Intelligent guiding method and device, storage medium and electronic equipment

Abstract

The invention relates to an intelligent guiding method and device, a storage medium and electronic equipment, and relates to the technical field of guiding service, and the method comprises the steps: obtaining a target doctor-seeing time period selected when a target doctor-seeing user makes an appointment for registration when the target doctor-seeing user arrives at a hospital; according to the crowd type of the target doctor-seeing user and the target doctor-seeing time period, determining an in-hospital suitable navigation path corresponding to the target doctor-seeing user and sending the in-hospital suitable navigation path to a terminal of the target doctor-seeing user; when the target doctor-seeing user arrives at the target doctor-seeing department based on the in-hospital suitable navigation path, determining a suitable waiting area corresponding to the target doctor-seeing user from waiting areas of the target doctor-seeing department according to the crowd type; and sending a sign-in and number taking prompt to the terminal, and sending a number calling prompt of a consulting room of a target doctor to the terminal when the target doctor successfully signs in and takes a number. The method and the device have the effect of improving the experience of the user seeing a doctor in the hospital.

Description

Technical Field

[0001] The present application relates to the technical field of guidance services, and in particular to an intelligent guidance method, device, storage medium and electronic device. Background Art

[0002] Guidance service is an important part of the hospital. It provides effective guidance and help to patients through professional medical guides or intelligent systems. The purpose of this service is to improve the service efficiency and quality of the hospital, while providing patients with a convenient medical treatment experience. Among them, the common service scenarios of guidance services are: users who come to the hospital for treatment do not know how to go to the corresponding department, and they need to be guided to the corresponding department. When the patients arrive at the department, they also need to be reminded to take a number and sign in in time, so that the patients have a better experience.

[0003] At present, the guidance service of the hospital is usually implemented in the following way: relying on the staff at the manual guidance desk to inform the patients of the general method to go to the corresponding department. After the patients arrive at the corresponding department, they are mainly reminded to take numbers and queue up through prompt signs. Once the patients do not see the prompt signs in time, they will still look for staff for consultation. Under this method, users who need to see a doctor will actively ask questions many times, resulting in a poor experience for users in the hospital. Summary of the invention

[0004] In order to improve the user's experience of visiting a hospital, the present application provides a smart guidance method, device, storage medium and electronic device.

[0005] In a first aspect of the present application, a smart guidance method is provided, which specifically includes: When the target patient arrives at the hospital, the target patient time slot selected by the target patient when making an appointment is obtained, and the target patient is a user who has successfully made an appointment at the hospital; According to the population type of the target patient user and the target visit time period, determine the appropriate in-hospital navigation path corresponding to the target patient user and send it to the terminal of the target patient user, and the appropriate in-hospital navigation path is used to guide the target patient user to the corresponding target visit department in a targeted manner; When the target patient arrives at the target clinic department based on the appropriate navigation path within the hospital, a suitable waiting area corresponding to the target patient is determined from the waiting area of ​​the target clinic department according to the type of the population; A sign-in and number-taking reminder is sent to the terminal, and when the target patient successfully signs in and takes a number, a target doctor's office call reminder is sent to the terminal. The sign-in and number-taking reminder is used to remind the target patient to sign in, take a number and go to the suitable waiting area to wait. The target doctor's office is the office where the target doctor selected by the target patient when making an appointment is located.

[0006] By adopting the above technical solution, after obtaining the target visit time period of the target visit user, combined with the population type of the target visit user, a personalized and targeted suitable navigation path in the hospital is provided for the target visit user, thereby guiding the target visit user to better go to the target visit department to queue for treatment within the target visit time period, without having to ask for the route to go many times. Further, according to the type of population, the most suitable queuing waiting area for the target visit user is determined. Then, after the target visit user arrives at the target visit department, a personalized sign-in reminder is sent to its terminal to remind the target visit user to sign in in time to take a number and queue up in a suitable waiting area for the number to be called. Finally, after the target visit user successfully signs in and takes a number, a call reminder is sent to the terminal in real time to prevent the target visit user from missing a number, thereby improving the user's experience of visiting the hospital to a certain extent.

[0007] Optionally, determining a suitable in-hospital navigation path corresponding to the target patient visiting user and the target visiting time period according to the population type of the target patient visiting user and sending the path to the terminal of the target patient visiting user specifically includes: Determine at least one to-be-selected in-hospital navigation route whose estimated arrival time is within the target consultation time period; When the target patient visitor is a slow-walking type, the number of historical fall accidents in each of the to-be-selected in-hospital navigation paths is determined, and in the order of the number of accidents from small to large, the to-be-selected in-hospital navigation paths with the first preset number are selected from the to-be-selected in-hospital navigation paths and determined as the path that is not prone to fall; Obtaining accident areas of historical fall accidents in each of the paths that are not prone to falling, counting the number of occurrences of each of the accident areas, and selecting accident areas with a preset second number from each of the accident areas in descending order of the number of occurrences as accident-prone areas of the corresponding paths that are not prone to falling; Calculate the first weight of each of the non-falling paths and the second weight of the corresponding accident-prone areas; determine the suitable in-hospital navigation path corresponding to the target patient from each of the non-falling paths based on the first weight and the corresponding second weight and send it to the terminal of the target patient; the first weight is the ratio of the number of accidents corresponding to each non-falling path to the sum of the number of accidents of all non-falling paths; the second weight is the ratio of the number of occurrences of a single accident-prone area corresponding to the non-falling path to the sum of the number of occurrences of all corresponding accident-prone areas.

[0008] By adopting the above technical solution, the more accidents there are, the more likely a fall will occur in the corresponding in-hospital navigation path to be selected, and thus a path that is not prone to falling will be determined; the greater the number of accidents, the more likely a fall will occur in the corresponding accident area, and thus the accident-prone area corresponding to the path that is not prone to falling will be determined. Finally, based on the analysis of the first weight of each path that is not prone to falling and the second weight of each corresponding area that is prone to accidents, the in-hospital suitable navigation path that is relatively least likely to fall is selected from each path that is not prone to falling, so that the target patient is not prone to falling on the way to the target department.

[0009] Optionally, determining, according to the first weight and the corresponding second weight, a suitable in-hospital navigation path corresponding to the target patient from each of the non-falling paths and sending the path to the terminal of the target patient, specifically includes: Calculate the product of the first weight of each of the non-falling paths and the corresponding second weights to obtain a corresponding first weight product; Sum the first weight products corresponding to the single non-falling path to obtain the corresponding sum of the first weight products; The minimum sum of the first weighted products is selected from the sums of the first weighted products, and the low-fall path corresponding to the minimum sum of the first weighted products is determined as the suitable in-hospital navigation path corresponding to the target patient user and sent to the terminal of the target patient user.

[0010] By adopting the above technical solution, the larger the first weight product, the greater the possibility that the target patient will fall in the corresponding accident-prone area. Furthermore, the larger the sum of the first weight products, the greater the overall possibility that the target patient will fall in the corresponding non-falling path. Finally, the non-falling path corresponding to the minimum sum of the first weight products is determined as the appropriate in-hospital navigation path suitable for the target patient, thereby guiding the target patient to queue up for treatment in the target treatment department within the target treatment period, and preventing the target patient from falling on the way.

[0011] Optionally, the method further includes: Calculate the second weight product of the first weight of the suitable navigation path within the hospital and the second weight of each corresponding accident-prone area; Selecting a target second weighted product greater than a preset first product threshold from each of the second weighted products, and determining an accident-prone area corresponding to each of the target second weighted products as a warning accident area; When the target patient arrives at each of the warning accident areas according to the suitable navigation path in the hospital, a fall warning message is sent to the terminal.

[0012] By adopting the above technical solution, the larger the second weight product is, the greater the possibility that the target patient will fall in the corresponding accident-prone area. The target second weight product greater than the preset first product threshold is determined, and the accident-prone area corresponding to the target second weight product and the accident-prone area where the target patient is more likely to fall are determined as warning accident areas. When the target patient passes through the warning accident area, a fall warning message is sent to the terminal, thereby reminding the target patient to be vigilant about the fall problem and avoid fall accidents.

[0013] Optionally, the determining, according to the first weight and the corresponding second weight, from each of the non-falling paths, an in-hospital suitable navigation path corresponding to the target patient visiting user and sending the path to the terminal of the target patient visiting user specifically includes: Calculate the product of the first weight of each of the non-falling paths and the corresponding second weights to obtain the corresponding first weight product, and sum the first weight products corresponding to a single non-falling path to obtain the sum of the corresponding first weight products; Obtain the number of appointments corresponding to the target doctor in each consultation period on that day, and select the third consultation period from each consultation period in descending order of the number of appointments as the easy-to-queue period; Counting the number of historical numbers taken by the target doctor in each sub-period within a single easy-to-queue period, and selecting a sub-period with a preset fourth number from each of the sub-periods in descending order of the number of historical numbers taken as the easily congested sub-period of the corresponding easy-to-queue period; When the target consultation period is a period prone to queuing, the third weight of the target consultation period and the fourth weight of each corresponding sub-period prone to congestion are calculated, wherein the third weight is the ratio of the number of registrations in the target consultation period to the sum of the number of registrations in all periods prone to queuing, and the fourth weight is the ratio of the number of historical registrations in a single sub-period prone to congestion corresponding to the target consultation period to the sum of the number of historical registrations in all corresponding sub-periods prone to congestion; Calculate the third weight product of the target visit time period and the corresponding fourth weights, select a target third weight product that is less than a preset second product threshold from the third weight products, and select a target first weight product sum that is less than a preset first product sum threshold from the sum of the first weight products; The non-falling path corresponding to the sum of the first weight products of each target and whose estimated arrival time is in the congested sub-time period corresponding to the third weight product of the target is determined as a suitable navigation path within the hospital, and the suitable navigation path within the hospital is sent to the terminal of the target medical user.

[0014] By adopting the above technical solution, the larger the third weight product is, the more likely users who choose to see a doctor during the target consultation period will be crowded in the corresponding sub-period that is prone to crowding to get a number and queue up, and the more serious the queuing situation will be. The crowded sub-period corresponding to the target third weight product is a sub-period within the target consultation period where the possibility of crowding to get a number and queue up is relatively small, and the non-falling path corresponding to the sum of the target first weight products is an in-hospital navigation path where the target user is less likely to fall. Finally, if the estimated arrival time of the non-falling path corresponding to the sum of the target first weight products is within the crowded sub-period corresponding to the target third weight product, then the corresponding non-falling path is determined as the in-hospital suitable navigation path for the target user. The target user goes to the target consultation department according to this in-hospital suitable navigation path, which can not only avoid falling to a certain extent, but also avoid the situation of crowding and queuing, and improve the experience of queuing and calling numbers.

[0015] Optionally, the method further includes: When the target consultation time period is not an easy-to-queue time period, determining whether an adjacent consultation time period before the target consultation time period is an easy-to-queue time period, and if so, determining the adjacent consultation time period as the previous easy-to-queue time period; Calculate the sum of the fourth weight products of the third weight of the previous easy-to-queue time period and the fourth weights of the corresponding easy-to-crowd sub-time periods, and if the sum of the fourth weight products is greater than the preset second product sum threshold, calculate the time difference between the estimated arrival time of the non-easy-to-fall path corresponding to the sum of the first weight products of each target and the start time of the target consultation time period; The maximum time difference is selected from each of the time differences, and the non-falling path corresponding to the maximum time difference is determined as the suitable in-hospital navigation path corresponding to the target patient user and sent to the terminal of the target patient user.

[0016] By adopting the above technical solution, if the target consultation period is not a period prone to queuing, it means that the queuing situation for number taking is good during the target consultation period. Furthermore, if the sum of the fourth weight products is greater than the preset second product sum threshold, it means that the queuing situation in the entire previous easy queuing period is relatively serious, and many patients belonging to the previous easy queuing period will most likely continue to queue for treatment during the target consultation period. In this case, the path that is not prone to falling corresponding to the maximum time difference is determined as a suitable navigation path within the hospital, so that when the target patient arrives at the corresponding target consultation department according to the suitable navigation path within the hospital, he can try to stagger the queue with the patients in the previous easy queuing period who are still queuing, so that the target patient can get a better queuing and waiting experience.

[0017] Optionally, determining a suitable waiting area corresponding to the target medical user from the waiting area of ​​the target medical department according to the type of the population specifically includes: If the crowd type is a slow-walking type, then when the number of people queuing before the target patient exceeds a preset threshold, determine a first area within a preset distance from the target doctor's office and a second area within a preset distance from the toilet on the same floor, where the preset distance is the longest distance suitable for the target patient to walk; The first area, the second area and the waiting area of ​​the target medical department are intersected to obtain a suitable waiting area corresponding to the target medical user.

[0018] By adopting the above technical solution, if the number of people in the queue exceeds the quantity threshold, it means that the target patient needs to wait in line for a long time. Then, the first area, the second area and the waiting area of ​​the target treatment department are intersected to obtain the overlapping area in these three areas at the same time, and determine it as the suitable waiting area corresponding to the target patient. When the target patient is waiting for his number to be called in this suitable waiting area, whether he goes to the toilet due to a long waiting time or goes to the clinic when his number is called, the walking distance is shorter and more suitable, which is more convenient for this target patient.

[0019] In a second aspect of the present application, a smart guidance device is provided, specifically comprising: An information acquisition module is used to acquire the target consultation time period selected by the target consultation user when making an appointment when the target consultation user arrives at the hospital, wherein the target consultation user is a user who has successfully made an appointment at the hospital; A path determination module is used to determine the appropriate in-hospital navigation path corresponding to the target patient according to the population type of the target patient and the target visit time period, and send it to the terminal of the target patient. The appropriate in-hospital navigation path is used to guide the target patient to the corresponding target visit department in a targeted manner. An area determination module, used for determining a suitable waiting area corresponding to the target medical user from the waiting area of ​​the target medical department according to the type of the population when the target medical user arrives at the target medical department based on the suitable navigation path in the hospital; The number calling reminder module is used to send a sign-in and number taking reminder to the terminal, and when the target patient successfully signs in and takes a number, sends a call reminder of the target doctor's office to the terminal. The sign-in and number taking reminder is used to remind the target patient to sign in, take a number and go to the suitable waiting area to wait. The target doctor's office is the office where the target doctor selected by the target patient when making an appointment is located.

[0020] By adopting the above technical solution, the information acquisition module obtains the target consultation time period, the path determination module determines the appropriate navigation path within the hospital corresponding to the target consultation user and sends it to the terminal of the target consultation user, then the area determination module determines the appropriate waiting area corresponding to the target consultation user from the waiting area of ​​the target consultation department, and finally the number calling reminder module sends a sign-in and number taking reminder to the terminal, and when the target consultation user successfully signs in and takes the number, the number calling reminder of the target doctor's office is sent to the terminal.

[0021] In a third aspect of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is loaded and executed by a processor, the method steps described in any one of the first aspects are performed.

[0022] In a fourth aspect of the present application, an electronic device is provided, specifically comprising: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the processor is used to load and execute the computer program stored in the memory so that the electronic device performs the method as described in any one of the first aspects.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: after obtaining the target visit time period of the target visit user, combined with the population type of the target visit user, a personalized and targeted suitable navigation path in the hospital is provided for the target visit user, thereby guiding the target visit user to better go to the target visit department to queue up for treatment within the target visit time period, without having to ask for the route to go many times. Further, according to the type of population, the most suitable queuing waiting area for the target visit user is determined. Then, after the target visit user arrives at the target visit department, a personalized sign-in reminder is sent to its terminal to remind the target visit user to sign in in time to take a number and queue up in a suitable waiting area for the number to be called. Finally, after the target visit user successfully signs in and takes a number, a call reminder is sent to the terminal in real time to prevent the target visit user from missing a number, thereby improving the user's experience of visiting the hospital to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of a smart guidance method provided in an embodiment of the present application; Figure 2 It is a flowchart of another intelligent guidance method provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of a smart guidance device provided in an embodiment of the present application; Figure 4 It is a schematic diagram of the structure of another intelligent guidance device provided in an embodiment of the present application.

[0025] Explanation of the accompanying drawings: 11. Information acquisition module; 12. Path determination module; 13. Area determination module; 14. Call reminder module; 15. Accident reminder module; 16. Navigation sending module. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0028] In the description of the embodiments of the present application, the term "and / or" is only a kind of association relationship describing the associated objects, indicating that there may be three kinds of relationships, for example, A and / or B, which can represent: A exists alone, B exists alone, and A and B exist at the same time. In addition, unless otherwise specified, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] See also Figure 1 The present application discloses a flowchart of a smart guidance method, which is applied to a smart guidance device and can also be implemented by a computer program or run on a smart guidance device based on a server of a von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S101: When the target patient arrives at the hospital, the target consultation time period selected by the target patient when making an appointment is obtained.

[0030] Specifically, in an embodiment of the present application, the target user is a user who has successfully made an appointment at the hospital, and the target consultation period is the time period when the target user wants to go for consultation. For example, the target user needs a doctor's help in diagnosing obstetrics-related problems, so an appointment is made through the hospital service-related client or applet in the terminal, and doctor A in the obstetrics department is selected. The consultation periods corresponding to doctor A are 8:00-9:00, 9:30-10:30, etc. on the same day. If the target user selects 9:30-10:30, then 9:30-10:30 is the target consultation period selected by the target user when making an appointment, doctor A is the target doctor selected by the target user when making an appointment, and obstetrics is the target department that the target user is going to.

[0031] It should be noted that the execution subject of the intelligent guidance method disclosed in the embodiment of the present application is a server, which can be a client or a background server of a small program related to hospital services in the terminal of the target patient, and the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. The terminal can be a smart phone or a personal computer.

[0032] Furthermore, after the target patient successfully makes an appointment, the server will send the appointment information to the terminal of the target patient through the client. The appointment information includes but is not limited to the doctor, department, date and target time period, and the appointment information corresponding to the target patient is stored in the server's database. Furthermore, with the target patient's consent to access the location information, the location information of the target patient on the appointment date is obtained by calling the interface. If the location information is the location information of the hospital, it is determined that the target patient has arrived at the hospital, and the server extracts the appointment information corresponding to the target patient from the database, and finally obtains the target time period selected by the target patient when making the appointment based on the appointment information.

[0033] S102: According to the population type and target visiting time period of the target visiting user, determine the appropriate in-hospital navigation path corresponding to the target visiting user and send it to the terminal of the target visiting user. The appropriate in-hospital navigation path is used to specifically guide the target visiting user to the corresponding target visiting department.

[0034] Specifically, the crowd type refers to the classification of users according to different characteristics in order to better understand the needs and behaviors of users. In an embodiment of the present application, the crowd type of the target patient users includes but is not limited to the slow walking type or the poor hearing type, etc. A feasible way to determine the crowd type of the target patient users is to input the registration information of the target patient users on the client or applet related to the hospital service and the registered department information into the crowd type prediction model to obtain it, wherein the registration information includes but is not limited to name, age and other information. In addition, the crowd type prediction model can be a trained convolutional neural network model or a recurrent neural network model. The training process is briefly described as follows: the registration information and registered department information of historical patients marked with the correct crowd type are used as training samples to train the model until the model converges. This is a prior art and will not be repeated here.

[0035] Furthermore, according to the population type and target visit time period of the target visit user, a targeted in-hospital navigation path, i.e., an appropriate in-hospital navigation path, is determined for the target visit user, and sent to the terminal of the target visit user, so as to better guide the target visit user to the corresponding target visit department, so that the visit experience of the hospital is better. Furthermore, a feasible way to determine an appropriate in-hospital navigation path is: based on the location information of the target visit user when arriving at the hospital and the location information of the target visit department, multiple in-hospital navigation paths are determined through a preset navigation tool, and the estimated navigation time corresponding to each in-hospital navigation path is determined, and finally, according to the current time and the estimated navigation time, the corresponding estimated arrival time is determined, i.e., the time to arrive at the target visit department, and at least one in-hospital navigation path to be selected whose estimated arrival time is within the target visit time period is selected from the multiple in-hospital navigation paths. Furthermore, if the target patient user population type is the slow walking type, for example, the target patient users are elderly people or pregnant women and other groups with limited mobility, which means that the target patient users have poor walking stability or convenience and are prone to falling. Therefore, the historical monitoring video obtained by the camera is used to determine the historical fall accidents that have occurred, and then the number of historical fall accidents in each to-be-selected in-hospital navigation path is counted, that is, the number of accidents. The more the number of accidents, the more likely the corresponding to-be-selected in-hospital navigation path is to have falls. Then, in order of the number of accidents from small to large, the to-be-selected in-hospital navigation paths with the preset first number are selected from each to-be-selected in-hospital navigation path and determined as the path that is not prone to falling, that is, the to-be-selected in-hospital navigation path where people are not likely to fall, wherein the first number can be set as: 20% of the total number of to-be-selected in-hospital navigation paths.

[0036] Furthermore, the specific accident areas of historical fall accidents that occurred in a single path that is not easy to fall are determined, and the number of occurrences of each accident area is counted. The greater the number of occurrences, the more likely falls are to occur in the corresponding accident area. In order of the number of occurrences from large to small, the second number of accident areas is selected from each accident area and determined as the accident-prone area of ​​the corresponding path that is not easy to fall, that is, the area in the path that is not easy to fall where falls are likely to occur.

[0037] Further, the first weight of each path that is not easy to fall and the second weight of the corresponding accident-prone area are calculated, the first weight is the ratio of the number of accidents corresponding to each path that is not easy to fall to the sum of the number of accidents of all paths that are not easy to fall, and the second weight is the ratio of the number of occurrences of a single accident-prone area corresponding to the path that is not easy to fall to the sum of the number of occurrences of all corresponding accident-prone areas. Further, according to each first weight and the corresponding second weight, a suitable navigation path in the hospital is determined from each path that is not easy to fall. The specific process is: the first weight of each path that is not easy to fall and the product of the second weight of each corresponding accident-prone area are calculated to obtain the corresponding first weight product. The larger the first weight product is, the greater the possibility that the target patient will fall in the corresponding accident-prone area. Then, the first weight products corresponding to the single path that is not easy to fall are summed to obtain the corresponding sum of the first weight products. The larger the sum of the first weight products is, the greater the overall possibility that the target patient will fall in the corresponding path that is not easy to fall. Finally, the minimum sum of the first weighted products is selected from the sums of the first weighted products, and the corresponding path that is not easy to fall is determined as the suitable navigation path in the hospital suitable for this target patient, and the suitable navigation path in the hospital is sent to the terminal of the target patient, so as to guide the target patient to queue up for the target treatment department during the target treatment period, and at the same time, it can also prevent the target patient from falling on the way. In addition, illustratively, if the population type of the target patient is a wheelchair user, then the in-hospital navigation path suitable for them can be determined as an barrier-free navigation path. Alternatively, if the population type is a person with poor eyesight, the in-hospital navigation path with better lighting conditions can be determined as a suitable path.

[0038] In other embodiments, after the appropriate navigation path in the hospital is determined, the first weight of the appropriate navigation path in the hospital and the second weight product of the corresponding second weights of each accident-prone area are calculated, and then the target second weight product is selected from each second weight product, that is, the second weight product is greater than the preset first product threshold. The target patient is prone to fall in the accident-prone area corresponding to the target second weight product, so the accident-prone area corresponding to the target second weight product is determined as a warning accident area. Finally, when the target patient walks along the appropriate navigation path in the hospital and passes through the warning accident area, a fall warning message is sent to his terminal to remind the target patient to be vigilant about the fall problem.

[0039] In another embodiment, a feasible way to determine a suitable navigation path in the hospital is as follows: after determining the sum of the first weight products corresponding to a single path that is not prone to falling, the number of registrations corresponding to each consultation period of the target doctor on the day is determined through the appointment registration data in the backend server of the client or applet related to the hospital service. The larger the number of registrations, the more users the target doctor needs to see during the corresponding consultation period. According to the order of the number of registrations from large to small, the third number of consultation periods are selected from each consultation period to be determined as the easy queuing period, that is, the period when the target doctor is prone to queuing. Further, according to the historical number-taking records of the target doctor, the sub-periods in which the number-taking is distributed in a single easy queuing period are determined, and the historical number of number-taking in each sub-period is counted. The more the number of historical number-taking, the easier it is for the users to gather in the corresponding sub-period to take numbers and queue. Then, according to the order of the historical number of number-taking from large to small, the fourth number of sub-periods are selected from each sub-period to be determined as the easily crowded sub-period of the corresponding easy queuing period, that is, the sub-period where it is easy to gather to take numbers and queue.

[0040] Furthermore, when the target consultation time period is a time period prone to queuing, the third weight of the target consultation time period and the fourth weights of the corresponding sub-time periods prone to congestion are calculated, the third weight being the ratio of the number of registrations in the target consultation time period to the sum of the number of registrations in all time periods prone to queuing, and the fourth weight being the ratio of the historical number of number taking in a single sub-time period prone to congestion corresponding to the target consultation time period to the sum of the historical number of number taking in all corresponding sub-time periods prone to congestion.

[0041] Calculate the third weight product of the third weight of the target consultation time period and the fourth weight of each corresponding sub-period prone to congestion. The larger the third weight product is, the more likely it is that users who choose to visit the doctor during the target consultation time period will be crowded in the corresponding sub-period prone to congestion to queue up, and the more serious the queuing situation will be. Then compare each third weight product with the preset second product threshold, and select the target third weight product that is less than the second product threshold, and at the same time select the sum of the target first weight products that is less than the preset first product sum threshold from the sum of each first weight product. Among them, the easily crowded sub-period corresponding to the target third weight product is the sub-period within the target consultation time period with a low possibility of crowding to queue up, and the non-falling path corresponding to the sum of the target first weight products is the in-hospital navigation path where the target consultation user is less likely to fall.

[0042] Furthermore, it is determined whether the estimated arrival time of the non-falling path corresponding to the sum of the first weighted products of each target is within the congested sub-time period corresponding to the third weighted product of the target. If so, the corresponding non-falling path is determined as the suitable navigation path in the hospital for the target patient, and the suitable navigation path in the hospital is sent to the terminal of the target patient. The target patient goes to the target treatment department according to the suitable navigation path in the hospital, which can not only avoid falling to a certain extent, but also avoid queuing, thereby reducing the time cost of waiting in line to be called.

[0043] In another embodiment, if the target consultation period is not an easy-to-queue period, indicating that the number-taking queuing situation is good within the target consultation period, then it is determined whether the consultation period of the target doctor before the target consultation period and adjacent to the target consultation period (adjacent consultation period) is an easy-to-queue period, and if so, then this adjacent consultation period is determined as the previous easy-to-queue period. Further, the fourth weight product of the third weight of the previous easy-to-queue period and the fourth weight of each corresponding easy-to-crowd sub-period is calculated and summed to obtain the corresponding sum of the fourth weight products. The larger the sum of the fourth weight products, the more serious the queuing situation of the entire previous easy-to-queue period. If the sum of the fourth weighted products is greater than the preset threshold of the sum of the second products, it means that the queuing situation in the entire previous easy-to-queue period is relatively serious, and there is a high probability that many patients in the previous easy-to-queue period will continue to queue for treatment in the target treatment period. Then, the time difference between the estimated arrival time of the non-falling path corresponding to the sum of the first weighted products of each target and the start time of the target treatment period is calculated, and the maximum time difference is selected from each time difference. The non-falling path corresponding to the maximum time difference is determined as the suitable navigation path in the hospital and sent to the terminal, so that when the target patients arrive at the corresponding target treatment department according to the suitable navigation path in the hospital, they can try to stagger the queue with the patients in the previous easy-to-queue period who are still queuing, so that the target patients can get a better queuing and waiting experience.

[0044] S103: When the target patient arrives at the target treatment department based on the appropriate navigation path in the hospital, a suitable waiting area corresponding to the target patient is determined from the waiting area of ​​the target treatment department according to the type of people.

[0045] Specifically, after the appropriate in-hospital navigation path suitable for the target patient is determined, based on this in-hospital appropriate navigation path, the corresponding augmented reality (AR) navigation is generated through the preset navigation tool and displayed on the terminal of the target patient, so as to better guide the target patient to the target department accurately. Among them, AR navigation refers to the way in which augmented reality technology assists users in route navigation, which superimposes virtual navigation path information on the field of vision of the real world to provide intuitive navigation guidance. In addition, the navigation tool can be a Gaode map tool.

[0046] After the target patient arrives at the target clinic department, the appropriate waiting area corresponding to the target patient is determined from the waiting area of ​​the target clinic department according to the type of crowd. The waiting area is the area where the target patient waits for the corresponding doctor to call the number after taking the number. For example, if the target patient is a person with poor hearing, then a waiting area within a fixed distance range is selected from the waiting area to be determined as the appropriate waiting area for the target patient. The fixed distance range is a circular area with a fixed distance radius and a queue calling machine as the center. The fixed distance is the farthest distance that a user with poor hearing can hear clearly. In summary, determining the corresponding appropriate waiting area according to the type of crowd of the target patient can bring the target patient a better experience of queuing and waiting for the number to be called.

[0047] S104: Send a sign-in number-taking reminder to the terminal, and when the target patient successfully signs in and takes a number, send a call reminder of the target doctor's office to the terminal. The sign-in number-taking reminder is used to remind the target patient to sign in, take a number and go to a suitable waiting area to wait.

[0048] Specifically, the target doctor's office is the office where the target doctor is located when the target patient user makes an appointment. After the appropriate waiting area is determined, a sign-in number collection reminder is sent to the terminal, thereby reminding the target patient user to promptly queue up on the self-service sign-in and registration machine after arriving at the target treatment department, and go to the appropriate waiting area to wait for the target doctor's number to be called. When the server obtains the sign-in and number collection record of the target patient user through the self-service sign-in and registration machine, it is determined that the target patient user has successfully signed in and collected the number, and then sends the target doctor's office call reminder to the terminal, thereby realizing the synchronization of the target doctor's call number information to the target patient user's terminal, to a certain extent avoiding the target patient user from missing the number.

[0049] See also Figure 2The present application embodiment discloses a flow chart of another intelligent guidance method, which is applied to an intelligent guidance device and can also be implemented by a computer program or run on an intelligent guidance device based on a server of a von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S201: When the target patient arrives at the hospital, the target consultation time period selected by the target patient when making an appointment is obtained.

[0050] S202: According to the population type and target visiting time period of the target visiting user, determine the appropriate in-hospital navigation path corresponding to the target visiting user and send it to the terminal of the target visiting user. The appropriate in-hospital navigation path is used to specifically guide the target visiting user to the corresponding target visiting department.

[0051] For details, please refer to steps S101-S102, which will not be described in detail here.

[0052] S203: When the target patient arrives at the target treatment department based on the appropriate navigation path in the hospital, if the crowd type is a slow-walking type, then when the number of people queuing before the target patient exceeds a preset number threshold, determine a first area within a preset distance of the target doctor's office and a second area within a preset distance of the toilet; S204: Intersecting the first area, the second area, and the waiting area of ​​the target medical department to obtain a suitable waiting area corresponding to the target medical user.

[0053] Specifically, when the target patient arrives at the target clinic, if the target patient is a slow-walking type, for example, the target patient is an elderly person or a pregnant woman with limited mobility, then the number of people in the queue before the target patient is obtained from the hospital's queuing system, and the number of people in the queue is compared with the preset threshold value. If the number of people in the queue exceeds the threshold value, it means that the target patient needs to wait in line for a long time, then the first area within the preset distance of the target doctor's office is determined, that is, the area closer to the target doctor's office, and the toilet on the same floor as the target doctor's office is determined, that is, the second area within the preset distance of the toilet on the same floor. Specifically, based on the electronic floor plan of this floor, the first area and the second area can be determined with the location of the target doctor's office and the location of the toilet on the same floor as the center of the circle and the preset distance as the radius. Among them, the preset distance is the farthest distance suitable for the target patient to walk.

[0054] Furthermore, the preset MATLAB tool is used to intersect the first area, the second area and the waiting area of ​​the target treatment department, and the overlapping area that is simultaneously in these three areas is obtained, and is determined as the suitable waiting area corresponding to the target treatment user. When the target treatment user is waiting to be called in this suitable waiting area, whether he goes to the toilet due to a long waiting time or goes to the consulting room when his number is called, the walking distance is shorter, which is more convenient for the target treatment user.

[0055] S205: Send a sign-in number collection reminder to the terminal, and when the target patient successfully signs in and takes a number, send a call reminder of the target doctor's office to the terminal. The sign-in number collection reminder is used to remind the target patient to sign in, take a number and go to a suitable waiting area to wait.

[0056] For details, please refer to step S104, which will not be described in detail here.

[0057] The implementation principle of a smart guidance method in an embodiment of the present application is as follows: after obtaining the target visit time period of the target visit user, combined with the population type of the target visit user, a personalized and targeted suitable navigation path in the hospital is provided for the target visit user, thereby guiding the target visit user to better go to the target visit department to queue up for treatment within the target visit time period, without having to ask for the route to go many times. Further, according to the type of population, the most suitable queuing waiting area for the target visit user is determined. Then, after the target visit user arrives at the target visit department, a personalized sign-in and number-taking reminder is sent to its terminal to remind the target visit user to take a number and sign in in time, and queue up in a suitable waiting area to wait for the number to be called. Finally, after the target visit user successfully signs in and takes a number, a number-calling reminder is sent to the terminal in real time to prevent the target visit user from missing a number, thereby improving the user's experience of visiting the hospital to a certain extent.

[0058] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0059] See also Figure 3 , is a schematic diagram of the structure of the smart guidance device provided in the embodiment of the present application. The application in the smart guidance device can be realized as all or part of the device through software, hardware or a combination of both. The device includes an information acquisition module 11, a path determination module 12, an area determination module 13 and a call reminder module 14.

[0060] The information acquisition module 11 is used to obtain the target consultation time period selected by the target consultation user when making an appointment when the target consultation user arrives at the hospital. The target consultation user is a user who has successfully made an appointment at the hospital; The path determination module 12 is used to determine the appropriate in-hospital navigation path corresponding to the target patient according to the population type and target visit time of the target patient, and send it to the terminal of the target patient. The appropriate in-hospital navigation path is used to guide the target patient to the corresponding target visit department in a targeted manner; The area determination module 13 is used to determine the appropriate waiting area corresponding to the target medical user from the waiting area of ​​the target medical department according to the type of people when the target medical user arrives at the target medical department based on the appropriate navigation path in the hospital; The number calling reminder module 14 is used to send a sign-in number taking reminder to the terminal, and when the target patient successfully signs in and takes a number, it sends a call reminder of the target doctor's office to the terminal. The sign-in number taking reminder is used to remind the target patient to sign in, take a number and go to a suitable waiting area to wait. The target doctor's office is the office where the target doctor selected by the target patient when making an appointment is located.

[0061] Optionally, the path determination module 12 is specifically configured to: Determine at least one candidate in-hospital navigation path with an estimated arrival time within a target consultation period; When the target patient visitor type is a slow walker, the number of historical fall accidents in each candidate hospital navigation path is determined, and the candidate hospital navigation path with the first preset number is selected from each candidate hospital navigation path in ascending order of the number of accidents and determined as a path that is not prone to fall; Obtain the accident areas of historical fall accidents in each path that is not prone to falling, count the number of occurrences of each accident area, and select the accident area with the second preset number from each accident area in descending order of the number of occurrences as the accident-prone area of ​​the corresponding path that is not prone to falling; Calculate the first weight of each path that is not prone to falling and the second weight of the corresponding accident-prone area; determine the appropriate in-hospital navigation path corresponding to the target patient from each path that is not prone to falling based on the first weight and the corresponding second weight and send it to the terminal of the target patient; the first weight is the ratio of the number of accidents corresponding to each path that is not prone to falling to the sum of the number of accidents of all paths that are not prone to falling; and the second weight is the ratio of the number of occurrences of a single accident-prone area corresponding to the path that is not prone to falling to the sum of the number of occurrences of all corresponding accident-prone areas.

[0062] Optionally, the path determination module 12 is specifically configured to: Calculate the product of the first weight of each non-falling path and the corresponding second weights to obtain the corresponding first weight product; Sum the first weight products corresponding to a single non-falling path to obtain the corresponding sum of the first weight products; The minimum sum of the first weighted products is selected from the sums of the first weighted products, and the low-fall path corresponding to the minimum sum of the first weighted products is determined as the in-hospital suitable navigation path corresponding to the target patient user and sent to the terminal of the target patient user.

[0063] Optional, such as Figure 4 As shown, the device also includes an accident reminder module 15, which is specifically used for: Calculate the second weight product of the first weight of the suitable navigation path within the hospital and the second weight of each corresponding accident-prone area; Selecting a target second weighted product greater than a preset first product threshold from each second weighted product, and determining an accident-prone area corresponding to each target second weighted product as a warning accident area; When the target patient arrives at each warning accident area according to the appropriate navigation path in the hospital, a fall warning message is sent to the terminal.

[0064] Optionally, the path determination module 12 is specifically configured to: Calculate the product of the first weight of each non-falling path and the corresponding second weights to obtain the corresponding first weight product, and sum the first weight products corresponding to a single non-falling path to obtain the sum of the corresponding first weight products; Obtain the number of appointments corresponding to the target doctor in each consultation period on the day, and select the third numbered consultation period from each consultation period in descending order of the number of appointments as the easy-to-queue period; The number of historical number-taking of the target doctor in each sub-period within a single easy-queuing period is counted, and the sub-period with the fourth number preset in the order from large to small is selected from each sub-period to be determined as the easy-crowding sub-period of the corresponding easy-queuing period; When the target consultation period is a period prone to queuing, the third weight of the target consultation period and the fourth weight of each corresponding sub-period prone to congestion are calculated, the third weight being the ratio of the number of registrations in the target consultation period to the sum of the number of registrations in all periods prone to queuing, and the fourth weight being the ratio of the number of historical registrations in a single sub-period prone to congestion corresponding to the target consultation period to the sum of the number of historical registrations in all corresponding sub-periods prone to congestion; Calculate the third weight of the target visit time period and the third weight product of the corresponding fourth weights, select a target third weight product that is less than a preset second product threshold from the third weight products, and select a target first weight product sum that is less than a preset first product sum threshold from the sum of the first weight products; The non-falling path corresponding to the sum of the first weight products of each target and whose estimated arrival time is in the congested sub-time period corresponding to the third weight product of the target is determined as the suitable navigation path within the hospital, and the suitable navigation path within the hospital is sent to the terminal of the target medical user.

[0065] Optionally, the device further includes a navigation sending module 16, which is specifically used to: When the target consultation period is not an easy-to-queue period, determine whether the adjacent consultation period before the target consultation period is an easy-to-queue period, and if so, determine the adjacent consultation period as the previous easy-to-queue period; Calculate the sum of the fourth weight products of the third weight of the previous easy-to-queue time period and the fourth weights of the corresponding easy-to-crowd sub-time periods. If the sum of the fourth weight products is greater than the preset second product sum threshold, calculate the time difference between the estimated arrival time of the non-easy-to-fall path corresponding to the sum of the first weight products of each target and the start time of the target consultation time period; The maximum time difference is selected from each time difference, and the non-falling path corresponding to the maximum time difference is determined as the in-hospital suitable navigation path corresponding to the target patient user and sent to the terminal of the target patient user.

[0066] Optionally, the region determination module 13 is specifically configured to: If the crowd type is a slow-walking type, then when the number of people queuing before the target patient exceeds the preset number threshold, determine the first area within the preset distance of the target doctor's office and the second area within the preset distance of the toilet on the same floor. The preset distance is the longest distance suitable for the target patient to walk; The first area, the second area and the waiting area of ​​the target clinic department are intersected to obtain a suitable waiting area corresponding to the target clinic user.

[0067] It should be noted that the smart guidance device provided in the above embodiment only uses the division of the above functional modules as an example when executing the smart guidance method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the smart guidance device provided in the above embodiment and the smart guidance method embodiment belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0068] An embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, an intelligent guidance method of the above embodiment is adopted.

[0069] Among them, the computer program can be stored in a computer-readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or certain middleware, etc. The computer-readable medium includes any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer-readable medium includes but is not limited to the above-mentioned components.

[0070] Among them, through this computer-readable storage medium, an intelligent guidance method of the above embodiment is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0071] An embodiment of the present application also discloses an electronic device, in which a computer program is stored in a computer-readable storage medium, and when the computer program is loaded and executed by a processor, the above-mentioned intelligent guidance method is adopted.

[0072] The electronic device may be a desktop computer, a laptop computer, a cloud server or other electronic device, and the electronic device includes but is not limited to a processor and a memory. For example, the electronic device may also include input and output devices, a network access device, and a bus.

[0073] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0074] Among them, the memory can be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device, or it can be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD) or a flash memory card (FC) equipped on the electronic device. Moreover, the memory can also be a combination of an internal storage unit and an external storage device of the electronic device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0075] Among them, through this electronic device, an intelligent guidance method of the above embodiment is stored in the memory of the electronic device, and is loaded and executed on the processor of the electronic device for easy use.

[0076] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A smart guidance method, characterized in that: The method comprises: When the target patient arrives at the hospital, the target patient time slot selected by the target patient when making an appointment is obtained, and the target patient is a user who has successfully made an appointment at the hospital; According to the population type of the target patient user and the target visit time period, determine the appropriate in-hospital navigation path corresponding to the target patient user and send it to the terminal of the target patient user, and the appropriate in-hospital navigation path is used to guide the target patient user to the corresponding target visit department in a targeted manner; When the target patient arrives at the target clinic department based on the appropriate navigation path within the hospital, a suitable waiting area corresponding to the target patient is determined from the waiting area of ​​the target clinic department according to the type of the population; A sign-in and number-taking reminder is sent to the terminal, and when the target patient successfully signs in and takes a number, a target doctor's office call reminder is sent to the terminal. The sign-in and number-taking reminder is used to remind the target patient to sign in, take a number and go to the suitable waiting area to wait. The target doctor's office is the office where the target doctor selected by the target patient when making an appointment is located.

2. The intelligent guidance method according to claim 1, characterized in that: The determining, according to the population type of the target patient-visiting user and the target patient-visiting time period, a suitable in-hospital navigation path corresponding to the target patient-visiting user and sending the path to the terminal of the target patient-visiting user specifically includes: Determine at least one to-be-selected in-hospital navigation route whose estimated arrival time is within the target consultation time period; When the target patient visitor is a slow-walking type, the number of historical fall accidents in each of the to-be-selected in-hospital navigation paths is determined, and in the order of the number of accidents from small to large, the to-be-selected in-hospital navigation paths with the first preset number are selected from the to-be-selected in-hospital navigation paths and determined as the path that is not prone to fall; Obtaining accident areas of historical fall accidents in each of the paths that are not prone to falling, counting the number of occurrences of each of the accident areas, and selecting accident areas with a preset second number from each of the accident areas in descending order of the number of occurrences as accident-prone areas of the corresponding paths that are not prone to falling; Calculate the first weight of each of the non-falling paths and the second weight of the corresponding accident-prone areas; determine the suitable in-hospital navigation path corresponding to the target patient from each of the non-falling paths based on the first weight and the corresponding second weight and send it to the terminal of the target patient; the first weight is the ratio of the number of accidents corresponding to each non-falling path to the sum of the number of accidents of all non-falling paths; the second weight is the ratio of the number of occurrences of a single accident-prone area corresponding to the non-falling path to the sum of the number of occurrences of all corresponding accident-prone areas.

3. The intelligent guidance method according to claim 2, characterized in that: The determining, based on the first weight and the corresponding second weight, from each of the non-falling paths, a suitable in-hospital navigation path corresponding to the target patient visiting user and sending the path to the terminal of the target patient visiting user specifically includes: Calculate the product of the first weight of each of the non-falling paths and the corresponding second weights to obtain a corresponding first weight product; Sum the first weight products corresponding to the single non-falling path to obtain the corresponding sum of the first weight products; The minimum sum of the first weighted products is selected from the sums of the first weighted products, and the low-fall path corresponding to the minimum sum of the first weighted products is determined as the suitable in-hospital navigation path corresponding to the target patient user and sent to the terminal of the target patient user.

4. The intelligent guidance method according to claim 2, characterized in that: The method further comprises: Calculate the second weight product of the first weight of the suitable navigation path within the hospital and the second weight of each corresponding accident-prone area; Selecting a target second weighted product greater than a preset first product threshold from each of the second weighted products, and determining an accident-prone area corresponding to each of the target second weighted products as a warning accident area; When the target patient arrives at each of the warning accident areas according to the suitable navigation path in the hospital, a fall warning message is sent to the terminal.

5. The intelligent guidance method according to claim 2, characterized in that: The determining, based on the first weight and the corresponding second weight, from each of the non-falling paths, a suitable in-hospital navigation path corresponding to the target patient visiting user and sending the path to the terminal of the target patient visiting user specifically includes: Calculate the product of the first weight of each of the non-falling paths and the corresponding second weights to obtain the corresponding first weight product, and sum the first weight products corresponding to a single non-falling path to obtain the sum of the corresponding first weight products; Obtain the number of appointments corresponding to the target doctor in each consultation period on that day, and select the third consultation period from each consultation period in descending order of the number of appointments as the easy-to-queue period; Counting the number of historical numbers taken by the target doctor in each sub-period within a single easy-to-queue period, and selecting a sub-period with a preset fourth number from each of the sub-periods in descending order of the number of historical numbers taken as the easily congested sub-period of the corresponding easy-to-queue period; When the target consultation period is a period prone to queuing, the third weight of the target consultation period and the fourth weight of each corresponding sub-period prone to congestion are calculated, wherein the third weight is the ratio of the number of registrations in the target consultation period to the sum of the number of registrations in all periods prone to queuing, and the fourth weight is the ratio of the number of historical registrations in a single sub-period prone to congestion corresponding to the target consultation period to the sum of the number of historical registrations in all corresponding sub-periods prone to congestion; Calculate the third weight product of the target visit time period and the corresponding fourth weights, select a target third weight product that is less than a preset second product threshold from the third weight products, and select a target first weight product sum that is less than a preset first product sum threshold from the sum of the first weight products; The non-falling path corresponding to the sum of the first weight products of each target and whose estimated arrival time is in the congested sub-time period corresponding to the third weight product of the target is determined as a suitable navigation path within the hospital, and the suitable navigation path within the hospital is sent to the terminal of the target medical user.

6. The intelligent guidance method according to claim 5, characterized in that: The method further comprises: When the target consultation time period is not an easy-to-queue time period, determining whether an adjacent consultation time period before the target consultation time period is an easy-to-queue time period, and if so, determining the adjacent consultation time period as the previous easy-to-queue time period; Calculate the sum of the fourth weight products of the third weight of the previous easy-to-queue time period and the fourth weights of the corresponding easy-to-crowd sub-time periods, and if the sum of the fourth weight products is greater than the preset second product sum threshold, calculate the time difference between the estimated arrival time of the non-easy-to-fall path corresponding to the sum of the first weight products of each target and the start time of the target consultation time period; The maximum time difference is selected from each of the time differences, and the non-falling path corresponding to the maximum time difference is determined as the suitable in-hospital navigation path corresponding to the target patient user and sent to the terminal of the target patient user.

7. The intelligent guidance method according to claim 1, characterized in that: Determining a suitable waiting area corresponding to the target medical user from the waiting area of ​​the target medical department according to the type of the population specifically includes: If the crowd type is a slow-walking type, then when the number of people queuing before the target patient exceeds a preset threshold, determine a first area within a preset distance from the target doctor's office and a second area within a preset distance from the toilet on the same floor, where the preset distance is the longest distance suitable for the target patient to walk; The first area, the second area and the waiting area of ​​the target medical department are intersected to obtain a suitable waiting area corresponding to the target medical user.

8. A smart guidance device, characterized in that: include: An information acquisition module (11) is used to acquire the target consultation time period selected by the target consultation user when making an appointment when the target consultation user arrives at the hospital, wherein the target consultation user is a user who has successfully made an appointment at the hospital; A path determination module (12) is used to determine, according to the population type of the target patient user and the target visit time period, an appropriate in-hospital navigation path corresponding to the target patient user and send the path to the terminal of the target patient user, wherein the appropriate in-hospital navigation path is used to specifically guide the target patient user to the corresponding target visit department; An area determination module (13) is used to determine a suitable waiting area corresponding to the target patient from the waiting area of ​​the target patient department according to the type of the population when the target patient arrives at the target patient department based on the suitable navigation path within the hospital; The number calling reminder module (14) is used to send a sign-in number taking reminder to the terminal, and when the target patient successfully signs in and takes a number, send a call number reminder of the target doctor's office to the terminal, the sign-in number taking reminder is used to remind the target patient to sign in, take a number and go to the suitable waiting area to wait, and the target doctor's office is the office where the target doctor selected by the target patient when making an appointment is located.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is loaded and executed by a processor, the method according to any one of claims 1 to 7 is adopted.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor loads and executes the computer program, the method according to any one of claims 1 to 7 is adopted.

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