tours, but these still present issues such as inadequate interactive experience after content updates, and a lack of personalized recommendations. Therefore, a guided tour system integrating contactless interaction, dynamic content management, and intelligent data analysis is needed. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a contactless intelligent tour guide system, which not only improves hygiene and safety, but also enhances user experience and reduces operation and maintenance costs.

[0004] The technical solution adopted by the present invention to solve the technical problem is: a contactless intelligent tour guide system, comprising

[0005] Identification module, used to trigger the tour guide service through QR code scanning, RFID tag reading or Bluetooth beacon matching;

[0006] Content management module, storing multilingual guide content, supporting cloud synchronization and dynamic updates;

[0007] The voice explanation module integrates the TTS technology module (text-to-speech technology) to support voice command control and offline caching;

[0008] AR augmented reality module, based on the SLAM algorithm (simultaneous localization and mapping) module or ARCore / ARKit framework, overlays virtual content onto real scenes and supports gesture interaction;

[0009] User interaction module, supporting gesture operation, voice control and screen touch interaction;

[0010] The data analysis module collects user behavior data and optimizes tour recommendations through machine learning algorithms.

[0011] In one embodiment, the QR code scanning of the identification module of the contactless intelligent tour guide system sets the ZXing or QR Code Reader library to resolve the exhibit ID. The RFID tag is a high-frequency passive tag that supports direct reading by the NFC function of the mobile phone. The Bluetooth beacon is based on the iBeacon protocol and determines the distance threshold between the user and the exhibit through the RSSI signal strength.

[0012] In one embodiment, the multi-language switching of the content management module of the contactless intelligent guide system supports automatic matching of the user device language or manual selection, and the dynamic update is achieved through differential technology, pushing the changed data to the user end to reduce traffic consumption.

[0013] In one embodiment, the voice explanation module of the contactless intelligent tour guide system supports semantic understanding of voice instructions, responds to natural language requests, and manages offline cache content through an LRU algorithm to retain frequently accessed data.

[0014] In one embodiment, the AR augmented reality module of the contactless intelligent tour guide system realizes spatial alignment of virtual content and real exhibits based on a SLAM algorithm module.

[0015] In one embodiment, the virtual content of the contactless intelligent guide system needs to be verified through spatial calibration before being superimposed to ensure that the error with the exhibit position is less than a preset threshold. The AR interaction data is uploaded to the cloud for optimizing the virtual content design.

[0016] In one embodiment, the user interaction module of the contactless intelligent navigation system sets up a layered interactive interface, including a child mode and an expert mode. The child mode simplifies the operation logic and recommends AR interactive games. The expert mode opens up 3D model detail viewing and in-depth literature reading functions.

[0017] In one embodiment, the user behavior data of the data analysis module of the contactless intelligent tour guide system includes the length of stay, the number of AR interactions and the path deviation rate. A clustering algorithm is used to divide user interest tags to provide differentiated tour guide recommendations for different groups.

[0018] An interactive method for a contactless intelligent tour guide system, using the contactless intelligent tour guide system, comprises the following steps:

[0019] S1: Triggering the navigation service through the identification module;

[0020] S2: Load the corresponding guide content from the cloud or local through the content management module;

[0021] S3: Automatically play the voice explanation through the voice explanation module, and the playback can be controlled by voice commands;

[0022] S4: By starting the AR augmented reality module, virtual content is superimposed on the real scene based on the SLAM algorithm module or ARCore / ARKit framework;

[0023] S5: Supports gesture operation and screen touch interaction through the user interaction module;

[0024] S6: Collect user behavior data through the data analysis module and optimize the recommended navigation path.

[0025] In one embodiment, the interaction method of the contactless intelligent tour guide system also includes real-time crowd flow monitoring and dynamic path planning. The real-time crowd flow monitoring uses Bluetooth beacons or Wi-Fi probes to count the crowd density in the exhibition area. The dynamic path planning adjusts the recommended route based on the crowd density to avoid congestion and balance the load in the exhibition area.

[0026] The beneficial effects of this application are:

[0027] This application provides a contactless intelligent tour guide system, which realizes contactless service triggering through technologies such as QR codes, RFID, Bluetooth beacons, etc., and combines content management, voice explanation, AR augmented reality, user interaction and data analysis to improve tour guide efficiency and user experience.

[0028] The content management module of the navigation system adopts multi-language switching and dynamic updates to meet the user's multi-language switching needs and reduce user-side traffic and storage usage.

[0029] The voice explanation module of the tour guide system adopts voice command semantic understanding and offline cache management to achieve intelligent interaction and network adaptability.

[0030] The AR augmented reality and user interaction modules of the guide system adopt SLAM algorithm modules and interaction methods to achieve high-precision superposition and diversified interaction.

[0031] The user interaction mode of the guide system adopts child mode and expert mode, realizing layered services and improving user participation.

[0032] The data analysis module of the guide system uses user behavior data and clustering algorithms to achieve accurate recommendations and high efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a structural diagram of the contactless intelligent tour guide system according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0035] like Figure 1 As shown, the embodiment of the present application provides a contactless intelligent tour guide system, including

[0036] Identification module, used to trigger the tour guide service through QR code scanning, RFID tag reading or Bluetooth beacon matching;

[0037] Content management module, storing multilingual guide content, supporting cloud synchronization and dynamic updates;

[0038] Voice explanation module, integrated with TTS technology module, supports voice command control and offline caching;

[0039] AR augmented reality module, based on SLAM algorithm module or ARCore / ARKit framework, overlays virtual content onto real scenes and supports gesture interaction;

[0040] User interaction module, supporting gesture operation, voice control and screen touch interaction;

[0041] The data analysis module collects user behavior data and optimizes the recommended navigation path through machine learning algorithms.

[0042] Specifically, the user operation process and system response process are as follows:

[0043] Step 1: User enters the navigation area

[0044] When users enter guided areas such as museums, exhibition halls, or tourist attractions, they open the guided tour application on their mobile phones or other smart devices. The system automatically detects the network status of the device, loads local cached content (such as voice explanations and AR resources), and connects to the cloud server to obtain the latest data.

[0045] Step 2: Device permission authorization

[0046] Users authorize applications to access hardware functions such as the camera (for QR code scanning), NFC (for RFID reading), Bluetooth (for beacon matching), and microphone (for voice control).

[0047] Step 3: Matching logo recognition with exhibits

[0048] QR code scanning: Users use their mobile phone camera to scan the QR code near the exhibit, and the system uses the ZXing or QR Code Reader library to resolve the exhibit ID;

[0049] RFID reading: The user places the mobile phone close to the RFID tag of the exhibit, and the system reads the tag information through the NFC function;

[0050] Bluetooth beacon matching: When a user approaches an exhibit, the system receives the Bluetooth beacon exhibit ID through the iBeacon protocol and combines the RSSI signal strength to determine the distance between the user and the exhibit (e.g., automatically triggering if within 1 meter).

[0051] Step 4: Activate the tour service

[0052] The system loads the corresponding guide content (text, voice, AR resources) from the content management module according to the exhibit ID and displays the guide interface on the user's device.

[0053] Step 5: Voice explanation and voice control

[0054] The system automatically plays the audio explanation of the current exhibit (supports multi-language switching), and users can control the playback through voice commands (such as "pause", "switch language", "repeat explanation").

[0055] The voice explanation module integrates the TTS technology module and supports offline caching to ensure smooth playback even when the network is poor.

[0056] Step 6: AR augmented reality experience

[0057] When the user clicks the "AR Mode" button, the system starts the AR augmented reality module and superimposes virtual content (such as 3D models and historical scene restoration) onto real exhibits based on the SLAM algorithm module or ARCore / ARKit framework.

[0058] Users can interact with AR models through gestures (such as pinching to zoom, sliding to rotate) or screen touch. The system records the interaction data and uploads it to the cloud for content optimization.

[0059] Step 7: Multi-language switching and dynamic updates

[0060] Users can manually switch language versions (such as Chinese, English, Japanese, etc.) on the navigation interface, and the system will dynamically load text, voice and AR resources in the corresponding language.

[0061] Step 8: Layered Interaction Mode Selection

[0062] Children's Mode: The system provides an icon-based interface and voice guidance, recommends AR interactive games and simplified explanations to attract children to participate.

[0063] Expert Mode: The system allows for detailed viewing of 3D models, in-depth reading of literature, and guidance of academic references to meet the needs of professional users.

[0064] Step 9: Personalized tour route recommendation

[0065] The data analysis module collects user behavior data (length of stay, number of AR interactions, path deviation rate) and divides user interest tags (such as "history enthusiast" and "technology enthusiast") through clustering algorithms.

[0066] Based on interest tags and collaborative filtering algorithms, the system generates personalized guide routes (such as the shortest route, in-depth explanation route, and interactive priority route) and displays recommended routes in real time in the interface.

[0067] Step 10: Crowd Flow Monitoring and Dynamic Path Planning

[0068] The system uses Bluetooth beacons or Wi-Fi probes to count the real-time flow of people in the exhibition area, generate a heat map and display it on the navigation interface.

[0069] Based on the crowd flow heat map and user interest tags, the system uses an ant colony algorithm to dynamically adjust the recommended routes, avoid congested areas and balance the load of the exhibition area.

[0070] Step 11: Upload user behavior data and optimize machine learning models

[0071] The system synchronizes user behavior logs (such as duration of stay, AR interaction data, and path deviation rate) to the cloud in real time.

[0072] The cloud server trains the machine learning model offline based on user behavior data to optimize the tour recommendation algorithm and AR content design.

[0073] Step 12: The user leaves the navigation area

[0074] When the user leaves the navigation area or closes the application, the system automatically saves the user behavior data and ends the navigation service.

[0075] An example of a museum scene tour is as follows:

[0076] Users use their mobile phones to scan the corresponding QR code in the exhibition hall, and the system plays the Chinese voice explanation and displays the AR restoration model. The user switches to the English explanation, and the system dynamically loads the English content. The user can zoom in and out of the 3D model of the exhibits through gestures. The system records the interaction data and uploads it to the cloud. The system recommends the next exhibit based on the user's stay time.

[0077] Examples of tourist attraction guides are as follows:

[0078] When the user approaches a scenic spot, the Bluetooth beacon automatically triggers the guided tour service, and the system plays a historical introduction to the scenic spot. The user clicks on "AR mode", and the system superimposes the virtual historical scene onto the real landscape. The system recommends in-depth tour routes based on the user's interests and provides real-time traffic flow prompts.

[0079] This system achieves contactless interaction through a sign recognition module, resolving the sanitation and safety issues associated with traditional guide systems. It also integrates content management, voice commentary, augmented reality, user interaction, and data analysis modules to create a multimodal experience, enhancing user engagement and information acquisition efficiency. It also implements dynamic updates and intelligent features, adapting to changing scenarios and providing personalized services. This guide system not only improves sanitation and safety, but also enhances the user experience and reduces operational costs. It can be widely used in museums, exhibition halls, tourist attractions, and other settings.

[0080] In one embodiment, the QR code scanning of the identification module of the contactless intelligent tour guide system sets the ZXing or QR Code Reader library to parse the exhibit ID. The RFID tag is a high-frequency passive tag that supports direct reading by the mobile phone NFC function. The Bluetooth beacon is based on the iBeacon protocol and determines the distance threshold between the user and the exhibit through the RSSI signal strength. The QR code is scanned to parse the exhibit ID through the ZXing or QR Code Reader library. The RFID tag can directly read the high-frequency passive tag information through the mobile phone NFC without the need for additional equipment. The Bluetooth beacon, based on the iBeacon protocol, determines the distance between the user and the exhibit through the RSSI signal strength, for example, automatically triggering within 1 meter. This setting supports contactless triggering of mainstream mobile devices (Android / IOS), improving compatibility and interaction efficiency.

[0081] In one embodiment, the multi-language switching of the content management module of the contactless intelligent tour guide system supports automatic matching of the user's device language or manual selection. This allows for automatic content matching based on the user's device voice or manual selection, enabling multi-language switching. This setting meets international requirements and eliminates the need for repeated scanning and recognition to switch languages.

[0082] In one embodiment, the voice explanation module of the contactless intelligent tour guide system supports semantic understanding of voice instructions, responds to natural language requests, and manages offline cache content through the LRU algorithm to retain high-frequency access data. Natural language processing (NLP) technology is used to parse user instructions (such as "switch to English"), and the LRU algorithm is used to prioritize the retention of high-frequency access content and automatically clean up low-frequency data. This setting supports natural language instructions, reduces user learning costs, and realizes intelligent interaction. This setting ensures smooth use even when the network is poor through offline caching, thereby improving network adaptability. The module can understand the instructions issued by the user through voice, process requests made in natural language, and run without a network, providing cached content for user access.

[0083] In one embodiment, the contactless intelligent tour guide system's augmented reality (AR) module uses a SLAM algorithm to achieve spatial alignment between virtual content and real-world exhibits. Cameras and sensors construct a real-time environmental map, enabling spatial alignment of virtual content and real-world exhibits. Spatial alignment error is less than 5cm, enhancing the realism of the AR experience. Users can manipulate the AR model through gestures such as pinching or swiping the screen, adapting to different user preferences.

[0084] In one embodiment, the contactless intelligent navigation system's virtual content must undergo spatial calibration verification before being overlaid to ensure that the positional error with the exhibit is less than a preset threshold. AR interaction data is then uploaded to the cloud for optimization of the virtual content design. Exhibit coordinates are pre-calibrated to ensure that the positional error of the virtual content overlay is less than a preset threshold (e.g., 5 cm) to avoid misleading virtual content caused by misalignment. User AR interaction data (e.g., motor and rotation) is uploaded to the cloud for improvement of the virtual content design, achieving sustainable optimization.

[0085] In one embodiment, the user interaction module of the contactless intelligent tour guide system features a layered interface, including a child mode and an expert mode. The child mode simplifies operation logic and recommends AR interactive games, while the expert mode enables detailed viewing of 3D models and in-depth reading of literature. This layered service meets the differentiated needs of different user groups and increases engagement among both children and experts.

[0086] In one embodiment, the user behavior data of the data analysis module of the contactless intelligent tour guide system includes the length of stay, the number of AR interactions, and the path deviation rate. A clustering algorithm is used to divide user interest tags to provide differentiated tour guide recommendations for different groups. K-means and other algorithms are used to divide user interest tags (such as "history enthusiasts" and "technology enthusiasts"). The path deviation rate refers to the degree to which the user deviates from the system-recommended path during the tour. The system makes optimized recommendations based on user behavior analysis. This data analysis module realizes personalized and intelligent tour guide recommendations, thereby improving user experience, optimizing resource allocation, improving tour guide efficiency, and enhancing interactivity and fun.

[0087] The embodiment of the present application further provides an interactive method for a contactless intelligent tour guide system, which uses the contactless intelligent tour guide system and includes the following steps:

[0088] S1: Triggering the guided tour service through the identification module. Users trigger the guided tour service by scanning the QR code of the exhibit, reading the RFID tag, or matching the Bluetooth beacon;

[0089] S2: Load the corresponding guide content from the cloud or local computer through the content management module. The guide content includes multilingual text, voice, AR resources, etc.

[0090] S3: Automatically play the voice explanation through the voice explanation module, and can control the playback through voice commands (such as "pause", "switch language", "repeat explanation");

[0091] S4: By starting the AR augmented reality module, virtual content is superimposed on the real scene based on the SLAM algorithm module or ARCore / ARKit framework. The user clicks the "AR mode" button, and the system superimposes the virtual content on the real scene;

[0092] S5: Supports gestures and screen touch interaction through the user interaction module, such as pinch-to-zoom, slide-to-rotate, etc.

[0093] S6: Collect user behavior data through the data analysis module and optimize the recommended navigation path.

[0094] The above-mentioned interactive method of the contactless intelligent guide system realizes contactless guidance, multimodal interactive experience, dynamic content management and intelligent recommendation. It can be widely used in museums, exhibition halls, tourist attractions, theme parks and other scenarios, helping the digital transformation of cultural venues and has significant social and commercial value.

[0095] In one embodiment, the interaction method of the contactless intelligent tour guide system also includes real-time crowd flow monitoring and dynamic path planning. The real-time crowd flow monitoring uses Bluetooth beacons or Wi-Fi probes to count the crowd density in the exhibition area. The dynamic path planning adjusts the recommended route based on the crowd density to avoid congestion and balance the load in the exhibition area. The real-time crowd flow in the exhibition area is counted by Bluetooth beacons or Wi-Fi probes, and a heat map is generated and displayed on the tour guide interface. Based on the crowd flow heat map and user interest tags, the system uses an ant colony algorithm to dynamically adjust the recommended route to avoid congested areas and balance the load in the exhibition area. This setting not only avoids congestion in the exhibition area, but also greatly improves the user's visiting experience.

[0096] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A contactless intelligent tour guide system, characterized in that: include Identification module, used to trigger the tour guide service through QR code scanning, RFID tag reading or Bluetooth beacon matching; Content management module, storing multilingual guide content, supporting cloud synchronization and dynamic updates; Voice explanation module, integrated with TTS technology module, supports voice command control and offline caching; AR augmented reality module, based on SLAM algorithm module or ARCore / ARKit framework, overlays virtual content onto real scenes and supports gesture interaction; User interaction module, supporting gesture operation, voice control and screen touch interaction; The data analysis module collects user behavior data and optimizes the recommended navigation path through machine learning algorithms.

2. The contactless intelligent tour guide system according to claim 1, characterized in that: The QR code scanning of the identification module sets the ZXing or QR Code Reader library to resolve the exhibit ID. The RFID tag is a high-frequency passive tag that supports direct reading by the NFC function of the mobile phone. The Bluetooth beacon is based on the iBeacon protocol and determines the distance threshold between the user and the exhibit through the RSSI signal strength.

3. The contactless intelligent tour guide system according to claim 1, characterized in that: The multi-language switching of the content management module supports automatic matching of the user device language or manual selection.

4. The contactless intelligent tour guide system according to claim 1, characterized in that: The voice explanation module supports semantic understanding of voice instructions, responds to natural language requests, and manages offline cache content through the LRU algorithm to retain frequently accessed data.

5. The contactless intelligent tour guide system according to claim 1, characterized in that: The AR augmented reality module realizes spatial alignment of virtual content and real exhibits based on the SLAM algorithm module.

6. The contactless intelligent tour guide system according to claim 5, characterized in that: Before the virtual content is superimposed, it must pass spatial calibration verification to ensure that the position error with the exhibit is less than a preset threshold. The AR interaction data is uploaded to the cloud for optimizing the virtual content design.

7. The contactless intelligent tour guide system according to claim 1, characterized in that: The user interaction module sets up a layered interactive interface, including a child mode and an expert mode. The child mode simplifies the operation logic and recommends AR interactive games. The expert mode opens up the functions of viewing 3D model details and in-depth reading of documents.

8. The contactless intelligent tour guide system according to claim 1, characterized in that: The user behavior data of the data analysis module includes the length of stay, the number of AR interactions and the path deviation rate. A clustering algorithm is used to divide user interest tags to provide differentiated guided tour recommendation paths for different groups.

9. An interactive method for a contactless intelligent tour guide system, using the contactless intelligent tour guide system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1: Triggering the navigation service through the identification module; S2: Load the corresponding guide content from the cloud or local through the content management module; S3: Automatically play the voice explanation through the voice explanation module, and the playback can be controlled by voice commands; S4: By starting the AR augmented reality module, virtual content is superimposed on the real scene based on the SLAM algorithm module or ARCore / ARKit framework; S5: Supports gesture operation and screen touch interaction through the user interaction module; S6: Collect user behavior data through the data analysis module and optimize the recommended navigation path.

10. The interactive method of the contactless intelligent tour guide system according to claim 9, characterized in that: It also includes real-time crowd flow monitoring and dynamic path planning. The real-time crowd flow monitoring uses Bluetooth beacons or Wi-Fi probes to count the crowd density in the exhibition area. The dynamic path planning adjusts the recommended route based on the crowd density to avoid congestion and balance the load in the exhibition area.

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