Barrier-free AI intelligent guiding method and system

Abstract

The invention provides a barrier-free AI intelligent guiding method. The barrier-free AI intelligent guiding method comprises the following steps: establishing a medical database on an AI intelligent cloud platform; the patient evokes the mobile phone APP through voice and records disease information and a doctor-seeing plan through the mobile phone APP, and the doctor-seeing plan reflects target doctor-seeing time and a doctor-seeing time period of the patient; the AI intelligent cloud platform receives the disease information, obtains an analysis result through an analysis strategy according to the received disease information, judges the disease condition according to the analysis result, generates initial diagnosis information, obtains a scheduling table through a matching strategy according to the initial diagnosis information, and sends the treatment information to the mobile phone APP and the AI hospital guide robot; according to the treatment information, the AI hospital guide robot corresponding to the strategy is matched, and the AI hospital guide robot timely arrives at a reception point for waiting according to the patient information; and after the patient arrives at the hospital, the AI hospital guide robot identifies the identity of the patient, acquires the treatment information of the patient, and realizes hospital treatment navigation.

Description

Technical Field

[0001] The present invention relates to the technical field of guidance systems, and more specifically to a barrier-free AI intelligent guidance method and system. Background Art

[0002] At present, when visually impaired people visit hospitals for treatment, the hospital's registration equipment and consultation devices are fixed. In some links, staff are still needed to assist patients in completing inquiries, registration, and borrowing and returning fees, etc. During the service process, service quality decline or human errors are inevitable. Moreover, for visually impaired patients, they cannot use current equipment and can only rely on staff, which requires a lot of manpower. Moreover, the current medical treatment process cannot achieve full end-to-end coverage of the entire link, and the patient experience is poor. Summary of the invention

[0003] In view of the deficiencies in the prior art, the object of the present invention is to provide an accessible AI intelligent guidance system to overcome the above-mentioned defects in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions: A barrier-free AI intelligent guidance method, comprising: S1: Establish a medical database on the AI ​​intelligent cloud platform, which includes all hospital departments, doctor information, scheduling information, etc., and establish a patient database, which records patient identity information and medical information. The AI ​​intelligent cloud platform can accept and store AI medical guidance robot order information, which includes reservation information and usage information; S2: The patient activates the mobile phone APP with voice and enters the symptom information and the consultation plan through the mobile phone APP. The consultation plan reflects the patient's target consultation time and available consultation time period; S3: The AI ​​intelligent cloud platform receives the disease information, obtains the analysis result through the analysis strategy according to the received disease information, judges the disease condition according to the analysis result and generates the initial diagnosis information, wherein the disease condition includes the patient's disease type, the urgency of the disease, etc. S4: The initial diagnosis information is matched with a schedule table, which reflects the schedule information of the doctors in the corresponding department. The initial diagnosis information is readjusted through a self-adjustment strategy according to the patient's treatment plan, historical doctors and the schedule table to obtain the treatment information, which includes the initial diagnosis result and the appointment registration result, and the treatment information is sent to the mobile phone APP and the AI ​​guidance robot; S5: The AI ​​medical guide robot corresponding to the matching strategy is selected according to the medical information, and the AI ​​medical guide robot arrives at the reception point in time to wait according to the patient information; S6: After the patient arrives at the hospital, the AI ​​guidance robot identifies the patient, obtains the patient's medical information, and realizes the navigation within the hospital.

[0005] Preferably, the self-regulation strategy comprises a replacement step, The replacement step determines the urgency of the patient's condition based on the symptom information, and combines the assigned urgency of the patient's condition, the scheduling information of the historical doctors, the order information of the AI ​​guidance robot, and the patient's treatment plan to adjust the patient's initial diagnosis information to obtain a treatment recommendation. The patient selects the treatment information based on the treatment recommendation. Among the treatment information, for patients with lower urgency of the patient's condition, historical doctors are given priority in matching within the treatment plan.

[0006] Preferably, the self-adjustment strategy also includes a dynamic analysis step. When the patient's condition is of high urgency and all AI guidance robots are in working condition, the dynamic analysis step obtains the AI ​​guidance robot's corresponding patient's medical treatment process information within the corresponding time period, generates an AI guidance schedule based on the medical treatment process information and the corresponding process duration, adjusts the working hours of the AI ​​guidance robot and the corresponding patient's medical treatment time, and ensures that the current patient's medical treatment process is matched with the corresponding AI guidance robot.

[0007] Preferably, S6 includes an intra-hospital navigation step, which includes establishing an intra-hospital map in advance, including the hospital departments and guide labels, and the guide labels can obtain patient medical information, and guide the patient to a designated medical point based on the patient medical information.

[0008] Preferably, the intra-hospital navigation step further includes an obstacle avoidance sub-step, and the obstacle avoidance sub-step includes: Use the camera and lidar on the AI ​​medical guidance robot to obtain images and point clouds of the obstacle map and obtain obstacle images; Preprocess the obstacle map image, obtain the outline edge line of the obstacle, and compare the obstacle type and obstacle coordinates through the obstacle database; The obstacle coordinates and contour edge lines are transmitted to the in-hospital map, and navigation is re-performed according to the corrected in-hospital map to correct the navigation route; Issue an obstacle avoidance action command to complete obstacle avoidance.

[0009] Preferably, a mobile obstacle avoidance strategy is provided in the obstacle avoidance sub-step, and the mobile obstacle avoidance strategy is used to obtain multiple frames of obstacle images taken continuously within a predetermined time, obtain pixel movement in the multiple frames of obstacle images to identify the position points of the mobile obstacles, determine the moving trajectory of the mobile obstacles according to the position points, and adjust the navigation route according to the moving trajectory.

[0010] Preferably, the AI ​​intelligent cloud platform is also connected to a taxi-hailing system, which utilizes the AI ​​intelligent cloud platform to obtain taxi-hailing demands from mobile phone APP and AI medical guidance robot, generates taxi-hailing orders and sends them to the taxi-hailing system, and feeds back the taxi-hailing information to the mobile phone APP and AI medical guidance robot.

[0011] Preferably, the analysis strategy includes obtaining the patient's symptom information, extracting keywords from the symptom information, matching them in the hospital cloud platform database, obtaining symptom types, and storing the patient's historical diagnosis and treatment data in the hospital cloud platform, sorting the historical diagnosis and treatment data and symptom types according to matching results and severity, obtaining a patient health table, obtaining initial diagnosis results based on the patient health table, and making an appointment based on the initial diagnosis results.

[0012] Preferably, the S6 also includes a medical consultation navigation method, and the medical consultation navigation method includes S61: guiding the patient to see a doctor and synchronizing the medical information in real time; S62: Complete the fee settlement according to the doctor's prescription and with the patient's authorization; S63: Guide the patient to complete tests, X-rays and other examinations, and remind the patient to rest and wait for the test results; S64: Inform the patient that the report has been sent for a follow-up visit and synchronize the doctor's diagnosis results; S65: Guide the patient to get the medication and send the patient to the pick-up point.

[0013] An accessible AI intelligent guidance system, comprising Mobile phone APP is used to interact directly with patients, receive disease information input, user instructions, and provide information feedback; The AI ​​guidance robot interacts directly with patients to complete the entire chain of services including identity recognition, hospital navigation, medical care, fee settlement, laboratory tests, and medication collection, and has the ability to interact with voice and voiceprint throughout the process. The AI ​​intelligent cloud platform, as the system's computing and control center, is responsible for command computing, data statistics, and strategy algorithm operation. It is interconnected with the hospital cloud platform, mobile APP, and AI guidance robot to achieve initial symptom screening, accurate registration, and real-time information sharing; The mobile phone APP, AI smart cloud platform and AI medical guidance robot work together.

[0014] The beneficial effects of the present invention are as follows: the AI ​​medical guidance robot is used to realize full-link intelligent medical guidance control, which saves a lot of manpower while improving correction efficiency and greatly enhancing the patient experience; the full-link interconnection of mobile phone APP-AI intelligent cloud platform-hospital cloud platform-AI medical guidance robot is realized, and information is shared in real time to provide patients with more comprehensive services. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of the present invention; Figure 2 It is a module diagram of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] It should be noted that when a component is referred to as being "fixed to" another component, it may be directly on the other component or there may also be a component centered. When a component is considered to be "connected to" another component, it may be directly connected to the other component or there may also be a component centered. When a component is considered to be "set on" another component, it may be directly set on the other component or there may also be a component centered. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0019] The embodiments of the present invention are further described in detail below with reference to the accompanying drawings: A barrier-free AI intelligent guidance method, comprising: S1: Establish a medical database on the AI ​​intelligent cloud platform, which includes all hospital departments, doctor information, scheduling information, etc., and establish a patient database, which records patient identity information and medical information. The AI ​​intelligent cloud platform can accept and store AI guidance robot order information, which includes reservation information and usage information. The AI ​​intelligent cloud platform is used to store hospital information, patient information and AI guidance information, and perform data processing and other operations; S2: The patient uses voice to wake up the mobile phone APP, and enters the symptom information and the treatment plan through the mobile phone APP. The treatment plan reflects the patient's target treatment time and the available treatment time period; when the patient feels abnormal, the patient can use voice to wake up the mobile phone APP, and enter the symptom information through the mobile phone APP. The treatment plan includes the patient's target treatment time and the available treatment time period. Through the treatment plan, the patient's correction time can be adjusted within the patient's acceptable range to ensure that the patient is accompanied by the AI ​​guide robot and the corresponding doctor during the treatment process; S3: The AI ​​intelligent cloud platform receives the disease information, obtains the analysis results through the analysis strategy according to the received disease information, judges the disease conditions according to the analysis results and generates the initial diagnosis information. The disease conditions include the patient's disease type, the urgency of the disease, etc. The urgency of the disease includes Level 1 critical patients, whose condition is not life-threatening at any time, such as cardiac and respiratory arrest, shock, etc., Level 2 critical patients, whose condition is critical or rapidly deteriorates, and there may be a risk of illness, such as respiratory difficulties, acute stroke, Level 3 emergency patients, whose condition is urgent and there is a potential life-threatening situation, such as acute asthma, chest and abdominal pain, etc., Level 4 non-emergency patients, whose condition is general, such as mild pain without dangerous characteristics, and no need for suturing The AI ​​​​intelligent cloud platform can detect minor abrasions, grade 5 mild discomfort, such as occasional headaches, toothaches, mild diarrhea, etc.; the symptom information is encrypted and transmitted to the AI ​​intelligent cloud platform, and the analysis strategy is used to conduct in-depth analysis of the received symptom information to obtain the analysis results. Based on the analysis results, the patient's symptom condition is judged and the corresponding initial diagnosis results are generated, such as possible symptom names, severity, and appointment registration results, such as recommended departments, doctors, and consultation times; the generated consultation information is encrypted and sent to the patient's mobile phone APP and AI guidance robot. The mobile phone APP will feedback the consultation information to the patient, and the AI ​​guidance robot will prepare subsequent guidance services based on the consultation information; S4: The initial diagnosis information is matched with a schedule, which reflects the schedule information of the doctors in the corresponding department. The initial diagnosis information is readjusted through a self-adjustment strategy according to the schedule, the patient's visit plan, the historical doctors and the schedule to obtain the visit information, including the initial diagnosis result and the appointment registration result. The visit information is sent to the mobile phone APP and the AI ​​guidance robot. The initial diagnosis information is matched with the schedule information of the visiting doctor. According to the patient's visit plan and the patient's historical visit record, a variety of visit suggestions are generated, and readjusted according to the priority to obtain the visit information, including the initial diagnosis result and the appointment registration result. The visit information is sent to the mobile phone APP and the AI ​​guidance robot to facilitate the patient's visit; The self-regulation strategy includes the replacement step, The replacement step is to determine the urgency of the patient's condition based on the symptom information, and to adjust the patient's initial diagnosis information based on the assigned urgency of the patient's condition, the scheduling information of the historical doctors, the order information of the AI ​​guidance robot, and the patient's treatment plan to obtain a treatment recommendation. The patient selects the treatment information based on the treatment recommendation. Among the treatment information, for patients with lower urgency of the patient's condition, historical doctors are given priority within the treatment plan. According to the urgency of the patient's condition, level 4 non-emergency patients and level 5 mildly uncomfortable patients are given priority to match historical doctors, so that doctors can better understand the patient's treatment. For emergency patients, timely medical treatment is given priority.

[0020] The self-adjustment strategy also includes a dynamic analysis step. When the patient's condition is highly urgent and all AI guide robots are in working condition, the dynamic analysis step is performed to obtain the AI ​​guide robot's corresponding patient's medical process information within the corresponding time period, and generate an AI guide schedule based on the medical process information and the corresponding process duration, and adjust the working hours of the AI ​​guide robot and the corresponding patient's medical time to ensure that the current patient's medical process is matched with the corresponding AI guide robot. During the working process of the AI ​​guide robot, when a more urgent patient is received and there is currently no AI guide robot available, the working hours of the AI ​​Dao Zheng robot and the corresponding patient's medical time are adjusted, and the patient's medical time is adjusted, such as advancing the patient's medical consultation or examination to facilitate the early termination of the current patient's medical examination, or when the patient is in a long examination process, the current AI guide robot can be guided to receive patients with urgent conditions.

[0021] S5: The AI ​​medical guide robot arrives at the reception point in time and waits according to the location information sent by the patient's mobile phone APP. The AI ​​medical guide robot can obtain the location information sent by the patient's mobile phone APP and obtain the patient's current location in real time. The AI ​​medical guide robot has built-in map data and path planning algorithms to calculate the optimal path from the current location to the reception point. The robot moves autonomously according to the planned path and goes to the reception point where the patient is located. After the AI ​​medical guide robot arrives at the reception point, it waits for the patient to arrive; S6: After the patient arrives at the hospital, the AI ​​medical guide robot identifies the patient's identity, obtains the patient's medical information, and realizes in-hospital medical navigation based on the patient's medical information; when the patient arrives at the hospital, the AI ​​medical guide robot obtains the patient's identity through face recognition and voiceprint recognition, ensures the accuracy of the patient's identity, and quickly determines the patient's identity. The AI ​​medical guide robot maintains real-time communication with the AI ​​smart cloud platform to obtain the patient's medical information. Before face recognition and voiceprint recognition, they are all performed after obtaining the patient's consent on the collection APP.

[0022] S6 includes the steps of in-hospital navigation. The in-hospital navigation steps include completing the establishment of the in-hospital map in advance and obtaining the patient's medical information. According to the patient's medical information, the patient is guided to the designated medical point. The AI ​​medical guide robot is equipped with a high-precision in-hospital bottom, including detailed information such as the layout of each floor, the location of the department, and the traffic flow. The AI ​​medical guide robot calculates the best route from the current location to the medical point based on the patient's medical information and the in-hospital map data using the path planning algorithm, and the AI ​​medical guide robot provides detailed navigation guidance to the patient through voice broadcast. During the navigation process, the robot will adjust the path planning in real time to cope with dynamic changes within the hospital, such as elevator full load, corridor congestion, etc. Under the guidance of the AI ​​arrival robot, the patient can smoothly reach the designated medical point for treatment, and the patient is guided to leave the hospital.

[0023] The AI ​​intelligent cloud platform is linked to the elevator control system and the AI ​​medical guide robot. The AI ​​medical guide robot is used to obtain the patient's real-time location, and through the AI ​​intelligent cloud platform, the patient can select the floor, so that the patient can reach the designated destination floor without any operation.

[0024] The intra-hospital navigation step also includes an obstacle avoidance sub-step, which includes: The camera and laser radar on the AI ​​guidance robot are used to obtain images and point clouds of the obstacle map, and obtain obstacle images. The AI ​​guidance robot is equipped with a camera and laser radar. The camera is used to obtain high-resolution images of the surrounding environment, and the laser radar is used to scan the surrounding environment to generate 3D point cloud data and provide accurate spatial information. Preprocess the obstacle map image, obtain the outline edge line of the obstacle, and compare the obstacle type and obstacle coordinates through the obstacle database; perform denoising, grayscale, edge detection and other processing on the image obtained by the camera to obtain the outline edge line of the obstacle more clearly, and remove noise points from the point cloud data, and separate the power data into different objects or obstacles, and fuse the edge line after image processing with the point cloud data of the lidar to obtain a more accurate obstacle position and shape, and compare the identified obstacle outline edge line with the preset obstacle database to determine the type of obstacle, such as pedestrians, wheelchairs, beds, etc. Based on the fused data, calculate the precise coordinates of the obstacle; The coordinates and contour edge lines of obstacles are transmitted to the in-hospital map, and navigation is re-performed according to the corrected in-hospital map to correct the navigation route; the coordinates and contour edge lines of obstacles are transmitted to the in-hospital map system to realize the real-time update of map information, and the navigation path is re-planned according to the updated map information to ensure that the identified obstacles are avoided and a new collision-free path is generated; Obstacle avoidance action commands are issued to complete obstacle avoidance. According to the corrected navigation route, obstacle avoidance action commands are issued to the patient to remind the patient to avoid obstacles.

[0025] The AI ​​intelligent cloud platform is also connected to a taxi-hailing system, which uses the AI ​​intelligent cloud platform to obtain taxi-hailing demands from mobile APP and AI medical guidance robots, generate taxi-hailing orders and send them to the taxi-hailing system, and feed back taxi-hailing information to mobile APP and AI medical guidance robots; The analysis strategy includes obtaining the patient's symptom information, extracting keywords from the symptom information, matching them in the hospital cloud platform database, obtaining symptom types, and storing the patient's historical diagnosis and treatment data in the hospital cloud platform. The historical diagnosis and treatment data and symptom types are sorted by matching results and severity to obtain the patient's health form. Based on the patient's health form, the initial diagnosis result is obtained, and an appointment is made based on the initial diagnosis result; based on natural language processing, the symptoms are processed by word segmentation and part-of-speech tagging to extract relevant keywords about the disease, and the extracted keywords are matched with the symptom descriptions in the hospital cloud platform database to find the related symptom types, calculate the similarity between the keywords and the symptom descriptions in the database, determine the possible symptom types, and consult a doctor. The hospital cloud platform retrieves the patient's historical diagnosis and treatment data, including past dispute results, treatment records, medication status, etc., and obtains the patient's possible diseases, allergy history, and drug reactions based on the resignation results. The current symptom type, historical diagnosis and treatment data, and the severity of the symptoms, such as pain level and duration, are comprehensively evaluated, and a sorting algorithm is applied to sort possible diseases according to the evaluation results. Based on the above analysis, the patient's health table is constructed, listing possible diseases, related symptoms, severity, historical diagnosis and treatment data, and other information. Based on the information in the health table, the AI ​​smart cloud platform gives preliminary diagnosis results and suggestions. Based on the initial diagnosis results, the platform automatically recommends suitable departments and doctors to patients, generates appointment registration information, and realizes automatic registration operations.

[0026] S6 also includes a medical consultation navigation method, which includes S61: Guide patients to doctors and synchronize their medical information in real time; AI medical guidance robots plan and guide patients to designated doctors’ offices based on hospital maps and patient medical information. This includes instructing patients on which elevator to take, which corridor to walk in, how to turn, and other specific steps. During the guidance process, AI medical guidance robots can synchronize patients’ medical information through mobile phone apps and the hospital cloud platform, ensuring that doctors can understand patients’ conditions in advance and improve medical efficiency. S62: Complete fee settlement according to the doctor's prescription and with the patient's authorization; after the doctor issues a prescription, the relevant information will be automatically transmitted to the hospital cloud platform and the AI ​​guidance robot; the AI ​​guidance robot displays the prescription details and fee information to the patient through voice or screen display, and completes the fee settlement through mobile payment, medical insurance card or other payment methods with the patient's authorization.

[0027] S63: Guide patients to complete tests, X-rays and other examinations, and remind patients to rest and wait for test results; according to the doctor's prescription, the AI ​​guidance robot will guide patients to the corresponding examination department, such as the laboratory, radiology department, etc.; on the way to the examination department, the AI ​​guidance robot will remind patients to pay attention to the preparations before the examination, such as fasting, holding urine, etc., as well as precautions during the examination; after the examination is completed, the AI ​​guidance robot will inform the patient of the approximate waiting time and remind the patient to wait for the test results in the rest area. At the same time, the robot can synchronize the examination results with the hospital cloud platform in real time, and notify the patient immediately once the results are out; S64: Inform the patient that the report has been issued for a follow-up visit and synchronize the doctor's diagnosis results; when the patient's examination report is available, the AI ​​guidance robot will promptly notify the patient through mobile phone APP, SMS or voice; after the patient confirms receipt of the report, the AI ​​guidance robot will guide the patient back to the doctor's office for a follow-up visit. Before the follow-up visit, the robot can synchronize the doctor's diagnosis results and treatment recommendations so that the patient can understand the condition S65: Guide patients to get medicine and send them to the pick-up point After the doctor prescribes the medicine, the AI ​​guidance robot will guide the patient to the pharmacy to get the medicine; the AI ​​guidance robot can synchronize prescription information with the pharmacy system in real time to ensure that patients can quickly get the required medicine; when picking up medicine, the AI ​​guidance robot can provide patients with medication guidance, including drug usage, dosage, precautions, etc.; finally, the AI ​​guidance robot can send patients to the hospital's pick-up point, such as parking lots, bus stops, subway stations, etc., to ensure that patients leave the hospital safely.

[0028] An accessible AI intelligent guidance system, comprising Mobile APP is used to interact directly with patients, receive symptom information input, user instructions, and provide information feedback. It can be used to query hospital information, make appointments, view examination results, etc. According to the processing results of the AI ​​intelligent cloud platform, it can provide timely feedback to patients, such as successful registration notification, guidance on the treatment department, examination precautions, etc., and it can be linked with the AI ​​guidance robot to try to pass the patient's location information, treatment needs, etc. to the AI ​​guidance robot; AI medical guide robots interact directly with patients to complete the entire chain of services, including identity recognition, hospital navigation, medical care, fee settlement, laboratory tests, and medication collection. They also have the ability to interact with voice and voiceprints throughout the process. AI medical guide robots accompany patients throughout the medical treatment process and guide patients The AI ​​intelligent cloud platform, as the system's computing and control center, is responsible for command computing, data statistics, and strategy algorithm operation. It is interconnected with the hospital cloud platform, mobile APP, and AI medical guidance robot to achieve initial symptom screening, accurate registration, and real-time information sharing. It is used to receive commands from mobile APP and AI medical guidance robots, perform rapid computing and processing, and conduct statistics and analysis on all data in the system, including patient visit data and medical resource usage. Mobile APP, AI smart cloud platform and AI medical guidance robot work together.

[0029] The system architecture of the AI ​​medical guidance robot includes SOC+DDR+UFS combination, used for system and application operation and data storage; Vision systems for face recognition, map creation, and obstacle avoidance; Voice module and speaker for voice interaction and real-time broadcast; Navigation module, which provides positioning information and navigation engine to achieve accurate in-hospital navigation; The motor system controls the robot's movements, including turning, walking, and other actions; Touch display screen provides visual interactive interface or advertising display.

[0030] The above are only preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. An accessible AI intelligent guidance method, characterized in that: include S1: Establish a medical database on the AI ​​intelligent cloud platform, which includes all hospital departments, doctor information, scheduling information, etc., and establish a patient database, which records patient identity information and medical information. The AI ​​intelligent cloud platform can accept and store AI medical guidance robot order information, which includes reservation information and usage information; S2: The patient activates the mobile phone APP with voice and enters the symptom information and the consultation plan through the mobile phone APP. The consultation plan reflects the patient's target consultation time and available consultation time period; S3: The AI ​​intelligent cloud platform receives the disease information, obtains the analysis result through the analysis strategy according to the received disease information, judges the disease condition according to the analysis result and generates the initial diagnosis information, wherein the disease condition includes the patient's disease type, the urgency of the disease, etc.; S4: The initial diagnosis information is matched with a schedule table, which reflects the schedule information of the doctors in the corresponding department. The initial diagnosis information is readjusted through a self-adjustment strategy according to the patient's treatment plan, historical doctors and the schedule table to obtain the treatment information, which includes the initial diagnosis result and the appointment registration result, and the treatment information is sent to the mobile phone APP and the AI ​​guidance robot; S5: The AI ​​medical guide robot corresponding to the matching strategy is selected according to the medical information, and the AI ​​medical guide robot arrives at the reception point in time to wait according to the patient information; S6: After the patient arrives at the hospital, the AI ​​guidance robot identifies the patient, obtains the patient's medical information, and realizes the navigation within the hospital.

2. The barrier-free AI intelligent guidance method according to claim 1, characterized in that: The self-regulation strategy includes a replacement step, The replacement step determines the urgency of the patient's condition based on the symptom information, and combines the assigned urgency of the patient's condition, the scheduling information of the historical doctors, the order information of the AI ​​guidance robot, and the patient's treatment plan to adjust the patient's initial diagnosis information to obtain a treatment recommendation. The patient selects the treatment information based on the treatment recommendation. Among the treatment information, for patients with lower urgency of the patient's condition, historical doctors are given priority in matching within the treatment plan.

3. The barrier-free AI intelligent guidance method according to claim 2, characterized in that: The self-adjustment strategy also includes a dynamic analysis step. When the patient's condition is of high urgency and all AI medical guide robots are in working condition, the dynamic analysis step obtains the medical treatment process information of the AI ​​medical guide robot corresponding to the patient within the corresponding time period, generates an AI medical guide schedule based on the medical treatment process information and the corresponding process duration, adjusts the working hours of the AI ​​medical guide robot and the corresponding patient's medical treatment time, and ensures that the current patient's medical treatment process is matched with the corresponding AI medical guide robot.

4. The barrier-free AI intelligent guidance method according to claim 1, characterized in that: The S6 includes an intra-hospital navigation step, which includes completing the establishment of an intra-hospital map in advance, obtaining patient consultation information, and guiding the patient to a designated consultation point based on the patient consultation information.

5. The barrier-free AI intelligent guidance method according to claim 3, characterized in that: The intra-hospital navigation step also includes an obstacle avoidance sub-step, and the obstacle avoidance sub-step includes: Use the camera and lidar on the AI ​​medical guidance robot to obtain images and point clouds of the obstacle map and obtain obstacle images; Preprocess the obstacle map image, obtain the outline edge line of the obstacle, and compare the obstacle type and obstacle coordinates through the obstacle database; The obstacle coordinates and contour edge lines are transmitted to the in-hospital map, and navigation is re-performed according to the corrected in-hospital map to correct the navigation route; Issue an obstacle avoidance action command to complete obstacle avoidance.

6. The barrier-free AI intelligent guidance method according to claim 4, characterized in that: A mobile obstacle avoidance strategy is provided in the obstacle avoidance sub-step, and the mobile obstacle avoidance strategy is used to obtain multiple frames of obstacle images taken continuously within a predetermined time, obtain pixel movement in the multiple frames of obstacle images to identify the position points of the mobile obstacles, determine the moving trajectory of the mobile obstacles according to the position points, and adjust the navigation route according to the moving trajectory.

7. The barrier-free AI intelligent guidance method according to claim 1, characterized in that: The AI ​​intelligent cloud platform is also connected to a taxi-hailing system, which uses the AI ​​intelligent cloud platform to obtain taxi-hailing demands from mobile phone APP and AI medical guidance robot, generate taxi-hailing orders and send them to the taxi-hailing system, and feed back taxi-hailing information to mobile phone APP and AI medical guidance robot.

8. The barrier-free AI intelligent guidance method according to claim 1, characterized in that: The analysis strategy includes obtaining the patient's symptom information, extracting keywords from the symptom information, and matching them in the hospital cloud platform database to obtain symptom types, and storing the patient's historical diagnosis and treatment data in the hospital cloud platform, sorting the historical diagnosis and treatment data and symptom types according to matching results and severity to obtain a patient health table, obtaining initial diagnosis results based on the patient health table, and making appointments based on the initial diagnosis results.

9. The barrier-free AI intelligent guidance method according to claim 1, characterized in that: The S6 also includes a medical consultation navigation method, and the medical consultation navigation method includes S61: guiding the patient to see a doctor and synchronizing the medical information in real time; S62: Complete the fee settlement according to the doctor's prescription and with the patient's authorization; S63: Guide the patient to complete tests, X-rays and other examinations, and remind the patient to rest and wait for the test results; S64: Inform the patient that the report has been sent for a follow-up visit and synchronize the doctor's diagnosis results; S65: Guide the patient to get the medication and send the patient to the pick-up point.

10. An accessible AI intelligent guidance system, characterized in that: include Mobile phone APP is used to interact directly with patients, receive disease information input, user instructions, and provide information feedback; The AI ​​guidance robot interacts directly with patients to complete the entire chain of services including identity recognition, hospital navigation, medical care, fee settlement, laboratory tests, and medication collection, and has the ability to interact with voice and voiceprint throughout the process. The AI ​​intelligent cloud platform, as the system's computing and control center, is responsible for command computing, data statistics, and strategy algorithm operation. It is interconnected with the hospital cloud platform, mobile APP, and AI guidance robot to achieve initial symptom screening, accurate registration, and real-time information sharing; The mobile phone APP, AI smart cloud platform and AI medical guidance robot work together.

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