A dynamic thermal comfort evaluation method and system for hospital outpatient departments

Abstract

The present invention relates to the technical field of dynamic thermal comfort assessment of hospital outpatient departments, and discloses a method and system for dynamic thermal comfort assessment of hospital outpatient departments. The method comprises: dividing the hospital outpatient department into functional areas; analyzing the activities of doctors and patients in different areas to determine whether to use the RWI indicator to assess the thermal comfort of medical personnel and the PMV indicator to assess the thermal comfort of medical staff; obtaining environmental layout data and pedestrian feature data of different areas of the outpatient department to construct an intelligent agent model; combining the results obtained by simulating the model with actual environmental parameters, using the RWI indicator to assess the RWI value of medical personnel, and using the PMV indicator to calculate the PMV value of medical staff, to obtain a dynamic thermal comfort assessment result of the hospital outpatient department. The present invention can provide a more refined thermal comfort assessment result, thereby improving the standardization and refinement of the thermal environment management of the outpatient department.

Description

Technical Field

[0001] The present invention relates to the technical field of energy conservation and emission reduction, and in particular to a method and system for evaluating dynamic thermal comfort in a hospital outpatient department. Background Art

[0002] Improving the medical environment and enhancing its comfort are crucial for stabilizing patients' moods and ensuring efficient medical staff work. Improving the patient experience and promoting high-quality services are also essential requirements for further improving the medical and health service system. As large public medical facilities, hospitals have complex structures and high environmental comfort requirements, resulting in energy consumption that is three to four times higher than that of typical public buildings. Especially in hot and humid climates, the energy consumed to create a comfortable thermal environment accounts for over 50% of the total energy required for building operations. However, increasing comfort and reducing energy consumption are often contradictory concepts. Increasing comfort requires lower air conditioning set points and longer operating times, which inevitably leads to increased building energy consumption. Therefore, accurately assessing the comfort temperature of hospital users and controlling the indoor environment based on their actual thermal needs is a major challenge in hospital energy management and a crucial task in promoting the high-quality development of the medical and health service system and green buildings.

[0003] The evaluation and control of the thermal environment of hospital outpatient buildings is extremely complex. On the one hand, the functional zoning of hospitals is complex, and different areas have different environmental standards. On the other hand, as a medical facility, the user group of the hospital is very special, mainly patients and medical staff. At present, most of the evaluation methods for hospital thermal comfort use surveys to analyze the temperature preferences of specific groups and specific functional areas (operating rooms, wards, consulting rooms, etc.). Some scholars have also used building thermodynamics and airflow simulation technology to simulate the thermal comfort of hospital wards. Although these invention embodiments provide some valuable information for the control of the hospital thermal environment, there is still a certain gap in terms of the comprehensive optimization of the medical environment, and they cannot provide favorable support for the refined thermal environment management of outpatient departments. Summary of the Invention

[0004] In view of this, the present invention provides a method and system for evaluating the dynamic thermal comfort of a hospital outpatient department to solve the problem of how to improve the evaluation accuracy of the outpatient department's thermal comfort and provide favorable support for refined outpatient department thermal environment management.

[0005] In a first aspect, the present invention provides a method for evaluating dynamic thermal comfort in a hospital outpatient department, the method comprising:

[0006] Divide the hospital outpatient department into functional areas;

[0007] The activity behaviors of doctors and patients in different areas were analyzed, and based on the analysis results, the RWI index was used to evaluate the thermal comfort of medical personnel, and the PMV index was used to evaluate the thermal comfort of medical staff;

[0008] Obtaining environmental layout data and pedestrian characteristic data of different areas of the outpatient department, and building an intelligent agent model based on the environmental layout data and pedestrian characteristic data;

[0009] Based on the intelligent agent model, intelligent agent simulation is performed to obtain simulation results. The simulation results are combined with actual environmental parameters to evaluate the RWI value of medical personnel using the RWI indicator, and the PMV value of medical staff is calculated using the PMV indicator to obtain the dynamic thermal comfort evaluation results of the hospital outpatient department.

[0010] The embodiment of the present invention provides a method for evaluating the dynamic thermal comfort of a hospital outpatient department. The method first divides the hospital outpatient department into functional areas, analyzes the activity behaviors of doctors and patients in different areas, and comprehensively considers the specific behavior patterns of different functional areas and different groups of people in these areas. The RWI indicator is used to evaluate the thermal comfort of medical personnel and the PMV indicator is used to evaluate the thermal comfort of medical staff, which can fully consider the different activity characteristics and needs of the two groups of people in the outpatient department. The environmental layout data and pedestrian characteristic data of different areas of the outpatient department are obtained to construct an intelligent body model, which fully integrates various key factors related to thermal comfort. The intelligent body model is used to perform simulation to obtain simulation results, and then the thermal comfort is evaluated in combination with actual environmental parameters. The thermal environment changes of the outpatient department in different time periods and different personnel flow conditions can be simulated to achieve dynamic evaluation with high accuracy. The obtained dynamic thermal comfort evaluation results can provide theoretical support for the regional and refined management of the thermal environment of large hospital outpatient departments, help to rationally allocate resources for adjusting the thermal environment, and achieve energy conservation and emission reduction while ensuring thermal comfort.

[0011] In an optional embodiment, the area division of the hospital outpatient department includes: dividing the outpatient department into treatment areas, public areas and waiting areas based on the behavioral characteristics of medical staff and patients, medical environment design guidelines and operating characteristics of the outpatient building.

[0012] The embodiment of the present invention divides the outpatient department into regions based on comprehensive factors. Each region has its own unique thermal comfort requirements. After the regions are divided, dynamic thermal comfort assessments of different groups of people can be performed more targeted, and resources can be reasonably allocated according to the needs of different regions.

[0013] In an optional embodiment, obtaining environmental layout data and pedestrian feature data of different areas of the outpatient department, and constructing an intelligent agent model based on the environmental layout data and pedestrian feature data, includes:

[0014] Obtain floor plans and spatial layouts of different areas of the outpatient department for physical environment modeling;

[0015] Obtain the medical process of medical personnel, the number of patients seen in the outpatient department, the average duration of the consultation, and environmental monitoring data of different areas of the outpatient department for pedestrian flow modeling;

[0016] An intelligent agent model is formed based on the interaction of the physical environment modeling and the pedestrian flow modeling.

[0017] The physical environment modeling of the embodiment of the present invention takes into account the internal furnishings and indoor environment of the outpatient department, and the pedestrian flow modeling takes into account the influence of individual factors such as the patient's treatment process, clothing and activity level. The considerations are more comprehensive, which improves the accuracy and rationality of the evaluation results.

[0018] In an optional implementation, performing agent simulation based on the agent model to obtain a simulation result includes:

[0019] The model was simulated using the outpatient department's floor plan and spatial layout, the thermal resistance of patients' clothing, metabolic rate, comfortable walking speed, route selection strategy, waiting and treatment strategy, registration strategy, metabolic rate of medical staff, and thermal resistance of clothing as inputs. The simulation results included the real-time walking speed of patients and medical staff, the time spent in each area, effective metabolic rate, and effective thermal resistance of clothing.

[0020] The embodiment of the present invention utilizes input information such as the thermal resistance of clothing and metabolic rate of medical personnel and medical staff, combined with the effective metabolic rate and effective clothing thermal resistance obtained by simulation, to more accurately assess the thermal comfort needs of different personnel in various areas. Based on the results such as the time personnel stay in each area obtained by simulation, it provides rich data support for hospital managers, enabling them to reasonably allocate space and facility resources within the outpatient department.

[0021] In an optional embodiment, the method further includes:

[0022] The RWI index values ​​of medical personnel and the PMV values ​​of medical staff are matched with the preset thermal sensation scale to obtain the acceptable temperature ranges in different areas;

[0023] By analyzing the acceptable temperature ranges of medical personnel in different areas, the distribution results of RWI values ​​of medical personnel were obtained. By analyzing the acceptable temperature ranges of medical personnel and medical staff in the treatment area, the differences in thermal preferences between medical staff and medical personnel were obtained.

[0024] By analyzing the acceptable temperature ranges of medical personnel in different areas, the embodiment of the present invention obtains the distribution results of the RWI values ​​of medical personnel, which can provide a comprehensive and in-depth understanding of the thermal comfort of medical personnel in different areas of the outpatient department. By analyzing the acceptable temperature ranges of medical staff and patients in the treatment area, the difference in thermal preferences between medical staff and patients is obtained, and the difference in thermal preferences between doctors and patients is clarified, which helps to take some coordination measures in the treatment area, so as to meet the medical staff's demand for lower temperatures to ensure their work efficiency and comfort, while taking into account the thermal comfort of patients, and create a more harmonious and comfortable treatment environment.

[0025] In an optional embodiment, the method further includes: obtaining the length of stay of medical personnel during advance registration and on-site registration, standardizing the length of stay and the RWI value of the medical personnel, and dividing the medical personnel into two groups: on-site registration and advance registration, and using a group regression method to analyze the effects of registration method and length of stay on the thermal comfort of the medical personnel, and obtaining the analysis results.

[0026] By obtaining the length of time patients spend registering in advance and registering on-site, and analyzing its effect on thermal comfort, the embodiment of the present invention can clearly understand the differences between the two registration methods in terms of the patient experience. This helps hospital managers to gain an in-depth understanding of the actual conditions of patients under different registration methods, and helps to further optimize the registration process. For on-site registration, measures such as adding service windows and adopting intelligent queuing systems can be considered to shorten patient stay time and improve patients' thermal comfort and overall medical experience.

[0027] In a second aspect, the present invention provides a dynamic thermal comfort assessment system for a hospital outpatient department, comprising:

[0028] Outpatient department area division module, used to divide the hospital outpatient department into functional areas;

[0029] The thermal comfort evaluation index determination module is used to analyze the activities of doctors and patients in different areas, and based on the analysis results, determine whether to use the RWI index to evaluate the thermal comfort of medical personnel and the PMV index to evaluate the thermal comfort of medical staff;

[0030] An agent model building module is used to obtain environmental layout data and pedestrian feature data of different areas of the outpatient department, and build an agent model based on the environmental layout data and pedestrian feature data;

[0031] The dynamic thermal comfort assessment module is used to perform agent simulation based on the agent model to obtain simulation results, use the simulation results in combination with actual environmental parameters to evaluate the RWI value of medical personnel using the RWI indicator, and use the PMV indicator to calculate the PMV value of medical staff to obtain the dynamic thermal comfort assessment results of the hospital outpatient department.

[0032] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to execute the method for evaluating the dynamic thermal comfort of a hospital outpatient department according to the first aspect or any corresponding embodiment thereof.

[0033] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for evaluating the dynamic thermal comfort of a hospital outpatient department according to the first aspect or any corresponding embodiment thereof.

[0034] In a fifth aspect, the present invention provides a computer program product comprising computer instructions for causing a computer to execute the method for evaluating dynamic thermal comfort in a hospital outpatient department according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 is a flow chart of a method for evaluating dynamic thermal comfort in a hospital outpatient department according to an embodiment of the present invention;

[0037] Figure 2 is a flow chart of another method for evaluating dynamic thermal comfort in a hospital outpatient department according to an embodiment of the present invention;

[0038] Figure 3 (a) is a diagram showing the distribution of relative thermal comfort values ​​of medical personnel according to an embodiment of the present invention;

[0039] Figure 3 (b) is a diagram showing the distribution of relative thermal comfort values ​​of medical staff according to an embodiment of the present invention;

[0040] Figure 4(a) is a schematic diagram showing the difference in exposure time under different registration methods according to an embodiment of the present invention;

[0041] Figure 4 (b) is a schematic diagram of the regulatory effect of the registration method;

[0042] Figure 5 A structural block diagram of a dynamic thermal comfort evaluation system for a hospital outpatient department according to an embodiment of the present invention;

[0043] Figure 6 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0045] The assessment of thermal comfort in an outpatient department must not only consider the environmental factors of different functional areas but also comprehensively analyze the differences between patients and doctors, such as activity level, length of stay in different areas, and the impact of the thermal environment they experience. Failure to comprehensively incorporate these factors into the analysis may affect the accuracy of the outpatient department's dynamic thermal comfort assessment. Existing technologies and invention embodiments largely ignore the transitions between patients in different functional areas and the differences between patients and doctors.

[0046] First, existing assessment techniques fail to account for differences in activity levels between patients and physicians. During a medical consultation, patients engage in a variety of activities, such as queuing for appointments and signing in. They also walk and stand at varying speeds in public areas. Physicians, on the other hand, often work from a sitting or standing position, resulting in different activity and metabolic rates between physicians and patients. Failure to account for these differences in activity and metabolic activity may impede accurate assessment of their thermal comfort needs in different states.

[0047] Secondly, existing thermal comfort assessment technologies cannot take into account the transition and length of stay of patients in different functional areas. During the medical consultation process, patients enter the outpatient department from the outdoor environment, pass through the functional areas of the outpatient department with different temperatures, and make short stops in different areas. They experience a non-steady-state thermal environment. Doctors, on the other hand, stay in the consulting room for a long time and experience a steady-state thermal environment. Studies have shown that due to the shorter stay time, individuals exhibit a larger thermal capacity range in the transition space. If the patient's conversion and transition behavior between different functional areas is ignored and the changes in the patient's experience of the thermal environment and the length of stay are not included in the analysis, it will be impossible to provide favorable support for the precise and refined management of the outpatient department's thermal environment.

[0048] Thirdly, existing assessment techniques fail to consider the impact of the patient's medical process. Outpatient registration channels in major Chinese hospitals are primarily divided into two categories: on-site registration and advance registration. Advance registration patients are required to report and wait in advance, while on-site patients do not need to check in. Therefore, different registration methods involve different medical sequences. Previous patents and research have not considered the relationship between a patient's medical sequence, length of stay, and their thermal perception, resulting in a lack of evidence for optimizing the medical process and the outpatient department's thermal environment.

[0049] An embodiment of the present invention provides an embodiment of a method for evaluating the dynamic thermal comfort of a hospital outpatient department. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0050] In this embodiment, a method for evaluating the dynamic thermal comfort of a hospital outpatient department is provided. Figure 1 FIG. 1 is a flow chart of a method for evaluating dynamic thermal comfort in a hospital outpatient department according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0051] S101, divide the hospital outpatient department into functional areas.

[0052] This embodiment of the present invention divides the outpatient department into functional areas for the purpose of refined thermal management. Specifically, based on the behavioral characteristics of medical staff and patients, medical environment design guidelines, and the operational characteristics of the outpatient building, the outpatient department is divided into three areas: a diagnosis and treatment area, a public area, and a waiting area.

[0053] Specifically, the outpatient building's primary user base consists primarily of patients (excluding emergency patients) and their accompanying personnel. Patients typically complete their treatment independently or with the company of family or friends. Before visiting a doctor, they must first make an appointment. There are two common methods for making an appointment: advance registration (via the hospital's official website, WeChat official account, or by phone) and on-site registration. Patients who register in advance typically sign in at a self-service kiosk ten minutes in advance and then proceed to the waiting area to queue. Patients who register on the same day do not need to report to the clinic. Patients moving around slowly during appointment registration, check-in, and the waiting area are typically standing or sitting while waiting. After completing their consultation in the clinic, they return to the public area to complete activities such as paying bills and picking up medications. During their visit, not only does a patient's activity level change depending on the hospital's functional areas, but the thermal environment they experience also undergoes significant variations. Patients first enter the outpatient department's public areas, such as the consultation hall, from the scorching outdoors, and then proceed to the waiting area and treatment area. According to the Chinese General Hospital Building Design Code (GB51039-2022), the design temperature of outpatient department air conditioning should not exceed 26°C in summer, and the air conditioning temperature in the examination room should be 1°C to 2°C higher than that in the waiting area. Therefore, the thermal environment experienced by patients is dynamic and non-steady.

[0054] Medical staff in outpatient departments (mainly doctors) generally work in a sitting position and are less active. They mainly provide various medical and health services to patients in diagnosis and treatment and medical work areas, and are exposed to a stable thermal environment for a long time.

[0055] The outpatient department provides diagnosis, treatment, and consultation services to patients. Based on its functional use, the outpatient building is primarily composed of two areas: diagnosis and treatment space and public space, with transitional spaces connecting the two. The public space is the open area most directly serving patients and includes areas such as the outpatient lobby, rest areas, and restrooms. It provides patients with pre- and post-treatment services, including registration, pre-examination and triage, and billing. The diagnosis and treatment space consists of three parts: the waiting area, the diagnosis and treatment area, and the medical and nursing work area. The waiting area is for patients and their accompanying personnel to wait for medical treatment. The diagnosis and treatment area consists of several examination rooms. The medical and nursing work area is used for medical support and consists of offices, lounges, and other areas. In terms of the user groups of each area, the public space and waiting area are primarily used by patients and their accompanying personnel. The diagnosis and treatment area, on the other hand, is primarily used by medical staff, with patients and their accompanying personnel only staying briefly. Therefore, the embodiments of the present invention take into account the activity levels of patients and the user groups of different areas and divide the outpatient department into three parts: the diagnosis and treatment area, the public space, and the waiting area.

[0056] S102, analyzing the activities of doctors and patients in different areas, and based on the analysis results, determining to use the RWI indicator to evaluate the thermal comfort of medical personnel and the PMV indicator to evaluate the thermal comfort of medical staff.

[0057] Specifically, thermal comfort is a subjective feeling people have about the thermal environment. For steady-state environments, the PMV model (Predicted Mean Vote) is currently the most representative thermal comfort evaluation indicator and has been widely used. The PMV model expression, such as formula (1), is only applicable to people with a constant metabolic rate who are exposed to a steady-state thermal environment for a long time. Under real-world conditions, transition intervals where people stay for a short time are often encountered. This transition interval may connect two spaces with different thermal environment parameters such as air temperature and humidity. In this case, there is a certain deviation in the assessment of human thermal comfort based on PMV.

[0058] PMV=[0.303exp(-0.36M)+0.028]{MW-3.05×[5.733-0.000699(MW)≤

[0059] -P a ]-0.42[(MW)-58.15]-0.0173M(5.867-P a )-0.0014M(34-t a )-3.96

[0060] ×10 -3 f cl [(t cl +273) 4 -(t r +273) 4 ]-f cl h c (t cl -t a )}(1)

[0061] Where: M is the metabolic rate of the human body, W / m 2 ; W is the mechanical work done by the human body, W / m 2 ;P a is the partial pressure of water vapor around the human body, Pa; f cl is the clothing area coefficient, clo; t a is the indoor ambient air temperature, °C; t r is the average indoor radiation temperature, °C; t cl is the average temperature of the human body surface, °C; h c is the convection heat release coefficient, W / m 2 ℃;

[0062] For non-steady-state thermal environments, the Relative Warmth Index (RWI) was proposed by the U.S. Department of Transportation to determine the thermal environment of subway station platforms, concourses, and trains. This index takes into account the time it takes for the human body to switch between different scenarios within the transition space. Its core concept is that when the human body transitions from one activity state to another, the metabolic rate and clothing thermal resistance change, and it takes 6 minutes to reach the latest stable value. During this transition process, the metabolic rate and clothing thermal resistance are linearly related, as expressed below:

[0063]

[0064] Where: M is metabolic rate, W / m 2 ; τ is the time spent in the transition process, s; T a is the dry bulb temperature of the ambient air, °C; I cw is the thermal resistance of clothing, clo; I a is the thermal resistance of the air boundary layer outside the clothing, clo; R ​​is the average radiant heat per unit skin area, W / m 2 ;P v is the water vapor partial pressure, Pa;

[0065]

[0066]

[0067] Where: M1 is the metabolic rate at the beginning of the state, W / m 2 ; M2 is the metabolic rate at the end of the state; I1 is the thermal resistance of the clothes at the beginning of the state, clo; I2 is the thermal resistance of the clothes at the end of the state, clo.

[0068] During the medical consultation process, medical personnel shuttle between different functional areas of the outpatient department. Different areas are connected to two spaces with different thermal environment parameters such as air temperature and humidity. Therefore, the embodiment of the present invention uses the relative thermal index (RWI) indicator to evaluate the thermal comfort of medical personnel; for medical staff, they work in a sitting position in the clinic for a long time and are in a steady-state environment for a long time. Therefore, the PMV indicator is used to evaluate the comfort of medical personnel.

[0069] S103, obtaining environmental layout data and pedestrian feature data of different areas of the outpatient department, and building an intelligent agent model based on the environmental layout data and pedestrian feature data.

[0070] Specifically, the embodiment of the present invention adopts the Agent-based Model, which is an individual-based modeling method that can comprehensively consider the physical environment of the hospital outpatient department (outpatient department floor plan, layout and furnishings of spaces such as self-service machines, indoor environment, etc.) and pedestrian characteristics (medical process, walking speed, route selection, etc.) and their interactions. The modeling process is divided into two parts: physical environment modeling and pedestrian flow modeling, and the parameters of the model are set according to the actual situation of the case. In the embodiment of the present invention, the physical environment modeling takes into account the internal furnishings and indoor environment of the outpatient department, and the pedestrian flow modeling takes into account the influence of individual factors such as the patient's medical process, clothing and activity level. The comprehensive consideration of factors improves the accuracy and rationality of the evaluation results.

[0071] S104, performing agent simulation based on the agent model to obtain simulation results, using the simulation results in combination with actual environmental parameters to evaluate the RWI value of medical personnel using the RWI indicator, and using the PMV indicator to calculate the PMV value of medical staff, to obtain the dynamic thermal comfort evaluation results of the hospital outpatient department.

[0072] Specifically, this embodiment of the present invention uses an agent-based model to capture the dynamic changes in patients' walking speed and dwell time in different areas during their medical consultations. It then uses the RWI metric to assess patients' thermal comfort under different temperature settings. Environmental and individual variables that influence physicians' thermal comfort, such as temperature, relative humidity, and clothing thermal resistance, were collected through field surveys. The PMV tool developed by Tartarini et al. was then used to calculate the thermal comfort of medical staff.

[0073] The embodiment of the present invention uses the RWI indicator to evaluate the thermal comfort of medical personnel and the PMV indicator to evaluate the thermal comfort of medical staff, which can fully take into account the different activity characteristics and needs of the two groups of people in the outpatient department; obtains the environmental layout data of different areas of the outpatient department and pedestrian characteristic data to construct an intelligent model, fully integrates various key factors related to thermal comfort, uses the intelligent model to perform simulation to obtain simulation results, and then evaluates thermal comfort in combination with actual environmental parameters. It can simulate the changes in the thermal environment of the outpatient department in different time periods and different personnel flow conditions, and realize dynamic evaluation with high accuracy. The obtained dynamic thermal comfort evaluation results can provide theoretical support for the regional and refined management of the thermal environment of the outpatient department of large hospitals, help to rationally allocate resources for adjusting the thermal environment, and achieve energy conservation and emission reduction while ensuring thermal comfort.

[0074] This embodiment also provides a method for evaluating dynamic thermal comfort in a hospital outpatient department. The process includes the following steps:

[0075] S201, divide the hospital outpatient department into functional areas.

[0076] Specifically, such as Figure 2 As shown, this embodiment of the present invention divides the outpatient department into three areas: a treatment area, a public area, and a waiting area based on the behavioral characteristics of medical staff and employees, medical environment design guidelines, and the operational characteristics of the outpatient building. The specific analysis process is described in step S101 above and will not be repeated here.

[0077] S202: Analyze the activities of doctors and patients in different areas. Based on the analysis results, determine whether to use the RWI indicator to evaluate the thermal comfort of medical personnel and the PMV indicator to evaluate the thermal comfort of medical staff. For details, refer to the description of step S102 above and will not be repeated here.

[0078] S203, obtaining environmental layout data and pedestrian feature data of different areas of the outpatient department, and constructing an intelligent agent model based on the environmental layout data and pedestrian feature data.

[0079] Specifically, the present invention uses data collected from a large comprehensive hospital in Guangzhou as a modeling example. The main building, spanning floors 1 to 5, has a construction area of ​​84,581 square meters. The hospital sees an average of approximately 200 doctors per day, with an average daily outpatient volume exceeding 8,000. Daily consultation hours are 8:00 AM to 11:00 AM and 2:00 PM to 4:30 PM. Floor 1 has five entrances and exits, serving as a public area such as the outpatient lobby. It features 12 manual registration windows and 16 self-service kiosks for registration, check-in, and payment. Floors 2-5 primarily house outpatient departments and waiting areas, totaling over 140 rooms and 53 auxiliary rooms. Floors 3-5 are equipped with 10, 4, and 8 self-service kiosks for registration and check-in services, respectively. To maintain a favorable indoor thermal environment, the hospital consumes approximately 49.8065 million kW·h of electricity annually, primarily for the air conditioning system. The indoor environment of the clinic was measured using a thermohygrometer (FLUKE971, accuracy: ±0.5%) and an anemometer (HIMA 856). The measuring instruments were installed 1.1 meters above the ground. The test time was 11:00 am, with an outdoor ambient temperature of 31°C and a relative humidity of 65%. Dry-bulb temperature (Ta), relative humidity (RH), and air velocity (Va) were measured in three main areas. The results are shown in Table 1. The average indoor temperatures in the public area, waiting area, and treatment area were 26.30°C, 24.30°C, and 26.10°C, respectively, and the average air humidity was 35.1%, 43.50%, and 39.50°C.

[0080] Table 1 Measurement results of thermal environment in Dongchuan outpatient clinic

[0081]

[0082] S204, performing agent simulation based on the agent model to obtain simulation results, using the simulation results in combination with actual environmental parameters to evaluate the RWI value of medical personnel using the RWI indicator, and using the PMV indicator to calculate the PMV value of medical staff, to obtain a dynamic thermal comfort evaluation result of the hospital outpatient department.

[0083] Specifically, the embodiment of the present invention uses AnyLogic software to simulate dynamic thermal comfort. The model inputs are the thermal resistance of medical personnel's clothing, comfortable walking speed, route selection strategy, waiting and treatment strategy, and registration and appointment strategy. The walking speed of medical personnel is between 0.8-1.6m / s, showing a normal distribution, and the walking distance is between 0.300-0.450m. Summer clothes are usually short-sleeved, short or skirts, and the thermal resistance of clothes is generally around 0.5clo. The embodiment of the present invention sets the initial thermal resistance of patients' clothing to (0.500clo; σ=0.100). For the registration queue, the embodiment of the present invention selects according to the principle of proximity and shortest queue. For route selection strategies such as stairs or escalators, the embodiment of the present invention sets it to random selection at the nearest location. For the registration method, the embodiment of the present invention sets it in proportion based on the survey results, and the ratio of on-site registration and advance registration is approximately 3:7. The patient's real-time walking speed, time spent in each area, effective metabolic rate, and effective clothing thermal resistance are used as simulation outputs. Combined with the environmental parameters measured on site, the RWI indicator is used to calculate the patient's dynamic thermal comfort status.

[0084] For medical staff, the thermal resistance of their professional uniforms is usually about 0.650clo. Therefore, in the embodiment of the present invention, the thermal resistance of the doctor's clothes is set to (0.650clo, σ=0.1). According to ISO 8996:2021 issued by the International Energy Agency, the metabolic rates of sitting relaxation and sitting activity are 58.150W / m 2 , 69.780W / m 2 Therefore, the embodiment of the present invention sets the doctor's metabolic rate to 58.15W / m 2 -69.78W / m 2 For the environmental variables that affect thermal comfort, the embodiment of the present invention uses field surveys to obtain them, and then uses the PMV index to calculate the thermal comfort of medical staff.

[0085] The embodiment of the present invention captured the dynamic changes of patients visiting the hospital for about 2 hours, and output data of 3,600 patients and thermal comfort data of 140 doctors. The mean values ​​of the three areas are shown in Table 2. Comparing the patients' stay time in the three areas, it was found that the patients stayed in the public area for the longest time, followed by the waiting area and the treatment area, with mean stay times of 932.236s, 706.027s and 657.807s respectively. The walking speed varies with the individual activity sequence. The average walking speed in the public area is 0.907m / s. Since the patients are basically sitting in the waiting area and the treatment area, the output results of the model are all 0m / s.

[0086] Table 2 Observation and simulation results for different regions

[0087]

[0088] S205, the RWI index value of the medical personnel and the PMV value of the medical staff are matched with the preset thermal sensation scale to obtain the acceptable temperature ranges of different areas; by analyzing the acceptable temperature ranges of the medical personnel in different areas, the distribution results of the RWI values ​​of the medical personnel are obtained, and by analyzing the acceptable temperature ranges of the medical personnel and the medical staff in the treatment area, the difference results of the thermal preferences between the medical staff and the medical personnel are obtained.

[0089] Specifically, the present invention aligns the patient's RWI and the healthcare worker's PMV with the ASHRAE Thermal Perception Scale, defining temperatures between slightly cold and slightly hot as the acceptable temperature range. Specifically, RWI values ​​range from 0 to 1.5, and PMV values ​​range from -0.5 to 0.5. RWI values ​​closer to 0.8 indicate a closer approach to thermoneutrality, while PMV values ​​closer to 0 indicate a closer approach to thermoneutrality.

[0090] The results of the RWI distribution of medical personnel analyzed in the embodiment of the present invention include: the RWI values ​​in the public area are more dispersed and have the largest span, and the RWI values ​​of medical personnel in the waiting area and the treatment area have significant statistical differences at the same temperature. Figure 3As shown in (a), the range and overall distribution of thermal comfort levels in public areas are more dispersed and have a wider range than those in waiting and treatment areas. This indicates that even at the same temperature, there are significant differences in thermal sensations among medical personnel in public areas, meaning that thermal environment management is most difficult in public areas. Comparing the RWI values ​​in public, waiting, and treatment areas reveals that at the same temperature, the RWI values ​​of medical personnel in the waiting area are significantly higher than those in the public area. In public areas, medical personnel are in a mobile state, while in the waiting area, most medical personnel are sitting, and the comfortable temperature decreases significantly with reduced physical activity. In public areas, at 24°C, the RWI average was 0.132. At this time, the number of people in the acceptable temperature range was the largest, with a frequency of 54.08% and an RWI average of 0.132; the second highest temperature was 25°C, with an RWI average of 0.159 and a frequency of 38.79% in the acceptable temperature range; at 26°C and 27°C, the RWI averages were 0.187 and 0.215 respectively. At this time, only 25.66% and 12.32% of the people were in the acceptable temperature range respectively.

[0091] Because patients' activities in the waiting area and treatment area are similar, the RWI distribution in the two areas is similar. Comparing the RWI values ​​in the waiting area and treatment area revealed that, at the same temperature, the RWI values ​​of patients in the waiting area were slightly higher than those in the treatment area. To determine whether there was a statistical difference in thermal comfort between patients in the waiting area and the treatment room, a paired sample T-test was conducted on the RWI values. The results showed that there was a statistically significant difference in the RWI values ​​between patients in the waiting area and the treatment area (t = 25.985, p < 0.05). In the waiting area, the highest frequency of patients falling within the acceptable temperature range was 25°C, with a frequency of 92.04% and a mean RWI of 0.0853. This was followed by 26°C, with a frequency of 83.02% and a mean RWI of 0.112. At 27°C, 62.59% of patients fell within the acceptable temperature range, with a mean RWI of 0.140. This was lowest at 24°C, with a frequency of only 36.61% and a mean RWI of 0.059. Within the clinic, the highest frequency of patients falling within the acceptable temperature range was 26°C, with a frequency of 71.950% and a mean RWI of 0.097. This was followed by 25°C, with a frequency of 71.889% and a mean RWI of 0.068. At 24 and 27°C, the frequencies of patients falling within the acceptable temperature range were 62.501% and 61.176%, respectively, with means of 0.040 and 0.123, respectively.

[0092] The distribution of thermal comfort status of medical staff at different temperatures is as follows Figure 3(b) A comparison of the thermal perception of medical staff and patients in the treatment area reveals that medical staff tend to feel warmer at the same temperature setting. For example, at 25°C, the PMV value of medical staff approaches 0, while the mean RWI of patients at 26°C is closer to 0.8, indicating that they are closer to thermoneutral at 26°C. This reflects the difference in thermal preferences between medical staff and patients, with medical staff preferring lower temperature settings in the examination room. At 25°C, the frequency of medical staff falling within the acceptable thermal range was highest, at 97.457%, with a mean PMV of 0.107. This was followed by 24°C, where 96.610% of medical staff fell within the acceptable thermal range, with a mean PMV of -0.077. At 26°C and 27°C, 87.288% and 62.712% of medical staff fell within the acceptable thermal range, with mean PMVs of 0.279 and 0.453, respectively.

[0093] S206, obtain the length of stay of medical personnel in advance registration and on-site registration, standardize the length of stay and the RWI value of medical personnel, and divide medical personnel into two groups: on-site registration and advance registration. Use group regression method to analyze the effect of registration method and length of stay on the thermal comfort of medical personnel, and obtain the analysis results.

[0094] Specifically, the embodiment of the present invention conducted an independent sample test on the length of stay of medical personnel who registered in advance and registered on site, such as Figure 4 As shown in (a), the results show a significant statistical difference in the length of stay between those who registered in advance and those who registered on-site in the public area (t = -7.270, p = 0.001), reflecting the impact of registration method on patient treatment time. Patients who registered in advance spent significantly less time in the public area (mean M = 608.839, variance SD = 258.748) than those who registered on-site (mean M = 667.661, variance SD = 164.206). This indicates that pre-registration significantly reduces patient treatment time, indicating that patients' thermal comfort levels may be affected by registration method. No significant statistical difference was found between those who registered in advance and those who registered on-site in the waiting area and treatment area.

[0095] In order to explore the impact of registration method and stay time on patient thermal comfort, the present invention first standardized the stay time and the patient's RWI value. Due to the different dimensions and magnitudes of the stay time and RWI data, the present invention used the z-score method to standardize the data to eliminate this difference. The z-score method standardization formula is:

[0096]

[0097] Among them, X is the standardized value, Xi is the initial sample value, u is the mean value of the original sample, and σ is the standard deviation of the original sample.

[0098] Furthermore, the patients were divided into two groups: on-site registration and advance registration, and the group regression method was used to further analyze the effects of registration methods and stay time on patients' thermal comfort. Among them, group regression was used to examine the differences between the two groups, that is, the differences in the results of the regression model in different groups. The results showed that the stay time negatively affected the patients' thermal comfort level at a statistical level of 0.001, with a coefficient of -0.157. This shows that as the consultation time increases, the patients' thermal comfort in public areas will be significantly reduced. In addition, the registration method plays an important regulatory role in the relationship between the patients' stay time and thermal comfort level. The regulatory effect is as follows: Figure 4 (b) In the on-site registration group, the coefficient for length of stay was -0.138, significant at the 0.01 level. In the advance registration group, the relationship between length of stay and patient thermal comfort remained significant at the 0.01 level, with a coefficient of -0.156, significantly smaller than that of the on-site registration group. This indicates that advance registration can shorten patient consultation time, thereby improving patient thermal comfort. Therefore, improving the medical process and shortening consultation time are important ways to improve comfort levels in outpatient clinics.

[0099] The embodiment of the present invention makes the evaluation results more accurate by incorporating the medical treatment process under different registration methods into the thermal comfort assessment process, and can deeply analyze the impact of registration methods and medical treatment processes on patients' thermal comfort levels, and can provide a management basis for optimizing the medical treatment process of outpatient departments.

[0100] This embodiment also provides a dynamic thermal comfort assessment system for hospital outpatient departments. This system is used to implement the aforementioned embodiments and preferred implementations, and details already described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the systems described in the following embodiments are preferably implemented using software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0101] This embodiment provides a dynamic thermal comfort evaluation system for hospital outpatient departments. Figure 5 As shown, including:

[0102] The outpatient department area division module 501 is used to divide the hospital outpatient department into functional areas;

[0103] Thermal comfort evaluation index determination module 502 is used to analyze the activities of doctors and patients in different areas and, based on the analysis results, determine whether to use the RWI index to evaluate the thermal comfort of medical personnel and the PMV index to evaluate the thermal comfort of medical staff;

[0104] An agent model building module 503 is used to obtain environmental layout data and pedestrian feature data of different areas of the outpatient department, and to build an agent model based on the environmental layout data and pedestrian feature data;

[0105] The dynamic thermal comfort assessment module 504 performs agent simulation based on the agent model to obtain simulation results. The simulation results are combined with actual environmental parameters to evaluate the RWI value of medical personnel using the RWI indicator, and the PMV value of medical staff is calculated using the PMV indicator to obtain the dynamic thermal comfort assessment results of the hospital outpatient department.

[0106] In some optional implementations, dividing the hospital outpatient department into regions includes:

[0107] Based on the behavioral characteristics of medical staff and patients, medical environment design guidelines and the operational characteristics of the outpatient building, the outpatient department is divided into treatment areas, public areas and waiting areas.

[0108] In some optional implementations, the agent model building module 503 includes:

[0109] The physical environment modeling unit is used to obtain the floor plans and spatial layouts of different areas of the outpatient department for physical environment modeling;

[0110] The pedestrian flow modeling unit is used to obtain the medical process of medical personnel, the number of patients received by the outpatient department, the average duration of the consultation, and the environmental monitoring data of different areas of the outpatient department for pedestrian flow modeling;

[0111] An intelligent agent model building unit is used to form an intelligent agent model based on the interaction between the physical environment modeling and the pedestrian flow modeling.

[0112] In some optional implementations, performing agent simulation based on the agent model to obtain a simulation result includes:

[0113] The model was simulated using the outpatient department's floor plan and spatial layout, the thermal resistance of patients' clothing, metabolic rate, comfortable walking speed, route selection strategy, waiting and treatment strategy, registration strategy, metabolic rate of medical staff, and thermal resistance of clothing as inputs. The simulation results included the real-time walking speed of patients and medical staff, the time spent in each area, effective metabolic rate, and effective thermal resistance of clothing.

[0114] In some optional embodiments, the system further comprises:

[0115] The acceptable temperature range analysis unit is used to match the RWI index value of medical personnel and the PMV value of medical staff with the ASHRAE thermal sensation scale to obtain the acceptable temperature range of different areas;

[0116] The thermal comfort analysis unit is used to obtain the distribution results of the RWI values ​​of medical personnel by analyzing the acceptable temperature ranges of medical personnel in different areas, and to obtain the differences in thermal preferences between medical personnel and medical staff by analyzing the acceptable temperature ranges of medical personnel and medical staff in the treatment area.

[0117] In some optional embodiments, the system further comprises:

[0118] The registration method and thermal comfort analysis unit is used to obtain the length of stay of medical personnel during advance registration and on-site registration, standardize the length of stay and the RWI values ​​of medical personnel, and divide medical personnel into two groups: on-site registration and advance registration. The group regression method is used to analyze the effects of registration method and length of stay on the thermal comfort of medical personnel, and the analysis results are obtained.

[0119] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0120] The dynamic thermal comfort assessment system for the hospital outpatient department in this embodiment is presented in the form of functional units, where the units refer to ASIC (Application Specific Integrated Circuit) circuits, processors and memories that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0121] The embodiment of the present invention also provides a computer device having the above Figure 5 The evaluation system of dynamic thermal comfort in hospital outpatient department is shown.

[0122] See also Figure 6 , Figure 6 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 6 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 6A processor 10 is taken as an example.

[0123] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0124] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0125] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0126] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0127] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0128] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor central control system or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0129] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0130] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for evaluating dynamic thermal comfort in a hospital outpatient department, characterized in that: include: Divide the hospital's outpatient department into functional areas, including: dividing the outpatient department into treatment areas, public areas, and waiting areas based on the behavioral characteristics of medical staff and patients, medical environment design guidelines, and the operational characteristics of the outpatient building; The activity behaviors of doctors and patients in different areas were analyzed, and based on the analysis results, the RWI index was used to evaluate the thermal comfort of medical personnel, and the PMV index was used to evaluate the thermal comfort of medical staff; Obtaining environmental layout data and pedestrian characteristic data of different areas of the outpatient department, and building an intelligent agent model based on the environmental layout data and pedestrian characteristic data, including: Obtain floor plans and spatial layouts of different areas of the outpatient department for physical environment modeling; Obtain the medical process of medical personnel, the number of patients seen in the outpatient department, the average duration of the consultation, and environmental monitoring data of different areas of the outpatient department for pedestrian flow modeling; forming an agent model based on the interaction of the physical environment modeling and the pedestrian flow modeling; Performing an agent simulation based on the agent model to obtain a simulation result, using the simulation result in combination with actual environmental parameters using the RWI indicator to evaluate the RWI value of medical personnel, and using the PMV indicator to calculate the PMV value of medical personnel, to obtain a dynamic thermal comfort evaluation result of the hospital outpatient department; performing an agent simulation based on the agent model to obtain a simulation result includes: The model was simulated using the outpatient department's floor plan and spatial layout, the patient's clothing thermal resistance, metabolic rate, comfortable walking speed, route selection strategy, waiting and treatment strategy, and registration strategy, as well as the metabolic rate and clothing thermal resistance of the medical staff. The simulation results included the patient's and the medical staff's real-time walking speed, the time spent in each area, the effective metabolic rate, and the effective clothing thermal resistance. The RWI index values ​​of medical personnel and the PMV values ​​of medical staff are matched with the preset thermal sensation scale to obtain the acceptable temperature ranges in different areas; By analyzing the acceptable temperature ranges of medical personnel in different areas, the distribution results of RWI values ​​of medical personnel were obtained. By analyzing the acceptable temperature ranges of medical personnel and medical staff in the treatment area, the differences in thermal preferences between medical staff and medical personnel were obtained.

2. The method according to claim 1, characterized in that Also includes: The length of stay of medical personnel in advance registration and on-site registration was obtained, the stay time and the RWI values ​​of medical personnel were standardized, and medical personnel were divided into two groups: on-site registration and advance registration. The group regression method was used to analyze the effects of registration method and stay time on the thermal comfort of medical personnel, and the analysis results were obtained.

3. A dynamic thermal comfort evaluation system for hospital outpatient departments, characterized in that: include: The outpatient department area division module is used to divide the hospital outpatient department into functional areas, including: Based on the behavioral characteristics of medical staff and patients, medical environment design guidelines and the operational characteristics of the outpatient building, the outpatient department is divided into treatment areas, public areas and waiting areas; The thermal comfort evaluation index determination module is used to analyze the activities of doctors and patients in different areas, and based on the analysis results, determine whether to use the RWI index to evaluate the thermal comfort of medical personnel and the PMV index to evaluate the thermal comfort of medical staff; The intelligent agent model building module is used to obtain the environmental layout data and pedestrian characteristic data of different areas of the outpatient department, and build an intelligent agent model based on the environmental layout data and pedestrian characteristic data, including: The physical environment modeling unit is used to obtain the floor plans and spatial layouts of different areas of the outpatient department for physical environment modeling; The pedestrian flow modeling unit is used to obtain the medical process of medical personnel, the number of patients received by the outpatient department, the average duration of the consultation, and the environmental monitoring data of different areas of the outpatient department for pedestrian flow modeling; an agent model building unit, configured to form an agent model based on the interaction between the physical environment modeling and the pedestrian flow modeling; A dynamic thermal comfort assessment module is configured to perform agent simulation based on the agent model to obtain simulation results, use the simulation results in combination with actual environmental parameters to evaluate the RWI values ​​of medical personnel using the RWI indicator, and use the PMV indicator to calculate the PMV values ​​of medical personnel to obtain dynamic thermal comfort assessment results of the hospital outpatient department. The simulation results obtained by performing agent simulation based on the agent model include: The model was simulated using the outpatient department's floor plan and spatial layout, the patient's clothing thermal resistance, metabolic rate, comfortable walking speed, route selection strategy, waiting and treatment strategy, and registration strategy, as well as the metabolic rate and clothing thermal resistance of the medical staff. The simulation results included the patient's and the medical staff's real-time walking speed, the time spent in each area, the effective metabolic rate, and the effective clothing thermal resistance. The acceptable temperature range analysis unit is used to match the RWI index value of medical personnel and the PMV value of medical staff with the ASHRAE thermal sensation scale to obtain the acceptable temperature range of different areas; The thermal comfort analysis unit is used to obtain the distribution results of the RWI values ​​of medical personnel by analyzing the acceptable temperature ranges of medical personnel in different areas, and to obtain the differences in thermal preferences between medical personnel and medical staff by analyzing the acceptable temperature ranges of medical personnel and medical staff in the treatment area.

4. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the dynamic thermal comfort assessment method for a hospital outpatient department according to any one of claims 1 to 2 by executing the computer instructions.

5. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for evaluating dynamic thermal comfort of a hospital outpatient department according to any one of claims 1 to 2.

6. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for evaluating dynamic thermal comfort of a hospital outpatient department according to any one of claims 1 to 2.

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