Vision-based hospital infection sterilization quality control method

Abstract

The invention relates to the technical field of infection disinfection and killing, and discloses a visual sense-based hospital infection disinfection and killing quality control method, through systematic data acquisition and analysis, disinfection and killing work becomes more standardized and sustainable, and the method not only can ensure that the current disinfection and killing work accords with a specified standard, but also can ensure that the disinfection and killing work is more accurate. The method can provide data support for future disinfection and killing work, promote long-term hospital infection prevention and control work, hospitals need long-term and stable infection prevention and control measures, and through standardized evaluation and data tracking of the disinfection and killing effect, not only is the effect of current work improved, but also data support is provided for subsequent optimization and decision making. When environmental factors change or a disinfection path is incomplete, a hospital can maintain efficient disinfection operation in a complex environment through intelligent adjustment, and it is guaranteed that all areas are disinfected and covered timely and fully.

Description

Technical Field

[0001] The present invention relates to the technical field of infection disinfection and killing, and specifically to a method for quality control of hospital infection disinfection and killing based on vision. Background Art

[0002] In today's medical and health field, the prevention and control of hospital infections is an important and urgent task. Especially in disease prevention and control, the spread of hospital infections directly affects the health and treatment effects of patients. With the changes in the global public health situation, the prevention and control of hospital infections have gradually become the focus of attention of national health systems. Against this background, hospital disinfection and killing work is particularly important. Hospital disinfection and killing work not only relates to the cleanliness and hygiene level of the hospital environment, but also directly affects the spread of various pathogenic microorganisms such as bacteria and viruses in the hospital. Therefore, the quality control of hospital infection disinfection and killing has become a crucial issue in the medical industry, especially in the evaluation and quality control of disinfection and killing effects. In order to better ensure the hygiene of the hospital environment and reduce nosocomial cross-infection, it has become a very important direction to conduct real-time monitoring and optimization of the quality of hospital infection disinfection and killing based on advanced technologies such as vision recognition technology.

[0003] Although hospital disinfection and killing operations have formed certain systems and standards in many hospitals, in the actual implementation process, they often face multiple problems. First of all, the existing disinfection and killing quality assessment methods still rely on manual observation and empirical judgment. This method has a large degree of subjectivity and is difficult to accurately evaluate the comprehensiveness and effectiveness of disinfection and killing operations. Secondly, due to the complex internal structure of the hospital and the differences in the configuration and operation methods of disinfection and killing equipment, the disinfection and killing effects in each area are also different. There are often some "blind spots" or "vacuum intervals" that have not been effectively covered, and even some areas may not be cleaned at all. In addition, the existing disinfection and killing operation assessment system lacks consideration of environmental factors and does not effectively monitor and dynamically adjust the compensatory adjustments in the actual disinfection and killing process, resulting in uneven disinfection and killing effects. To sum up, the deficiencies of the existing disinfection and killing quality control system are mainly reflected in the lack of accurate and real-time feedback mechanisms and the ability to adapt to dynamic environmental changes.

[0004] Therefore, we propose a method for quality control of hospital infection disinfection and killing based on vision to solve the above-mentioned problems. Summary of the Invention

[0005] The object of the present invention is to provide a method for quality control of hospital infection disinfection and sterilization based on vision, so as to solve the problems in the above-mentioned background technology that the existing disinfection and sterilization quality assessment methods still rely on manual observation and empirical judgment. This method has a large subjectivity and is difficult to accurately evaluate the comprehensiveness and effectiveness of disinfection and sterilization operations. Secondly, due to the complex internal structure of the hospital and the differences in the configuration and operation methods of disinfection and sterilization equipment, the disinfection and sterilization effects in each area are also different, and there are often some "blind spots" or "vacuum intervals" that are not effectively covered, and even some areas may not be cleaned at all. In addition, the existing disinfection and sterilization operation assessment system lacks consideration of environmental factors (such as wind force, humidity, etc.) and does not effectively monitor and dynamically adjust the compensatory adjustments in the actual disinfection and sterilization process, resulting in uneven disinfection and sterilization effects.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for quality control of hospital infection disinfection and sterilization based on vision, the specific steps are as follows: S1. Collect multi-source data on the disinfection and sterilization area and disinfection and sterilization equipment, and perform preprocessing to generate a first data group and a second data group; S2. Analyze the first data group and the second data group to obtain the basic disinfection and sterilization area JMJ and the secondary disinfection and sterilization area RMJ, integrate and calculate the basic disinfection and sterilization area JMJ and the secondary disinfection and sterilization area RMJ to generate a disinfection and sterilization vacuum interval ZKJ, and analyze the rationality of the disinfection and sterilization vacuum interval ZKJ; S3. Analyze the first data group and the second data group to obtain the disinfection and sterilization compensation area BMJ, and integrate and analyze the disinfection and sterilization compensation area BMJ and the disinfection and sterilization vacuum interval ZKJ to determine whether the disinfection and sterilization vacuum interval can be compensated under normal movement; S4. Analyze the first data group and the second data group to obtain the extreme compensation value JBZ, and analyze the extreme compensation value JBZ and the disinfection and sterilization vacuum interval ZKJ to determine whether the disinfection and sterilization vacuum interval ZKJ can be satisfied under extreme conditions; S5. Adjust the extreme compensation value JBZ to adapt to the actual requirements, generate an actual instruction, and send it to the disinfection and sterilization personnel.

[0007] Preferably, in step S1, the first data group includes: the total disinfection and sterilization area A, the field of view range B, the path length C, and the number of actions D; The second data group includes: the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind force intensity H, and the atomization degree I.

[0008] Preferably, in step S2, the basic disinfection area JMJ is obtained by integrating and calculating the path length C, the number of actions D, the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind force intensity H, and the atomization degree I. By combining the moving interval E with the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. According to the change of the vertical spraying angle G, the influence in the vertical direction is reflected. The wind force correction factor is used to adjust. The greater the wind force, the more significant the influence. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation; In step S2, the secondary disinfection area RMJ is obtained by integrating and calculating the path length C, the number of actions D, the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind force intensity H, and the atomization degree I. By combining the moving interval E with the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation; In step S2, the disinfection vacuum interval ZKJ is obtained by subtracting the basic disinfection area JMJ and the secondary disinfection area RMJ from the total disinfection target area A. The basic disinfection area JMJ and the secondary disinfection area RMJ respectively represent the coverage areas of two stages. Their sum represents the actual area covered by the equipment. The remaining part is the area that cannot be covered, that is, the vacuum interval ZKJ.

[0009] Preferably, in the said step S2, the specific analysis method for the disinfection vacuum interval ZKJ is as follows: When ZKJ ≤ Y, it means that the current disinfection vacuum interval ZKJ is reasonable; When ZKJ > Y, it means that the current disinfection vacuum interval ZKJ is unreasonable; Where Y is a preset first threshold.

[0010] Preferably, in step S3, the disinfection compensation area BMJ is obtained by integrating and calculating the total disinfection area A, path length C, number of actions D, movement interval E, horizontal spraying angle F, vertical spraying angle G, wind intensity H, and atomization degree I. The total disinfection area A is the basis for preliminary calculation, representing the size of the area to be disinfected. By calculating the ratio of the path length C to the total area A, the coverage efficiency per meter of the path can be obtained. The longer the path length, the smaller the area that needs to be covered per unit path, thus affecting the actual disinfection effect. The ratio of the number of actions D to the path length C reflects the operation frequency per unit path. The higher the operation frequency, the better the coverage effect per unit path. The larger the spraying angle, the wider the spraying range of the device. By combining the movement interval E and the horizontal spraying angle F, the actual width covered by each spraying can be calculated. The vertical spraying angle G determines the depth and thickness of the spraying. The atomization degree I directly affects the coverage effect of the agent, and the atomization degree I is directly used as a correction factor and multiplied into the calculation.

[0011] Preferably, in step S3, the specific analysis method for analyzing the disinfection compensation area BMJ and the disinfection vacuum interval ZKJ is as follows: When BMJ < ZKJ, it means that the current disinfection compensation area BMJ cannot fill the disinfection vacuum interval ZKJ; When ZKJ ≥ Y, it means that the current disinfection compensation area BMJ can fill the disinfection vacuum interval ZKJ.

[0012] Preferably, in step S4, the extreme compensation value JBZ is obtained by integrating and calculating the total disinfection area A, field of view B, path length C, number of actions D, movement interval E, horizontal spraying angle F, vertical spraying angle G, wind intensity H, and atomization degree I. The total disinfection area A is the basis for preliminary calculation, representing the size of the area to be disinfected. By calculating the ratio of the path length C to the total area A, the coverage efficiency per meter of the path can be obtained. The longer the path length, the smaller the area that needs to be covered per unit path, thus affecting the actual disinfection effect. The ratio of the number of actions D to the path length C reflects the operation frequency per unit path. The higher the operation frequency, the better the coverage effect per unit path. The larger the spraying angle, the wider the spraying range of the device. By combining the movement interval E and the horizontal spraying angle F, the actual width covered by each spraying can be calculated. The vertical spraying angle G determines the depth and thickness of the spraying. The atomization degree I directly affects the coverage effect of the agent, and the atomization degree I is directly used as a correction factor and multiplied into the calculation.

[0013] Preferably, in step S4, the specific analysis method for the extreme compensation value JBZ and the disinfection vacuum interval ZKJ is as follows: When JBZ < ZKJ, it means that the current behavior cannot fill the disinfection vacuum interval ZKJ; When JBZ ≥ ZKJ, it means that the current behavior can fill the disinfection vacuum interval ZKJ.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Through systematic data collection and analysis, the disinfection work becomes more standardized and sustainable. This method can not only ensure that the current disinfection operations meet the specified standards, but also provide data support for future disinfection operations, promoting long-term hospital infection prevention and control work. Hospitals need long-term and stable infection prevention and control measures. By standardizing the evaluation of disinfection effects and tracking data, not only the effectiveness of current operations is improved, but also data support is provided for subsequent optimization and decision-making, making the hospital's infection prevention and control more scientific and long-term.

[0015] 2. The implementation of the dynamic adjustment strategy can ensure that the disinfection operations achieve optimal effects under different circumstances, especially when environmental factors change or the disinfection path is incomplete. Through intelligent adjustment, hospitals can maintain efficient disinfection operations in complex environments, ensuring that all areas are covered by timely and sufficient disinfection, thereby further reducing the risk of nosocomial infections. This is highly consistent with the goal of hospital infection prevention and control, enhancing the flexibility and response speed of prevention and control operations. Description of the Drawings

[0016] Figure 1 It is a method step diagram of the present invention. Detailed Embodiments

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiment 1: Please refer to Figure 1 , a method for quality control of hospital infection disinfection based on vision, and the specific steps are as follows: S1. Collect multi-source data on the disinfection area and disinfection equipment, and perform preprocessing to generate a first data group and a second data group; S2. Analyze the first data group and the second data group to obtain the basic disinfection area JMJ and the secondary disinfection area RMJ, and perform integrated calculation on the basic disinfection area JMJ and the secondary disinfection area RMJ to generate a disinfection vacuum interval ZKJ, and perform rationality analysis on the disinfection vacuum interval ZKJ; S3. Analyze the first data group and the second data group to obtain the disinfection compensation area BMJ, and integrate and analyze the disinfection compensation area BMJ with the disinfection vacuum interval ZKJ to determine whether the disinfection vacuum interval can be compensated under normal movement; S4. Analyze the first data group and the second data group to obtain the extreme compensation value JBZ, and analyze the extreme compensation value JBZ with the disinfection vacuum interval ZKJ to determine whether the disinfection vacuum interval ZKJ can be satisfied under extreme conditions; S5. Adjust the extreme compensation value JBZ to make it adapt to the actual requirements, generate an actual instruction, and send it to the disinfection personnel.

[0019] In this embodiment: Through visual technology and multi-source data collection, this method can monitor the working status of the disinfection area and disinfection equipment in real time, automatically generate data groups and analyze them, so as to achieve accurate evaluation of disinfection quality. Compared with traditional manual monitoring, this automated monitoring system can reduce human errors and improve the accuracy of evaluation. Based on the analysis and integration of dynamic data, it can effectively identify the blind spots in hospital disinfection, ensure that every area can be comprehensively disinfected, and avoid potential infection risks.

[0020] By integrating and calculating the basic disinfection area JMJ and the secondary disinfection area RMJ, the disinfection vacuum interval ZKJ, that is, the area not effectively covered during the disinfection process, can be identified, and these areas can be effectively compensated by the compensation area BMJ. This ensures the comprehensiveness of disinfection operations and avoids the problem of uneven coverage in traditional disinfection methods. This method can also judge whether the "vacuum interval" can be effectively compensated based on real-time data, thus greatly reducing the hidden danger of infection transmission and improving the consistency of disinfection effect.

[0021] The disinfection effect not only depends on the equipment configuration and operation, but is also affected by environmental factors such as wind force, humidity, and temperature. Traditional disinfection methods often ignore the changes in these dynamic environmental factors. However, this method can adjust the disinfection strategy according to the actual environment by analyzing and correcting these factors in real time. Under extreme conditions such as strong wind and high humidity, by calculating the extreme compensation value JBZ, the disinfection strategy can be adjusted to ensure that the disinfection effect still meets the requirements even in a harsh environment.

[0022] After analyzing and adjusting the extreme compensation value JBZ, this method can generate precise instructions for actual requirements and automatically send them to the disinfection personnel. This not only improves the work efficiency of the disinfection personnel, but also ensures the accuracy and efficiency of the disinfection process, avoiding mistakes in manual operations. The disinfection personnel can quickly adjust their work strategies according to the real-time data and feedback provided by the system, thereby improving the operation efficiency and reducing resource waste.

[0023] Through an intelligent and automated disinfection quality control method, hospitals can better carry out infection control and management. This not only helps reduce the incidence of nosocomial infections but also improves the overall hygiene level of the hospital. The optimization and precision improvement of disinfection operations make the hospital's infection prevention and control measures more effective, and on the premise of meeting high-standard hygiene requirements, it can reduce resource waste and improve the overall operational efficiency of the hospital.

[0024] This method is based on the real-time analysis of a large amount of data. It can not only provide immediate feedback but also support long-term management and decision-making. Hospital managers can make scientific decisions based on the data reports of disinfection effects, optimize the allocation and usage strategies of disinfection resources. The data accumulated over the long term can also be used to formulate the standards and processes for hospital infection prevention and control, promoting the standardization and scientificization of hospital infection control management.

[0025] Embodiment 2: Please refer to Figure 1 , in step S1, the first data set includes: total disinfection area A, field of view B, path length C, and number of actions D; The second data set includes: movement interval E, horizontal spraying angle F, vertical spraying angle G, wind intensity H, and atomization degree I.

[0026] In this embodiment: Through multi-source data collection, all relevant information of the hospital disinfection area can be accurately obtained, including the total disinfection area A, field of view B, path length C, and number of actions D, etc. This data collection provides a basis for subsequent disinfection quality assessment and decision-making, thus ensuring the comprehensiveness and accuracy of disinfection coverage. The implementation of this data collection method helps to overcome the inaccuracy and omission in traditional manual monitoring, providing more accurate and systematic disinfection effect data, meeting the requirements of high-standard disinfection effects for hospital infection prevention and control.

[0027] By analyzing the ratio between the path length C and the total disinfection area A, the coverage efficiency per meter of the path can be better evaluated. The longer the path, the smaller the area that needs to be covered per unit path. Based on this analysis, the disinfection path and equipment configuration can be optimized, reducing duplicate coverage and ensuring the efficiency of the operation. The hospital environment is usually complex and diverse, and the optimization of the disinfection operation path is crucial for improving the operation efficiency and reducing resource waste. Through intelligent path analysis and optimization, the accuracy of disinfection operations can be improved, reducing disinfection blind spots and ensuring that infection prevention and control measures are more scientific and reasonable.

[0028] Combined with data such as the moving interval E, the horizontal spraying angle F, and the vertical spraying angle G, the actual coverage range and depth of each spraying can be calculated. This enables the system to dynamically adjust the spraying strategy to ensure that the disinfectant evenly covers each area, avoiding uneven spraying effects or uncovered areas. This dynamic adjustment method can effectively solve the problem of insufficient spraying coverage in existing disinfection work and prevent the occurrence of "blind spots" or "vacuum intervals". By real-time adjusting the spraying angle and interval, the comprehensiveness of the disinfection effect can be ensured, and the risk of nosocomial infection transmission can be minimized to the greatest extent.

[0029] By monitoring the wind force intensity H and the atomization degree I in real time, the spraying strategy can be corrected in real time to ensure the even coverage of the agent under different environmental conditions. For example, when the wind force is strong, the system can automatically adjust the spraying intensity to avoid uneven diffusion of the agent. The real-time analysis of the atomization effect can optimize the coverage effect of the disinfectant, ensure even spraying, and improve the disinfection efficiency. Traditional disinfection methods often fail to fully consider the dynamic changes of environmental factors, which easily leads to uneven spraying coverage and thus affects the disinfection effect. By real-time correcting the wind force and atomization degree, this method can avoid the negative impact of environmental changes on the disinfection effect to the greatest extent and ensure the high efficiency of the disinfection process in various environments.

[0030] By collecting the real-time data of the first data group and the second data group, the system can immediately evaluate the coverage effect of each disinfection area and generate real-time feedback. This enables the disinfection personnel to flexibly adjust the work strategy and operation method according to the data and analysis provided by the system. This real-time feedback mechanism meets the requirements of hospital infection control for rapid response and efficient management, can timely detect deficiencies in the disinfection operation, and make corresponding adjustments to ensure the timely and effective implementation of infection prevention and control measures.

[0031] By accurately analyzing factors such as the disinfection path, spraying angle, and number of actions, unnecessary resource waste can be effectively reduced. After optimizing the disinfection path and equipment configuration, the disinfection personnel can complete the operation more efficiently, saving time and the amount of disinfectant used. Hospital infection prevention and control requires both high efficiency and resource conservation. Through refined disinfection work, the operation efficiency is improved, and resource waste is avoided, meeting the dual requirements of modern hospital management for resource conservation and efficient operation.

[0032] Through systematic data collection and analysis, disinfection work becomes more standardized and sustainable. This method can not only ensure that the current disinfection operation meets the specified standards but also provide data support for future disinfection operations, promoting long-term hospital infection prevention and control work. Hospitals need long-term and stable infection prevention and control measures. By standardizing the evaluation of the disinfection effect and tracking the data, not only the effect of the current operation is improved, but also data support is provided for subsequent optimization and decision-making, making the hospital's infection prevention and control more scientific and long-term.

[0033] Based on these precise data analyses and real-time feedback, hospitals can better control the sources of infection during disinfection operations and reduce the occurrence of cross-infection. This not only improves the hospital's hygiene management level but also ensures the health and safety of patients. Through more precise and intelligent disinfection quality control, this method can effectively reduce the incidence of nosocomial infections and enhance the hospital's infection prevention and control capabilities. This is closely in line with the current high standards in the medical industry for patient safety and medical quality.

[0034] Example 3: Please refer to Figure 1 , in step S2, the basic disinfection area JMJ is obtained by integrating and calculating the path length C, the number of actions D, the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I. By combining the moving interval E and the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. According to the change of the vertical spraying angle G, the influence in the vertical direction is reflected. The wind correction coefficient is used to adjust. The greater the wind, the more significant the influence. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation; The specific calculation formula is as follows: ; In the formula: D1 is the number of the first action, E1 is the first moving interval, F1 is the first horizontal spraying angle, G1 is the first vertical spraying angle, I1 is the first atomization degree, and H1 is the first wind intensity.

[0035] In step S2, the secondary disinfection area RMJ is obtained by integrating and calculating the path length C, the number of actions D, the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I. By combining the moving interval E and the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. According to the change of the vertical spraying angle G, the influence in the vertical direction is reflected. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation; The specific calculation formula is as follows: ; In the formula: D2 is the number of the second action, E2 is the second moving interval, F2 is the second horizontal spraying angle, G2 is the second vertical spraying angle, I2 is the second atomization degree, and H2 is the second wind intensity.

[0036] In step S2, the disinfection vacuum area ZKJ is calculated by subtracting the basic disinfection area JMJ and the secondary disinfection area RMJ from the total disinfection target area A. The basic disinfection area JMJ and the secondary disinfection area RMJ respectively represent the coverage areas of two stages. Their sum represents the actual area covered by the equipment, and the remaining part is the area that cannot be covered, that is, the vacuum area ZKJ. The specific calculation formula is as follows: ; In the formula: A is the disinfection target area, JMJ is the basic disinfection area, and RMJ is the secondary disinfection area RMJ.

[0037] In this embodiment: By integrating and calculating multiple factors such as the path length C, the number of actions D, the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I, the coverage effect of each disinfection area is accurately evaluated. This precise calculation ensures the comprehensiveness and efficiency of the disinfection operation, can effectively cover each area, reduce the existence of the non-disinfected area, that is, the "vacuum area", and improve the comprehensiveness and safety of infection prevention and control. This improvement meets the requirements of hospital infection prevention and control for high-standard disinfection effects, and minimizes the risk of nosocomial cross-infection to the greatest extent.

[0038] By combining the moving interval E and the horizontal spraying angle F, the actual width covered by each spraying is calculated; at the same time, the vertical spraying angle G determines the depth and thickness of the spraying. The adjustment of the vertical spraying angle can effectively reflect the influence of the spraying in the vertical direction. This method can flexibly adjust the width and depth of the spraying according to the actual situation to ensure that each area can be comprehensively and evenly covered. By optimizing the spraying range and depth, the risk of incomplete disinfection in local areas is reduced, and the disinfection effect is more balanced and accurate. This control method effectively improves the quality of disinfection, ensures that each corner can be covered by enough disinfectant, and thus improves the overall hygiene level of the hospital.

[0039] The wind intensity H and the atomization degree I are used as correction factors and are dynamically corrected in the calculation. The greater the wind force, the more significant the diffusion of the sprayed agent, and the higher the atomization degree, the higher the uniformity of the sprayed agent. By considering the influence of environmental factors on the disinfection effect in real time, the disinfection strategy can be effectively adjusted to avoid the problem of uneven spraying caused by changes in wind force, humidity, etc. For example, in the case of strong wind, the system can adjust the spraying intensity or spraying mode to ensure that the agent can be evenly distributed. This intelligent adjustment ensures that the disinfection operation can maintain stability and efficiency in different environments, enhances the adaptability of the system, and ensures that the disinfection quality is not affected regardless of environmental changes.

[0040] This method adjusts the execution strategy of disinfection operations in real time by dynamically analyzing various influencing factors such as path length, spraying angle, and environmental factors. Specifically, the system can adjust the spraying strategy according to the environmental changes and equipment performance of each operation, optimize the equipment configuration, and ensure that the disinfection operation is more efficient. This method avoids the inefficiency problems caused by fixed configuration and paths in traditional disinfection operations. Through data-driven dynamic adjustment, the disinfection operation can be continuously optimized according to the actual situation, ensuring the maximization of resource utilization, reducing waste, and improving the overall work efficiency. This provides a more flexible and efficient disinfection management solution for hospitals, enhancing the hospital's ability and response speed in preventing and controlling hospital infections.

[0041] By comprehensively considering the path length C, the number of actions D, the moving interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I, the actual coverage area of each secondary disinfection can be accurately calculated. This refined calculation method enables the secondary disinfection to more precisely make up for the deficiencies in the basic disinfection. Especially in complex environments, it can more accurately handle the distribution problem of the disinfectant.

[0042] Traditional disinfection methods often cannot accurately evaluate the disinfection effect under different operating conditions. Through this calculation of comprehensive data, it can ensure that the coverage effect of the secondary disinfection is more precise, reduce the coverage blind spots caused by changes in equipment configuration or environmental factors, thereby effectively improving the quality of the disinfection operation, reducing the risk of nosocomial infection, and enhancing the hospital's ability to prevent and control infections.

[0043] By combining the moving interval E with the horizontal spraying angle F, the actual coverage width of each spraying can be dynamically calculated, and the spraying depth and thickness can be further adjusted by combining the vertical spraying angle G. This calculation method can adjust the spraying strategy of the disinfection equipment according to different paths and angles.

[0044] In traditional disinfection operations, due to the lack of precise dynamic adjustment, the disinfectant may often fail to completely cover each area, especially the spraying depth and width are difficult to accurately control. Through this calculation method, the spraying range can be flexibly adjusted according to the specific environment and requirements, ensuring that each area can be evenly and sufficiently covered by the disinfectant, thus greatly improving the comprehensiveness and uniformity of the disinfection operation.

[0045] By introducing the wind correction coefficient H and the atomization degree I, the spraying effect of the disinfectant is dynamically adjusted. The greater the wind intensity, the more significant the diffusion of the agent, which may lead to uneven coverage; the atomization degree determines the uniformity of the agent distribution.

[0046] Traditional disinfection methods often overlook the impact of environmental changes on spraying effects. In particular, changes in wind force and atomization degree may lead to uneven disinfection effects, resulting in insufficient coverage of certain areas by the disinfectant. By dynamically correcting these factors, the system can adjust the spraying strategy in real time to ensure stable and balanced disinfection effects. For a complex environment like a hospital, the dynamic correction of environmental factors can ensure that the disinfection effect is not affected by external environmental fluctuations, guaranteeing the efficiency of disinfection work.

[0047] By calculating the basic disinfection area JMJ and the secondary disinfection area RMJ and integrating them, these two parts of the area can be subtracted from the total disinfection target area A, thereby accurately identifying the uncovered area, that is, the disinfection vacuum interval ZKJ.

[0048] There are often some "vacuum intervals" or blind spots inside the hospital. Especially when the equipment configuration or operation path arrangement is improper, these areas may not be effectively disinfected, increasing the risk of cross-infection. Through this method, the disinfection effect can be evaluated in real time and these vacuum intervals can be identified to ensure that every area of the hospital is covered by the disinfection work, reducing the hidden danger of hospital infection transmission. The implementation of this method has effectively improved the scientific nature and pertinence of disinfection operations and reduced the infection risk.

[0049] By conducting multi-source data collection and analysis on the first data group and the second data group, the disinfection compensation area BMJ and the extreme compensation value JBZ can be automatically generated, and it can be dynamically determined whether the vacuum interval can be compensated, generating real-time feedback and adjustment instructions.

[0050] Compared with traditional manual operations, this method can monitor and adjust disinfection operations in real time through an intelligent data analysis and real-time feedback system, reducing human errors and operation delays. Disinfection personnel can quickly adjust the operation strategy according to the suggestions automatically generated by the system to ensure that every area can be processed in a timely and accurate manner, improving the operation efficiency and quality. The improvement of this intelligent level makes the hospital infection prevention and control work more efficient and scientific, meeting the requirements of modern hospital management for efficient and automated operations.

[0051] By accurately calculating the disinfection coverage area of each area, it can be ensured that the disinfectant is only used in the areas that need compensation, while avoiding repeated disinfection of areas that have been fully covered, optimizing the use of resources.

[0052] This method can help hospitals optimize the allocation of disinfection resources, avoid unnecessary consumption, and at the same time improve the efficiency of disinfection operations. Especially in the case of great pressure on epidemic prevention and control, reasonable allocation of disinfection resources can not only reduce cost expenditures for hospitals, but also improve the overall prevention and control effect. Through intelligent optimization of resource allocation, hospitals can ensure efficient disinfection while reducing the waste of disinfectants and human resources.

[0053] By integrating multi-dimensional data and combining dynamic adjustment with intelligent compensation strategies, this method can monitor and correct deficiencies in disinfection operations in real time, ensuring that each area meets the specified disinfection standards.

[0054] Traditional disinfection methods often rely on manual experience, with significant subjectivity and errors. However, this method, through intelligent data processing and feedback, can ensure that hospital infection prevention and control work is more accurate and scientific. Hospitals can make decisions based on real-time data and feedback, improving the accuracy of infection control and further enhancing patient safety.

[0055] Example 4: Please refer to Figure 1 , in step S2, the specific analysis method for the disinfection vacuum interval ZKJ is as follows: When ZKJ ≤ Y, it means that the current disinfection vacuum interval ZKJ is reasonable; When ZKJ > Y, it means that the current disinfection vacuum interval ZKJ is unreasonable; where Y is a preset first threshold.

[0056] In this embodiment: By setting the preset first threshold Y, the system can analyze and judge in real time whether the current disinfection vacuum interval ZKJ is reasonable. If the value of the current vacuum interval is less than the preset threshold Y, it is considered that the vacuum interval is reasonable and the disinfection effect meets the requirements; if the value of the vacuum interval is greater than the preset threshold, it is considered that there are deficiencies in the current disinfection operation and compensation adjustment is required.

[0057] This improvement point can help hospitals monitor and evaluate the coverage effect of disinfection operations in real time. Traditional disinfection methods often cannot accurately identify which areas are not effectively covered, resulting in potential infection transmission risks. By judging the reasonableness of the vacuum interval in real time, hospitals can take timely measures to ensure the comprehensiveness and effectiveness of disinfection operations. This improvement significantly improves the accuracy and timeliness of hospital infection prevention and control and reduces the error of human judgment.

[0058] By analyzing the reasonableness of the disinfection vacuum interval ZKJ, the system can dynamically adjust the disinfection strategy and resource allocation. If it is found that the current disinfection operation cannot cover some areas, the system will automatically adjust the spraying path, spraying angle or compensate for the amount of disinfectant used to ensure that there are no blind spots or omitted areas.

[0059] The implementation of the dynamic adjustment strategy can ensure that the disinfection operation can obtain the optimal effect under different circumstances, especially when environmental factors change or the disinfection path is incomplete. Through intelligent adjustment, hospitals can maintain efficient disinfection operations in complex environments, ensure that all areas are disinfected in a timely and sufficient manner, and thus further reduce the risk of nosocomial infection. This is highly consistent with the goal of hospital infection prevention and control and improves the flexibility and response speed of prevention and control operations.

[0060] By setting a preset threshold Y and combining real-time monitoring data, the system can automatically determine whether the current disinfection vacuum interval is reasonable, thus avoiding manual intervention. The system can automatically give the result of rationality analysis without manual judgment.

[0061] This automated analysis method can reduce manual errors and improve the overall efficiency of disinfection work. In a hospital environment, disinfection operations are usually time-consuming and involve multiple complex areas. Automated analysis not only reduces the workload of disinfection personnel but also improves the accuracy and timeliness of operations. This improvement helps to enhance the hospital's infection control level and reduce the potential risks brought by human operations.

[0062] Based on real-time data analysis and the set threshold Y, the system can provide data-driven decision support for the hospital. Judging whether the disinfection vacuum interval ZKJ is reasonable directly affects the subsequent disinfection adjustment strategy and instruction generation.

[0063] Data-driven decision support enables the hospital to make precise adjustment decisions based on objective data analysis rather than relying on subjective experience or single perception. This method can ensure that the hospital's infection prevention and control work not only meets the standard requirements but also can be flexibly adjusted according to the actual situation, further improving the overall infection prevention and control level of the hospital and minimizing the occurrence probability of nosocomial infections.

[0064] By setting a clear threshold Y, the system can standardize the evaluation process of disinfection operations, enabling the coverage effect of each disinfection area to be evaluated according to a unified standard, and there is also a clear standard basis for the rationality of the disinfection vacuum interval.

[0065] The disinfection work can not only achieve real-time dynamic adjustment but also ensure the standardization and controllability of the entire disinfection process. For the hospital, this can ensure that each disinfection operation meets high-standard quality requirements, further enhancing the credibility and sustainability of infection prevention and control, and ensuring that the hospital continuously provides a safe and sterile environment.

[0066] The system makes a rationality analysis of the disinfection vacuum interval ZKJ and makes real-time adjustments according to the data, enabling the hospital to continuously optimize the disinfection effect during long-term operation and gradually establish an efficient infection prevention and control system.

[0067] This continuous optimization method can not only improve the short-term disinfection effect but also continuously improve the disinfection quality in the long-term infection prevention and control management by accumulating data and experience, and establish a more efficient work process. This has a positive impact on the long-term operation of the hospital and the infection prevention and control effect.

[0068] Example Five: Please refer to Figure 1, in step S3, the disinfection compensation area BMJ is obtained by integrating and calculating the total disinfection area A, path length C, number of actions D, moving interval E, horizontal spraying angle F, vertical spraying angle G, wind intensity H, and atomization degree I. The total disinfection area A is the basis for preliminary calculation and represents the size of the area to be disinfected. By calculating the ratio of the path length C to the total area A, the coverage efficiency per meter of the path can be obtained. The longer the path length, the smaller the area that needs to be covered per unit path, thus affecting the actual disinfection effect. The ratio of the number of actions D to the path length C reflects the operation frequency per unit path. The higher the operation frequency, the better the coverage effect per unit path. The larger the spraying angle, the wider the spraying range of the device. By combining the moving interval E with the horizontal spraying angle F, the actual width covered by each spraying can be calculated. The vertical spraying angle G determines the depth and thickness of the spraying. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation; The specific calculation method is as follows: ; In the formula: D1 is the number of the first action, E1 is the first moving interval, F1 is the first horizontal spraying angle, G1 is the first vertical spraying angle, I1 is the first atomization degree, and H1 is the first wind intensity; D2 is the number of the second action, E2 is the second moving interval, F2 is the second horizontal spraying angle, G2 is the second vertical spraying angle, I2 is the second atomization degree, and H2 is the second wind intensity; A is the total disinfection area.

[0069] In this embodiment: By integrating and calculating multiple factors such as the total disinfection area A, path length C, number of actions D, moving interval E, spraying angles F and G, wind intensity H, and atomization degree I, the coverage effect of the disinfection area can be accurately evaluated. The comprehensive consideration of these factors ensures that the actual coverage ability of each meter of the path and each spraying operation is reasonably analyzed, thus avoiding the problem of insufficient coverage in traditional disinfection operations.

[0070] In an environment such as a hospital, the disinfection coverage efficiency is directly related to the effectiveness of infection control. Through meticulous calculations, it can be ensured that each area is fully covered. The disinfection operation no longer relies on manual estimation but is based on precise data analysis, improving the quality and effect of disinfection. This not only enhances the comprehensiveness of hospital infection prevention and control but also avoids possible "blind spots" or "vacuum intervals", minimizing the risk of cross-infection to the greatest extent.

[0071] Calculate the actual coverage area for each spraying by combining the path length C, the number of actions D, and the spraying angles F and G. This adjustment enables the spraying strategy to be flexibly changed according to the actual situation, optimizing the spraying range and depth of the disinfection operation.

[0072] Traditional disinfection methods often have fixed spraying patterns and ranges, which may lead to over-cleaning in some areas while other areas are not effectively treated. By dynamically adjusting the spraying range and depth, it is ensured that each area can receive an appropriate amount of chemical agent coverage according to the demand, avoiding problems such as resource waste and uneven disinfection effects. This improvement enhances the accuracy and flexibility of the disinfection operation, making the disinfection work more efficient and meeting the requirements of high-standard infection prevention and control in hospitals.

[0073] Through the correction of environmental factors such as wind intensity H and atomization degree I, the disinfection operation can be adjusted in a timely manner according to external conditions. The greater the wind force, the more significant the diffusion of the sprayed chemical agent, and the higher the atomization degree, the more uniform the distribution of the chemical agent. The system automatically adjusts these factors to ensure that the coverage effect of the chemical agent is not affected by adverse environmental factors.

[0074] Environmental factors such as wind force and humidity will directly affect the disinfection effect. Traditional methods often do not consider these factors, resulting in uneven disinfection effects. By dynamically correcting these environmental impacts, this method can ensure that the disinfection effect remains stable under different environmental conditions. Especially when there are significant environmental differences between different areas in the hospital, this adjustment is particularly important. Through these corrections, the infection prevention and control measures in the hospital become more refined and reliable.

[0075] By analyzing the two disinfection operations D1, E1, F1, G1, I1, H1 and D2, E2, F2, G2, I2, H2 separately, it is possible to adjust the parameters of each operation according to the actual situation and optimize the spraying effect of each disinfection. This way ensures that the disinfection operation can adapt to different areas, paths, spraying angles, and environmental conditions.

[0076] Compared with traditional disinfection methods, this method ensures the efficiency and accuracy of the disinfection process through intelligent automatic analysis and adaptive adjustment. The internal structure of the hospital is complex, and the requirements and environmental conditions of the disinfection areas are variable. Adopting this intelligent adjustment mechanism can avoid errors in manual operations, reduce unnecessary resource waste, and ensure that all areas are effectively disinfected, thereby improving the overall infection prevention and control level.

[0077] By optimizing factors such as spraying angle, path length, and action frequency, ensure that the dosage of the chemical agent in each disinfection area reaches the best ratio, and there will be no situation of chemical agent waste or insufficient coverage. After the calculation method is refined, the use of disinfectants will be more reasonable.

[0078] In the disinfection and sterilization operations of a hospital, disinfectants are an important resource. By accurately calculating the dosage of disinfectant required for each disinfection task, unnecessary waste can be avoided. By reducing the waste of disinfectant and improving the efficiency of disinfection and sterilization, the hospital can reduce costs while ensuring the quality of disinfection and sterilization operations. This has a positive promoting effect on resource management, budget control, and overall operation optimization, improving the operational efficiency of the hospital.

[0079] Through real-time feedback on multi-dimensional data such as the total disinfection area A, disinfection path, number of actions, spraying angle, etc., the system can provide precise guidance for disinfection personnel and optimize operation strategies.

[0080] Through the real-time feedback mechanism, disinfection personnel can adjust their working methods in a timely manner according to the instructions and analysis results of the system. This data-driven decision support not only improves the intelligence level of disinfection and sterilization operations but also ensures that each disinfection task meets the standard requirements, contributing to the timeliness and accuracy of hospital infection prevention and control.

[0081] Example Six: Please refer to Figure 1 , in step S3, the specific analysis method for analyzing the disinfection compensation area BMJ and the disinfection vacuum interval ZKJ is as follows: When BMJ < ZKJ, it means that the current disinfection compensation area BMJ cannot fill the disinfection vacuum interval ZKJ; When ZKJ ≥ Y, it means that the current disinfection compensation area BMJ can fill the disinfection vacuum interval ZKJ.

[0082] In this embodiment: 1. Accurately judge the compensation ability and operation adjustment By comparing and analyzing the disinfection compensation area BMJ and the disinfection vacuum interval ZKJ, the system can judge whether the current disinfection compensation area is sufficient to fill the vacuum interval. When BMJ is greater than or equal to ZKJ, it means that the current disinfection operation can completely cover all areas; if BMJ is less than ZKJ, it means that there are uncovered areas, and the compensation strategy needs to be adjusted or the use of disinfectant needs to be increased.

[0083] This dynamic judgment mechanism can ensure that disinfection operations can be adaptively adjusted according to real-time feedback and data, avoiding the situation of insufficient coverage. Through the intelligent judgment system, the hospital can make adjustments at the first time when problems are found, effectively reducing the blind spots in the disinfection process and ensuring the comprehensiveness and balance of disinfection effects. This method highly conforms to the requirements of high efficiency and accuracy in hospital infection prevention and control and can greatly reduce the risk of cross-infection.

[0084] In the disinfection and sterilization operation, if it is found that the current disinfection compensation area BMJ is not sufficient to fill the disinfection vacuum interval ZKJ, the system will automatically adjust the disinfection strategy, such as by increasing the compensation dosage, changing the spraying path, or adjusting the spraying frequency, to ensure that all untreated areas are covered.

[0085] This improvement can ensure the dynamic optimization of disinfection and sterilization operations. Traditional disinfection methods may not be able to detect and address the issue of insufficient coverage in a timely manner. Through intelligent analysis, hospitals can detect and adjust disinfection operations in real time to ensure that every area is adequately cleaned and disinfected. This makes infection prevention and control more scientific and precise, greatly improves work efficiency, and avoids waste of resources.

[0086] By automatically analyzing the disinfection compensation area BMJ and the disinfection vacuum interval ZKJ, errors in manual operations and judgments are reduced. The system can give optimal decisions based on actual data, and disinfection personnel only need to execute the adjustment suggestions of the system without relying on experience and manual calculations.

[0087] In disinfection work, manual operations are often affected by subjective factors, resulting in errors or omissions. Through the system's automatic judgment, disinfection personnel can complete tasks efficiently, reduce errors and repetitive labor, and improve work precision. This improvement enhances the standardization and consistency of hospital disinfection work, saves time and costs, and improves infection prevention and control efficiency.

[0088] When the system detects that the disinfection compensation area cannot fill the vacuum interval, it can immediately give feedback and provide adjustment suggestions. This means that hospital infection prevention and control managers can understand the actual effect of disinfection operations in real time and respond promptly to ensure that remedial measures are taken in a timely manner.

[0089] In a hospital environment, disinfection work requires a high level of real-time response ability, especially during critical periods of epidemic prevention and control. This method enhances the hospital's control ability over disinfection operations through real-time data feedback and intelligent judgment. Hospital managers can make quick responses based on system suggestions to ensure that infection prevention and control measures are not delayed, thereby improving the timeliness and accuracy of hospital infection control.

[0090] By analyzing the disinfection requirements of each area and combining the relationship between the disinfection compensation area and the vacuum interval, the system can dynamically adjust the disinfection strategies for different areas. For example, in some areas, due to the influence of equipment configuration or environmental factors, the disinfection effect may be inferior to other areas, and the system will specifically increase the compensation area to ensure that all areas are adequately disinfected.

[0091] The hospital environment is usually complex and changeable, with different disinfection requirements for each area, and may be affected by factors such as environmental changes and equipment status. Through this method, disinfection operations can be dynamically adapted to the specific requirements of different areas to ensure that the disinfection effect of each area meets the standards. This highly adaptable disinfection control method effectively enhances the hospital's infection prevention and control ability, ensuring efficient disinfection under various environmental conditions.

[0092] Based on the relationship between the disinfection compensation area BMJ calculated in real time and the disinfection vacuum interval ZKJ, the system can intelligently adjust the usage amount of the disinfectant to ensure reasonable allocation of resources. If the current compensation area is not sufficient to cover the vacuum interval, the system will automatically increase the dosage of the disinfectant to avoid waste of resources.

[0093] By optimizing the use of disinfectants, hospitals can reduce the waste of chemicals and ensure the efficient progress of disinfection operations. At the same time, this also helps hospitals control the cost of disinfection operations, improve resource utilization rate on the premise of ensuring disinfection quality. This improvement meets the hospital's requirements for resource conservation and efficient management, and improves the overall operation efficiency.

[0094] Example 7: Please refer to Figure 1 , in step S4, the extreme compensation value JBZ is obtained by integrating and calculating the total disinfection area A, field of view range B, path length C, number of actions D, moving interval E, horizontal spraying angle F, vertical spraying angle G, wind force intensity H, and atomization degree I. The total disinfection area A is the basis for preliminary calculation, representing the size of the area that needs to be disinfected. By calculating the ratio of the path length C to the total area A, the coverage efficiency per meter of the path can be obtained. The longer the path length, the smaller the area that needs to be covered per unit path, thus affecting the actual disinfection effect. The ratio of the number of actions D to the path length C reflects the operation frequency per unit path. The higher the operation frequency, the better the coverage effect per unit path. The larger the spraying angle, the wider the spraying range of the device. By combining the moving interval E and the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. The atomization degree I directly affects the coverage effect of the chemical agent, and the atomization degree I is directly used as a correction factor and multiplied into the calculation; The specific calculation method is as follows: ; In the formula: D1 is the number of actions for the first time, E1 is the moving interval for the first time, F1 is the horizontal spraying angle for the first time, G1 is the vertical spraying angle for the first time, I1 is the atomization degree for the first time, and H1 is the wind force intensity for the first time; D2 is the number of actions for the second time, E2 is the moving interval for the second time, F2 is the horizontal spraying angle for the second time, G2 is the vertical spraying angle for the second time, I2 is the atomization degree for the second time, and H2 is the wind force intensity for the second time; A is the total disinfection area, C is the path length, and B is the field of view range.

[0095] In this embodiment: By integrating multiple factors such as the total disinfection area A, the field of view B, the path length C, the number of actions D, the moving interval E, the spraying angles F and G, the wind intensity H, and the atomization degree I, the extreme compensation value JBZ is calculated. This improvement ensures that the disinfection operation can be flexibly adjusted according to different environmental conditions, operation modes, and equipment configurations to cope with various complex situations.

[0096] Traditional disinfection methods usually rely on fixed modes for operation and may not be able to cope with various dynamically changing environmental factors such as wind force and humidity. By calculating the extreme compensation value, the system can automatically adjust the operation parameters according to different conditions such as equipment status and environmental changes to ensure that each area receives sufficient disinfection coverage. This flexibility ensures that the hospital can still maintain a high level of infection prevention and control in a complex environment, meeting the high standards of the hospital under dynamically changing conditions.

[0097] By integrating and analyzing different spraying angles and the path length C, etc., the extreme compensation value JBZ can reflect the potential "vacuum intervals" or "blind spots" in the disinfection process caused by equipment configuration or environmental factors such as wind force and atomization degree. If the system detects these blind spots, it will make adjustments according to the extreme compensation value to fill these uncovered areas.

[0098] The internal structure of the hospital is complex, and traditional methods often ignore the differences in spraying effects in different areas, resulting in some areas not being effectively disinfected. By calculating the extreme compensation value JBZ, these "blind spots" can be accurately identified and filled, avoiding insufficient disinfection in the hospital environment and reducing the risk of cross-infection. Ensure that each area can be effectively covered, thus greatly improving the comprehensiveness and accuracy of hospital infection prevention and control.

[0099] By performing real-time calculations in combination with multiple parameters such as path length, spraying angle, and environmental factors, the extreme compensation value JBZ can automatically adjust the execution strategy of the disinfection operation. For example, if the system detects that the spraying effect is greatly affected by wind force, it will automatically increase the spraying dose or change the spraying frequency to compensate for the adverse effects brought by the wind force.

[0100] Traditional disinfection methods often rely on manual adjustment of operation strategies and lack a real-time response mechanism. Through this intelligent adjustment, the hospital can respond to environmental changes in real time, improve the adaptability and response speed of the operation. This automated mechanism improves the efficiency of the disinfection operation, ensures high-efficiency infection prevention and control, reduces the need for manual intervention and potential errors, and thus improves work efficiency and accuracy.

[0101] By calculating the extreme compensation value JBZ, the system can optimize the distribution of disinfectants to ensure that disinfection operations can meet the requirements without waste in specific areas or conditions. Especially in situations with large environmental changes, the system can adjust the amount of disinfectant used in real time to avoid problems of over-disinfection or under-disinfection.

[0102] This intelligent resource optimization can help hospitals save disinfectants in disinfection work, reduce unnecessary waste, and at the same time ensure the comprehensiveness and efficiency of disinfection operations. With the intelligence of resource allocation, the operating costs of hospitals are effectively controlled, and resources are used more efficiently, meeting the requirements of modern hospital management for efficient resource utilization.

[0103] By analyzing the extreme compensation value JBZ, hospitals can accurately evaluate and adjust the quality and effect of disinfection operations to ensure comprehensive and balanced disinfection coverage in any situation. This method provides data-driven decision support and optimizes infection prevention and control measures.

[0104] The core goal of hospital infection prevention and control is precision management. Through this intelligent and data-driven method, hospitals can precisely control the disinfection effect in each area. The system can provide real-time feedback on the status of disinfection operations to ensure that the disinfection work in each area meets the predetermined standards, thereby improving the hospital's infection prevention and control level, ensuring patient safety, and reducing the in-hospital infection rate.

[0105] Through the automated calculation and adjustment of the extreme compensation value JBZ, the system can reduce the workload of disinfection personnel, automatically generate adjustment instructions, and avoid errors caused by manual judgment. Disinfection personnel usually need to handle a large number of complex tasks in the daily work of the hospital, and manual operations are often easily affected by fatigue and errors. Through the automated calculation of the extreme compensation value, disinfection personnel can focus more on task execution without the need to frequently adjust and judge operation strategies. This not only improves operation efficiency but also reduces the risk of human errors, making the hospital's disinfection operations more standardized and automated and improving work quality.

[0106] Example 8: Please refer to Figure 1 , in step S4, the specific analysis method of the extreme compensation value JBZ and the disinfection vacuum interval ZKJ is as follows: When JBZ < ZKJ, it means that the current behavior cannot fill the disinfection vacuum interval ZKJ; When JBZ ≥ ZKJ, it means that the current behavior can fill the disinfection vacuum interval ZKJ.

[0107] In this embodiment: By comparing and analyzing the extreme compensation value JBZ with the disinfection vacuum interval ZKJ, the system can determine in real time whether the current disinfection operation is sufficient to cover the uncovered areas. When the extreme compensation value JBZ can cover the disinfection vacuum interval ZKJ, the system considers the current operation to be sufficient; otherwise, further compensation measures are required.

[0108] This real-time judgment mechanism can ensure the adaptability and comprehensiveness of disinfection operations under different environmental conditions. Traditional methods often rely on manual judgment, which is prone to incomplete coverage. Through intelligent comparison and analysis, the system can immediately identify and feedback whether the disinfection operation meets the expected standards, thus avoiding omissions and inadequacies and ensuring the efficiency and comprehensiveness of disinfection work.

[0109] If the system detects that the current extreme compensation value JBZ is not sufficient to cover the disinfection vacuum interval ZKJ, it will automatically adjust the disinfection operation strategy, such as increasing the dosage of the disinfectant, changing the spraying path, or adjusting the spraying frequency, to ensure that all areas are properly treated.

[0110] In high-risk environments such as hospitals, disinfection operations must be without blind spots and omissions. By automatically adjusting the disinfection strategy, hospitals can cope with different environmental factors and equipment configuration differences, ensuring that every area can be fully covered by disinfection. This improvement greatly reduces the mistakes in traditional manual intervention, enhances the hospital's infection prevention and control capabilities, and makes the disinfection operation more efficient and flexible.

[0111] By calculating the relationship between the extreme compensation value JBZ and the disinfection vacuum interval ZKJ, the system can make automatic responses. When the system finds that the current operation cannot cover the vacuum interval, it can quickly analyze the reasons and propose corresponding adjustment measures to ensure that the disinfection work can flexibly meet different operation requirements.

[0112] The intelligent automatic response system can adjust the parameters of the disinfection operation in real time, enabling disinfection personnel to quickly make compensation adjustments without being limited by environmental changes and equipment configurations. Therefore, the hospital's infection prevention and control becomes more efficient and precise, especially in complex and dynamic environmental conditions, and can timely respond to and eliminate potential risks.

[0113] By analyzing the extreme compensation value JBZ and the disinfection vacuum interval ZKJ, the system can optimize the allocation of resources. For example, when the vacuum interval ZKJ is large, the system will appropriately increase the amount of disinfectant or adjust the spraying frequency to ensure the reasonable configuration and efficient utilization of resources.

[0114] Traditional disinfection methods often lack consideration of resource optimization, which may lead to waste or shortage of disinfectants. Through intelligent analysis and dynamic adjustment, the system can ensure that disinfection resources are used in the optimal ratio in each area, avoiding waste of resources while ensuring the comprehensiveness of disinfection effects. This is of great significance to the hospital's operating cost control and resource conservation.

[0115] By combining disinfection compensation analysis with preset standards, the system can intelligently evaluate the effectiveness of disinfection operations based on real-time data and ensure that each area meets the prescribed disinfection standards. This not only avoids the risk of infection caused by insufficient disinfection, but also ensures the scientificity and accuracy of the operation process.

[0116] The infection prevention and control tasks of hospitals require that disinfection work must be not only efficient but also precise. Through this data-driven analysis method, the hospital can disinfect each area with higher standards and requirements to ensure that every corner is adequately treated. Compared with the traditional disinfection method that relies on manual experience, this method reduces human bias, improves the scientificity and accuracy of disinfection work, and further ensures the hygiene of the hospital and the safety of patients.

[0117] By calculating the relationship between the extreme compensation value JBZ and the disinfection vacuum interval ZKJ in real time, the system can provide hospital managers with real-time disinfection effect feedback and make decisions quickly based on the feedback. This not only improves management efficiency, but also enhances the hospital's response capabilities in dealing with public health emergencies.

[0118] For hospitals, real-time management and decision-making are the key to efficient infection prevention and control. Through this real-time calculation and feedback, hospitals can understand the effectiveness of disinfection at any time and quickly adjust their operation strategies when problems are found, avoiding infection prevention and control errors caused by delayed feedback in traditional methods. This improvement enhances the flexibility and emergency response capabilities of hospitals, and helps improve the overall hospital management level and risk resistance. The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0119] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for quality control of hospital infection disinfection and sterilization based on vision, characterized in that: The specific steps are as follows: S1. Collect multi-source data for the disinfection area and disinfection equipment and perform preprocessing to generate a first data group and a second data group; S2. Analyze the first data group and the second data group to obtain the basic disinfection area JMJ and the secondary disinfection area RMJ, and perform integrated calculation on the basic disinfection area JMJ and the secondary disinfection area RMJ to generate a disinfection vacuum interval ZKJ, and perform rationality analysis on the disinfection vacuum interval ZKJ; S3. Analyze the first data group and the second data group to obtain the disinfection compensation area BMJ, and perform integrated analysis on the disinfection compensation area BMJ and the disinfection vacuum interval ZKJ to determine whether the disinfection vacuum interval can be compensated under normal movement; S4. Analyze the first data group and the second data group to obtain the extreme compensation value JBZ, and analyze the extreme compensation value JBZ and the disinfection vacuum interval ZKJ to determine whether the disinfection vacuum interval ZKJ can be satisfied under extreme conditions; S5. Adjust the extreme compensation value JBZ to make it adapt to the actual requirements, generate an actual instruction, and send it to the disinfection personnel.

2. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 1, characterized in that: In step S1, the first data group includes: the total disinfection area A, the field of view B, the path length C, and the number of actions D; The second data group includes: the movement interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I.

3. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 2, characterized in that: In step S2, the basic disinfection area JMJ is obtained by integrating and calculating the path length C, the number of actions D, the movement interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I. By combining the movement interval E and the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the spraying depth and thickness. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation.

4. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 3, wherein: In step S2, the secondary disinfection area RMJ is obtained by integrating and calculating the path length C, the number of actions D, the movement interval E, the horizontal spraying angle F, the vertical spraying angle G, the wind intensity H, and the atomization degree I. By combining the movement interval E and the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the spraying depth and thickness. The atomization degree I directly affects the coverage effect of the medicament, and the atomization degree I is directly used as a correction factor and multiplied into the calculation.

5. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 4, wherein: In step S2, the disinfection vacuum interval ZKJ is obtained by subtracting the basic disinfection area JMJ and the secondary disinfection area RMJ from the total disinfection target area A. The basic disinfection area JMJ and the secondary disinfection area RMJ respectively represent the coverage areas of two stages, and their sum represents the actual area covered by the equipment. The remaining part is the area that cannot be covered, that is, the vacuum interval ZKJ.

6. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 5, characterized in that: In step S2, the specific analysis method for the disinfection vacuum interval ZKJ is as follows: When ZKJ ≤ Y, it means that the current disinfection vacuum interval ZKJ is reasonable; When ZKJ > Y, it means that the current disinfection vacuum interval ZKJ is unreasonable; where Y is a preset first threshold.

7. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 6, wherein: In step S3, the disinfection compensation area BMJ is obtained by integrating and calculating the total disinfection area A, path length C, number of actions D, moving interval E, horizontal spraying angle F, vertical spraying angle G, wind intensity H, and atomization degree I. The total disinfection area A is the basis for preliminary calculation, representing the size of the area to be disinfected. By the ratio of the path length C to the total area A, the coverage efficiency per meter of the path can be obtained. The longer the path length, the smaller the area that needs to be covered per unit path, thus affecting the actual disinfection effect. The ratio of the number of actions D to the path length C reflects the operation frequency per unit path. The higher the operation frequency, the better the coverage effect per unit path. The larger the spraying angle, the wider the spraying range of the device. By combining the moving interval E with the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. The atomization degree I directly affects the coverage effect of the agent, and the atomization degree I is directly used as a correction factor and multiplied into the calculation.

8. A method for quality control of hospital infection disinfection and sterilization based on vision according to claim 7, characterized in that: In step S3, the specific analysis method for analyzing the disinfection compensation area BMJ and the disinfection vacuum interval ZKJ is as follows: When BMJ < ZKJ, it means that the current disinfection compensation area BMJ cannot fill the disinfection vacuum interval ZKJ; When ZKJ ≥ Y, it means that the current disinfection compensation area BMJ can fill the disinfection vacuum interval ZKJ.

9. The method for quality control of hospital infection disinfection and sterilization based on vision according to claim 8, characterized in that: In step S4, the extreme compensation value JBZ is obtained by integrating and calculating the total disinfection area A, field of view B, path length C, number of actions D, moving interval E, horizontal spraying angle F, vertical spraying angle G, wind intensity H, and atomization degree I. The total disinfection area A is the basis for preliminary calculation, representing the size of the area to be disinfected. By the ratio of the path length C to the total area A, the coverage efficiency per meter of the path can be obtained. The longer the path length, the smaller the area that needs to be covered per unit path, thus affecting the actual disinfection effect. The ratio of the number of actions D to the path length C reflects the operation frequency per unit path. The higher the operation frequency, the better the coverage effect per unit path. The larger the spraying angle, the wider the spraying range of the device. By combining the moving interval E with the horizontal spraying angle F, the actual width covered by each spraying is calculated. The vertical spraying angle G determines the depth and thickness of the spraying. According to the change of the vertical spraying angle G, the influence in the vertical direction is reflected. The wind correction coefficient is used for adjustment. The greater the wind, the more significant the influence. The atomization degree I directly affects the coverage effect of the agent, and the atomization degree I is directly used as a correction factor and multiplied into the calculation.

10. A method for quality control of hospital infection disinfection and sterilization based on vision according to claim 9, characterized in that: In step S4, the specific analysis method for the extreme compensation value JBZ and the disinfection vacuum interval ZKJ is as follows: When JBZ < ZKJ, it means that the current behavior cannot fill the disinfection vacuum interval ZKJ; When JBZ ≥ ZKJ, it means that the current behavior can fill the disinfection vacuum interval ZKJ.

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