CN112216144A - Big data line-moving planning analysis method based on hospital parking lot - Google Patents
Big data line-moving planning analysis method based on hospital parking lot Download PDFInfo
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- CN112216144A CN112216144A CN202011092609.8A CN202011092609A CN112216144A CN 112216144 A CN112216144 A CN 112216144A CN 202011092609 A CN202011092609 A CN 202011092609A CN 112216144 A CN112216144 A CN 112216144A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
- G08G1/148—Management of a network of parking areas
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
Abstract
The invention discloses a large data line planning analysis method based on a hospital parking lot, which is used for solving the problem that a user is inconvenient to park in a hospital due to the fact that the user cannot reasonably match a parking space according to a line value of the user and the large data of the hospital parking lot; the user inputs the name of the hospital, the patient information and the body part name through the mobile phone terminal and sends the name to the dynamic line planning module; the moving line planning module plans and analyzes the name of the hospital and the name of the body part to obtain a hospital parking space; according to the invention, the line-of-movement value of the user is obtained by analyzing the hospital data, the corresponding parking area is matched with the line-of-movement value, the parking space of the parking area is selected, the parking space picture is shot for the parking space through the unmanned aerial vehicle, and the parking value of the parking space is obtained by analyzing the picture, so that the corresponding parking space of the hospital parking lot is reasonably selected through the parking value, and the user can conveniently park.
Description
Technical Field
The invention relates to the technical field of hospital parking lot analysis, in particular to a large data line planning analysis method based on a hospital parking lot.
Background
With the development of social economy, a hospital parking lot can not meet the requirements in a certain specific time period, generally waits for hours to see a doctor for half an hour, and various waiting people in the hospital are anxious, so that the doctor-patient relationship is tense to a certain extent, and the roads around the hospital are also congested.
The existing big data analysis method for the hospital parking lot cannot reasonably match the parking space according to the line of action value of the user and by combining the big data of the hospital parking lot, so that the user is inconvenient to park in the hospital.
Disclosure of Invention
The invention aims to provide a large data line-moving planning analysis method based on a hospital parking lot, aiming at solving the problem that a user is inconvenient to park in a hospital due to the fact that the user cannot reasonably match a parking space according to a line-moving value of the user and the large data of the hospital parking lot; according to the invention, the line-of-movement value of the user is obtained by analyzing the hospital data, the corresponding parking area is matched with the line-of-movement value, the parking space of the parking area is selected, the parking space picture is shot for the parking space through the unmanned aerial vehicle, and the parking value of the parking space is obtained by analyzing the picture, so that the corresponding parking space of the hospital parking lot is reasonably selected through the parking value, and the user can conveniently park.
The purpose of the invention can be realized by the following technical scheme: a big data line-moving planning analysis method based on a hospital parking lot comprises the following steps:
s1: hospital data are collected through a data collection module and sent to a server;
s2: the user inputs the name of the hospital, the patient information and the body part name through the mobile phone terminal and sends the name to the dynamic line planning module; the dynamic line planning module plans and analyzes the name of the hospital and the name of the body part to obtain the parking space of the hospital, and the specific steps are as follows:
s21: hospital data corresponding to the hospital are stored in the server according to the name of the hospital; analyzing hospital data to obtain a dynamic line value DX of a user;
s22: matching the dynamic line value DX to a corresponding parking area, and marking the parking area as a selected parking area;
s23: acquiring a parking space of the selected parking area, and matching and calculating the parking space and a user to obtain a parking value of the parking space; selecting the parking space with the largest parking value as the hospital parking space of the user;
s3: and carrying out route planning on the positions of the parking spaces of the hospital and the positions of the users and generating parking route navigation.
Preferably, the hospital data includes hospital visit information and hospital parking lot information; the hospital visiting information comprises the name and the position of a hospital department, the registration of the rest non-visiting patients, the name of the body part treated by the hospital department and a case opened by a doctor of the hospital department for the patient; the case includes the name, age, payment amount of the patient and the required instrument for the patient examination; the hospital parking lot information comprises the position of a parking space, the number plate of a vehicle staying on the parking space and the starting time of vehicle parking; the patient information includes the patient's name, registered number, and age.
Preferably, the specific steps of analyzing the hospital data to obtain the action line value of the user in S21 are as follows:
s211: matching the body part name with the hospital visit information to obtain the name of the corresponding hospital department, obtaining the remaining registration of the hospital department without visiting the doctor, comparing the registered number with the remaining registration of the hospital department without visiting the doctor to obtain the queuing number of the patients and marking the queuing number as M1;
s212: setting the names corresponding to all body parts to correspond to a preset value, matching the input body part names with all the body parts to obtain corresponding preset values, and marking the preset values as M2;
s213: the age of the patient was labeled M3; the number of patients with illness is labeled M4; normalizing the queuing number, the preset value, the age and the sick times of the patients and taking the numerical values;
s214: using formulas
Acquiring a line-moving value DX of a user; wherein b1, b2, b3 and b4 are all preset proportionality coefficients; mu is a correction factor and takes the value of 0.98451.
Preferably, the step of matching to the corresponding parking area through the action line value DX in S22 is:
s221: dividing a parking lot of a hospital into a plurality of parking areas; each parking area comprises a plurality of parking spaces;
s222: obtaining the current real-time position of a user vehicle, calculating the distance difference between the current real-time position of the user and the position of a parking area to obtain the distance between vehicles, and marking the distance as C1;
s223: calculating the distance difference between the position of the parking area and the position of the body part submitted by the user corresponding to the hospital department to obtain the distance between the departments of the vehicle and the vehicle, and marking the distance as C2;
s224: setting all parking areas to correspond to a vehicle area value; calculating the difference value between the area value of the parking area and the dynamic line value DX of the user, taking the absolute value to obtain the dynamic difference value of the parking area and marking the dynamic difference value as C3;
s225: normalizing the vehicle distance, the vehicle-related distance and the dynamic difference value and obtaining numerical values of the vehicle distance, the vehicle-related distance and the dynamic difference value; using formulas
Acquiring a kiss value CK of the parking area; wherein b5, b6 and b7 are all preset proportionality coefficients;
s226: and selecting the parking area with the maximum vehicle kiss value as the selected parking area.
Preferably, the specific step of calculating the parking value of the parking space by matching the parking space with the user in S23 is as follows:
s231: acquiring hospital parking lot information, screening parking spaces in a selected parking area, and marking parking spaces without parking on the parking spaces as primary parking spaces;
s232: acquiring the number of the initially selected parking spaces, and marking the initially selected parking spaces as selected parking spaces of users when the number of the initially selected parking spaces is equal to one;
s233: when the number of the initially selected parking spaces is more than one, the parking value of the initially selected parking spaces is calculated, and the specific process is as follows:
coating a preset color on a parking space on a hospital parking lot; shooting parking space pictures of the initially selected parking spaces by the unmanned aerial vehicle, wherein the pictures comprise the initially selected parking spaces and two parking spaces on two adjacent sides of the initially selected parking spaces;
processing the parking space picture, amplifying the parking space picture by a plurality of times to form a pixel grid picture, selecting a central line of a primary parking space in the pixel grid picture, uniformly selecting a plurality of nodes on the central line, making rays perpendicular to the central line from the nodes to two sides, and stopping the rays when the rays contact pixel grids different from a preset color; counting lengths corresponding to rays on two sides of the node and summing to obtain the total length of the node; summing the total lengths of all nodes on the central line and taking the average value to obtain the parking value of the initially selected parking space; selecting the parking space with the largest parking value as the hospital parking space of the user;
s234: when the number of the initially selected parking spaces is equal to zero, acquiring the vehicle moving time of the initially selected parking spaces in the server; and calculating the time difference between the vehicle moving time and the current time to obtain the time difference, and selecting the initially selected parking space with the minimum time difference as the hospital parking space of the user.
Preferably, the server further comprises a parking space analysis module; the parking space analysis module is used for analyzing the vehicle moving time of the vehicles staying on the parking space, and the specific analysis steps are as follows:
SS 1: acquiring patient information submitted by a user corresponding to a staying vehicle, and acquiring a case corresponding to the patient information; the age of the patient is labeled R1; acquiring instruments required by patient examination, setting all instruments for hospital detection to correspond to an instrument value, and matching the instruments required by patient examination with all instruments for hospital detection to obtain corresponding preset values;
SS 2: summing the preset values matched with the instruments required by the patient examination to obtain a preset total value and marking as R2;
SS 3: acquiring the corresponding queuing number of the hospital detection instruments and marking the queuing number as R3;
SS 4: the age, the preset total value and the queuing number are subjected to de-normalization treatment, the numerical values are taken, and the vehicle moving length RZ of the vehicles staying in the parking space is obtained by using a formula RZ which is R1 multiplied by d1+ R2 multiplied by d2+ R2 multiplied by d 3; wherein d1, d2 and d3 are all preset proportionality coefficients;
SS 5: and adding the vehicle moving time to the starting time of the vehicle parking to obtain the vehicle moving time of the vehicle.
Compared with the prior art, the invention has the beneficial effects that:
1. hospital data are collected through a data collection module and sent to a server; the user inputs the name of the hospital, the patient information and the body part name through the mobile phone terminal and sends the name to the dynamic line planning module; the moving line planning module plans and analyzes the name of the hospital and the name of the body part to obtain a hospital parking space, and performs route planning on the position of the hospital parking space and the position of the user and generates parking route navigation; the parking space of the parking area is selected by matching the corresponding parking area through the moving line value, the parking space picture is shot through the unmanned aerial vehicle, the parking space picture is analyzed to obtain the parking value of the parking space, and therefore the parking space of the corresponding hospital parking lot is reasonably selected through the parking value, and convenience is brought to the user for parking.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a schematic view of the present invention for processing vehicle pictures.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, a method for planning and analyzing a data movement line based on a hospital parking lot includes the following steps:
s1: hospital data are collected through a data collection module and sent to a server;
s2: the user inputs the name of the hospital, the patient information and the body part name through the mobile phone terminal and sends the name to the dynamic line planning module; the dynamic line planning module plans and analyzes the name of the hospital and the name of the body part to obtain the parking space of the hospital, and the specific steps are as follows:
s21: hospital data corresponding to the hospital are stored in the server according to the name of the hospital; analyzing hospital data to obtain a dynamic line value DX of a user; the method comprises the following specific steps:
s211: matching the body part name with the hospital visit information to obtain the name of the corresponding hospital department, obtaining the remaining registration of the hospital department without visiting the doctor, comparing the registered number with the remaining registration of the hospital department without visiting the doctor to obtain the queuing number of the patients and marking the queuing number as M1;
s212: setting the names corresponding to all body parts to correspond to a preset value, matching the input body part names with all the body parts to obtain corresponding preset values, and marking the preset values as M2;
s213: the age of the patient was labeled M3; the number of patients with illness is labeled M4; normalizing the queuing number, the preset value, the age and the sick times of the patients and taking the numerical values;
s214: using formulas
Acquiring a line-moving value DX of a user; wherein b1, b2, b3 and b4 are all preset proportionality coefficients; mu is a correction factor, and the value is 0.98451;
s22: matching the dynamic line value DX to a corresponding parking area, and marking the parking area as a selected parking area; the method comprises the following steps:
s221: dividing a parking lot of a hospital into a plurality of parking areas; each parking area comprises a plurality of parking spaces;
s222: obtaining the current real-time position of a user vehicle, calculating the distance difference between the current real-time position of the user and the position of a parking area to obtain the distance between vehicles, and marking the distance as C1;
s223: calculating the distance difference between the position of the parking area and the position of the body part submitted by the user corresponding to the hospital department to obtain the distance between the departments of the vehicle and the vehicle, and marking the distance as C2;
s224: setting all parking areas to correspond to a vehicle area value; calculating the difference value between the area value of the parking area and the dynamic line value DX of the user, taking the absolute value to obtain the dynamic difference value of the parking area and marking the dynamic difference value as C3;
s225: normalizing the vehicle distance, the vehicle-related distance and the dynamic difference value and obtaining numerical values of the vehicle distance, the vehicle-related distance and the dynamic difference value; using formulas
Acquiring a kiss value CK of the parking area; wherein b5, b6 and b7 are all preset proportionality coefficients;
s226: selecting the parking area with the maximum vehicle kiss value as the selected parking area;
s23: acquiring a parking space of the selected parking area, and matching and calculating the parking space and a user to obtain a parking value of the parking space; selecting the parking space with the largest parking value as the hospital parking space of the user; the method comprises the following specific steps:
s231: acquiring hospital parking lot information, screening parking spaces in a selected parking area, and marking parking spaces without parking on the parking spaces as primary parking spaces;
s232: acquiring the number of the initially selected parking spaces, and marking the initially selected parking spaces as selected parking spaces of users when the number of the initially selected parking spaces is equal to one;
s233: when the number of the initially selected parking spaces is more than one, the parking value of the initially selected parking spaces is calculated, and the specific process is as follows:
coating a preset color on a parking space on a hospital parking lot; shooting parking space pictures of the initially selected parking spaces by the unmanned aerial vehicle, wherein the pictures comprise the initially selected parking spaces and two parking spaces on two adjacent sides of the initially selected parking spaces;
processing the parking space picture, amplifying the parking space picture by a plurality of times to form a pixel grid picture, selecting a central line of a primary parking space in the pixel grid picture, uniformly selecting a plurality of nodes on the central line, making rays perpendicular to the central line from the nodes to two sides, and stopping the rays when the rays contact pixel grids different from a preset color; counting lengths corresponding to rays on two sides of the node and summing to obtain the total length of the node; summing the total lengths of all nodes on the central line and taking the average value to obtain the parking value of the initially selected parking space; selecting the parking space with the largest parking value as the hospital parking space of the user;
s234: when the number of the initially selected parking spaces is equal to zero, acquiring the vehicle moving time of the initially selected parking spaces in the server; calculating the time difference between the vehicle moving time and the current time to obtain the time difference, and selecting the initially selected parking space with the minimum time difference as the hospital parking space of the user;
s3: and carrying out route planning on the positions of the parking spaces of the hospital and the positions of the users and generating parking route navigation.
The hospital data comprises hospital clinic information and hospital parking lot information; the hospital visiting information comprises the name and the position of a hospital department, the registration of the rest non-visiting patients, the name of the body part treated by the hospital department and a case opened by a doctor of the hospital department for the patient; the case includes the name, age, payment amount of the patient and the required instrument for the patient examination; the hospital parking lot information comprises the position of a parking space, the number plate of a vehicle staying on the parking space and the starting time of vehicle parking; the patient information comprises the name, registered number and age of the patient;
the server also comprises a parking space analysis module; the parking space analysis module is used for analyzing the vehicle moving time of the vehicles staying on the parking space, and the specific analysis steps are as follows:
SS 1: acquiring patient information submitted by a user corresponding to a staying vehicle, and acquiring a case corresponding to the patient information; the age of the patient is labeled R1; acquiring instruments required by patient examination, setting all instruments for hospital detection to correspond to an instrument value, and matching the instruments required by patient examination with all instruments for hospital detection to obtain corresponding preset values;
SS 2: summing the preset values matched with the instruments required by the patient examination to obtain a preset total value and marking as R2;
SS 3: acquiring the corresponding queuing number of the hospital detection instruments and marking the queuing number as R3;
SS 4: the age, the preset total value and the queuing number are subjected to de-normalization treatment, the numerical values are taken, and the vehicle moving length RZ of the vehicles staying in the parking space is obtained by using a formula RZ which is R1 multiplied by d1+ R2 multiplied by d2+ R2 multiplied by d 3; wherein d1, d2 and d3 are all preset proportionality coefficients;
SS 5: and adding the vehicle moving time to the starting time of the vehicle parking to obtain the vehicle moving time of the vehicle.
The above formulas are obtained by collecting a large amount of data and performing software simulation, and the coefficients in the formulas are set by those skilled in the art according to actual conditions
When the hospital data acquisition system is used, hospital data are acquired through the data acquisition module and are sent to the server; the user inputs the name of the hospital, the patient information and the body part name through the mobile phone terminal and sends the name to the dynamic line planning module; the moving line planning module plans and analyzes the name of the hospital and the name of the body part to obtain a hospital parking space, and performs route planning on the position of the hospital parking space and the position of the user and generates parking route navigation; the method comprises the steps that a line-of-motion value of a user is obtained through analysis of hospital data, corresponding parking areas are matched through the line-of-motion value, parking spaces of the parking areas are selected, parking space pictures are taken through the unmanned aerial vehicle for the parking spaces, and the parking spaces are analyzed to obtain parking values of the parking spaces, so that the corresponding parking spaces of the hospital parking lot are reasonably selected through the parking values, and the user can conveniently park;
acquiring patient information submitted by a user corresponding to a staying vehicle, and acquiring a case corresponding to the patient information; the age of the patient is labeled R1; acquiring instruments required by patient examination, setting all instruments for hospital detection to correspond to an instrument value, and matching the instruments required by patient examination with all instruments for hospital detection to obtain corresponding preset values; summing the preset values matched with the instruments required by the patient examination to obtain a preset total value and marking as R2; acquiring the corresponding queuing number of the hospital detection instruments and marking the queuing number as R3; the age, the preset total value and the queuing number are subjected to de-normalization treatment, the numerical values are taken, and the vehicle moving length RZ of the vehicles staying in the parking space is obtained by using a formula RZ which is R1 multiplied by d1+ R2 multiplied by d2+ R2 multiplied by d 3; adding the vehicle moving time to the starting time of the vehicle parking to obtain the vehicle moving time of the vehicle; through the case that acquires patient information correspondence and combine age, predetermine total value, the quantity of lining up and obtain the vehicle moving that stops the vehicle on the parking stall long, through the vehicle moving time that the long analysis obtained the vehicle when moving, conveniently remind the reasonable parking of user, avoid dwell time overlength, influence the parking area parking of hospital.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (6)
1. A big data line planning analysis method based on a hospital parking lot is characterized by comprising the following steps:
s1: hospital data are collected through a data collection module and sent to a server;
s2: the user inputs the name of the hospital, the patient information and the body part name through the mobile phone terminal and sends the name to the dynamic line planning module; the dynamic line planning module plans and analyzes the name of the hospital and the name of the body part to obtain the parking space of the hospital, and the specific steps are as follows:
s21: hospital data corresponding to the hospital are stored in the server according to the name of the hospital; analyzing hospital data to obtain a dynamic line value DX of a user;
s22: matching the dynamic line value DX to a corresponding parking area, and marking the parking area as a selected parking area;
s23: acquiring a parking space of the selected parking area, and matching and calculating the parking space and a user to obtain a parking value of the parking space; selecting the parking space with the largest parking value as the hospital parking space of the user;
s3: and carrying out route planning on the positions of the parking spaces of the hospital and the positions of the users and generating parking route navigation.
2. The line planning analysis method based on the big data of the hospital parking lot according to claim 1, wherein the hospital data comprises hospital visit information and hospital parking lot information; the hospital visiting information comprises the name and the position of a hospital department, the registration of the rest non-visiting patients, the name of the body part treated by the hospital department and a case opened by a doctor of the hospital department for the patient; the case includes the name, age, payment amount of the patient and the required instrument for the patient examination; the hospital parking lot information comprises the position of a parking space, the number plate of a vehicle staying on the parking space and the starting time of vehicle parking; the patient information includes the patient's name, registered number, and age.
3. The hospital parking lot big data movement line planning analysis method according to claim 1, wherein the specific steps of analyzing the hospital data to obtain the movement line value of the user in S21 are as follows:
s211: matching the body part name with the hospital visit information to obtain the name of the corresponding hospital department, obtaining the remaining registration of the hospital department without visiting the doctor, comparing the registered number with the remaining registration of the hospital department without visiting the doctor to obtain the queuing number of the patients and marking the queuing number as M1;
s212: setting the names corresponding to all body parts to correspond to a preset value, matching the input body part names with all the body parts to obtain corresponding preset values, and marking the preset values as M2;
s213: the age of the patient was labeled M3; the number of patients with illness is labeled M4; normalizing the queuing number, the preset value, the age and the sick times of the patients and taking the numerical values;
s214: using formulas
Acquiring a line-moving value DX of a user; wherein b1, b2, b3 and b4 are all preset proportionality coefficients; mu is a correction factor and takes the value of 0.98451.
4. The hospital parking lot big data-based line-of-action planning analysis method according to claim 1, wherein the step of matching to the corresponding parking area through the line-of-action value DX in S22 is as follows:
s221: dividing a parking lot of a hospital into a plurality of parking areas; each parking area comprises a plurality of parking spaces;
s222: obtaining the current real-time position of a user vehicle, calculating the distance difference between the current real-time position of the user and the position of a parking area to obtain the distance between vehicles, and marking the distance as C1;
s223: calculating the distance difference between the position of the parking area and the position of the body part submitted by the user corresponding to the hospital department to obtain the distance between the departments of the vehicle and the vehicle, and marking the distance as C2;
s224: setting all parking areas to correspond to a vehicle area value; calculating the difference value between the area value of the parking area and the dynamic line value DX of the user, taking the absolute value to obtain the dynamic difference value of the parking area and marking the dynamic difference value as C3;
s225: normalizing the vehicle distance, the vehicle-related distance and the dynamic difference value and taking the values; using formulas
Acquiring a kiss value CK of the parking area; wherein b5, b6 and b7 are all preset proportionality coefficients;
s226: and selecting the parking area with the maximum vehicle kiss value as the selected parking area.
5. The hospital parking lot big data movement line planning analysis method according to claim 1, wherein the specific steps of matching and calculating the parking space and the user to obtain the parking value of the parking space in S23 are as follows:
s231: acquiring hospital parking lot information, screening parking spaces in a selected parking area, and marking parking spaces without parking on the parking spaces as primary parking spaces;
s232: acquiring the number of the initially selected parking spaces, and marking the initially selected parking spaces as selected parking spaces of users when the number of the initially selected parking spaces is equal to one;
s233: when the number of the initially selected parking spaces is more than one, the parking value of the initially selected parking spaces is calculated, and the specific process is as follows:
coating a preset color on a parking space on a hospital parking lot; shooting parking space pictures of the initially selected parking spaces by the unmanned aerial vehicle, wherein the pictures comprise the initially selected parking spaces and two parking spaces on two adjacent sides of the initially selected parking spaces;
processing the parking space picture, amplifying the parking space picture by a plurality of times to form a pixel grid picture, selecting a central line of a primary parking space in the pixel grid picture, uniformly selecting a plurality of nodes on the central line, making rays perpendicular to the central line from the nodes to two sides, and stopping the rays when the rays contact pixel grids different from a preset color; counting lengths corresponding to rays on two sides of the node and summing to obtain the total length of the node; summing the total lengths of all nodes on the central line and taking the average value to obtain the parking value of the initially selected parking space; selecting the parking space with the largest parking value as the hospital parking space of the user;
s234: when the number of the initially selected parking spaces is equal to zero, acquiring the vehicle moving time of the initially selected parking spaces in the server; and calculating the time difference between the vehicle moving time and the current time to obtain the time difference, and selecting the initially selected parking space with the minimum time difference as the hospital parking space of the user.
6. The hospital parking lot big data based line planning analysis method according to claim 1, wherein a parking space analysis module is further included in the server; the parking space analysis module is used for analyzing the vehicle moving time of the vehicles staying on the parking space, and the specific analysis steps are as follows:
SS 1: acquiring patient information submitted by a user corresponding to a staying vehicle, and acquiring a case corresponding to the patient information; the age of the patient is labeled R1; acquiring instruments required by patient examination, setting all instruments for hospital detection to correspond to an instrument value, and matching the instruments required by patient examination with all instruments for hospital detection to obtain corresponding preset values;
SS 2: summing the preset values matched with the instruments required by the patient examination to obtain a preset total value and marking as R2;
SS 3: acquiring the corresponding queuing number of the hospital detection instruments and marking the queuing number as R3;
SS 4: the age, the preset total value and the queuing number are subjected to de-normalization treatment, the numerical values are taken, and the vehicle moving length RZ of the vehicles staying in the parking space is obtained by using a formula RZ which is R1 multiplied by d1+ R2 multiplied by d2+ R2 multiplied by d 3; wherein d1, d2 and d3 are all preset proportionality coefficients;
SS 5: and adding the vehicle moving time to the starting time of the vehicle parking to obtain the vehicle moving time of the vehicle.
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| CN113034897A (en) * | 2021-02-20 | 2021-06-25 | 柳州慧龙智能科技发展有限公司 | Intelligent parking guide system for parking in residential area |
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