Hospital intelligent medical guidance system based on AI visual identification and man-machine conversation function

Abstract

The invention relates to a hospital intelligent medical guidance system, which integrates a plurality of advanced artificial intelligence technologies and modules, and aims to improve the intelligent level of hospital navigation, illness state communication and medical service. The core of the system comprises a human-carrying intelligent medical guide robot which has the functions of deformation, intelligent mechanical arm operation, multi-modal interaction, emergency response and the like, and precise positioning and intelligent path planning are achieved by integrating a multi-modal sensor and an edge calculation module. In addition, the system also covers an intelligent medical guidance robot partner. And the knowledge processing and reasoning module constructs a knowledge graph, so that the interpretability and federal learning ability of the system are improved. The data management and communication module ensures data security, synchronization and anomaly detection, and supports multi-channel communication at the same time. And the medical history and illness state communication module realizes remote reservation, voice recognition and medical history management. On the whole, through high integration and intelligent design, the hospital service efficiency and the patient experience are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of medical assistance equipment, and in particular to a hospital intelligent medical guidance robot and its companion system based on artificial intelligence (AI) visual recognition and human-computer dialogue functions. The system is intended to provide a full range of medical assistance services for patients with mobility difficulties such as the elderly, the weak, the sick and the disabled. Background Art

[0002] In the prior art, patients often face cumbersome formalities and complicated processes when visiting hospitals. This process is even more difficult for elderly patients or patients with limited mobility who are not accompanied by a companion. They need to move around and queue up frequently during registration, payment, examination, and medication collection, which not only takes time but also increases the physical burden. In addition, the internal environment of the hospital is complex and the departments are widely distributed. Patients often get lost or go to the wrong place because they are unfamiliar with the environment.

[0003] Although the existing medical guides in hospitals provide assistance to patients with limited mobility to a certain extent, the shortage of personnel and high costs cannot meet the high-frequency needs of patients in terms of navigation, procedure handling, information exchange, etc. during the medical treatment process. Therefore, there is an urgent need for an intelligent medical assistance system to help patients efficiently complete the entire medical treatment process, improve medical treatment efficiency and reduce the burden on patients. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent hospital medical guidance system based on AI visual recognition and human-computer dialogue functions. The system has functions such as intelligent navigation, automatic obstacle avoidance, natural language communication, and procedure assistance, so as to help patients easily complete all aspects of hospital visits.

[0005] To achieve the above object, the present invention provides the following technical solutions: An intelligent hospital medical guidance system based on AI visual recognition and human-computer dialogue functions, including: Patient-Carrying Intelligent Medical GuidanceRbt: The robot has a transformation function and can switch between independent walking mode and a ride-on smart medical guide vehicle mode to carry patients and achieve automatic navigation walking. It is equipped with AI-based smart robotic arms and grippers to achieve multifunctional medical guidance functions such as supporting patients or providing patients with a ride to the hospital.

[0006] At the same time, the system includes but is not limited to the following functions and modules: AI Knwledge Feed Mdule: The knowledge base data such as hospital environment data, medical treatment process, patient precautions, etc. are provided to the AI ​​system in real time through knowledge graph, semantic network and natural language processing technology, so that it can provide personalized guidance and feedback according to the needs of different patients.

[0007] Key features include: Integration of environmental information and process data: Information on hospital departments, diagnosis and treatment processes, equipment locations, doctor arrangements, etc. is incorporated into the knowledge base to support dynamic updates. AI can access in real time and provide customized guidance based on the patient's location and specific needs.

[0008] Patient-related precautions: including the patient's health status, special needs, contraindications, etc., so that AI can provide targeted guidance during interaction, such as reminding patients to bring examination documents or pay attention to specific precautions.

[0009] Frequently Asked Questions (FAQ) Database: Integrates frequently asked questions such as "How do I make an appointment?" and "How do I pay?" AI can provide patients with instant answers through natural language understanding, avoiding repeated information entry.

[0010] Knowledge graph and semantic reasoning: By building and maintaining a knowledge graph covering entities such as doctors, departments, equipment, processes and their relationships, AI can infer the best medical process based on actual conditions and guide patients in real time.

[0011] Multimodal feedback and interaction: AI can interact with patients through multimodal forms such as voice, touch, and images, provide real-time feedback on hospital processes and department information, and improve user experience.

[0012] Self-learning and optimization: The AI ​​system can continuously optimize the knowledge base by analyzing patients’ questions and behavioral data, gradually adapt to the needs of different patients, and improve service accuracy.

[0013] AI Knowledge Reasoning and Feedback Module: Responsible for parsing the knowledge base content provided by the AI ​​"feeding" module and providing personalized feedback to patients in the form of voice or text. Through user interaction data, AI can automatically infer the patient's current needs and adjust suggestions and guidance in real time.

[0014] Key features include: Intelligent reasoning: Using natural language processing technology, AI can automatically retrieve the most relevant knowledge content based on patient needs and generate precise answers or guidance.

[0015] Personalized feedback: Based on the patient's historical data, health information, and current environment, AI can give personalized suggestions (such as reminding whether the registration for the day has been completed and whether special examinations are needed).

[0016] Multi-language support: Supports multi-language voice and text feedback to meet the needs of patients in different languages.

[0017] Contextual awareness: Combines environmental sensors with patient status to understand the current context and dynamically adjust prompts (such as reminding waiting time when queuing or providing information about nearby rest areas).

[0018] Multimodal Sensor Integration Unit: Integrated cameras, microphones, speakers, touch sensors and environmental perception sensors to capture multi-source data and enhance system perception capabilities.

[0019] Edge Computing Module: Process sensor data locally in real time to reduce data transmission latency and improve response speed.

[0020] Intelligent Path Engine: It includes AI-based intelligent path designer and automatic obstacle avoidance components to enable autonomous navigation, obstacle detection and avoidance of medical guidance robots.

[0021] Precise positioning module: AI-based floor and department positioning technology ensures that the medical guidance robot arrives at the designated location accurately.

[0022] Voice and touch interaction module (Vice and Touch Interaction Mdule): It supports speech recognition, semantic understanding, speech synthesis and touch feedback to achieve multi-channel interactive communication with users.

[0023] Energy Management Module: Machine learning algorithms are used to optimize the charging and energy consumption strategies of the medical guidance robot to ensure continuous and stable operation of the system.

[0024] Emergency Response Module: When an emergency is detected, medical personnel are automatically contacted and emergency procedures are initiated.

[0025] QR code scanning and payment function (QR Cde Scanning and Payment Functin): Support scanning QR code to complete payment transactions.

[0026] Intelligent Guidance System: Enter hospital-related data in advance and provide patients with guidance on the medical process.

[0027] Mobility Platform Module (Mbility Platfrm Mdule): Control the movement and interaction of the intelligent medical guidance robot to improve the dynamics and fun of the interaction.

[0028] Intelligent medical guidance robot companion: The companion is mechanically independent of the portable intelligent medical guidance robot, but retains all intelligent functions and does not have the function of riding. It can include intelligent walking robots, intelligent medical guidance carts, intelligent medical guidance drones, etc. The companion is equipped with the following AI functions: Language Semantic Cmprehension Engine Dialogue Management Module Joint Operation Component (Jint peratin Cmpnent) to achieve coordinated actions between the medical guidance robot and its partner Remote Monitoring Engine, which enables caregivers to remotely monitor and assist patients via a secure encrypted connection Privacy Protection Module (Privacy Protection Module) uses data anonymization and encryption technology to ensure user data privacy and security The portable intelligent medical guide robot is provided with a mobile phone card slot for inserting, fixing and electrically connecting the medical guide smartphone. The medical guide smartphone has all the AI ​​functions of the robot (including APP), can be removed from the card slot for the patient to carry with him, and acts as a portable medical guide.

[0029] The intelligent medical guide robot companion is also provided with a mobile phone card slot for inserting an electrically connected medical guide smartphone. The smartphone also has AI functions and can be unplugged and carried around to assist patients in completing medical assistance.

[0030] Intelligent medical guidance robots also include: Environmental Perceptin Sensrs: Temperature, humidity, light and other sensors that monitor the physical parameters of the patient's environment in real time.

[0031] Power Management Module (Pwer Management Mdule): manages the power supply of each part of the system to ensure stable operation of the system.

[0032] Unconventional Behavior Monitor (Uncnventinal Behavir Mnitr): Uses support vector machines (SVM) and advanced cognitive networks (Advanced Cgnitive Netwrk) to identify potentially dangerous behaviors or abnormal activities and send alerts in multiple formats through the data communication core (Data Cmmunicatin Cre).

[0033] Knowledge Graph and Semantic Network Module: Build and maintain a knowledge graph containing various medical entities and their relationships, and support semantic understanding and reasoning.

[0034] Explainability and Transparency Module: Improves the explainability of AI model decision-making process and enhances user trust.

[0035] Federated Learning Module: Optimize AI models with distributed learning while maintaining data privacy.

[0036] Information storage components include: Data Encryption Module: Ensures secure storage and transmission of sensitive data.

[0037] Data Synchronization Module: Maintains the consistency of local and cloud data in real time.

[0038] Data Backup Module: Regularly back up important data to prevent data loss.

[0039] Data Coordination Component: Ensures synchronization between local and cloud data.

[0040] Data Communications Core (Data Cmmunicatin Cre), including: Real-time voice and text notification function: send voice and text notifications to preset recipients.

[0041] Emergency Alarm Function: Send an alarm signal and notify relevant personnel in an emergency.

[0042] Multi-Channel Communication Interface: supports multiple methods of data transmission such as Wi-Fi, Bluetooth, and 5G.

[0043] The intelligent medical guidance robot and its companion are equipped with: Multimodal Learning Module: Integrate and process multimodal data such as images, text, audio, and touch to improve understanding and generation capabilities.

[0044] Anomaly Detection and Risk Management Module: Detects system anomalies (such as sensor failures, data anomalies) in real time and takes corresponding risk management measures.

[0045] Knowledge graph and semantic network module: build and maintain knowledge graphs containing entities and relationships, and support semantic reasoning.

[0046] Explainability and transparency module: Enhance the transparency of AI decision-making process.

[0047] Federated learning module: Optimize AI models through distributed learning under the premise of data privacy.

[0048] Intelligent medical guidance robots include: Medical robot intelligent mechanical arm (Rbtic Arm): equipped with a gripper, used for grabbing test orders, delivering medical records, etc. Equipment: Robot control module (Rbtic Cntrl Mdule): uses AI algorithm to achieve precise operation and task execution of the robotic arm.

[0049] Object Recognition Module: Uses AI to identify and locate interactive objects.

[0050] Haptic Feedback Module: Provides tactile feedback during robot arm operation to improve accuracy and safety.

[0051] The system can also communicate with the user about medical history and current medical condition information, including monetary interaction (such as receiving registration fees and medical treatment fees). The configurations are: Language Semantic Cmprehension Engine Dialogue Management Module Speech Recognition Module Speech Synthesis Module Payment Processing Module: supports multiple payment methods and ensures transaction security Medical Record Management Module: Integrates with the hospital's electronic medical record system to ensure accurate acquisition and updating of medical history information The system further comprises: Remote Reservation Function: Allows users to remotely book the intelligent medical guidance robot through the mobile APP before seeing a doctor and complete relevant procedures in advance, equipped with: User Authentication Module: Uses AI to authenticate users during remote booking and check-in (including fingerprint and facial recognition).

[0052] Appointment Scheduling Module: Integrate with hospital information system to manage reservation and queuing information and support dynamic adjustment and optimization.

[0053] Full-Prcess Scene Text Recording Function: Converts audio and video interactions into text records through AI, supporting automatic summarization and keyword extraction.

[0054] Real-time Translation Module: Uses AI to translate interactive content into different languages ​​to meet the needs of multilingual users.

[0055] Notification and Reminder Module: Send appointment confirmation, medical appointment reminder and other notifications through the APP.

[0056] Natural Language Processing and Multimodal Learning Features: Convolutional Neural Networks (CNNs) and Transformer Models: Real-time analysis of video streams for multimodal image analysis (such as facial authentication, action command parsing, emotion monitoring, and environmental perception).

[0057] Automatic speech recognition (ASR) and text-to-speech synthesis (TTS): realize two-way interaction between speech input and output.

[0058] Jint Representatin Learning: Maps visual, speech, and text data to a shared representation space through deep learning models, supporting cross-modal reasoning and response generation.

[0059] Sentiment and context analysis module (Emtin and Cntext Analysis Mdule): optimize system response and improve user experience through sentiment recognition and context analysis.

[0060] Real-time Interaction and Feedback Capability: Provides low-latency response and multi-tasking capabilities to achieve efficient collaboration of image recognition, voice commands, and natural language conversations.

[0061] Data Security and Privacy Protection: Encryption and anonymization technology and federated learning modules are used to ensure user data security and privacy.

[0062] Knowledge Graph and Semantic Reasoning: Build and maintain knowledge graphs to support semantic understanding and reasoning.

[0063] Explainability and Transparency Module: Improves the explainability of AI models, helping users understand the system decision-making process and enhance trust. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a tree-like mind map of the hospital's intelligent medical guidance system based on AI visual recognition and human-computer dialogue functions.

[0065] The following is a detailed interpretation of the functions and coordination relationships of the relevant AI modules in the mind map: Camera unit and CNN deep learning algorithm: Function: The camera captures the video stream in real time, and the CNN algorithm performs advanced image processing on the video stream (such as face verification, action command analysis, and emotion monitoring).

[0066] Coordination: The camera provides raw data, which is processed by CNN to provide data support for facial authentication, motion command parsing, and emotion monitoring components.

[0067] AI Processing Unit: Function: Contains language semantic understanding engine, dialogue management module, and intelligent response generator, which are used to process user voice and text input and generate responses.

[0068] Coordination: The language semantic understanding engine parses the input, the dialogue management module manages multiple rounds of dialogue and context tracking, and the intelligent response generator outputs appropriate answers.

[0069] Information storage components, data encryption, and data coordination components: Function: The information storage component stores and processes data, analysis results, and interaction records. The data encryption module ensures data security, and the data coordination component ensures that local and cloud data are consistent.

[0070] Coordination: The information storage component provides data access services for other modules, the data encryption module ensures security, and the data coordination component ensures synchronization and seamless access.

[0071] Intelligent path engine and precise positioning module: Function: The intelligent path engine (including path designer and automatic obstacle avoidance components) realizes autonomous navigation and obstacle avoidance, and the precise positioning module realizes precise positioning of floors and departments in the hospital.

[0072] Coordination: The path designer plans the best route, the obstacle avoidance component adjusts the travel path in real time, and precise positioning provides accurate location information to ensure that the robot arrives at the designated location.

[0073] Human-computer interaction module: Function: Supports semantic processing, speech recognition, speech synthesis, and voice or text interaction with users.

[0074] Coordination: Works closely with the AI ​​processing unit to convert user input into a processable format and provide system responses as voice or text feedback.

[0075] Adaptive learning components: Function: Continuously optimize system performance through behavior pattern analyzer and future trend analyzer.

[0076] Coordination: The behavior pattern analyzer analyzes user and environmental data to provide reference for the future trend analyzer, predict potential problems and provide optimization solutions.

[0077] Abnormal behavior monitor and data communication core: Function: The irregular behavior monitor uses SVM and advanced cognitive networks to detect potential dangers or anomalies and sends alerts through the data communication core.

[0078] Coordination: The monitor monitors the behavior in real time and immediately sends an alarm through the data communication core if an abnormality is found.

[0079] Medical robot intelligent robotic arm, robotic arm management component, entity sensor: Function: The intelligent robotic arm is responsible for grasping and delivering tasks, the robotic arm management component realizes precise operation, and the entity sensor recognizes the position and shape of the interactive object.

[0080] Coordination: The robot management component controls the robot's movements, and the entity sensor provides object information to ensure the robot's precise operation.

[0081] Medical guide robot companion and joint operation components, remote monitoring engine, remote booking function: Function: The medical guidance robot companion is independent of the main robot and has the same intelligent functions (without riding), including dialogue understanding, joint operation, remote monitoring, and remote booking.

[0082] Coordination: The companion works in coordination with the main robot through the joint operation component, the remote monitoring engine allows caregivers to supervise and assist in real time, and the remote booking function allows users to complete the relevant procedures before the visit. DETAILED DESCRIPTION

[0083] System overall architecture: The hardware includes electric medical guidance robots, cameras, sensors, and robotic arms; the software includes AI modules, navigation systems, and human-computer interaction systems. Real-time data transmission and processing are achieved through wireless networks and cloud services.

[0084] Patient appointment process: Make an appointment for the smart medical guidance service through the APP, official website or phone. After the user registers and verifies, fill in the arrival time and symptom information, and the system notifies and reminds the patient to arrange the medical appointment.

[0085] Intelligent medical guidance robot receives patients: After the patient arrives at the hospital, the system uses facial recognition components to verify his or her identity, and the robot uses precise positioning and intelligent routing to go to the designated location to pick up the patient.

[0086] Guide patients through the consultation process: The semantic understanding engine is used to understand the patient's symptoms, and the knowledge graph is used to determine the department to be treated.

[0087] Registration and payment can be completed through QR code scanning and payment function.

[0088] The robot's intelligent mechanical arm helps deliver or collect documents.

[0089] Intelligent route planner and obstacle avoidance components ensure smooth navigation along the way.

[0090] During the process of medical consultation, examination and medication collection, the medical guidance robot companion can work together to save patients time and energy.

[0091] If the patient does not need to ride, they can choose a smart medical guidance car, smart medical guidance drone, or take a medical guidance smartphone from the robot for assistance. These devices are equipped with visual recognition and intelligent voice interaction, and can assist patients in completing medical treatment steps at any time.

[0092] Medical guide robot companion functions: It can act independently and provide intelligent services, and the joint operation components ensure that it works in coordination with the main robot.

[0093] The remote monitoring engine allows caregivers to remotely view and assist patients.

[0094] The remote booking function supports patients to check in in advance.

[0095] Coordinated operation of software and hardware: Sensors and cameras acquire data, and the AI ​​module analyzes and processes it.

[0096] Navigation and positioning ensure that the robot reaches its destination accurately.

[0097] The human-computer interaction module realizes voice dialogue and text communication.

[0098] The energy management module optimizes the charging strategy.

[0099] The irregular behavior monitor sends an alarm in an emergency through the data communication core.

[0100] System expansion functions: Multimodal learning integrates data from multiple sources.

[0101] The anomaly detection and risk management module responds to system anomalies.

[0102] Knowledge graphs and semantic networks support deeper semantic understanding and decision-making.

[0103] The explainability and transparency module improves the credibility of the system.

[0104] Practicality The present invention greatly simplifies the patient consultation process, improves efficiency and satisfaction, and reduces the cost of medical guidance. The system's automation and intelligent features help hospitals optimize resources and have broad application prospects.

[0105] For patients who do not need the riding function, they can directly book a medical guidance robot companion to serve as a companion or medical guide.

[0106] in conclusion The present invention provides a hospital intelligent medical guide robot and companion system that integrates multiple AI functions, innovatively applies artificial intelligence technology to the field of medical auxiliary equipment, and effectively solves the problem of cumbersome patient visits and lack of intelligent assistance in the prior art. The system has reasonable design, complete functions, good practicality and market prospects.

Claims

1. A hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function, characterized in that: include: Patient-Carrying Intelligent Medical Guidance Rbt, which has a deformation function and can switch between an independent walking mode and a rideable intelligent medical guidance vehicle mode to carry patients and realize automatic navigation walking; the intelligent medical guidance robot is equipped with an AI-based intelligent mechanical arm, including a gripper, to realize a multifunctional medical guidance function of supporting patients or providing patients with a ride for medical treatment, and further includes: AI "feeding" function module (AI Knwledge Feed Mdule): This module is responsible for "feeding" hospital environment data, medical procedures, patient precautions and other knowledge base data to the AI ​​system in real time through knowledge graphs, semantic networks and natural language processing technologies, so that it can provide personalized guidance and feedback based on different patient needs. This module can continuously update and optimize the knowledge base to ensure that AI can handle changes in the hospital environment, process adjustments and new patient needs; AI Knowledge Reasoning and Feedback Module: This module is responsible for parsing the knowledge base content provided by the AI ​​"feeding" module and providing personalized feedback to patients through voice or text. Combined with the user's interactive data, AI can automatically reason, judge the patient's current needs, and adjust suggestions and guidance in real time; Multimodal Sensor Integrated Unit, which integrates a camera, microphone, speaker, touch sensor, and environmental perception sensor to capture multi-source data to enhance the system's perception capabilities; Edge computing module, which is used to process sensor data locally in real time, reduce data transmission delay and improve response speed; Intelligent Path Engine, including AI-based intelligent path designer and automatic obstacle avoidance components, for autonomous navigation and obstacle detection and avoidance of the medical guidance robot; Precise Positioning Module: AI-based floor and department positioning technology ensures that the medical guidance robot can accurately reach the designated location; The Voice and Touch Interaction Module (Vice and Touch Interaction Module) supports semantic interaction processing, speech recognition, speech synthesis and touch feedback, and is used for multi-channel interactive communication with users; Energy Management Module: uses machine learning algorithms to optimize the charging and energy consumption strategies of the medical guidance robot to ensure the continuous and stable operation of the system; The Emergency Response Module, which automatically contacts medical personnel and initiates emergency procedures when an emergency is detected; QR code scanning and payment function (QR Cde Scanning and Payment Functin), enabling the intelligent medical guidance robot to handle payment transactions; Intelligent Guidance System, which inputs relevant hospital data in advance and provides guidance on the medical process; Mobile platform module (Mbility Platform Mdule), used to control the movement and interaction of the intelligent medical guidance robot, and improve the dynamics and fun of the interaction; The intelligent medical guidance robot companion is mechanically independent of the portable intelligent medical guidance robot, retaining all its intelligent functions but without the riding function, including but not limited to intelligent walking robots, intelligent medical guidance carts, and intelligent medical guidance drones; the companion is equipped with the following AI functions: Language Semantic Cmprehension Engine; Dialogue Management Module (Dialgue Management Mdule); Joint Operation Component (Jint peratin Cmpnent), which enables coordinated actions between the medical guidance robot and its partner; Remote Monitoring Engine, which enables caregivers to remotely monitor and assist patients over a secure encrypted connection; The privacy protection module (Privacy Prtectin Mdule) uses data anonymization and encryption technology to ensure the privacy and security of user data.

2. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The portable intelligent medical guide robot is provided with a mobile phone card slot, which is used to insert a fixed and electrically connected medical guide smartphone. The medical guide smartphone has all the AI ​​functions of the portable intelligent medical guide robot, including APP; the medical guide smartphone can be unplugged from the mobile phone card slot of the portable intelligent medical guide robot for the patient to carry with him as a portable medical guide.

3. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The intelligent medical guide robot companion is provided with a mobile phone card slot, which is used to insert a fixed and electrically connected medical guide smartphone. The medical guide smartphone has all the AI ​​functions of the portable intelligent medical guide robot, including APP; the medical guide smartphone can be unplugged from the mobile phone card slot of the intelligent medical guide robot companion for the patient to carry with him as a portable medical guide.

4. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The intelligent medical guidance robot further comprises: Environmental Perceptin Sensrs, including temperature and humidity sensors, light sensors, etc., are used to monitor the physical parameters of the patient's environment in real time; Power Management Module (Pwer Management Mdule), used to manage the power supply of various parts of the system to ensure the continuous and stable operation of the system; Unconventional Behavior Monitor (Uncnventinal Behavir Mnitr), which uses Support Vector Machine (SVM) and Advanced Cgnitive Network (Advanced Cgnitive Netwrk) to identify potentially dangerous behaviors or abnormal activities and send alerts in multiple formats through the Data Cmmunicatin Cre; Knowledge Graph and Semantic Network Module: builds and maintains knowledge graphs containing entities and their relationships, supporting semantic understanding and reasoning; Explainability and Transparency Module: Improves the explainability of AI models, helps understand the decision-making process of the system, and enhances user trust; The Federated Learning Module supports optimizing AI models through distributed learning while ensuring data privacy.

5. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The information storage component comprises: Data Encryption Module, used to ensure the secure storage and transmission of sensitive data; Data synchronization module (Data Synchrnizatin Mdule), used to maintain the consistency of local and cloud data in real time; Data Backup Mdule: regularly back up important data to prevent data loss; Data Coordination Component (Data Crdinatin Cmpnent) achieves consistency between local and cloud data.

6. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1, characterized in that: The data communication core (Data Cmmunicatin Cre) includes: Real-time voice and text notification function, used to send voice and text notifications to preset recipients; Emergency alarm function, used to send out alarm signals and notify relevant personnel in emergency situations; Multi-Channel Communication Interface (MCI) supports data transmission through multiple communication methods such as Wi-Fi, Bluetooth, and 5G.

7. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The intelligent medical guidance robot and the medical guidance robot companion are configured with: Multimodal Learning Module: It integrates and processes data from different modalities (such as images, text, audio, and touch) to improve the system's understanding and generation capabilities. Anomaly Detection and Risk Management Module: detects abnormal situations in the system in real time, such as sensor failures, data anomalies, etc., and takes corresponding risk management measures; Knowledge Graph and Semantic Network Module: builds and maintains knowledge graphs containing entities and their relationships, supporting semantic understanding and reasoning; Explainability and Transparency Module: Improves the explainability of AI models, helps understand the decision-making process of the system, and enhances user trust; The Federated Learning Module supports optimizing AI models through distributed learning while ensuring data privacy.

8. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The intelligent medical guidance robot comprises: Wheelchair Intelligent Robotic Arm is equipped with a gripper to perform tasks such as grabbing test orders and delivering medical records. It is equipped with: The robot control module (Rbtic Cntrl Mdule) uses AI algorithms to achieve precise operation and task execution of the robot arm; Object Recognition Module (Object Recgnitin Mdule), using AI to identify and locate interactive objects; The haptic feedback module (Haptic Feedback Mdule) provides tactile feedback during the operation of the robotic arm to improve the accuracy and safety of the operation.

9. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The system can communicate with the user about the medical history and the condition of the current visit, including monetary exchange, such as receiving registration fees and medical fees, and is configured with: Language Semantic Cmprehension Engine, which interprets user input and generates appropriate responses; Dialogue Management Module, used to manage multi-round dialogues and context tracking; Speech Recgnitin Mdule, used to convert user's voice input into text; Speech Synthesis Module, which is used to convert the system's text response into speech output; Payment Processing Module: It integrates multiple payment methods (such as mobile payment and credit card payment) and ensures transaction security. The Medical Record Management Module is integrated with the hospital's electronic medical record system to ensure accurate acquisition and updating of medical history information.

10. The hospital intelligent medical guidance system based on AI visual recognition and human-computer dialogue function according to claim 1 is characterized in that: The system further comprises: The remote reservation function (Remte Reservatin Functin) allows users to remotely book the intelligent medical guidance robot through the mobile APP before the consultation and handle all the procedures before the consultation. The configuration includes: User Authentication Module (User Authentication Module), which uses AI to verify user identity during remote booking and check-in, including biometric technology (such as fingerprint and facial recognition); Appointment Scheduling Module (Appintment Scheduling Mdule), which is integrated with the hospital information system to manage reservation and queuing information and support dynamic adjustment and optimization; Full-process scene text recording function (Full-process Scene Text Recording Function), which uses AI modules to convert audio and video interactions into text records, and supports automatic summarization and keyword extraction; Real-time translation module (Real-time Translatin Mdule), which uses AI to translate interactive content into different languages ​​to support the needs of multilingual user groups; Notification and Reminder Module: sends appointment confirmation, medical appointment reminder and other notifications to users through the APP; Natural Language Processing and Multimodal Learning Features, including: Convolutional neural networks (CNNs) and Transformer models for capturing and analyzing video streams in real time, performing multimodal image analysis such as facial authentication, action command parsing, emotion monitoring, and environmental perception; Automatic speech recognition (ASR) and text-to-speech synthesis (TTS) enable two-way interaction between speech input and output; Jint Representatin Learning, which uses deep learning models to map visual, speech, and text data into a shared representation space, supporting cross-modal reasoning and response generation; Sentiment and context analysis module (Emtin and Cntext Analysis Mdule), which optimizes system response and improves user interaction experience through sentiment recognition and context analysis; Real-time interaction and feedback capability, providing low-latency response and multi-tasking capabilities, supporting efficient collaboration of image recognition, voice commands and natural language conversations; Data Security and Privacy Protection (Data Security and Privacy Prtectin), using data encryption, anonymization technology and federated learning modules to ensure the security and privacy of user data; Knowledge Graph and Semantic Reasoning: Supporting the semantic understanding and reasoning functions of the system by building and maintaining knowledge graphs; The Explainability and Transparency Module improves the explainability of AI models, helps users understand the system decision-making process, and enhances trust.

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