CN114739413A - Hospital indoor navigation method based on artificial intelligence and related equipment - Google Patents
Hospital indoor navigation method based on artificial intelligence and related equipment Download PDFInfo
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Abstract
The application provides a hospital indoor navigation method, a hospital indoor navigation device, electronic equipment and a storage medium based on artificial intelligence, wherein the hospital indoor navigation method based on artificial intelligence comprises the following steps: acquiring all passable paths in a hospital range; when a navigation request is received, confirming a path to be planned based on the real-time position of the patient and a preset position point; calculating the passing distance of the passable path according to the actual distance of the passable path and the historical passing time; planning a path based on the path to be planned and the passing distance to obtain a planned path; generating a virtual arrow at a mobile phone terminal based on the planned path and the 3D model of the hospital to obtain a navigation result; and collecting the actual passing time of each passing path in the planned path to update the passing distance of the passable path for the next path planning. The method and the device comprehensively consider two aspects of traffic convenience and traffic distance to obtain an accurate planned path, meanwhile, three-dimensional navigation is achieved by means of the 3D model, and accuracy of indoor navigation is improved.
Description
Technical Field
The application relates to the technical field of artificial intelligence, in particular to a hospital indoor navigation method and device based on artificial intelligence, electronic equipment and a storage medium.
Background
When a patient is in a doctor, and the patient or a family member is in urgent need of examination or treatment, the patient or the family member cannot quickly and accurately find the department or the imaging room for examination and examination.
Usually, path planning is performed by calculating actual distances between different position points, and two-dimensional navigation is realized in a two-dimensional plane map of a hospital, however, the passing convenience of the planned path cannot be guaranteed in this way, and it is difficult for a patient to accurately identify the corresponding relationship between the two-dimensional navigation and the indoor actual position, and further the accuracy of indoor navigation is low.
Disclosure of Invention
In view of the above, there is a need to provide an artificial intelligence based hospital indoor navigation method and related devices to solve the technical problem of how to improve the accuracy of indoor navigation, wherein the related devices include an artificial intelligence based hospital indoor navigation apparatus, an electronic device and a storage medium.
The hospital indoor navigation method based on artificial intelligence comprises the following steps:
acquiring all position points and path nodes of each floor plane in a hospital, wherein the path nodes comprise path inflection points and path bifurcation points, and the position points comprise positions of each department and a landing entrance in the hospital;
judging whether any two path nodes can pass through, if so, directly connecting the two path nodes, and traversing all the path nodes to obtain a passable path of each floor;
when a navigation request is received, acquiring the real-time position of a patient according to a Bluetooth sensor, and confirming a path to be planned based on the real-time position and a preset position point, wherein the path to be planned comprises a target floor, a path starting point and a path terminal point;
calculating the passing distance of all passable paths in the target floor according to the actual distance of the passable paths and the historical passing time;
performing path planning on the path to be planned based on the passing distance of the passable path to obtain a planned path;
acquiring a 3D model of the target floor, and generating a virtual arrow at an intelligent terminal based on the planned path and the 3D model of the target floor to acquire a navigation result;
and acquiring the actual passing time of each passing path in the planned path to update the passing distance of the passable path, and using the actual passing time for the path planning of the next hospital indoor navigation.
In some embodiments, the acquiring a real-time position of the patient according to the bluetooth sensor and confirming the path to be planned based on the real-time position and the preset position point includes:
judging whether the floors of the real-time position and the preset position point are the same or not;
if the real-time position is the same as the preset position, taking the floor where the real-time position is located, the real-time position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a route to be planned;
if the real-time positions are different, acquiring a stair opening with the shortest distance to the real-time position as a target position point, and respectively taking the floor where the real-time position is located, the real-time position and the target position point as a target floor, a route starting point and a route terminal point to form a first path to be planned; and acquiring the corresponding coordinate position of the target position point in the floor where the preset position point is located, and taking the floor where the preset position point is located, the corresponding coordinate position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a second path to be planned.
In some embodiments, said calculating the transit distances for all traversable paths in the target floor as a function of actual distances and historical transit times for the traversable paths comprises:
acquiring all passable paths in the target floor;
calculating the average value of all historical transit time of the passable paths to obtain the average transit time of each passable path;
calculating the passing convenience degree of each passable path based on the average passing time and the actual distance, wherein the passing convenience degree meets the relation:
wherein l1-2Is the actual distance of traversable path 1-2, t1-2The average transit time of the traversable paths 1-2,
the maximum value of the ratio of the actual distance of the passable paths to the average passing time in the target floor, i represents the actual passing distance of all the passable paths, t represents the average passing time of all the passable paths, and alpha1-2The passing convenience of the passable path 1-2 is in a value range of [0, 1%]；
Calculating a passing distance of each passable path based on the passing convenience and the actual distance, wherein the passing distance satisfies the relation:
L1-2＝(1-α1-2)×l1-2
wherein l1-2Is the actual distance, alpha, of the traversable path 1-21-2For passing convenience of passable routes, L1-2Is the passing distance of the passable path 1-2.
In some embodiments, the path planning on the path to be planned based on the passing distance of the passable path to obtain a planned path includes:
a1, obtaining a path node closest to the path starting point as a first target path node;
a2, taking a first target path node as a starting point, acquiring all passable paths connected with the first target path node in target floors of the path to be planned to form a first passable path set;
a3, calculating the estimated cost of each passable path in the first passable path set according to a preset estimated cost model;
a4, selecting a passable path corresponding to the minimum estimated cost in the first passable path set as a first target path, and using a path node on the first target path as a second target path node;
a5, judging whether a connection between the second target path node and the path end point is a passable path to obtain a planning signal, wherein the planning signal comprises termination and continuation; if the path is a passable path, the planning signal is terminated, and the path starting point, the path end point and all target path nodes of the path to be planned are connected to obtain a planned path; if the route is not a passable route, the planning signal is continued, and the steps A2 to A4 are repeatedly executed by taking the second target route node as a starting point until the final planned route is obtained when the planning signal is terminated.
In some embodiments, the preset estimated cost model satisfies the relation:
wherein the content of the first and second substances,
is a passable path n1-n*The distance of the passage of (a) is,
for the passable path n1-n*Middle path node n*(x) coordinate position of (c)2，y2) For the path end point of the path to be planned, f (n)1-n*) For the passable path n1-n*The estimated cost of (2).
In some embodiments, the obtaining the 3D model of the target floor and generating a virtual arrow at the mobile phone terminal based on the planned path to obtain the navigation result includes:
establishing a live-action 3D model of each floor of the hospital according to indoor scanning equipment;
acquiring position information of a patient in real time according to a Bluetooth sensor, mapping the position information to a 3D model of a target floor, and displaying the 3D model of the target floor on an intelligent terminal;
and generating virtual arrows on the intelligent terminal based on the position information and the planned path of the patient to obtain a navigation result, wherein the virtual arrows comprise arrows indicating directions such as forward movement, left turning and right turning.
In some embodiments, the collecting the actual transit time of each of the planned routes to update the transit distance of the passable route includes:
acquiring the actual passing time of the patient through each passable path in the planned path;
updating the average passing time of each passable path based on the actual passing time, wherein the calculation formula of the updating process is as follows:
wherein, t1-2To update the average transit time of the traversable paths 1-2 before,
for the real transit time of a patient through the navigable path 1-2 acquired in real time,
updated average transit time for the traversable path 1-2;
updating a transit distance of the traversable path based on the updated average transit time.
The embodiment of the present application still provides an indoor navigation head of hospital based on artificial intelligence, the device includes:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring all position points in the hospital and path nodes of each floor plane, the path nodes comprise path inflection points and path bifurcation points, and the position points comprise positions of each department and each landing in the hospital;
the traversing unit is used for judging whether any two path nodes can pass through or not, if so, the two path nodes are directly connected, and all path nodes are traversed to obtain a passable path of each floor;
the system comprises a confirming unit, a processing unit and a processing unit, wherein the confirming unit is used for acquiring the real-time position of a patient according to a Bluetooth sensor when a navigation request is received, and confirming a path to be planned based on the real-time position and a preset position point, and the path to be planned comprises a target floor, a path starting point and a path terminal point;
the calculation unit is used for calculating the passing distance of all passable paths in the target floor according to the actual distance and the historical passing time of the passable paths;
the path planning unit is used for carrying out path planning on the path to be planned based on the passing distance of the passable path to obtain a planned path;
the navigation unit is used for acquiring the 3D model of the target floor and generating a virtual arrow at the intelligent terminal based on the planned path and the 3D model of the target floor to acquire a navigation result;
and the updating unit is used for acquiring the actual passing time of each passing path in the planned path to update the passing distance of the passable path, and is used for path planning of next hospital indoor navigation.
An embodiment of the present application further provides an electronic device, where the electronic device includes:
a memory storing at least one instruction;
and the processor executes the instructions stored in the memory to realize the artificial intelligence based hospital indoor navigation method.
The embodiment of the present application further provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the artificial intelligence based hospital indoor navigation method.
In conclusion, the passing convenience of all the passable paths in each floor can be obtained by collecting the passing time of the patient passing the passable paths, the two aspects of the passing convenience and the passing distance are comprehensively considered in the path planning process to obtain an accurate planned path, meanwhile, three-dimensional accurate navigation is realized by means of the 3D model, and the accuracy of indoor navigation is improved.
Drawings
Fig. 1 is a flow chart of a preferred embodiment of an artificial intelligence based hospital room navigation method to which the present application relates.
Fig. 2 is a functional block diagram of a preferred embodiment of an artificial intelligence based hospital room navigation device to which the present application relates.
Fig. 3 is a schematic structural diagram of an electronic device according to a preferred embodiment of the artificial intelligence based hospital room navigation method.
Detailed Description
For a clearer understanding of the objects, features and advantages of the present application, reference will now be made in detail to the present application with reference to the accompanying drawings and specific examples. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict. In the following description, numerous specific details are set forth to provide a thorough understanding of the present application, and the described embodiments are merely a subset of the embodiments of the present application and are not intended to be a complete embodiment.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The embodiment of the Application provides an artificial intelligence based hospital indoor navigation method, which can be applied to one or more electronic devices, wherein the electronic devices are devices capable of automatically performing numerical calculation and/or information processing according to preset or stored instructions, and hardware of the electronic devices includes but is not limited to a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device and the like.
The electronic device may be any electronic product capable of performing human-computer interaction with a client, for example, a Personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game machine, an Internet Protocol Television (IPTV), an intelligent wearable device, and the like.
The electronic device may also include a network device and/or a client device. Wherein the network device includes, but is not limited to, a single network server, a server group consisting of a plurality of network servers, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network servers.
The Network where the electronic device is located includes, but is not limited to, the internet, a wide area Network, a metropolitan area Network, a local area Network, a Virtual Private Network (VPN), and the like.
Fig. 1 is a flow chart of a preferred embodiment of the method for indoor navigation of a hospital based on artificial intelligence according to the present application. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs.
And S10, acquiring all position points in the hospital and path nodes of each floor plane, wherein the path nodes comprise path inflection points and path bifurcation points, and the position points comprise positions of each department and each landing in the hospital.
In an optional embodiment, a floor plan of each floor in a hospital is obtained, and path nodes are selected from the floor plan of each floor, wherein the path nodes comprise all path inflection points and path bifurcation points in the floor plan; each path node is assigned with a unique ID, which may be a number or a letter, and the application is not limited.
In this alternative embodiment, all location points within the hospital range are obtained, where the location points include location information of all departments and stairways, and the location information includes the floor where the location points are located and coordinate locations in a floor plan. Illustratively, the position information of the CT department is {2, (x, y) }, which indicates that the coordinate position of the CT department in the 2-floor plan is (x, y).
And S11, judging whether any two path nodes can pass through, if so, directly connecting the two path nodes, and traversing all the path nodes to obtain a passable path of each floor.
In an optional embodiment, multiple path nodes are included in the same floor plan, whether any two path nodes can pass through is judged, if yes, the two nodes are directly connected to form a passable path, all path nodes in the same floor plan are traversed to obtain all passable paths in one floor, and each passable path is a straight line segment.
In this alternative embodiment, the traversable path for each floor within the hospital domain can be obtained by traversing all path nodes within each floor plan in the same manner.
Therefore, the passable path of each floor can be obtained, and a data basis is provided for subsequent path planning.
And S12, when the navigation request is received, acquiring the real-time position of the patient according to the Bluetooth sensor, and confirming a path to be planned based on the real-time position and a preset position point, wherein the path to be planned comprises a target floor, a path starting point and a path terminal point.
In an optional embodiment, when a patient has a navigation demand, a preset position point is input at an intelligent terminal and a navigation request is sent, at this time, a real-time position of the patient is acquired by means of a bluetooth sensor pre-deployed in a hospital, the real-time position includes a floor where the patient is located and a coordinate position in a floor plan, the intelligent terminal can be a mobile device such as a smart phone or a smart bracelet, and the preset position point is a department where the patient wants to arrive.
In this optional embodiment, the acquiring a real-time position of the patient according to the bluetooth sensor, and determining the path to be planned based on the real-time position and the preset position point includes:
judging whether the floors of the real-time position and the preset position point are the same or not;
if the real-time position is the same as the preset position, taking the floor where the real-time position is located, the real-time position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a route to be planned;
if the real-time positions are different from each other, acquiring a stair opening with the shortest distance to the real-time position as a target position point, and taking the floor where the real-time position is located, the real-time position and the target position point as a target floor, a route starting point and a route terminal point respectively to form a first path to be planned; and acquiring the corresponding coordinate position of the target position point in the floor where the preset position point is located, and taking the floor where the preset position point is located, the corresponding coordinate position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a second path to be planned.
In this optional embodiment, in each path to be planned, the path starting point and the path ending point are both located in the same target floor, and the path planning results of all paths to be planned are combined to form a complete path from the initial position to the preset position point.
Illustratively, assume a patient real-time position of {2, (x)1，y1) The preset position point is {2, (x)2，y2) The corresponding path to be planned is {2, (x)1，y1)→(x2，y2) I.e. a starting point (x) is indicated on floor 21，y1) End point is (x)2，y2) The path of (2).
Illustratively, assume a patient real-time position of {2, (x)1，y1) The preset position point is {5 (x)2，y2) Firstly, the distance coordinate position (x) in the floor 2 is obtained1，y1) The nearest position point of the stair opening is taken as a target position point (x)3，y3) Then the first path to be planned is {2, (x)1，y1)→(x3，y3) Means to plan a real-time position (x) from the patient on floor 21，y1) To the stair opening (x)3，y3) A path of (a); further obtain a target position point (x)3，y3) Corresponding coordinate position within floor 5
The second path to be planned is
I.e. to indicate that a starting point is planned on the floor 5
End point is (x)2，y2) The path of (2).
In this way, all the paths to be planned can be obtained in response to the patient's navigation needs.
S13, calculating the passing distance of all passable paths in the target floor according to the actual distance of the passable paths and the historical passing time.
In an alternative embodiment, said calculating the transit distances for all traversable paths in said target floor from the actual distances and the historical transit times of the traversable paths comprises:
acquiring all passable paths in the target floor;
calculating the average value of all historical transit time of the passable paths to obtain the average transit time of each passable path;
calculating the passing convenience of each passable path based on the average passing time and the actual distance;
and calculating the passing distance of each passable path based on the passing convenience and the actual distance.
In an optional embodiment, all passable paths in the target floor corresponding to the path to be planned are obtained, and an ID is allocated to each passable path according to different path nodes, where for example, if IDs of two path nodes connected by one passable path are 1 and 2 respectively, the path ID of the passable path is 1-2.
In this optional embodiment, the average value of the time spent by the patient to pass through the passable paths in the historical time is further counted to obtain the average passing time of each passable path, and the passing convenience of each passable path is calculated based on the average passing time of each passable path, taking passable path 1-2 as an example, and the passing convenience satisfies the following relation:
wherein l1-2Actual distance, t, for traversable path 1-21-2The average transit time of the traversable paths 1-2,
the maximum value of the ratio of the actual distance of the passable paths to the average passing time in the target floor is represented by l, the actual passing distance of all the passable paths is represented by t, and the average passing time of all the passable paths is represented by t; alpha is alpha1-2The value range is [0,1 ] for the passing convenience of the passable path 1-2]The larger the value is, the more convenient the passable path 1-2 is to pass through.
In this optional embodiment, the greater the passing convenience of the passable path is, the shorter the time taken for the patient to pass through the passable path is, in order to preferentially select the passable path with the greater passing convenience in the path planning process, the passing distance of each passable path in the target floor corresponding to the path to be planned is calculated by integrating the passing convenience and the actual distance, taking passable paths 1-2 as an example, and the passing distance of the passable path satisfies the relation:
L1-2＝(1-α1-2)×l1-2
wherein l1-2Is the actual distance, alpha, of the traversable path 1-21-2For passing convenience of passable routes, L1-2Is the passing distance of the passable path 1-2. When the actual distances of the passable paths are the same, the larger the passing convenience degree is, the smaller the corresponding passing distance is.
Therefore, the passing distance of each passable path is obtained by comprehensively considering the actual distance and the passing convenience of the passable path, so that the passing actual distance and the passing convenience are considered in a path planning result.
And S14, planning the path of the path to be planned based on the passing distance of the passable path to obtain a planned path.
In an optional embodiment, a path to be planned comprises a target floor, a path starting point and a path ending point, the passing distance of each passable path in the target floor is obtained, and a planned path from the path starting point to the path ending point is planned in the target floor based on the passing distance of the passable path and a path planning algorithm. It should be noted that, if there are multiple paths to be planned, path planning is performed on each path to be planned to obtain a planned path, and the path planning processes of the paths to be planned are independent of each other.
In this alternative embodiment, with path to be planned { N, (x)1，y1)→(x2，y2) Explaining the path planning process in detail for an example, wherein N is a target floor of the path to be planned, (x)1，y1)，(x2，y2) Respectively a path starting point and a path end point of the path to be planned. The step of planning the path to be planned based on the passing distance of the passable path to obtain a planned path comprises the following steps:
a1, obtaining and routing start point (x)1，y1) Taking the path node with the closest distance as a first target path node;
a2, taking a first target path node as a starting point, acquiring all passable paths connected with the first target path node in a target floor N to form a first passable path set;
a3, calculating an estimated cost of each path in the first passable path set according to a preset estimated cost model, where the estimated cost satisfies the relation:
wherein the content of the first and second substances,
is a passable path n1-n*The distance of the passage of (a) is,
for the passable path n1-n*Middle path node n*(x) coordinate position of (c)2，y2) For the path end point of the path to be planned, f (n)1-n*) For the passable path n1-n*The estimated cost of (2);
a4, selecting a passable path corresponding to the minimum estimated cost in the first passable path set as a first target path, and using a path node on the first target path as a second target path node;
a5, judging whether a connection line between the second target path node and the path end point is a passable path or not to obtain a planning signal, wherein the planning signal comprises a termination and a continuation; if the path is a passable path, the planning signal is terminated, and the path starting point, the path end point and all target path nodes of the path to be planned are connected to obtain a planned path; if the route is not a passable route, the planning signal is continued, and the steps A2 to A4 are repeatedly executed by taking the second target route node as a starting point until the final planned route is obtained when the planning signal is terminated.
Therefore, the planning paths of all paths to be planned are obtained, and the actual passing distance and the passing convenience of the planning paths are comprehensively considered.
And S15, acquiring the 3D model of the target floor, and generating a virtual arrow at the intelligent terminal based on the planned path to acquire a navigation result.
In an optional embodiment, the obtaining the 3D model of the target floor and generating a virtual arrow at the mobile phone terminal based on the planned path to obtain the navigation result includes:
establishing a live-action 3D model of each floor of the hospital according to indoor scanning equipment;
acquiring position information of a patient in real time according to a Bluetooth sensor, mapping the position information to a 3D model of a target floor, and displaying the 3D model of the target floor on an intelligent terminal;
and generating virtual arrows on the intelligent terminal based on the position information and the planned path of the patient to obtain a navigation result, wherein the virtual arrows comprise arrows indicating directions such as forward movement, left turning and right turning.
In this optional embodiment, the constructing a live-action 3D model of each floor of the hospital according to the indoor scanning device includes: the method comprises the steps of collecting depth image data frames and panoramic images of each floor room of a hospital by using indoor scanning equipment integrating an RGB-D sensor and a panoramic camera, so as to obtain high-precision indoor three-dimensional point clouds and construct a live-action 3D model of each floor room of the hospital, wherein the RGB-D sensor can collect depth information of each pixel point in an image.
So, with the help of the 3D model of target floor, the patient can accurately judge self position, improves the accuracy of navigation to improve patient's experience of seeking medical advice.
And S16, collecting the actual passing time of each passing path in the planned path to update the passing distance of the passable path, and using the actual passing time for the path planning of the next hospital indoor navigation.
In an optional embodiment, the collecting the actual passing time of each passing route in the planned route to update the passing distance of the passable route includes:
acquiring the actual passing time of the patient through each passable path in the planned path;
updating the average passing time of each passable path based on the actual passing time;
updating a transit distance of the traversable path based on the updated average transit time.
In an optional embodiment, the position information of the patient is collected in real time based on a bluetooth sensor deployed in a hospital, the actual passing time of each passable path in the planned path is calculated according to the time when the patient reaches the path node, and the average passing time of each passable path is updated based on the actual passing time, taking passable paths 1-2 as an example, the calculation formula of the updating process is as follows:
wherein, t1-2To update the average transit time of the traversable paths 1-2 before,
for the real transit time of a patient through the navigable path 1-2 acquired in real time,
is the updated average transit time of the traversable path 1-2.
In this optional embodiment, the passing distances of all passable paths in the target floor are further updated based on the updated average passing time, and the updated passable distances are used in path planning of next hospital indoor navigation, so as to ensure that the path planning result has better passing convenience.
Therefore, after each route planning, the actual time of the patient passing through the passable route is acquired, and the passing distance of the passable route is updated in real time, so that the passing convenience of the route planning result is better.
Referring to fig. 2, fig. 2 is a functional block diagram of a preferred embodiment of the artificial intelligence based hospital room navigation device according to the present application. The artificial intelligence based hospital room navigation apparatus 11 includes an acquisition unit 110, a traversal unit 111, a confirmation unit 112, a calculation unit 113, a path planning unit 114, a navigation unit 115, and an update unit 116. A module/unit as referred to herein is a series of computer readable instruction segments capable of being executed by the processor 13 and performing a fixed function, and is stored in the memory 12. In the present embodiment, the functions of the modules/units will be described in detail in the following embodiments.
In an optional embodiment, the obtaining unit 110 is configured to obtain all location points in the hospital and path nodes of each floor plane, where the path nodes include path inflection points and path branching points, and the location points include locations of each department and each landing entrance in the hospital.
In an optional embodiment, a floor plan of each floor in a hospital is obtained, and path nodes are selected from the floor plan of each floor, wherein the path nodes comprise all path inflection points and path bifurcation points in the floor plan; each path node is assigned with a unique ID, which may be a number or a letter, and the application is not limited.
In this alternative embodiment, all location points within the hospital range are obtained, where the location points include location information of all departments and stairways, and the location information includes the floor where the location points are located and coordinate locations in a floor plan. Illustratively, the position information of the CT department is {2, (x, y) }, which indicates that the coordinate position of the CT department in the 2-floor plan is (x, y).
In an optional embodiment, the traversing unit 111 is configured to determine whether any two of the path nodes can pass through, and if so, directly connect the two path nodes, and traverse all the path nodes to obtain a passable path for each floor.
In an optional embodiment, multiple path nodes are included in the same floor plan, whether any two path nodes can pass through is judged, if yes, the two nodes are directly connected to form a passable path, all path nodes in the same floor plan are traversed to obtain all passable paths in one floor, and each passable path is a straight line segment.
In this alternative embodiment, the traversable path for each floor within the hospital may be obtained by traversing all path nodes within each floor plan in the same manner.
In an optional embodiment, the confirming unit 112 is configured to, when receiving the navigation request, obtain the real-time position of the patient according to the bluetooth sensor, and confirm a path to be planned based on the real-time position and the preset position point, where the path to be planned includes a target floor, a path starting point, and a path ending point.
In an optional embodiment, when a patient has a navigation demand, a preset position point is input at an intelligent terminal and a navigation request is sent, at this time, a real-time position of the patient is acquired by means of a bluetooth sensor pre-deployed in a hospital, the real-time position includes a floor where the patient is located and a coordinate position in a floor plan, the intelligent terminal can be a mobile device such as a smart phone or a smart bracelet, and the preset position point is a department where the patient wants to arrive.
In this optional embodiment, the acquiring a real-time position of the patient according to the bluetooth sensor, and confirming the path to be planned based on the real-time position and the preset position point includes:
judging whether the floors of the real-time position and the preset position point are the same or not;
if the real-time position is the same as the preset position, taking the floor where the real-time position is located, the real-time position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a route to be planned;
if the real-time positions are different from each other, acquiring a stair opening with the shortest distance to the real-time position as a target position point, and taking the floor where the real-time position is located, the real-time position and the target position point as a target floor, a route starting point and a route terminal point respectively to form a first path to be planned; and acquiring the corresponding coordinate position of the target position point in the floor where the preset position point is located, and taking the floor where the preset position point is located, the corresponding coordinate position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a second path to be planned.
In this optional embodiment, in each path to be planned, the path starting point and the path ending point are both on the same target floor, and the path planning results of all paths to be planned are combined to form a complete path from the initial position to the preset position point.
Illustratively, assume a patient real-time position of {2, (x)1，y1) The preset position point is {2, (x)2，y2) The corresponding path to be planned is {2, (x)1，y1)→(x2，y2) I.e. a starting point (x) is indicated on floor 21，y1) End point is (x)2，y2) The path of (c).
Illustratively, assume a patient real-time position of {2, (x)1，y1) The preset position point is {5 (x)2，y2) Firstly, the distance coordinate position (x) in the floor 2 is obtained1，y1) The nearest position point of the stair opening is taken as a target position point (x)3，y3) Then the first path to be planned is {2, (x)1，y1)→(x3，y3) Means to plan a real-time position (x) from the patient on floor 21，y1) To the stair opening (x)3，y3) A path of (a); further obtaining a target location point (x)3，y3) Corresponding coordinate position within floor 5
The second path to be planned is
I.e. to indicate that a starting point is planned on the floor 5
End point is (x)2，y2) The path of (2).
In an alternative embodiment the calculation unit 113 is arranged to calculate the traffic distances for all traversable paths in the destination floor from the actual distances and the historical traffic times of the traversable paths.
In an alternative embodiment, the calculating the passing distances of all the passable paths in the target floor according to the actual distances of the passable paths and the historical passing time comprises:
acquiring all passable paths in the target floor;
calculating the average value of all historical transit time of the passable paths to obtain the average transit time of each passable path;
calculating the passing convenience of each passable path based on the average passing time and the actual distance;
and calculating the passing distance of each passable path based on the passing convenience degree and the actual distance.
In an optional embodiment, all passable paths in the target floor corresponding to the path to be planned are obtained, and an ID is allocated to each passable path according to different path nodes, where for example, if IDs of two path nodes connected by one passable path are 1 and 2 respectively, the path ID of the passable path is 1-2.
In this optional embodiment, the average value of the time spent by the patient to pass through the passable path in the historical time is further counted to obtain the average passing time of each passable path, and the passing convenience degree of each passable path is calculated based on the average passing time of each passable path, taking passable paths 1-2 as an example, and the passing convenience degree satisfies the following relation:
wherein l1-2Is the actual distance of traversable path 1-2, t1-2The average transit time of the traversable paths 1-2,
the maximum value of the ratio of the actual distance of the passable paths to the average passing time in the target floor is represented by l, the actual passing distance of all the passable paths is represented by t, and the average passing time of all the passable paths is represented by t; alpha is alpha1-2The value range is [0,1 ] for the passing convenience of the passable path 1-2]The larger the value, the more convenient the passable path 1-2 is to pass.
In this optional embodiment, the greater the passing convenience of the passable path is, the shorter the time taken for the patient to pass through the passable path is, in order to preferentially select the passable path with the greater passing convenience in the path planning process, the passing distance of each passable path in the target floor corresponding to the path to be planned is calculated by integrating the passing convenience and the actual distance, taking passable paths 1-2 as an example, and the passing distance of the passable path satisfies the relation:
L1-2＝(1-α1-2)×l1-2
wherein l1-2Is the actual distance, alpha, of the traversable path 1-21-2For passing convenience of passable routes, L1-2Is the passing distance of the passable path 1-2. When the actual distances of the passable paths are the same, the larger the passing convenience degree is, the smaller the corresponding passing distance is.
In an optional embodiment, the path planning unit 114 is configured to perform path planning on the path to be planned based on a passing distance of the passable path to obtain a planned path.
In an optional embodiment, a path to be planned comprises a target floor, a path starting point and a path ending point, the passing distance of each passable path in the target floor is obtained, and a planned path from the path starting point to the path ending point is planned in the target floor based on the passing distance of the passable path and a path planning algorithm. It should be noted that, if there are multiple paths to be planned, path planning is performed on each path to be planned to obtain a planned path, and the path planning processes of the paths to be planned are independent of each other.
In this alternative embodiment, with path to be planned { N, (x)1，y1)→(x2，y2) Explaining the path planning process in detail for an example, wherein N is a target floor of the path to be planned, (x)1，y1)，(x2，y2) Respectively a path starting point and a path end point of the path to be planned. The step of planning the path to be planned based on the passing distance of the passable path to obtain a planned path comprises the following steps:
a1, obtaining and routing start point (x)1，y1) Taking the path node closest to the target path node as a first target path node;
a2, taking a first target path node as a starting point, acquiring all passable paths connected with the first target path node in a target floor N to form a first passable path set;
a3, calculating an estimated cost of each path in the first passable path set according to a preset estimated cost model, where the estimated cost satisfies the relation:
wherein the content of the first and second substances,
is a passable path n1-n*The distance of the passage of (a) is,
for the passable path n1-n*Middle path node n*(x) coordinate position of (c)2，y2) For the path end point of the path to be planned, f (n)1-n*) For the passable path n1-n*The estimated cost of (2);
a4, selecting a passable path corresponding to the minimum estimated cost in the first passable path set as a first target path, and using a path node on the first target path as a second target path node;
a5, judging whether a connection line between the second target path node and the path end point is a passable path or not to obtain a planning signal, wherein the planning signal comprises a termination and a continuation; if the path is a passable path, the planning signal is terminated, and the path starting point, the path end point and all target path nodes of the path to be planned are connected to obtain a planned path; if the route is not a passable route, the planning signal is continued, and the steps A2 to A4 are repeatedly executed by taking the second target route node as a starting point until the final planned route is obtained when the planning signal is terminated.
In an alternative embodiment, the navigation unit 115 is configured to obtain a 3D model of the target floor, and generate a virtual arrow in the intelligent terminal based on the planned path and the 3D model of the target floor to obtain a navigation result.
In an optional embodiment, the obtaining the 3D model of the target floor and generating a virtual arrow at the mobile phone terminal based on the planned path to obtain the navigation result includes:
establishing a live-action 3D model of each floor of the hospital according to indoor scanning equipment;
acquiring position information of a patient in real time according to a Bluetooth sensor, mapping the position information to a 3D model of a target floor, and displaying the 3D model of the target floor on an intelligent terminal;
and generating virtual arrows on the intelligent terminal based on the position information and the planned path of the patient so as to obtain a navigation result, wherein the virtual arrows comprise arrows which indicate directions such as forward movement, left turning and right turning.
In this optional embodiment, the constructing a live-action 3D model of each floor of the hospital according to the indoor scanning device includes: the method comprises the steps of collecting depth image data frames and panoramic images of each floor room of a hospital by using indoor scanning equipment integrating an RGB-D sensor and a panoramic camera, so as to obtain high-precision indoor three-dimensional point clouds and construct a live-action 3D model of each floor room of the hospital, wherein the RGB-D sensor can collect depth information of each pixel point in an image.
In an alternative embodiment, the updating unit 116 collects the actual passing time of each passing path in the planned path to update the passing distance of the passable path for the path planning of the next hospital room navigation.
In an optional embodiment, the collecting the actual passing time of each passing route in the planned route to update the passing distance of the passable route includes:
acquiring the actual passing time of the patient through each passable path in the planned path;
updating the average passing time of each passable path based on the actual passing time;
updating a transit distance of the traversable path based on the updated average transit time.
In an optional embodiment, the position information of the patient is collected in real time based on a bluetooth sensor deployed in a hospital, the actual passing time of each passable path in the planned path is calculated according to the time when the patient reaches the path node, and the average passing time of each passable path is updated based on the actual passing time, taking passable paths 1-2 as an example, the calculation formula of the updating process is as follows:
wherein, t1-2To update the average transit time of the traversable paths 1-2 before,
for the real transit time of a patient through the navigable path 1-2 acquired in real time,
is the updated average transit time of the traversable path 1-2.
In this optional embodiment, the passing distances of all passable paths in the target floor are further updated based on the updated average passing time, and the updated passable distances are used in path planning of next hospital indoor navigation, so as to ensure that the path planning result has better passing convenience.
According to the technical scheme, the passing convenience of all the passable paths in each floor can be acquired by acquiring the passing time of the patient through the passable paths, the two aspects of the passing convenience and the passing distance are comprehensively considered in the path planning process to obtain an accurate planned path, three-dimensional accurate navigation is realized by means of the 3D model, and the accuracy of indoor navigation is improved.
Please refer to fig. 3, which is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. The electronic device 1 comprises a memory 12 and a processor 13. The memory 12 is used for storing computer readable instructions, and the processor 13 is used for executing the computer readable instructions stored in the memory to realize the artificial intelligence based hospital room navigation method in any one of the above embodiments.
In an alternative embodiment, the electronic device 1 further comprises a bus, a computer program stored in said memory 12 and executable on said processor 13, such as an artificial intelligence based hospital room navigation program.
Fig. 3 shows only the electronic device 1 with the memory 12 and the processor 13, and it will be understood by those skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or a combination of certain components, or a different arrangement of components.
In connection with fig. 1, the memory 12 in the electronic device 1 stores a plurality of computer-readable instructions to implement an artificial intelligence based hospital indoor navigation method, and the processor 13 can execute the plurality of instructions to implement:
acquiring all position points and path nodes of each floor plane in a hospital, wherein the path nodes comprise path inflection points and path bifurcation points, and the position points comprise positions of each department and a landing entrance in the hospital;
judging whether any two path nodes can pass through, if so, directly connecting the two path nodes, and traversing all the path nodes to obtain a passable path of each floor;
when a navigation request is received, acquiring the real-time position of a patient according to a Bluetooth sensor, and confirming a path to be planned based on the real-time position and a preset position point, wherein the path to be planned comprises a target floor, a path starting point and a path terminal point;
calculating the passing distance of all passable paths in the target floor according to the actual distance of the passable paths and the historical passing time;
performing path planning on the path to be planned based on the passing distance of the passable path to obtain a planned path;
acquiring a 3D model of the target floor, and generating a virtual arrow at an intelligent terminal based on the planned path and the 3D model of the target floor to acquire a navigation result;
and acquiring the actual passing time of each passing path in the planned path to update the passing distance of the passable path, and using the actual passing time for the path planning of the next hospital indoor navigation.
Specifically, the processor 13 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the instruction, which is not described herein again.
It will be understood by those skilled in the art that the schematic diagram is only an example of the electronic device 1, and does not constitute a limitation to the electronic device 1, the electronic device 1 may have a bus-type structure or a star-shaped structure, the electronic device 1 may further include more or less hardware or software than those shown in the figures, or different component arrangements, for example, the electronic device 1 may further include an input and output device, a network access device, etc.
It should be noted that the electronic device 1 is only an example, and other existing or future electronic products, such as those that may be adapted to the present application, should also be included in the scope of protection of the present application, and are included by reference.
The processor 13 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 13 is a Control Unit (Control Unit) of the electronic device 1, connects various components of the electronic device 1 by various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules stored in the memory 12 (for example, executing an artificial intelligence-based hospital room navigation program, etc.), and calling data stored in the memory 12.
The processor 13 executes an operating system of the electronic device 1 and various installed application programs. The processor 13 executes the application program to implement the steps of each of the above-described embodiments of artificial intelligence based hospital indoor navigation methods, such as the steps shown in fig. 1.
Illustratively, the computer program may be partitioned into one or more modules/units, which are stored in the memory 12 and executed by the processor 13 to accomplish the present application. The one or more modules/units may be a series of computer-readable instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the electronic device 1. For example, the computer program may be divided into an acquisition unit 110, a traversal unit 111, a confirmation unit 112, a calculation unit 113, a path planning unit 114, a navigation unit 115, an update unit 116.
The integrated unit implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a computer device, or a network device) or a processor to execute parts of the artificial intelligence based indoor navigation method for a hospital according to the embodiments of the present application.
The integrated modules/units of the electronic device 1 may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the processes in the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer-readable storage medium and executed by a processor, to implement the steps of the embodiments of the methods described above.
Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), random-access Memory and other Memory, etc.
Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a string of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, which is used for verifying the validity (anti-counterfeiting) of the information and generating a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus. The bus is arranged to enable connection communication between the memory 12 and at least one processor 13 or the like.
The present application further provides a computer-readable storage medium (not shown), in which computer-readable instructions are stored, and the computer-readable instructions are executed by a processor in an electronic device to implement the artificial intelligence based hospital indoor navigation method according to any of the above embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
Furthermore, it will be obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means stated in the description may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present application and not for limiting, and although the present application is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present application without departing from the spirit and scope of the technical solutions of the present application.
Claims (10)
1. An artificial intelligence based hospital indoor navigation method is characterized by comprising the following steps:
acquiring all position points and path nodes of each floor plane in a hospital, wherein the path nodes comprise path inflection points and path bifurcation points, and the position points comprise positions of each department and a landing entrance in the hospital;
judging whether any two path nodes can pass through, if so, directly connecting the two path nodes, and traversing all the path nodes to obtain a passable path of each floor;
when a navigation request is received, acquiring the real-time position of a patient according to a Bluetooth sensor, and confirming a path to be planned based on the real-time position and a preset position point, wherein the path to be planned comprises a target floor, a path starting point and a path terminal point;
calculating the passing distance of all passable paths in the target floor according to the actual distance of the passable paths and the historical passing time;
performing path planning on the path to be planned based on the passing distance of the passable path to obtain a planned path;
acquiring a 3D model of the target floor, and generating a virtual arrow at an intelligent terminal based on the planned path and the 3D model of the target floor to acquire a navigation result;
and acquiring the actual passing time of each passing path in the planned path to update the passing distance of the passable path, and using the actual passing time for the path planning of the next hospital indoor navigation.
2. The artificial intelligence based hospital room navigation method of claim 1, wherein said obtaining a real-time position of a patient according to a bluetooth sensor and confirming a path to be planned based on the real-time position and a preset position point comprises:
judging whether the floors of the real-time position and the preset position point are the same or not;
if the real-time position is the same as the preset position, taking the floor where the real-time position is located, the real-time position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a route to be planned;
if the real-time positions are different from each other, acquiring a stair opening with the shortest distance to the real-time position as a target position point, and taking the floor where the real-time position is located, the real-time position and the target position point as a target floor, a route starting point and a route terminal point respectively to form a first path to be planned; and acquiring the corresponding coordinate position of the target position point in the floor where the preset position point is located, and taking the floor where the preset position point is located, the corresponding coordinate position and the preset position point as a target floor, a route starting point and a route terminal point respectively to form a second path to be planned.
3. The artificial intelligence based hospital indoor navigation method according to claim 1, wherein said calculating the passing distances of all passable paths in the target floor according to the actual distances and the historical passing times of the passable paths comprises:
acquiring all passable paths in the target floor;
calculating the average value of all historical transit time of the passable paths to obtain the average transit time of each passable path;
calculating the passing convenience degree of each passable path based on the average passing time and the actual distance, wherein the passing convenience degree meets the relation:
wherein l1-2Is the actual distance of traversable path 1-2, t1-2The average transit time of the traversable paths 1-2,
the maximum value of the ratio of the actual distance of the passable paths to the average passing time in the target floor is represented by l, the actual passing distance of all the passable paths is represented by t, and the average passing time of all the passable paths is represented by t; alpha is alpha1-2The value range is [0,1 ] for the passing convenience of the passable path 1-2]；
Calculating a passing distance of each passable path based on the passing convenience and the actual distance, wherein the passing distance satisfies the relation:
L1-2＝(1-α1-2)×l1-2
wherein l1-2Is the actual distance, alpha, of the traversable path 1-21-2For passing convenience of passable routes, L1-2Is the passing distance of the passable path 1-2.
4. The artificial intelligence based hospital indoor navigation method of claim 1, wherein the path planning of the path to be planned based on the passing distance of the passable path to obtain a planned path comprises:
a1, obtaining a path node closest to the path starting point as a first target path node;
a2, taking a first target path node as a starting point, acquiring all passable paths connected with the first target path node in target floors of the path to be planned to form a first passable path set;
a3, calculating the estimated cost of each passable path in the first passable path set according to a preset estimated cost model;
a4, selecting a passable path corresponding to the minimum estimated cost in the first passable path set as a first target path, and using a path node on the first target path as a second target path node;
a5, judging whether a connection between the second target path node and the path end point is a passable path to obtain a planning signal, wherein the planning signal comprises termination and continuation; if the path is a passable path, the planning signal is terminated, and the path starting point, the path end point and all target path nodes of the path to be planned are connected to obtain a planned path; if the route is not a passable route, the planning signal is continued, and the steps A2 to A4 are repeatedly executed by taking the second target route node as a starting point until the planning signal is terminated, so that a final planned route is obtained.
5. The artificial intelligence based indoor hospital navigation method of claim 4, wherein the preset estimated cost model satisfies the relation:
wherein the content of the first and second substances,
is available forRow path n1-n*The distance of the passage of (a) is,
for the passable path n1-n*Middle path node n*(x) coordinate position of (c)2,y2) For the path end point of the path to be planned, f (n)1-n*) For the passable path n1-n*The estimated cost of (c).
6. The artificial intelligence based hospital indoor navigation method according to claim 1, wherein the obtaining of the 3D model of the target floor and the generating of the virtual arrow at the mobile phone terminal based on the planned path to obtain the navigation result comprises:
establishing a live-action 3D model of each floor of the hospital according to indoor scanning equipment;
the method comprises the steps that position information of a patient is collected in real time according to a Bluetooth sensor, the position information is mapped to a 3D model of a target floor, and the 3D model of the target floor is displayed on an intelligent terminal;
and generating virtual arrows on the intelligent terminal based on the position information and the planned path of the patient to obtain a navigation result, wherein the virtual arrows comprise arrows indicating directions such as forward movement, left turning and right turning.
7. The artificial intelligence based hospital indoor navigation method of claim 1, wherein the collecting actual transit times of each transit path in the planned path to update transit distances of the traversable paths comprises:
acquiring the actual passing time of the patient through each passable path in the planned path;
updating the average passing time of each passable path based on the actual passing time, wherein the calculation formula of the updating process is as follows:
wherein, t1-2To update the average transit time of the traversable paths 1-2 before,
for the real transit time of a patient through the navigable path 1-2 acquired in real time,
updated average transit time for the traversable path 1-2;
updating a transit distance of the traversable path based on the updated average transit time.
8. An artificial intelligence based indoor navigation device for a hospital, the device comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring all position points in the hospital and path nodes of each floor plane, the path nodes comprise path inflection points and path bifurcation points, and the position points comprise positions of each department and each landing in the hospital;
the traversing unit is used for judging whether any two path nodes can pass through or not, if so, the two path nodes are directly connected, and all path nodes are traversed to obtain a passable path of each floor;
the system comprises a confirming unit, a processing unit and a processing unit, wherein the confirming unit is used for acquiring the real-time position of a patient according to a Bluetooth sensor when a navigation request is received, and confirming a path to be planned based on the real-time position and a preset position point, and the path to be planned comprises a target floor, a path starting point and a path terminal point;
the calculation unit is used for calculating the passing distance of all passable paths in the target floor according to the actual distance and the historical passing time of the passable paths;
the path planning unit is used for planning the path to be planned based on the passing distance of the passable path to obtain a planned path;
the navigation unit is used for acquiring the 3D model of the target floor and generating a virtual arrow at the intelligent terminal based on the planned path and the 3D model of the target floor to acquire a navigation result;
and the updating unit is used for acquiring the actual passing time of each passing path in the planned path to update the passing distance of the passable path, and is used for path planning of next hospital indoor navigation.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing computer readable instructions; and
a processor executing computer readable instructions stored in the memory to implement the artificial intelligence based hospital room navigation method of any one of claims 1 to 7.
10. A computer-readable storage medium having computer-readable instructions stored thereon which, when executed by a processor, implement the artificial intelligence based hospital room navigation method according to any one of claims 1 to 7.
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| CN115640921A (en) * | 2022-10-12 | 2023-01-24 | 中南大学湘雅医院 | Method and system for planning transfer path of critical patient in hospital |
| CN116437517A (en) * | 2023-06-14 | 2023-07-14 | 永林电子股份有限公司 | Be applied to hospital department of hospitalizing's LED lamp intelligent regulation and control system |
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|---|---|---|---|---|
| CN115640921A (en) * | 2022-10-12 | 2023-01-24 | 中南大学湘雅医院 | Method and system for planning transfer path of critical patient in hospital |
| CN116437517A (en) * | 2023-06-14 | 2023-07-14 | 永林电子股份有限公司 | Be applied to hospital department of hospitalizing's LED lamp intelligent regulation and control system |
| CN116437517B (en) * | 2023-06-14 | 2023-08-22 | 永林电子股份有限公司 | Be applied to hospital department of hospitalizing's LED lamp intelligent regulation and control system |
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