Intelligent monitoring method for environment temperature data of pediatric department

Abstract

The invention relates to the technical field of hospital temperature monitoring, in particular to an intelligent monitoring method for environment temperature data of pediatric departments, which comprises the following steps: dividing a plurality of different departments based on the pediatric department, determining the theoretical temperature range of each department, and collecting the temperature data of each department; comparing the theoretical temperature range with the temperature data to construct an abnormal temperature set of each department, calculating the temperature abnormity possibility, and determining temperature fluctuation characteristics through the abnormal temperature set; correcting the temperature abnormity possibility according to the temperature fluctuation characteristics, and screening to obtain a normal temperature department and an abnormal temperature department; analyzing temperature data of a temperature anomaly department to obtain the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation and control, and calculating the anomaly credibility in combination with the possibility of temperature interference and the possibility of normal temperature regulation and control; when the abnormal credibility is greater than a judgment threshold value, determining that a real temperature abnormal condition occurs in the current analysis department; accurate temperature monitoring of different types of departments is realized, and the accuracy of temperature monitoring is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hospital temperature monitoring, and particularly to an intelligent monitoring method for environmental temperature data in pediatric departments. Background Art

[0002] In pediatric departments of hospitals, due to children being in different age stages, there are significant differences in their adaptability to and requirements for environmental temperature. The age groups include infants, preschool children, and school-age children, and their immune capabilities against viruses and other pathogens also vary. Therefore, the control of environmental temperature data in pediatric departments needs to be more precise and meticulous than in other departments. Moreover, to ensure the comfort and health of children, it is necessary to continuously monitor the environmental temperature data in pediatric departments to promptly detect abnormal temperature conditions and adopt corresponding regulation strategies to maintain an appropriate environmental temperature.

[0003] Currently, the method commonly used for abnormal monitoring of temperature data in pediatric departments is to achieve it through an environmental temperature monitoring system. When an abnormal temperature is detected, the system will send a temperature regulation signal to the temperature regulation control system, i.e., the temperature control system, so as to achieve timely regulation of the temperature. However, this method mainly relies on the temperature change data within a single department and cannot achieve temperature regulation for different departments according to the regulation principle. Additionally, due to the movement of personnel between different departments, this monitoring method is easily interfered with, affecting the accuracy and reliability of temperature monitoring. Summary of the Invention

[0004] In order to solve the technical problems that the existing monitoring method has strong monitoring limitations and is easily interfered by human factors, affecting the monitoring accuracy, the purpose of the present invention is to provide an intelligent monitoring method for environmental temperature data in pediatric departments, and the specific technical solutions adopted are as follows: Based on pediatrics, divide into several different departments, determine the theoretical temperature range of each department, and collect the temperature data of each department; Compare the theoretical temperature range with the temperature data to construct the abnormal temperature set of each department, obtain the frequency of abnormal temperature occurrence to get the temperature abnormality possibility, and determine the temperature fluctuation characteristics through the abnormal temperature set; Correct the temperature abnormality possibility according to the temperature fluctuation characteristics and conduct screening to respectively determine the departments with normal temperature and the departments with abnormal temperature; Analyze the temperature data of the departments with abnormal temperature to obtain the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation, and combine the two to calculate the abnormal credibility; Set a judgment threshold. When the abnormal credibility is greater than the judgment threshold, it is determined that there is a real temperature abnormality in the currently analyzed department.

[0005] Preferably, the abnormal temperature set of each department is constructed by comparing the theoretical temperature range with the temperature data, the frequency of the abnormal temperature appearance is obtained to get the temperature abnormality possibility, and the temperature fluctuation characteristics are determined through the abnormal temperature set, including: When the temperature data is within the theoretical temperature range, it is considered normal and marked as 0; otherwise, it is considered abnormal. When the temperature data is higher than the theoretical temperature range, it is marked as positive, and when the temperature data is lower than the theoretical temperature range, it is marked as negative, generating a phasor distance , and the positive abnormal temperature set and the negative abnormal temperature set are constructed respectively according to the positive mark and the negative mark; The frequency of the abnormal temperature appearance is obtained to get the temperature abnormality possibility; The positive abnormal temperature set and the negative abnormal temperature set are analyzed respectively to determine the temperature fluctuation characteristics in turn.

[0006] Preferably, the frequency of the abnormal temperature appearance is obtained to get the temperature abnormality possibility, and the corresponding calculation formula is: Among them, represents the temperature abnormality possibility of the currently analyzed department; represents the frequency of the abnormal temperature appearance; represents the abnormal state mark of the th temperature data; represents the normalization function.

[0007] Preferably, the temperature fluctuation characteristics are determined, and the corresponding calculation formula is: Among them, represents the temperature fluctuation characteristics of the abnormal temperature set ; represents the number of elements in the abnormal temperature set ; represents the data of the temperature data in the corresponding time neighborhood; represents the standard deviation operation; represents the mean operation; represents the temperature abnormality possibility corresponding to the temperature data at the th acquisition moment in the corresponding time neighborhood; represents the abnormal state mark of the temperature data at the th acquisition moment in the corresponding time neighborhood; represents the normalization function.

[0008] Preferably, the temperature abnormality possibility is corrected according to the temperature fluctuation characteristics and screened to determine the temperature-normal departments and the temperature-abnormal departments respectively, including: Select the maximum values from the positive abnormal temperature set and the negative abnormal temperature set based on the temperature fluctuation characteristics, and denote it as the temperature fluctuation value; Correct the temperature anomaly possibility through the temperature fluctuation value; Set a screening threshold. When the corrected temperature anomaly possibility is greater than the screening threshold, it indicates that the current analysis department has abnormal temperature; when the corrected temperature anomaly possibility is less than the screening threshold, it indicates that the current analysis department has normal temperature.

[0009] Preferably, correct the temperature anomaly possibility through the temperature fluctuation value, and the corresponding calculation formula is: Wherein, represents the corrected temperature anomaly possibility; represents the temperature anomaly possibility before correction; represents the temperature fluctuation value; represents the positive abnormal temperature set of the temperature fluctuation characteristics; represents the negative abnormal temperature set of the temperature fluctuation characteristics.

[0010] Preferably, analyze the temperature data of the departments with abnormal temperature to obtain the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation, and combine the two to calculate the abnormal credibility, including: The temperature data respectively include the temperature data inside and outside the departments with normal temperature and the departments with abnormal temperature; Based on the temperature data inside the department with abnormal temperature and the temperature data outside the department with abnormal temperature, construct a temperature difference sequence, fit the temperature difference sequence to obtain the slope of the fitted straight line, obtain the temperature difference change range of the department with abnormal temperature, and perform normalization processing. Combine the slope of the fitted straight line to obtain the possibility of temperature interference caused by human factors in the department with abnormal temperature; Respectively fit the temperature data of the departments with normal temperature and the departments with abnormal temperature to obtain the fitting parameters. Determine the temperature similarity between the department with abnormal temperature and the department with normal temperature through the fitting parameters. Analyze the temperature data outside the departments with normal temperature and the departments with abnormal temperature to obtain the possibility that the department with abnormal temperature belongs to normal temperature regulation; Combine the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation to calculate the abnormal credibility of the department with abnormal temperature.

[0011] Preferably, construct a temperature difference sequence, and the corresponding calculation formula is: Wherein, represents the temperature difference inside and outside the department with abnormal temperature; Represents the temperature data outside the department with abnormal temperature; Represents the temperature data inside the department with abnormal temperature; Obtain the temperature difference change range of the department with abnormal temperature and perform normalization processing. The corresponding calculation formula is: Where, Represents the temperature difference change range of the department with abnormal temperature; Represents the temperature difference between inside and outside the department at the end within the current analysis time neighborhood of the department with abnormal temperature; Represents the temperature difference between inside and outside the department at the beginning within the current analysis time neighborhood of the department with abnormal temperature; Where, Represents the temperature difference change range after normalization processing; Represents the normalization function; Obtain the possibility of temperature interference caused by human factors in the department with abnormal temperature. The corresponding calculation formula is: Where, Represents the possibility of temperature interference caused by human factors in the department with abnormal temperature; Represents the slope of the fitting line; Represents the temperature difference change range after normalization processing; Represents the normalization function.

[0012] Preferably, the fitting parameter is Where, Represents the slope of the temperature data inside the department with normal temperature or abnormal temperature changing with the ambient temperature, Represents the theoretical temperature balance benchmark of the department with normal temperature or abnormal temperature; Determine the temperature similarity between the department with abnormal temperature and the department with normal temperature through the fitting parameter. The corresponding calculation formula is: Where, Represents the temperature similarity between the currently analyzed department with abnormal temperature and the th department with normal temperature; Represents the fitting parameter of the department with abnormal temperature; Represents the th fitting parameter of the department with normal temperature; Represents the regulated temperature of the department with abnormal temperature; Represents the th regulated temperature of the department with normal temperature; Represents the normalization function; Obtain the possibility that the department with abnormal temperature belongs to normal temperature regulation. The corresponding calculation formula is: Wherein, represents the possibility that the currently analyzed department with abnormal temperature belongs to normal temperature regulation; represents the correlation operation; represents the temperature similarity between the currently analyzed department with abnormal temperature and the th department with normal temperature; represents the temperature data outside the department with abnormal temperature; represents the th temperature data outside the department with normal temperature.

[0013] Preferably, the abnormal credibility of the department with abnormal temperature is calculated by combining the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation. The corresponding calculation formula is: Wherein, represents the abnormal credibility; represents the possibility that the department with abnormal temperature belongs to normal temperature regulation; represents the possibility of temperature interference caused by human factors in the department with abnormal temperature; represents the normalization function.

[0014] The present invention has the following beneficial effects: By real-time monitoring of the temperature inside the department, it is possible to evaluate whether the temperature change in the department is within the normal fluctuation range, analyze the collected temperature data, first delimit the category of the department, analyze the temperature fluctuation characteristics in the time neighborhood, and perform correction, so as to screen the departments into departments with normal temperature and departments with abnormal temperature; then, by combining the temperature change data of the internal and external environments of the department and the change trend of the temperature data, it is possible to analyze whether there is temperature fluctuation caused by human factors; then, by comparing and analyzing the departments with normal temperature and the departments with abnormal temperature, it is possible to judge whether the temperature change is caused by normal environmental regulation measures or temperature abnormality caused by certain abnormal situations during the regulation process, and further determine the abnormal credibility of the temperature data, so as to effectively monitor and manage the temperature status of the department environment, achieve accurate temperature monitoring of different types of departments, and improve the accuracy of temperature monitoring. Description of the Drawings

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 The flowchart of the steps of an intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention; Figure 2 The schematic diagram of a pediatric department with normal temperature in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention Figure 1 ; Figure 3 The schematic diagram of a pediatric department with normal temperature in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention Figure 2 ; Figure 4 The schematic diagram of a pediatric department with abnormal temperature in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention Figure 1 ; Figure 5 The schematic diagram of a pediatric department with abnormal temperature in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention Figure 2 ; Figure 6 The schematic diagram of the possibility of temperature interference caused by human factors in a pediatric department with abnormal temperature in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention Figure 7 The schematic diagram of the possibility that a pediatric department with abnormal temperature belongs to normal temperature regulation in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention. Detailed implementation manners

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of an intelligent monitoring method for pediatric department environmental temperature data proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0019] The following specifically describes the specific solution of an intelligent monitoring method for pediatric department environmental temperature data provided by the present invention in conjunction with the accompanying drawings.

[0020] Please refer to Figure 1 , which shows the step flowchart of the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention. The method includes: Step S1: Divide several different departments based on pediatrics, determine the theoretical temperature range of each department, and collect the temperature data of each department; Step S2: Compare the theoretical temperature range with the temperature data to construct the abnormal temperature set of each department, obtain the frequency of abnormal temperature occurrences to get the temperature abnormality possibility, and determine the temperature fluctuation characteristics through the abnormal temperature set; Step S3: Correct the temperature abnormality possibility according to the temperature fluctuation characteristics, and perform screening to respectively determine the departments with normal temperature and the departments with abnormal temperature; Step S4: Analyze the temperature data of the departments with abnormal temperature to obtain the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation, and combine the two to calculate the abnormal credibility; Step S5: Set a judgment threshold. When the abnormal credibility is greater than the judgment threshold, it is determined that there is a real temperature abnormality in the currently analyzed department.

[0021] For better illustration, since the thermoregulatory center of children is not yet fully developed and is sensitive to changes in environmental temperature, a stable temperature in the pediatric department helps to maintain normal body temperature. Moreover, children are weak in temperature during illness and have higher requirements for the comfort of environmental temperature. A large temperature difference change will cause discomfort symptoms. Therefore, it is necessary to realize real-time monitoring and recording of the temperature changes in different functional departments of the pediatric department to continuously optimize the environmental conditions of the pediatric department and ensure that child patients of different ages receive treatment and care in a suitable environment.

[0022] Specifically, in step S1, several different departments are divided based on pediatrics. In the pediatric department, according to different populations or functions, the pediatric department is divided. For example, the pediatric department is divided into children's rooms, infant rooms, neonatal rooms, etc. according to age to meet the different needs of children of different ages in terms of immune capacity; or the pediatric department is divided into corridors, wards, diagnosis rooms, etc. according to functions to ensure that each area can provide suitable environments and conditions, that is, different departments maintain different temperatures to maintain the suitability of each department in terms of environmental factors such as temperature and humidity; and regardless of which way of division is used, each obtained area has the same theoretical temperature control method.

[0023] As an alternative implementation, in this embodiment, the pediatric department area is divided into a children's room, an infants' room, and a neonatal room according to different age groups.

[0024] Collect the temperature data of each department. Since each department is a relatively independent unit, the temperature adjustment of each department is achieved through its own temperature control system combined with actual analysis to optimize the existing temperature monitoring method and improve the applicable range. That is, collect the temperature data of each department through the temperature control system, namely the supply air temperature and the return air temperature. Among them, the supply air temperature represents the adjusted temperature of the temperature control system itself, and the return air temperature represents the current ambient temperature of the department. In addition, although the corridor outside the department is also equipped with a temperature control system to collect temperature data, for the temperature control accuracy of the corridor, it does not need to be controlled with high precision like inside the department. Therefore, the temperature data outside the department can also be obtained through the temperature control system in the corridor outside the department.

[0025] Optionally, the temperature data includes but is not limited to any one of the pediatric department category, the theoretically temperature range, the actual adjusted temperature, the indoor ambient temperature, and the outdoor ambient temperature to ensure the temperature suitability of the pediatric department.

[0026] It can be explained that for pediatric departments with different temperature accuracy requirements, different data sampling frequencies are adopted. That is, the higher the accuracy requirement of the department, the larger the sampling frequency. Because different departments may have different sensitivities and requirements for temperature, it is necessary to adjust the sampling frequency according to the actual situation to ensure the accuracy and timeliness of the data. For example, the temperature accuracy of the operating room is usually higher, and the sampling frequency is set higher; while the temperature accuracy of the ward is lower, and the sampling frequency can be correspondingly reduced.

[0027] For better illustration, in this embodiment, the temperature data within the historical 60 minutes during the collection moment is selected as the time neighborhood for analysis.

[0028] It can be understood that based on the analysis of any one of the pediatric departments, if there is a significant deviation between the temperature data collected during the monitoring process of the department and the theoretical temperature range, it indicates that there is a problem with the temperature of the department. In addition, if within a period of time, the temperature data of the department shows that abnormal conditions persist and the gap between the temperature data and the theoretical temperature range is large, it indicates a temperature anomaly. On the contrary, if the temperature data of the department is within the theoretical temperature range, or even if there are anomalies, they only fluctuate slightly at the edge of the theoretical temperature range, it indicates that the actual temperature data is within the normal range and there are no abnormal conditions that require special attention.

[0029] Furthermore, in step S2, it includes: Step S21: When the temperature data is within the theoretical temperature range, it indicates normal and is marked as 0; otherwise, it indicates abnormality. When the temperature data is higher than the theoretical temperature range, it is marked as positive, and when the temperature data is lower than the theoretical temperature range, it is marked as negative, generating a phase distance , and respectively constructing a positive abnormal temperature set and a negative abnormal temperature set according to the positive mark and the negative mark.

[0030] Make an explanation that the phase distance The value of is expressed as the minimum value of the difference between the corresponding temperature data in this time neighborhood and the theoretical temperature range. When the temperature data is higher than and / or lower than the theoretical temperature range, the status is respectively marked as +1 or -1. For example, the temperature data collected at the current collection moment in the children's room is 15°C, indicating abnormality, and the direction is marked as negative, and the phase distance value is determined to be , that is reflects the temperature abnormality status at the corresponding collection moment; then respectively construct a positive abnormal temperature set and a negative abnormal temperature set according to the positive mark and the negative mark, and denote them as and .

[0031] Step S22: Obtain the frequency of the abnormal temperature appearance to get the temperature abnormality possibility.

[0032] Make an explanation that both the too-high temperature and the too-low temperature indicate the appearance of abnormal temperature in the department. And if within this time neighborhood, there are abnormal temperature fluctuations only at some times, although the temperature data in the department is close to the theoretical temperature range, it indicates that there is still a relatively large temperature abnormality in this department.

[0033] Furthermore, in step S22, obtaining the frequency of the abnormal temperature appearance to get the temperature abnormality possibility, the corresponding calculation formula is: where represents the temperature abnormality possibility of the currently analyzed department; represents the frequency of the abnormal temperature appearance; represents the abnormal status mark of the th temperature data; represents the normalization function.

[0034] Make an explanation that represents the frequency of the abnormal temperature appearance, that is, it reflects the duration of the abnormal temperature in this time neighborhood.

[0035] Step S23: Analyze the positive abnormal temperature set and the negative abnormal temperature set respectively, and sequentially determine the temperature fluctuation characteristics.

[0036] Understandably, if the similarity of the abnormal temperature data in either the positive abnormal temperature set or the negative abnormal temperature set is higher, it indicates that the amplitude of the fluctuations causing the abnormal temperature data remains basically consistent in the time neighborhood. At this time, the difference between the corresponding abnormal temperature data and the theoretical temperature range is smaller, indicating that the number of moments when the temperature data is abnormal is less, that is, it indicates that the abnormal temperature data detected during the corresponding time belongs to normal temperature fluctuations. Therefore, the positive abnormal temperature set and the negative abnormal temperature set are analyzed separately to determine whether the temperature data in either set belongs to normal temperature fluctuations, avoiding the situation of incorrect screening.

[0037] Furthermore, in step S23, to determine the temperature fluctuation characteristics, the corresponding calculation formula is: where, represents the temperature fluctuation characteristics of the abnormal temperature set ; represents the number of elements in the abnormal temperature set ; represents the data of the temperature data in the corresponding time neighborhood; represents the standard deviation operation; represents the mean operation; represents the th collection moment in the corresponding time neighborhood, and the temperature anomaly possibility corresponding to the temperature data; represents the th collection moment in the corresponding time neighborhood, and the anomaly status flag of the temperature data; represents the normalization function.

[0038] Explanation is made that represents the temperature fluctuation characteristics of the abnormal temperature set , that is, the temperature fluctuation characteristics of the positive abnormal temperature set are , and the temperature fluctuation characteristics of the negative abnormal temperature set are ; when the temperature fluctuation characteristics are larger, it indicates that the temperature data in the corresponding abnormal temperature set has shown obvious fluctuations deviating from the theoretical temperature range, indicating that the temperature fluctuations in the time neighborhood exceed the normal temperature fluctuation range and belong to abnormal fluctuations. Therefore, further analysis is required to timely discover potential problems and take corresponding preventive measures to prevent problems in temperature regulation.

[0039] Furthermore, step S3 includes: Step S31: Based on the temperature fluctuation characteristics, select the maximum value in the positive abnormal temperature set and the negative abnormal temperature set, denoted as the temperature fluctuation value.

[0040] Make an explanation based on the positive and negative abnormal temperature sets obtained above and the negative abnormal temperature set of the temperature fluctuation characteristics and , select the maximum value of the temperature fluctuation condition as the temperature fluctuation value within the current analyzed time neighborhood , and the corresponding calculation formula is: That is, by restricting the temperature fluctuation, the monitoring accuracy of the department temperature data is improved.

[0041] Step S32: Correct the temperature anomaly possibility through the temperature fluctuation value.

[0042] Furthermore, in step S32, the temperature anomaly possibility is corrected through the temperature fluctuation value, and the corresponding calculation formula is: Among them, represents the corrected temperature anomaly possibility; represents the temperature anomaly possibility before correction; represents the temperature fluctuation value; represents the temperature fluctuation characteristics of the positive abnormal temperature set ; represents the negative abnormal temperature set of the temperature fluctuation characteristics.

[0043] Make an explanation that the temperature fluctuation value is used to determine the abnormal fluctuation situation of the temperature, and is corrected in combination with the temperature anomaly possibility to realize continuous monitoring of the temperature fluctuation, so as to determine the abnormal situation within the time neighborhood and avoid potential damage.

[0044] Please refer to Figures 2 - 5 , which respectively show the schematic diagrams of the normal temperature department, the normal temperature department Figure 1 , the abnormal temperature department Figure 2 and the abnormal temperature department Figure 1 for the intelligent monitoring method of the environmental temperature data of the pediatric department. Among them, in the schematic diagrams of the normal temperature department Figure 2 and the normal temperature department Figure 1 , different line segments are used to respectively determine the indoor temperature, outdoor temperature, set temperature of the department and the theoretical temperature range of the department. In addition, the shaded part is used to represent the suitable temperature interval of the corresponding department; while in the schematic diagrams of the abnormal temperature department Figure 2 and the abnormal temperature department Figure 1 and the abnormal temperature department Figure 2 , the shaded part is used to represent the acquisition interval of the abnormal temperature.

[0045] Step S33: Set a screening threshold. When the corrected temperature anomaly probability is greater than the screening threshold, it indicates that the current analysis department is a temperature anomaly department; when the corrected temperature anomaly probability is less than the screening threshold, it indicates that the current analysis department is a temperature normal department.

[0046] As an alternative implementation, in this embodiment, the screening threshold is .

[0047] Specifically, sequentially obtain the corrected temperature anomaly probability of each department to be analyzed. If the corrected temperature anomaly probability is greater than 0.2, it indicates that the temperature of the current department is abnormal; otherwise, it indicates that the temperature of the current department is normal. Based on this, classify all departments to respectively determine the temperature normal departments and temperature anomaly departments.

[0048] It can be understood that since the children's department houses children with low living abilities, there is usually a more frequent flow of people in and out, including medical staff, patient families, and other relevant personnel. And the frequent personnel flow makes the temperature data in the department very unstable. That is, every time someone enters or exits, the air exchange inside and outside the department will affect the change of the temperature data inside the department, making the temperature data inside and outside the department tend to be consistent. Therefore, this frequent personnel flow makes the temperature inside the department very unstable. So if only relying on the temperature monitoring device to judge whether the temperature data is abnormal, the normal temperature fluctuations in this case may also be wrongly regarded as abnormal temperatures, rather than real temperature anomalies, resulting in inaccurate temperature monitoring. So although the temperature monitoring of some departments shows anomalies, in fact, the temperatures of these departments may be in the normal adjustment process, thus leading to misjudgment of the temperature and further reducing the credibility of the monitored temperature data.

[0049] Furthermore, in step S4, it includes: The temperature data respectively includes the temperature data inside and outside the temperature normal departments and temperature anomaly departments.

[0050] Please refer to Figure 6 , which shows a schematic diagram of the probability of temperature interference caused by human factors in the temperature anomaly departments of the intelligent monitoring method for the environmental temperature data of the pediatric department provided by an embodiment of the present invention. Among them, the horizontal axis represents the department number of the temperature anomaly department; the vertical axis represents the probability of temperature interference caused by human factors in the temperature anomaly department.

[0051] Step S41: Construct a temperature difference sequence based on the temperature data inside the temperature-abnormal department and the temperature data outside the temperature-abnormal department, fit the temperature difference sequence to obtain the slope of the fitted straight line, acquire the temperature difference change amplitude of the temperature-abnormal department, perform normalization processing, and combine it with the slope of the fitted straight line to obtain the possibility of temperature interference caused by human factors in the temperature-abnormal department.

[0052] Make an explanation. Arbitrarily select a temperature-abnormal department for analysis. Based on the time neighborhood corresponding to the current analysis, subtract the temperature data outside the temperature-abnormal department from the temperature data inside the temperature-abnormal department to obtain the corresponding temperature difference sequence.

[0053] Further, in step S41, when constructing the temperature difference sequence, the corresponding calculation formula is: where, represents the temperature difference inside and outside the temperature-abnormal department; represents the temperature data outside the temperature-abnormal department; represents the temperature data inside the temperature-abnormal department.

[0054] Then perform least-squares fitting on the temperature difference sequence to obtain the slope of the fitted straight line. Among them, least-squares fitting is to find the best function matching of the data by minimizing the sum of the squares of the errors to obtain the fitted straight line, and then calculate the slope through where represents the slope, represents the intercept, and the slope explains the change rate of the fitted straight line variables and ; if the slope is less than 0 and close to 0, it indicates that the temperature difference inside and outside the temperature-abnormal department decreases with time, and at this time, the possibility of human factors causing air flow to affect temperature change is greater.

[0055] Acquire the temperature difference change amplitude of the temperature-abnormal department. The corresponding calculation formula is: where, represents the temperature difference change amplitude of the temperature-abnormal department; represents the temperature difference inside and outside the department at the end within the time neighborhood of the current analysis of the temperature-abnormal department; represents the temperature difference inside and outside the department at the beginning within the time neighborhood of the current analysis of the temperature-abnormal department.

[0056] It can be explained that if the temperature difference change amplitude When it indicates that the current temperature difference has decreased within the time neighborhood, that is, the temperature difference between the inside and outside of the temperature difference department is similar; conversely, if When it indicates that the temperature difference between the inside and outside of the abnormal temperature department is larger, it shows that the temperature data inside and outside the abnormal temperature department within the time neighborhood exhibits obvious regional identical characteristics. At this time, it reflects that the possibility of the abnormal temperature department being caused by human factors is greater; if the temperature difference does not show a decreasing characteristic or the temperature inside and outside the abnormal temperature department tends to be consistent, at this time, the possibility of the abnormal monitored temperature being caused by human factors is smaller.

[0057] Then perform normalization processing, and the corresponding calculation formula is: Among them, represents the change amplitude of the temperature difference after normalization processing; represents the normalization function.

[0058] Obtain the possibility that the abnormal temperature department is caused by temperature interference of human factors, and the corresponding calculation formula is: Among them, represents the possibility that the abnormal temperature department is caused by temperature interference of human factors; represents the slope of the fitting line; represents the change amplitude of the temperature difference after normalization processing; represents the normalization function.

[0059] It can be understood that judging the direction and magnitude of the temperature amplitude change according to the obtained possibility that the abnormal temperature department is caused by temperature interference of human factors will cause a certain misjudgment. That is, due to the change of the environmental temperature outside the abnormal temperature department, or a large amount of heat generated by the relevant medical equipment operating in the pediatric department, the temperature inside the department is seriously too high. At this time, the temperature control system of the department adjusts the temperature, causing the temperature difference between the inside and outside of the abnormal temperature department to show a decreasing trend in the regulation of temperature data. And these temperature changes are not normal changes caused by human factors, and there may also be abnormal temperature regulation, which in turn leads to inaccurate and untimely monitoring and regulation of the temperature data of the pediatric department.

[0060] Step S42: Respectively perform fitting on the temperature data in the normal temperature department and the abnormal temperature department to obtain fitting parameters, determine the temperature similarity between the abnormal temperature department and the normal temperature department through the fitting parameters, analyze the temperature data outside the normal temperature department and the abnormal temperature department, and obtain the possibility that the abnormal temperature department belongs to normal temperature regulation.

[0061] It should be noted that any department in pediatrics has the same temperature control standard for the same type. Therefore, the temperature of these departments is adjusted through their respective temperature control systems to ensure that the indoor temperature can reach a relatively consistent level. However, based on this situation for temperature control, the indoor temperatures of the departments are similar, while the temperature differences outside the departments may be caused by environmental temperature changes. If the temperature of a certain department is abnormal, but this abnormality is within the normal temperature fluctuation range, then the temperature control of the department with abnormal temperature should be similar to that of the departments with normal temperature. After the temperature is adjusted, it takes a certain amount of time for the temperature data inside and outside the department to reach a balanced state and for the temperatures to be similar. Therefore, for the departments in the process of temperature adjustment, a certain period of time is also needed to observe whether their temperatures can finally reach the expected balanced state.

[0062] Therefore, when the temperature control parameters of the departments are similar, the changing trend of the temperature data inside the departments will still show a certain regularity. If the temperature trend of a department with abnormal temperature is significantly different from that of the departments with normal temperature, it indicates that this temperature change difference has a high correlation with the environmental temperature change outside the department; specifically, the greater the temperature difference between the department with abnormal temperature and the departments with normal temperature of the same type, the greater the environmental temperature difference outside the department, that is, there is a positive correlation between the temperature differences inside and outside the department. When the temperature data inside the department is abnormal and the environmental temperature outside the department causes the temperature data inside the department to fail to reach equilibrium through the normal control mechanism, the abnormality of the temperature data inside the department with abnormal temperature is more likely to be a temporary phenomenon during the temperature control process of the department.

[0063] Furthermore, in step S42, the fitting parameter is , where represents the slope of the temperature data inside the department with normal temperature or abnormal temperature changing with the environmental temperature, and represents the theoretical temperature equilibrium benchmark of the department with normal temperature or abnormal temperature.

[0064] An explanation is made that the least squares fitting is performed on the temperature data inside the department with abnormal temperature to obtain the fitting parameter, which reflects the trend characteristics of the temperature data change inside the corresponding department.

[0065] The temperature similarity between the department with abnormal temperature and the departments with normal temperature is determined through the fitting parameter, and the corresponding calculation formula is: where represents the temperature similarity between the currently analyzed department with abnormal temperature and the th department with normal temperature; represents the fitting parameter of the department with abnormal temperature; Represents the fitting parameter of the th normal temperature department; Represents the regulated temperature of the department with abnormal temperature; Represents the th regulated temperature of the normal temperature department; Represents the normalization function.

[0066] The possibility that the department with abnormal temperature belongs to normal temperature regulation is obtained, and the corresponding calculation formula is: Among them, Represents the possibility that the currently analyzed department with abnormal temperature belongs to normal temperature regulation; Represents the correlation operation; Represents the temperature similarity between the currently analyzed department with abnormal temperature and the th normal temperature department; Represents the temperature data outside the department with abnormal temperature; Represents the th temperature data outside the normal temperature department.

[0067] Make an explanation, Represents the correlation operation, which is used to calculate the correlation of the difference sequence between the temperature similarity sequence and the temperature data to measure the linear relationship between the two sequences. The result range of this value is , among which, 1 represents a perfect positive correlation, -1 represents a perfect negative correlation, and 0 represents no linear correlation.

[0068] Step S43: Calculate the abnormal credibility of the department with abnormal temperature by combining the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation.

[0069] It can be understood that based on the foregoing analysis of temperature data, if the possibility that the currently analyzed department with abnormal temperature belongs to normal temperature regulation and the possibility of temperature interference caused by the corresponding human factors is relatively high, it means that the abnormal temperature phenomenon of this department with abnormal temperature belongs to the normal situation, that is, the abnormal credibility of the corresponding temperature data is relatively low, indicating that this department with abnormal temperature is not a real abnormality; on the contrary, when the abnormal credibility of the temperature data is high, it means that the abnormal temperature data of the department with abnormal temperature is a real situation.

[0070] Furthermore, in step S43, the abnormal credibility of the department with abnormal temperature is calculated by combining the possibility of temperature interference caused by human factors and the possibility of normal temperature regulation. The corresponding calculation formula is: Among them, Represents the abnormal credibility; Indicates the possibility that the department with abnormal temperature belongs to normal temperature regulation; Indicates the possibility that the temperature interference in the department with abnormal temperature is caused by human factors; Indicates the normalization function.

[0071] Please refer to Figure 7 , which shows a schematic diagram of the possibility that the department with abnormal temperature in the intelligent monitoring method for pediatric department environmental temperature data provided by an embodiment of the present invention belongs to normal temperature regulation. Among them, the horizontal axis represents the department number corresponding to the department with abnormal temperature; the vertical axis represents the abnormal credibility corresponding to the department with abnormal temperature; the horizontal line in the figure represents the judgment threshold; it can be seen from the figure that departments with abnormal temperature 1, 4, and 6 reflect real temperature regulation abnormal situations, while departments with abnormal temperature 2, 3, and 5 belong to normal temperature abnormalities caused by human factors or normal temperature regulation situations.

[0072] It is explained that in step S5, a judgment threshold is set. When the abnormal credibility is greater than the judgment threshold, it is determined that a real temperature abnormality occurs in the currently analyzed department.

[0073] As an optional implementation manner, in this embodiment, the judgment threshold is .

[0074] It can be explained that when the abnormal credibility is greater than the judgment threshold, that is, , it indicates that a real temperature abnormality has occurred in the currently analyzed department with abnormal temperature, and corresponding temperature abnormality prompts need to be given to medical staff. Then, based on the foregoing temperature abnormality judgment, each department with abnormal temperature is judged to obtain all departments belonging to real temperature abnormalities, and corresponding processing is carried out to timely solve potential problems.

[0075] It can be understood that through real-time monitoring of the internal temperature of the department, to evaluate whether the temperature change of the department is within the normal fluctuation range, analyze the collected temperature data, first delimit the category of the department, analyze the temperature fluctuation characteristics within the time neighborhood, and perform correction, and screen the departments into departments with normal temperature and departments with abnormal temperature; then combine the temperature change data inside and outside the department and the change trend of the temperature data to analyze whether there is temperature fluctuation caused by human factors; then through comparative analysis of departments with normal temperature and departments with abnormal temperature, judge whether the temperature change is caused by normal environmental regulation measures or temperature abnormality caused by certain abnormal situations during the regulation process, and then determine the abnormal credibility of the temperature data, so as to effectively monitor and manage the temperature status of the department environment, realize accurate temperature monitoring of different types of departments, and improve the accuracy of temperature monitoring.

[0076] It should be noted that the above order of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0077] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. An intelligent monitoring method for ambient temperature data in pediatric departments, characterized in that: The method comprises: Divide pediatrics into several different departments, determine the theoretical temperature range of each department, and collect temperature data for each department; Compare the theoretical temperature range with the temperature data to construct the abnormal temperature set for each department, obtain the frequency of abnormal temperature occurrence to obtain the possibility of temperature abnormality, and determine the temperature fluctuation characteristics through the abnormal temperature set; Correct the possibility of temperature abnormality according to the temperature fluctuation characteristics, and screen to determine the departments with normal temperature and abnormal temperature respectively; Analyze the temperature data of the temperature abnormality department to obtain the possibility of temperature interference caused by human factors and the possibility of normal temperature control, and combine the two to calculate the abnormal credibility; Set a judgment threshold. When the abnormal credibility is greater than the judgment threshold, it is determined that the current analysis department has a real temperature abnormality. Analyze the temperature data of the temperature abnormality department to obtain the possibility of temperature interference caused by human factors and the possibility of normal temperature control. Combine the two to calculate the abnormal credibility, including: The temperature data include temperature data inside and outside the department with normal temperature and the department with abnormal temperature respectively; Based on the temperature data inside and outside the temperature abnormality department, a temperature difference sequence is constructed, and the temperature difference sequence is fitted to obtain the slope of the fitting line. The temperature difference variation range of the temperature abnormality department is obtained and normalized. Combined with the slope of the fitting line, the possibility of temperature interference caused by human factors in the temperature abnormality department is obtained. The temperature data in the departments with normal temperature and the departments with abnormal temperature are fitted to obtain fitting parameters. The temperature similarity between the departments with abnormal temperature and the departments with normal temperature is determined by fitting parameters. The temperature data outside the departments with normal temperature and the departments with abnormal temperature are analyzed to obtain the possibility that the departments with abnormal temperature belong to normal temperature control. The abnormal credibility of the temperature abnormality department is calculated by combining the possibility of temperature interference caused by human factors and the possibility of normal temperature control.

2. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 1, characterized in that: Compare the theoretical temperature range with the temperature data to construct the abnormal temperature set for each department, obtain the frequency of abnormal temperature occurrence to obtain the possibility of temperature abnormality, and determine the temperature fluctuation characteristics through the abnormal temperature set, including: When the temperature data is within the theoretical temperature range, it is normal and marked as 0; otherwise, it is abnormal. When the temperature data is higher than the theoretical temperature range, it is marked as positive, and when the temperature data is lower than the theoretical temperature range, it is marked as negative. , construct the positive abnormal temperature set and the negative abnormal temperature set according to the positive mark and the negative mark respectively; Obtain the frequency of abnormal temperature occurrence to obtain the possibility of temperature anomaly; The positive abnormal temperature set and the negative abnormal temperature set are analyzed separately to determine the temperature fluctuation characteristics in turn.

3. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 2, characterized in that: The frequency of abnormal temperature occurrence is obtained to obtain the possibility of temperature anomaly. The corresponding calculation formula is: in, Indicates the possibility of abnormal temperature in the current analysis department; Indicates the frequency of abnormal temperature occurrence; Indicates Abnormal status mark of temperature data; Represents the normalization function.

4. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 2, characterized in that: Determine the temperature fluctuation characteristics, the corresponding calculation formula is: in, Indicates abnormal temperature set Temperature fluctuation characteristics; Indicates abnormal temperature set The number of elements in ; data representing temperature data in a corresponding time neighborhood; Indicates standard deviation operation; represents the mean operation; Indicates the first The possibility of temperature anomaly corresponding to the temperature data at each collection moment; Indicates the first Abnormal status mark of temperature data at each collection moment; Represents the normalization function.

5. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 2, characterized in that: Correct the possibility of temperature abnormality according to the temperature fluctuation characteristics, and screen to determine the departments with normal temperature and abnormal temperature, including: Based on the temperature fluctuation characteristics, the maximum value in the positive abnormal temperature set and the negative abnormal temperature set is selected and recorded as the temperature fluctuation value; Correct the possibility of temperature anomaly through temperature fluctuation value; Set a screening threshold. When the corrected temperature abnormality probability is greater than the screening threshold, it means that the current analysis department is a temperature abnormality department; when the corrected temperature abnormality probability is less than the screening threshold, it means that the current analysis department is a temperature normal department.

6. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 5, characterized in that: The possibility of temperature anomaly is corrected by the temperature fluctuation value. The corresponding calculation formula is: in, Indicates the possibility of corrected temperature anomaly; Indicates the possibility of temperature anomaly before correction; Indicates the temperature fluctuation value; Represents the positive abnormal temperature set Temperature fluctuation characteristics; Represents the negative abnormal temperature set temperature fluctuation characteristics.

7. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 1, characterized in that: Construct the temperature difference sequence, and the corresponding calculation formula is: in, Indicates the temperature difference between inside and outside of the temperature abnormality department; Indicates the temperature data outside the department with abnormal temperature; Indicates the temperature data in the department with abnormal temperature; Obtain the temperature difference variation range of the temperature abnormality department and perform normalization. The corresponding calculation formula is: in, Indicates the temperature difference change range of the temperature abnormality department; It represents the temperature difference between the inside and outside of the department at the end of the time neighborhood of the current analysis of the temperature abnormality department; It represents the temperature difference between the inside and outside of the department at the beginning of the time neighborhood of the current analysis of the temperature abnormality department; in, Indicates the change amplitude of temperature difference after normalization; represents the normalization function; The possibility that the temperature abnormality department is caused by human factors is obtained, and the corresponding calculation formula is: in, Indicates the possibility that the temperature disturbance in the department with abnormal temperature is caused by human factors; represents the slope of the fitted straight line; Indicates the change amplitude of temperature difference after normalization; Represents the normalization function.

8. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 1, characterized in that: The fitting parameters are ,in, It indicates the slope of the temperature data in the department with normal temperature or abnormal temperature changing with the ambient temperature. Indicates the theoretical temperature balance benchmark for a department with normal temperature or a department with abnormal temperature; The temperature similarity between the departments with abnormal temperature and the departments with normal temperature is determined by fitting parameters, and the corresponding calculation formula is: in, Indicates the temperature abnormality department currently analyzed and the The temperature similarity between the departments with normal temperature; represents the fitting parameters of the departments with abnormal temperature; Indicates Fitting parameters of normal temperature departments; Indicates the controlled temperature of the department with abnormal temperature; Indicates The temperature control of each department with normal temperature; represents the normalization function; The possibility of the temperature abnormality department belonging to normal temperature control is obtained, and the corresponding calculation formula is: in, Indicates the possibility that the temperature abnormality department currently analyzed belongs to normal temperature control; represents the correlation operation; Indicates the temperature abnormality department currently analyzed and the The temperature similarity between the departments with normal temperature; Indicates the temperature data outside the department with abnormal temperature; Indicates Temperature data outside the department with normal temperature.

9. The intelligent monitoring method for ambient temperature data of a pediatric department according to claim 1, characterized in that: The abnormal credibility of the temperature abnormality department is calculated by combining the possibility of temperature interference caused by human factors and the possibility of normal temperature control. The corresponding calculation formula is: in, Indicates the degree of credibility of the anomaly; It indicates the possibility that the temperature abnormality department belongs to normal temperature control; Indicates the possibility that the temperature disturbance in the department with abnormal temperature is caused by human factors; Represents the normalization function.

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