Hospital logistics management system and method based on digital twinning

Abstract

The invention discloses a hospital logistics management system and method based on digital twinning, and relates to the technical field of hospital logistics informationization. Through a model unit and an initialization unit, a three-dimensional entity model of a hospital is constructed, hardware equipment initialization is carried out, service data is acquired through a data acquisition unit, and the service data is transmitted to a server; in consideration of business data cross characteristics among a plurality of subsystems, a data processing unit is set to calculate the overlap ratio of business data between two subsystems, so that correlation coefficients are set for the two subsystems, and system characteristic values of the subsystems are calculated through a first formula in a data integration unit; the system characteristic value comprises an energy consumption value and a risk value of the hardware equipment, the system characteristic value is used as a judgment standard for judging whether a single subsystem has service early warning or risk, and the comprehensive management unit takes corresponding measures for processing aiming at the system characteristic values in different ranges, so that the system characteristic value of the hardware equipment is obtained. And the management efficiency of the whole hospital logistics management system is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of hospital logistics information technology, and in particular, to a hospital logistics management system and method based on digital twins. Background Art

[0002] The business areas involved in hospital logistics are very broad, including energy management, electromechanical systems and equipment management, comprehensive monitoring, central transportation, medical waste treatment, environmental monitoring and infrastructure management. With the continuous expansion of hospital scale and the continuous development of Internet IT technology and digital transformation, the importance of logistics work in hospitals has gradually become apparent.

[0003] However, most traditional hospital logistics management systems are systems designed for specific business needs, and face problems such as decentralized management and information silos. At the same time, the current logistics management systems mostly process collected data in the form of reports for presentation, and are unable to integrate and process data across multiple systems, nor are they able to visualize the integration results or provide managers with decision-making based on the integration results, ultimately leading to the overall low efficiency of existing hospital logistics management. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the present invention provides a hospital logistics management system based on digital twins, the system comprising:

[0005] Model unit: Build a physical 3D model of the hospital based on the BIM model and UE Unreal Engine;

[0006] Initialization unit: initializing the positions of multiple hardware devices in the solid three-dimensional model and assigning coordinate information to all hardware devices;

[0007] Data collection unit: Based on all hardware devices, collect data and analyze the data to obtain business data. All business data contains corresponding coordinate information;

[0008] Data processing unit: obtaining hardware devices included in each subsystem to obtain a first acquisition result, obtaining business data included in each subsystem as first business data based on the first acquisition result and all business data, storing the first business data of each subsystem in a corresponding data set, calculating the overlap of the first business data in any two data sets to obtain a calculation result, and setting a correlation coefficient between any subsystem and other subsystems based on the calculation result, and all correlation coefficients are greater than or equal to 0 and less than 1;

[0009] Data integration unit: based on all first business data of each subsystem, using a first formula to calculate a system characteristic value of each subsystem;

[0010] The first formula includes:

[0011]

[0012] is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem;

[0013] Comprehensive management unit: setting a first threshold, a second threshold and a third threshold for the system characteristic value of each subsystem, wherein the first threshold, the second threshold and the third threshold in each subsystem are different;

[0014] A single subsystem is obtained and recorded as subsystem E. When the system characteristic value of the subsystem E is less than or equal to the first threshold, no action is taken;

[0015] When the system characteristic value of the subsystem E is greater than the second threshold value and less than the third threshold value, the subsystem E is processed by a first method; the first method is: annotating the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first annotation result, and based on the first business data of the subsystem E, obtaining corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first annotation result and the second acquisition result;

[0016] When the system characteristic value of the subsystem E is greater than or equal to the third threshold, the first method is used to process the subsystem E, and all correlation coefficients of the subsystem E are obtained to obtain a third acquisition result, and based on the third acquisition result, the remaining subsystems are processed.

[0017] The present invention is implemented through the following technical scheme: firstly, a physical three-dimensional model of a hospital is constructed through a model unit, and the positions of multiple hardware devices in the physical three-dimensional model are initialized through an initialization unit, and coordinate information is assigned to each hardware device, and then data is collected and analyzed by the hardware devices in a data acquisition unit to obtain business data; the entire hospital logistics management system includes multiple subsystems (such as energy management, equipment management and environmental monitoring, etc.), and the business data of each subsystem is collected through the data acquisition unit;

[0018] The business data collected by each subsystem is processed by the data processing unit. Since there is overlap of business data between multiple subsystems in the actual hospital logistics management system, this solution uses the characteristics of overlap of business data between different subsystems to calculate the overlap of business data of any two subsystems to obtain the calculation result. Based on the calculation result, a correlation coefficient is assigned to any two subsystems. The purpose is that when a business warning or risk occurs in one of the subsystems, corresponding measures can be taken for the other subsystem based on the correlation coefficient, which not only solves the problem of separation between different subsystems, but also improves the management efficiency of the entire logistics management system.

[0019] The data integration unit calculates the system characteristic value of each subsystem by using the first formula. The system characteristic value includes the energy consumption value and risk value of the hardware device. The system characteristic value is used to determine whether the system has a business warning or risk.

[0020] Finally, the comprehensive management unit takes different measures based on the integration result of the data integration unit, specifically, sets the first threshold, the second threshold and the third threshold. When the system characteristic value of a single subsystem is less than or equal to the first threshold, no action is taken; when the system characteristic value of a single subsystem is greater than the first threshold and less than the second threshold, the first method is used to process the single subsystem, that is, the hardware devices included in the subsystem are marked in the solid three-dimensional model, and the business data includes coordinate information. The corresponding subsystem is checked through the marking results and the corresponding coordinate information; when the system characteristic value of a single subsystem is greater than or equal to the third threshold, the first method is also used to process the corresponding subsystem, but at the same time, all the correlation coefficients of the subsystem are obtained to obtain the acquisition result, and the subsystem related to the subsystem is processed through the acquisition result.

[0021] As an optional technical solution, the second formula is used to calculate the energy consumption value of the hardware device corresponding to the same first business data in each subsystem:

[0022]

[0023] t is the preset time period, ΔS j It is the change in the total energy consumption value of the hardware device corresponding to the same first business data within the preset time period.

[0024] As an optional technical solution, the third formula is used to calculate the risk value of the hardware device corresponding to the same first business data in each subsystem:

[0025]

[0026] P k is the total equipment risk value of the hardware equipment corresponding to the same first business data in each subsystem, Qk The total monitoring risk value of the hardware equipment corresponding to the same first business data in each subsystem.

[0027] As an optional technical solution, calculating the total equipment risk value of the hardware equipment corresponding to the same first business data in each subsystem includes:

[0028] Obtain service life data, warranty frequency data, and failure frequency data for a single hardware device in a single subsystem;

[0029] The service life data, the warranty frequency data and the failure frequency data are divided into data intervals in sequence, and each divided data interval is assigned a value to obtain a first assignment result;

[0030] Based on the first assignment result, the service life data of a single hardware device is converted into a service life risk value, the warranty frequency data is converted into a warranty risk value, and the failure frequency data is converted into a failure risk value;

[0031] Calculate the sum of the life risk value, the warranty risk value and the failure risk value of a single hardware device to obtain a device risk value of the single hardware device;

[0032] The equipment risk values ​​of all hardware devices included in the same first business data in a single subsystem are summed to obtain the total equipment risk value of the hardware devices corresponding to the same first business data.

[0033] As an optional technical solution, calculating the total monitoring risk value of the hardware device corresponding to the same first business data in each subsystem includes:

[0034] Get monitoring data of a single hardware device in a single subsystem;

[0035] Dividing the monitoring data into data intervals, and assigning a value to each divided data interval to obtain a second assignment result;

[0036] Based on the second assignment result, the monitoring data of the single hardware device is converted into a monitoring risk value to obtain a monitoring risk value of the single hardware device;

[0037] The monitoring risk values ​​of all hardware devices included in the same first business data in a single subsystem are summed to obtain the total monitoring risk value of the hardware devices corresponding to the same first business data.

[0038] As an optional technical solution, based on the third acquisition result, processing the remaining subsystems includes:

[0039] Obtain any subsystem among all subsystems except the subsystem E and record it as subsystem F;

[0040] Obtaining a correlation coefficient between the subsystem E and the subsystem F as a first correlation coefficient;

[0041] Determine whether the first correlation coefficient is 0, if so, do nothing, if not, use the second method to process.

[0042] As an optional technical solution, the second method includes:

[0043] Determine whether the first correlation coefficient is greater than a preset value. If so, process the subsystem F using the first method. If not, obtain the hardware devices corresponding to all the overlapping first service data of the subsystem E and the subsystem F as the first hardware devices.

[0044] All first hardware devices included in the subsystem F are marked in the physical three-dimensional model and corresponding coordinate information is obtained to obtain a second marking result, and the subsystem F is checked based on the second marking result.

[0045] As an optional technical solution, calculating the overlap of the first business data in any two data sets includes:

[0046] Data set C corresponds to subsystem c, and data set D corresponds to subsystem d. It is determined whether the data set C and the data set D have the same first business data. If so, the first business data in the data set C that is the same as that in the data set D is recorded as the second business data, and the fourth formula is used to calculate the overlap between the data set C and the data set D. If not, the correlation coefficient between subsystem c and subsystem d is set to 0.

[0047] The fourth formula is:

[0048]

[0049] η is the overlap degree of the first business data in the data set C and the data set D, H C is the data volume of all first service data in the system c per unit time, H D is the data volume of all first service data in the system d per unit time, H i is the data volume of all the second business data in the subsystem c or the subsystem d per unit time, and n is the number of the second business data in the subsystem c or the subsystem d.

[0050] As an optional technical solution, based on the calculation result, setting the correlation coefficient between any subsystem and other subsystems includes:

[0051] All historical data of any two subsystems are obtained, and based on the overlap of the first business data corresponding to the two subsystems, a correlation model is constructed and trained, and based on the trained correlation model, a correlation coefficient is set for any two subsystems.

[0052] In order to solve the deficiencies in the prior art, the present invention provides a hospital logistics management method based on digital twins, the method comprising the following steps:

[0053] Build a physical 3D model of the hospital based on the BIM model and UE Unreal Engine;

[0054] Initializing the positions of multiple hardware devices in the solid three-dimensional model and assigning coordinate information to all the hardware devices;

[0055] Based on all hardware devices, data is collected and analyzed to obtain business data. All business data contains corresponding coordinate information;

[0056] Acquire the hardware devices included in each subsystem to obtain a first acquisition result; based on the first acquisition result and all business data, acquire the business data included in each subsystem as first business data; store the first business data of each subsystem in a corresponding data set; calculate the overlap of the first business data in any two data sets to obtain a calculation result; and based on the calculation result, set a correlation coefficient between any subsystem and other subsystems, and all correlation coefficients are greater than or equal to 0 and less than 1;

[0057] Based on all the first business data of each subsystem, a system characteristic value of each subsystem is calculated using a first formula;

[0058] The first formula includes:

[0059]

[0060] is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem;

[0061] A first threshold, a second threshold and a third threshold are set for the system characteristic value of each subsystem, and the first threshold, the second threshold and the third threshold in each subsystem are different;

[0062] A single subsystem is obtained and recorded as subsystem E. When the system characteristic value of the subsystem E is less than or equal to the first threshold, no action is taken;

[0063] When the system characteristic value of the subsystem E is greater than the second threshold value and less than the third threshold value, the subsystem E is processed by a first method; the first method is: annotating the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first annotation result, and based on the first business data of the subsystem E, obtaining corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first annotation result and the second acquisition result;

[0064] When the system characteristic value of the subsystem E is greater than or equal to the third threshold, the first method is used to process the subsystem E, and all correlation coefficients of the subsystem E are obtained to obtain a third acquisition result, and based on the third acquisition result, the remaining subsystems are processed.

[0065] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0066] The present invention provides a hospital logistics management system based on digital twins. A three-dimensional entity model of a hospital is constructed and hardware equipment is initialized through a model unit and an initialization unit. Business data is acquired through a data acquisition unit. Considering the cross-characteristics of business data between multiple subsystems, a data processing unit is set to calculate the overlap of business data between two subsystems, thereby setting a correlation coefficient for the two subsystems. The system characteristic value of the subsystem is calculated through a first formula in a data integration unit. The system characteristic value includes an energy consumption value and a risk value of the hardware equipment. The system characteristic value is used as a criterion for determining whether a single subsystem has a business warning or risk. In addition, the comprehensive management unit takes corresponding measures for processing system characteristic values ​​in different ranges, thereby greatly improving the management efficiency of the entire hospital logistics management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation on the embodiments of the present invention;

[0068] Figure 1 This is a schematic diagram of the composition of a hospital logistics management system based on digital twins in the present invention;

[0069] Figure 2 It is a flowchart of a hospital logistics management method based on digital twins in the present invention. DETAILED DESCRIPTION

[0070] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those within the scope of this description. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0072] Embodiment 1

[0073] Please refer to Figure 1 , Figure 1 This is a schematic diagram of a hospital logistics management system based on digital twins in the present invention, which includes:

[0074] Model unit: Build a physical 3D model of the hospital based on the BIM model and UE Unreal Engine;

[0075] Initialization unit: initializing the positions of multiple hardware devices in the solid three-dimensional model, and assigning coordinate information to all hardware devices;

[0076] Data collection unit: Based on all hardware devices, collect data and analyze the data to obtain business data. All business data contains corresponding coordinate information;

[0077] Data processing unit: obtaining hardware devices included in each subsystem to obtain a first acquisition result, obtaining business data included in each subsystem as first business data based on the first acquisition result and all business data, storing the first business data of each subsystem in a corresponding data set, calculating the overlap of the first business data in any two data sets to obtain a calculation result, and setting a correlation coefficient between any subsystem and other subsystems based on the calculation result, and all correlation coefficients are greater than or equal to 0 and less than 1;

[0078] Data integration unit: based on all first business data of each subsystem, using a first formula to calculate a system characteristic value of each subsystem;

[0079] The first formula includes:

[0080]

[0081] is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem;

[0082] Comprehensive management unit: setting a first threshold, a second threshold and a third threshold for the system characteristic value of each subsystem, wherein the first threshold, the second threshold and the third threshold in each subsystem are different;

[0083] A single subsystem is obtained and recorded as subsystem E. When the system characteristic value of the subsystem E is less than or equal to the first threshold, no action is taken;

[0084] When the system characteristic value of the subsystem E is greater than the second threshold value and less than the third threshold value, the subsystem E is processed by a first method; the first method is: annotating the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first annotation result, and based on the first business data of the subsystem E, obtaining corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first annotation result and the second acquisition result;

[0085] When the system characteristic value of the subsystem E is greater than or equal to the third threshold, the first method is used to process the subsystem E, and all correlation coefficients of the subsystem E are obtained to obtain a third acquisition result, and based on the third acquisition result, the remaining subsystems are processed.

[0086] The specific embodiments of the present invention are as follows:

[0087] Model unit: BIM model, translated into Chinese as Building Information Model, is a technology that uses digital means to build a virtual building in the computer, which will provide a single, complete, and logically related building information library; UE Unreal Engine is a powerful and highly flexible real-time 3D creation tool. Through the use of BIM model and UE Unreal Engine, a physical 3D model of the hospital is constructed.

[0088] Initialization unit: obtain the actual location information of the hardware equipment in the hospital, initialize the position of each hardware equipment in the physical three-dimensional model, and assign coordinate information to each hardware equipment. The coordinate information can be combined with building number, floor and location data. The hardware equipment includes but is not limited to water meters, electricity meters, smoke sensors and humidity monitors.

[0089] Data acquisition unit: collects data through all hardware devices in each subsystem and analyzes it to obtain the business data of each subsystem.

[0090] Data processing unit: record the business data contained in each subsystem as the first business data, and store the first business data of each subsystem in the corresponding data set, calculate the overlap of the first business data in any two data sets to obtain the calculation result, that is, the overlap of the two subsystems. Since in the actual hospital logistics management system, there will be intersections of business data between multiple subsystems, when there is a business warning or risk in one of the subsystems, it will also affect the subsystem. Therefore, this embodiment sets a correlation coefficient for any two subsystems based on the calculation results, and takes corresponding measures based on the difference in the correlation coefficients.

[0091] This embodiment provides a method for calculating the overlap degree of first business data in any two data sets, specifically:

[0092] Data set C corresponds to subsystem c, and data set D corresponds to subsystem d. It is determined whether the data set C and the data set D have the same first business data. If so, the first business data in the data set C that is the same as that in the data set D is recorded as the second business data, and the fourth formula is used to calculate the overlap between the data set C and the data set D. If not, the correlation coefficient between subsystem c and subsystem d is set to 0.

[0093] The fourth formula is:

[0094]

[0095] η is the overlap degree of the first business data in the data set C and the data set D, H C is the data volume of all first service data in the system c per unit time, H D is the data volume of all first service data in the system d per unit time, H i is the data volume of all the second business data in the subsystem c or the subsystem d per unit time, and n is the number of the second business data in the subsystem c or the subsystem d.

[0096] This embodiment provides a method for setting a correlation coefficient of any subsystem with other subsystems, specifically:

[0097] All historical data of any two subsystems are obtained, and based on the overlap of the first business data corresponding to the two subsystems, a correlation model is constructed and trained, and based on the trained correlation model, a correlation coefficient is set for any two subsystems.

[0098] Data integration unit: Calculate the system characteristic value of each subsystem through the first formula. The system characteristic value includes the energy consumption value and risk value of the hardware device. That is, when the energy consumption of the device is too large or the risk of the device (including the device itself and the monitoring data) is too large, it is judged that the subsystem has a business warning or risk. The first formula includes:

[0099]

[0100] is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem;

[0101] The second formula is used to calculate the energy consumption value of the hardware device corresponding to the same first business data in each subsystem:

[0102]

[0103] t is the preset time period, ΔS j The change in the total energy consumption of the hardware device corresponding to the same first business data within the preset time period;

[0104] The third formula is used to calculate the risk value of the hardware device corresponding to the same first business data in each subsystem:

[0105]

[0106] P k is the total equipment risk value of the hardware equipment corresponding to the same first business data in each subsystem, Q k The total monitoring risk value of the hardware equipment corresponding to the same first business data in each subsystem.

[0107] Furthermore, calculating the total equipment risk value of the hardware equipment corresponding to the same first business data in each subsystem includes:

[0108] Obtain service life data, warranty frequency data, and failure frequency data for a single hardware device in a single subsystem;

[0109] The service life data, the warranty frequency data and the failure frequency data are divided into data intervals in sequence, and each divided data interval is assigned a value to obtain a first assignment result;

[0110] Based on the first assignment result, the service life data of a single hardware device is converted into a service life risk value, the warranty frequency data is converted into a warranty risk value, and the failure frequency data is converted into a failure risk value;

[0111] Calculate the sum of the life risk value, the warranty risk value and the failure risk value of a single hardware device to obtain a device risk value of the single hardware device;

[0112] The equipment risk values ​​of all hardware devices included in the same first business data in a single subsystem are summed to obtain the total equipment risk value of the hardware devices corresponding to the same first business data.

[0113] Among them, if the single hardware device is a smoke alarm, the service life data, warranty frequency data and failure frequency data of the smoke alarm are obtained, and the service life data, insurance frequency data and failure frequency data of the smoke alarm are converted into corresponding age risk value, warranty risk value and failure risk value by dividing the data interval and assigning values. The sum of the age risk value, warranty risk value and failure risk value of a single smoke alarm is calculated to obtain the equipment risk value of a single smoke alarm. The sum of the equipment risk values ​​of multiple smoke alarms is the total equipment risk value of the hardware equipment corresponding to the business data.

[0114] Furthermore, calculating the total monitoring risk value of the hardware device corresponding to the same first business data in each subsystem includes:

[0115] Get monitoring data of a single hardware device in a single subsystem;

[0116] Dividing the monitoring data into data intervals, and assigning a value to each divided data interval to obtain a second assignment result;

[0117] Based on the second assignment result, the monitoring data of the single hardware device is converted into a monitoring risk value to obtain a monitoring risk value of the single hardware device;

[0118] The monitoring risk values ​​of all hardware devices included in the same first business data in a single subsystem are summed to obtain the total monitoring risk value of the hardware devices corresponding to the same first business data.

[0119] Among them, for example, when calculating the total monitoring risk value for a humidity sensor, the monitoring data of the humidity sensor is obtained as humidity, and the humidity is divided into multiple data intervals, and each divided data interval is assigned a value. The significance of assigning values ​​through data intervals is to enable all different monitoring data to be calculated under the same measurement system. By dividing the data intervals and assigning values, the acquired humidity data is converted into a monitoring risk value. The sum of the monitoring risk values ​​of multiple humidity sensors is the total monitoring risk value of the hardware equipment corresponding to the business data.

[0120] Comprehensive management unit: If a single subsystem is obtained and recorded as subsystem E, the first threshold, second threshold and third threshold of subsystem E are ε1, ε2 and ε3 respectively, and ε1<ε2<ε3, the system characteristic value of subsystem E calculated by the first formula is when When , it means that the possibility of energy consumption and equipment risk in subsystem E is low, and no action is taken at this time; when , it indicates that there is a possibility of energy consumption and equipment risk in subsystem E at this time, and the entire subsystem E needs to be checked. This embodiment provides a first method for checking subsystem E, specifically: marking the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first marking result, and based on the first business data of the subsystem E, obtaining the corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first marking result and the second acquisition result. This indicates that subsystem E is likely to have energy consumption and equipment risks, and may affect other subsystems whose business data overlap with subsystem E. Therefore, the first method is first used to check subsystem E, and the correlation coefficient between subsystem E and other subsystems is obtained to obtain the third acquisition result. Based on the third acquisition result, the remaining subsystems are processed.

[0121] This embodiment provides a method for processing the remaining subsystems based on the correlation coefficient, specifically:

[0122] Obtain any subsystem among all subsystems except the subsystem E and record it as subsystem F;

[0123] Obtaining a correlation coefficient between the subsystem E and the subsystem F as a first correlation coefficient;

[0124] Determine whether the first correlation coefficient is 0, if so, do nothing, if not, use the second method to process;

[0125] The second method comprises:

[0126] Determine whether the first correlation coefficient is greater than a preset value. If so, process the subsystem F using the first method. If not, obtain the hardware devices corresponding to all the overlapping first service data of the subsystem E and the subsystem F as the first hardware devices.

[0127] All first hardware devices included in the subsystem F are marked in the physical three-dimensional model and corresponding coordinate information is obtained to obtain a second marking result, and the subsystem F is checked based on the second marking result.

[0128] For example, if subsystem F is obtained, the correlation coefficient between subsystem E and subsystem F is recorded as the first correlation coefficient g, and it is determined whether g is 0. If so, it means that there is no business data intersection between subsystem F and subsystem E, and no action is taken at this time; then it is determined whether g is greater than the preset value. If so, it means that the overlap between subsystem F and subsystem E is relatively high. When subsystem E has a business warning or risk, the entire subsystem F is also very likely to have a business warning or risk. Therefore, it is necessary to adopt the first method to process subsystem F. The specific processing measures of the first method have been explained in the above embodiment and will not be expanded here. If not, it means that there is a business intersection between subsystem F and subsystem E but the intersection is not high. When subsystem E has a business warning or risk, part of subsystem F has the possibility of business warning or risk. Therefore, it is only necessary to process the hardware devices that overlap with subsystem F and subsystem E. Specifically, the hardware devices that overlap with subsystem F and subsystem E are marked in the physical three-dimensional model to obtain a second marking result, and based on the second marking result, subsystem F is checked. It should be noted that when troubleshooting the hardware devices that overlap with subsystem F and subsystem E, it does not constitute duplication of work, because the system characteristics of the two subsystems are different, and when troubleshooting the same hardware device, the troubleshooting items are not exactly the same.

[0129] This embodiment constructs a physical three-dimensional model of the hospital and initializes all hardware devices. When a subsystem needs to be repaired or checked, the corresponding hardware devices in the physical three-dimensional model are marked, and the coordinate information of the hardware devices is used to facilitate the manager to plan the troubleshooting path and assign troubleshooting tasks; the business data of each subsystem is obtained, and the overlap between any two subsystems is calculated based on the business data, and the correlation coefficient is set for any two subsystems based on the overlap; the system characteristic value of each subsystem is calculated, and the system characteristic value is used as a criterion for judging whether the subsystem has risks. At the same time, different thresholds are set for the system characteristic values ​​of different subsystems, and different processing measures are set for different thresholds for the manager to choose. When the system characteristic value of a single subsystem exceeds or is equal to the set highest threshold, it is necessary not only to check the single subsystem, but also to process the subsystems related to the subsystem, and the processing measures also correspond to the correlation coefficient between the two subsystems.

[0130] Embodiment 2

[0131] Please refer to Figure 2 , Figure 2 This is a flowchart of a hospital logistics management method based on digital twins in the present invention, which includes the following steps:

[0132] Build a physical 3D model of the hospital based on the BIM model and UE Unreal Engine;

[0133] Initializing the positions of multiple hardware devices in the solid three-dimensional model and assigning coordinate information to all the hardware devices;

[0134] Based on all hardware devices, data is collected and analyzed to obtain business data. All business data contains corresponding coordinate information;

[0135] Acquire the hardware devices included in each subsystem to obtain a first acquisition result; based on the first acquisition result and all business data, acquire the business data included in each subsystem as first business data; store the first business data of each subsystem in a corresponding data set; calculate the overlap of the first business data in any two data sets to obtain a calculation result; and based on the calculation result, set a correlation coefficient between any subsystem and other subsystems, and all correlation coefficients are greater than or equal to 0 and less than 1;

[0136] Based on all the first business data of each subsystem, a system characteristic value of each subsystem is calculated using a first formula;

[0137] The first formula includes:

[0138]

[0139] is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem;

[0140] A first threshold, a second threshold and a third threshold are set for the system characteristic value of each subsystem, and the first threshold, the second threshold and the third threshold in each subsystem are different;

[0141] A single subsystem is obtained and recorded as subsystem E. When the system characteristic value of the subsystem E is less than or equal to the first threshold, no action is taken;

[0142] When the system characteristic value of the subsystem E is greater than the second threshold value and less than the third threshold value, the subsystem E is processed by a first method; the first method is: annotating the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first annotation result, and based on the first business data of the subsystem E, obtaining corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first annotation result and the second acquisition result;

[0143] When the system characteristic value of the subsystem E is greater than or equal to the third threshold, the first method is used to process the subsystem E, and all correlation coefficients of the subsystem E are obtained to obtain a third acquisition result, and based on the third acquisition result, the remaining subsystems are processed.

[0144] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0145] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A hospital logistics management system based on digital twins, comprising multiple subsystems, characterized in that: The system further comprises: Model unit: Build a physical 3D model of the hospital based on the BIM model and UE Unreal Engine; Initialization unit: initializing the positions of multiple hardware devices in the solid three-dimensional model and assigning coordinate information to all hardware devices; Data collection unit: Based on all hardware devices, collect data and analyze the data to obtain business data. All business data contains corresponding coordinate information; Data processing unit: obtaining hardware devices included in each subsystem to obtain a first acquisition result, obtaining business data included in each subsystem as first business data based on the first acquisition result and all business data, storing the first business data of each subsystem in a corresponding data set, calculating the overlap of the first business data in any two data sets to obtain a calculation result, and setting a correlation coefficient between any subsystem and other subsystems based on the calculation result, and all correlation coefficients are greater than or equal to 0 and less than 1; Data integration unit: based on all first business data of each subsystem, using a first formula to calculate a system characteristic value of each subsystem; The first formula includes: is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem; Comprehensive management unit: setting a first threshold, a second threshold and a third threshold for the system characteristic value of each subsystem, wherein the first threshold, the second threshold and the third threshold in each subsystem are different; A single subsystem is obtained and recorded as subsystem E. When the system characteristic value of the subsystem E is less than or equal to the first threshold, no action is taken; When the system characteristic value of the subsystem E is greater than the second threshold value and less than the third threshold value, the subsystem E is processed by a first method; the first method is: annotating the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first annotation result, and based on the first business data of the subsystem E, obtaining corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first annotation result and the second acquisition result; When the system characteristic value of the subsystem E is greater than or equal to the third threshold, the first method is used to process the subsystem E, and all correlation coefficients of the subsystem E are obtained to obtain a third acquisition result, and based on the third acquisition result, the remaining subsystems are processed.

2. According to claim 1, a hospital logistics management system based on digital twins is characterized in that: The second formula is used to calculate the energy consumption value of the hardware device corresponding to the same first business data in each subsystem: t is the preset time period, ΔS j It is the change in the total energy consumption value of the hardware device corresponding to the same first business data within the preset time period.

3. According to claim 1, a hospital logistics management system based on digital twins is characterized in that: The third formula is used to calculate the risk value of the hardware device corresponding to the same first business data in each subsystem: P k is the total equipment risk value of the hardware equipment corresponding to the same first business data in each subsystem, Q k The total monitoring risk value of the hardware equipment corresponding to the same first business data in each subsystem.

4. A hospital logistics management system based on digital twins according to claim 3, characterized in that: Calculating the total equipment risk value of the hardware equipment corresponding to the same first business data in each subsystem includes: Obtain service life data, warranty frequency data, and failure frequency data for a single hardware device in a single subsystem; The service life data, the warranty frequency data and the failure frequency data are divided into data intervals in sequence, and each divided data interval is assigned a value to obtain a first assignment result; Based on the first assignment result, the service life data of a single hardware device is converted into a service life risk value, the warranty frequency data is converted into a warranty risk value, and the failure frequency data is converted into a failure risk value; Calculate the sum of the life risk value, the warranty risk value and the failure risk value of a single hardware device to obtain a device risk value of the single hardware device; The equipment risk values ​​of all hardware devices included in the same first business data in a single subsystem are summed to obtain the total equipment risk value of the hardware devices corresponding to the same first business data.

5. According to claim 3, a hospital logistics management system based on digital twins is characterized in that: Calculating the total monitoring risk value of the hardware device corresponding to the same first business data in each subsystem includes: Get monitoring data of a single hardware device in a single subsystem; Dividing the monitoring data into data intervals, and assigning a value to each divided data interval to obtain a second assignment result; Based on the second assignment result, the monitoring data of the single hardware device is converted into a monitoring risk value to obtain a monitoring risk value of the single hardware device; The monitoring risk values ​​of all hardware devices included in the same first business data in a single subsystem are summed to obtain the total monitoring risk value of the hardware devices corresponding to the same first business data.

6. A hospital logistics management system based on digital twins according to claim 1, characterized in that: Based on the third acquisition result, processing the remaining subsystems includes: Obtain any subsystem among all subsystems except the subsystem E and record it as subsystem F; Obtaining a correlation coefficient between the subsystem E and the subsystem F as a first correlation coefficient; Determine whether the first correlation coefficient is 0, if so, do nothing, if not, use the second method to process.

7. A hospital logistics management system based on digital twins according to claim 6, characterized in that: The second method comprises: Determine whether the first correlation coefficient is greater than a preset value. If so, process the subsystem F using the first method. If not, obtain the hardware devices corresponding to all the overlapping first service data of the subsystem E and the subsystem F as the first hardware devices. All first hardware devices included in the subsystem F are marked in the physical three-dimensional model and corresponding coordinate information is obtained to obtain a second marking result, and the subsystem F is checked based on the second marking result.

8. According to claim 1, a hospital logistics management system based on digital twins is characterized in that: Calculating the overlap of the first business data in any two data sets includes: Data set C corresponds to subsystem c, and data set D corresponds to subsystem d. It is determined whether the data set C and the data set D have the same first business data. If so, the first business data in the data set C that is the same as that in the data set D is recorded as the second business data, and the fourth formula is used to calculate the overlap between the data set C and the data set D. If not, the correlation coefficient between the subsystem c and the subsystem d is set to 0. The fourth formula includes: η is the overlap degree of the first business data in the data set C and the data set D, H C is the data volume of all first service data in the system c per unit time, H D is the data volume of all first service data in the system d per unit time, H i is the data volume of all the second business data in the subsystem c or the subsystem d per unit time, and n is the number of the second business data in the subsystem c or the subsystem d.

9. A hospital logistics management system based on digital twins according to claim 1, characterized in that: Based on the calculation results, the correlation coefficients of any subsystem with other subsystems are set as follows: All historical data of any two subsystems are obtained, and based on the overlap of the first business data corresponding to the two subsystems, a correlation model is constructed and trained, and based on the trained correlation model, a correlation coefficient is set for any two subsystems.

10. A hospital logistics management method based on digital twins, characterized in that: The method comprises the following steps: Build a physical 3D model of the hospital based on the BIM model and UE Unreal Engine; Initializing the positions of multiple hardware devices in the solid three-dimensional model and assigning coordinate information to all the hardware devices; Based on all hardware devices, data is collected and analyzed to obtain business data. All business data contains corresponding coordinate information; Acquire the hardware devices included in each subsystem to obtain a first acquisition result; based on the first acquisition result and all business data, acquire the business data included in each subsystem as first business data; store the first business data of each subsystem in a corresponding data set; calculate the overlap of the first business data in any two data sets to obtain a calculation result; and based on the calculation result, set a correlation coefficient between any subsystem and other subsystems, and all correlation coefficients are greater than or equal to 0 and less than 1; Based on all the first business data of each subsystem, a system characteristic value of each subsystem is calculated using a first formula; The first formula includes: is the system eigenvalue of each subsystem, α j is the energy consumption value of the hardware device corresponding to the same first business data in each subsystem, β k is the risk value of the hardware device corresponding to the same first business data in each subsystem, and r is the number of different first business data in each subsystem; A first threshold, a second threshold and a third threshold are set for the system characteristic value of each subsystem, and the first threshold, the second threshold and the third threshold in each subsystem are different; A single subsystem is obtained and recorded as subsystem E. When the system characteristic value of the subsystem E is less than or equal to the first threshold, no action is taken; When the system characteristic value of the subsystem E is greater than the second threshold value and less than the third threshold value, the subsystem E is processed by a first method; the first method is: annotating the hardware devices included in the subsystem E in the solid three-dimensional model to obtain a first annotation result, and based on the first business data of the subsystem E, obtaining corresponding coordinate information to obtain a second acquisition result, and checking the subsystem E based on the first annotation result and the second acquisition result; When the system characteristic value of the subsystem E is greater than or equal to the third threshold, the first method is used to process the subsystem E, and all correlation coefficients of the subsystem E are obtained to obtain a third acquisition result, and based on the third acquisition result, the remaining subsystems are processed.

Images