Intelligent environment disinfection system and method based on iodophor

Abstract

The invention relates to the technical field of environment disinfection, in particular to an iodophor-based intelligent environment disinfection system and method.According to the system, disinfection condition judgment is formed by monitoring humidity pollutants and iodophor concentration in real time, regional priority values are generated by combining demand evaluation, paths are planned based on priorities, and resources are allocated; acquiring data before and after disinfection to generate an effect report, and dynamically adjusting distribution and concentration use according to feedback to form a complete closed loop. According to the method, through multi-dimensional parameter acquisition and cross analysis, a dynamic disinfection condition judgment standard can be established, regional priority ranking is completed in combination with pollution differences and humidity changes, demand distinguishing is more accurate, resource ratio and spraying amount adjustment are introduced in path planning, the coverage effect of a solution in a complex space is improved, and the solution quality is improved. And a feedback result is generated by comparing data before and after disinfection, and resource allocation and concentration control are dynamically corrected according to the feedback result, so that the overall optimization effect of reasonable sequence, full resource utilization and perfect feedback closed loop in a multi-region scene is realized.

Description

Technical Field

[0001] This invention relates to the field of environmental disinfection technology, and in particular to an intelligent environmental disinfection system and method based on iodine tincture. Background Technology

[0002] The field of environmental disinfection technology encompasses methods and devices for inhibiting or eliminating microorganisms such as bacteria, viruses, and fungi in specific environments. Its core content involves treating harmful microorganisms in the air, on object surfaces, and in liquid environments through physical, chemical, or biological means to reduce the risk of their spread and cross-infection. In its systematic development, environmental disinfection technology has gradually covered various application scenarios, including hospitals, schools, transportation, food processing, and public places, and has formed multiple technical pathways, including the use of chemical disinfectants, ultraviolet irradiation, ozone treatment, and aerosol suppression, aiming to provide adaptable disinfection methods for different usage needs.

[0003] Among them, the intelligent environmental disinfection system and method based on iodine tincture refers to an environmental disinfection solution that utilizes iodine tincture as the core disinfectant and combines sensor detection, liquid preparation, spraying and delivery, and environmental coverage control. It mainly covers the preparation and quantitative distribution of iodine tincture disinfectant, environmental parameter monitoring and disinfection condition triggering, liquid spraying path control, and multi-point coverage treatment. Through sensor acquisition and data-driven logic, it achieves the rational use and spatial distribution adjustment of the disinfectant. Overall, based on the chemical properties of iodine tincture and combined with liquid delivery and spraying execution units, it completes the automated disinfection process of the target environment.

[0004] Existing technologies mostly employ fixed triggering conditions and single-path execution modes, failing to flexibly adjust disinfection strategies based on differences in humidity and pollution levels in different areas. This results in insufficient treatment in some areas and repeated investment in others. In terms of resource allocation, there is a lack of dynamic adjustment mechanisms, making it impossible to optimize concentration distribution and usage in a timely manner according to environmental changes. Furthermore, the verification of disinfection results relies on a single execution, lacking continuous tracking of pollutant concentration differences, leading to an incomplete evaluation of effectiveness. In complex scenarios or when there are significant differences in needs, resource waste and uneven coverage often occur. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and to propose an intelligent environmental disinfection system and method based on iodine tincture.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent environmental disinfection system based on iodine tincture, the system comprising:

[0007] The environmental data monitoring module collects data on humidity, pollutant concentration, and iodine solution concentration in the disinfection area, monitors environmental changes in real time, determines whether the disinfection start-up conditions are met, analyzes the impact of humidity on pollutant concentration, determines whether the iodine concentration meets the start-up conditions, and generates the iodine disinfection start-up condition judgment result.

[0008] The disinfection priority calculation module assesses the disinfection needs of each disinfection area based on the iodine disinfection activation condition judgment result, sorts the areas with high humidity or high pollution concentration, calculates the execution order according to the demand, and generates the area disinfection priority value.

[0009] The path planning and resource scheduling module plans disinfection paths based on the regional disinfection priority value, combined with geographical information and pollution status, assesses the required concentration of iodine solution and resource amount for each path, adjusts the spraying amount according to the spraying path and equipment distribution, and generates a resource and path allocation plan.

[0010] The disinfection effect feedback module obtains the changes in the concentration of contaminants and the concentration of iodine solution after disinfection, determines whether the concentration of contaminants after disinfection meets the standards, compares the contaminant data before and after disinfection, calculates the actual coverage of the disinfectant in the area, and generates a disinfection effect evaluation report.

[0011] As a further aspect of the present invention, the iodine disinfection activation condition judgment result includes environmental compliance indicators, humidity influence parameters, and iodine concentration threshold; the regional disinfection priority value includes demand level parameters, urgency level parameters, and execution order parameters; the disinfection resource path allocation scheme includes path coverage indicators, resource allocation parameters, and spraying adjustment parameters; and the disinfection effect evaluation report includes pollutant change data, coverage effect data, and compliance data.

[0012] As a further aspect of the present invention, the environmental data monitoring module includes:

[0013] The humidity acquisition submodule acquires humidity data of the disinfection area collected by the smart sensor, organizes the humidity data in chronological order and by area number, compares the humidity data of the corresponding area at each time point with the humidity activation threshold, records the areas that do not meet the activation conditions and the corresponding time points, and determines the humidity segments that meet the activation conditions by combining the area and time dimensions, and obtains a list of humidity activation segments.

[0014] The pollutant concentration assessment submodule calls the area number of each time point in the humidity start-up zone list, matches the pollutant concentration data recorded by the pollutant sensor at the same time point, groups the concentration data and humidity data together, and determines the pollutant concentration response rate corresponding to the humidity change by calculating the average rate of change of pollutant concentration in the group, and obtains the pollutant response rate list.

[0015] The iodine concentration judgment submodule, based on the region number of each time point in the pollutant response rate list, calls the corresponding concentration data of the iodine concentration sensor to construct a set of mapping relationships between iodine concentration and pollutant response rate. By comparing the iodine concentration with the preset start-up concentration threshold and combining the consistency between the pollutant response rate change value and the time point of the humidity start-up zone, it determines whether the iodine meets the disinfection start-up requirements under the current conditions and generates the iodine disinfection start-up condition judgment result.

[0016] As a further aspect of the present invention, the disinfection priority calculation module includes:

[0017] The conditional filtering submodule, based on the area number and time point recorded in the iodine disinfection start condition judgment result, calls up the pollutant concentration data and humidity data of each area within the corresponding time period, compares the pollutant concentration value with the pollutant concentration benchmark threshold, filters the area data with a concentration greater than the threshold, then compares its corresponding humidity value with the humidity benchmark threshold, filters the area data with a humidity greater than the threshold, obtains the area number that meets both filtering conditions at the same time, and generates a list of high-demand area numbers.

[0018] The demand assessment submodule, based on each area number in the list of high-demand areas, calls the pollutant concentration value and humidity value of its corresponding time period, normalizes the two values ​​and weights them, sets the pollutant concentration weight coefficient and humidity weight coefficient as the pollutant coefficient value and humidity coefficient value respectively, and calculates the area demand value based on the weighted sum value to obtain the list of area disinfection demand values.

[0019] The sequential calculation submodule, based on the demand value of each region in the regional disinfection demand value list, arranges all regions in descending order of demand value, assigns sequential numbers to the arranged region numbers, pairs the region numbers with their sorting numbers, obtains the corresponding sorting number for each region as the disinfection priority value, and generates the regional disinfection priority value.

[0020] As a further aspect of the present invention, the path planning and resource scheduling module includes:

[0021] The path generation submodule, based on the order of the area numbers in the area disinfection priority value, calls the geographical location information of the corresponding area, calculates the geographical coordinate distance and connection direction between areas, plans a set of continuous path segments by traversing the shortest distance path between areas after priority value sorting, and establishes a correspondence between each path segment and its connected area number to generate a priority path number list.

[0022] The demand calculation submodule, based on the area numbers connected by each path segment in the priority path number list, calls the pollutant concentration value and humidity value corresponding to each area number, performs a weighted average of the pollutant concentration and humidity by path segment, compares the average value with the iodine concentration demand benchmark value, calculates the iodine solution demand per meter of path segment, and obtains the solution demand of the path segment.

[0023] The spraying adjustment submodule calls the unit demand data corresponding to each path segment in the solution demand of the path segment, matches the spraying equipment number and spraying radius value in the current path segment, calculates the overlap between the actual coverage area of ​​the spraying equipment and the area of ​​the path segment, multiplies the overlap with the unit solution demand of the path segment, obtains the adjusted spraying amount of each equipment in the path segment, and obtains the equipment spraying adjustment value.

[0024] The resource allocation submodule matches the remaining liquid volume of the adjustable equipment number with the current reserve iodine concentration based on the path segment number and spray volume requirement value corresponding to each equipment number in the equipment spray adjustment value, filters the equipment numbers whose reserve volume can cover the required spray volume, constructs a corresponding mapping set of path segments and equipment numbers, establishes the resource equipment number allocation relationship under each path segment, and generates a disinfection resource path allocation scheme.

[0025] As a further aspect of the present invention, the disinfection effect feedback module includes:

[0026] The concentration acquisition submodule acquires the pollutant concentration values ​​recorded by the pollutant sensors in each area after disinfection, and organizes them according to the area number and the acquisition time. It compares the acquired concentration values ​​with the pollutant baseline concentration threshold, filters out records with concentration values ​​less than or equal to the threshold and marks them as compliant area records, and marks the rest as non-compliant area records, generating a list of pollution compliance mark values.

[0027] The pollution change submodule, based on the area number in the pollution compliance marker value list, calls the pollutant concentration value before disinfection and the concentration value collected after iodine disinfection under the corresponding area number, calculates the difference between the concentration values ​​of the two time periods, divides the difference by the concentration value before disinfection to obtain the change ratio value, records the change ratio corresponding to each area number, and obtains the pollution concentration change rate list.

[0028] The coverage assessment submodule calls up the area number and change rate value in the pollution concentration change rate list, combines the spraying amount, spraying location and spraying equipment number in the iodine solution spraying record, calculates the cross ratio of the sprayed area and the area, and then weights and summarizes the cross ratio and the pollution concentration change rate to calculate the actual impact of iodine solution in the target polluted area under each area, and generates a disinfection effect assessment report.

[0029] As a further aspect of the present invention, the system further includes:

[0030] The resource dynamic scheduling module optimizes and adjusts the allocation of disinfectant and the spraying method within the area based on the disinfection resource path allocation scheme and disinfection effect evaluation report, monitors the use of disinfectant in real time, and dynamically adjusts the concentration of iodine solution and the amount of resources used according to the actual effect and needs, generating a resource scheduling adjustment scheme.

[0031] The resource scheduling and adjustment scheme includes allocation optimization parameters, spraying adjustment parameters, and concentration control parameters.

[0032] As a further aspect of the present invention, the resource dynamic scheduling module includes:

[0033] The dosage collection submodule, based on the equipment number and spray path number in the disinfection resource path allocation scheme, calls the real-time liquid volume record data and spray start and end time data during the spraying process, accumulates the total amount of spraying per unit time and collects it into the path number dimension, and then calculates the spraying rate value by combining the spraying duration under the path number to obtain a list of path spraying rate values.

[0034] The concentration adjustment submodule, based on the rate value corresponding to each path number in the path spraying rate value list, calls the pollutant concentration change value under the path number in the disinfection effect evaluation result, compares the difference between the spraying rate and the pollutant change value, records the path number where the spraying rate and the pollutant concentration change trend are opposite, and sets the adjustment range in combination with the iodine reserve concentration value under the current path number, obtains the iodine concentration adjustment value corresponding to each path, and obtains the path concentration adjustment value list.

[0035] The resource reallocation submodule calls all path numbers and concentration adjustment value data in the path concentration adjustment value list, matches the path number with the corresponding adjustable equipment number and the remaining liquid volume of the equipment, constructs a resource transfer matrix based on the current resource allocation and concentration adjustment value under the path number, and adjusts the resource allocation ratio of each equipment under the current path by the ratio difference between the remaining resource quantity and the demand quantity in the matrix, and generates a resource scheduling adjustment plan.

[0036] An intelligent environmental disinfection method based on iodine tincture, wherein the method is executed based on the aforementioned intelligent environmental disinfection system based on iodine tincture, and includes the following steps:

[0037] S1: Acquire data collected by humidity sensor, pollutant concentration data detected by air quality sensor, and iodine solution concentration data collected by solution concentration sensor within the disinfection area. Timestamp the three types of data and establish a unified sequence to generate iodine disinfection start condition judgment results.

[0038] S2: Based on the judgment result of the iodine disinfection start condition, call the pollutant concentration data and humidity data of each area, compare the pollutant concentration data with the air quality standard to obtain the exceedance difference, compare the humidity data with the set humidity threshold to obtain the exceedance difference, perform a weighted calculation on the exceedance difference and exceedance difference to obtain the disinfection demand data of each area, and then sort the disinfection demand data of all areas to generate the area disinfection priority value.

[0039] S3: Call the regional disinfection priority value and combine it with the geographical location information of each disinfection area to calculate the path of the priority order, compare the path length with the spray coverage of the spraying equipment, convert it into iodine consumption data, and generate a disinfection resource path allocation scheme.

[0040] S4: Based on the disinfection resource path allocation scheme, call the post-disinfection data collected by the pollutant concentration sensor, compare it with the pre-disinfection pollutant concentration data, calculate the pollutant concentration reduction, and combine it with the iodine solution concentration change data to obtain the coverage data and generate a disinfection effect evaluation report.

[0041] S5: Based on the disinfection effect evaluation report, retrieve the data on the amount of iodine solution used and the spraying method, adjust the regional iodine solution allocation, calculate the difference in spraying concentration after adjustment, and generate a resource scheduling adjustment plan.

[0042] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0043] In this invention, by collecting and cross-analyzing environmental parameters from multiple dimensions, dynamic judgment criteria for disinfection conditions can be formed. By combining differences in pollution and changes in humidity, the priority ranking of disinfection areas can be achieved, enabling precise differentiation of disinfection needs in different areas. By superimposing resource allocation and spray volume adjustment during the path planning process, the uniform coverage effect of the solution in complex spaces can be improved. By comparing data before and after disinfection, targeted effect feedback can be generated, further supporting the dynamic correction of resource allocation and concentration control. Thus, a comprehensive optimization effect of reasonable disinfection sequence, full resource utilization, and perfect feedback loop can be achieved in multiple areas and scenarios. Attached Figure Description

[0044] Figure 1 This is a system flowchart of the present invention;

[0045] Figure 2 This is a flowchart of the system sub-modules of the present invention;

[0046] Figure 3 This is a flowchart of the method of the present invention. Detailed Implementation

[0047] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0048] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0049] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0050] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0051] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0052] Please see Figure 1 This invention provides a technical solution: an intelligent environmental disinfection system based on iodine tincture, the system comprising:

[0053] The environmental data monitoring module collects real-time data on humidity, pollutant concentration, and iodine solution concentration in the disinfection area through intelligent sensors. It uses real-time data to monitor environmental changes, determine whether the disinfection area meets the disinfection start-up conditions, and analyzes the impact of humidity on pollutant concentration to determine whether the iodine solution concentration meets the start-up conditions, generating the iodine disinfection start-up condition judgment result.

[0054] The disinfection priority calculation module, based on the iodine disinfection start condition judgment result, calls the pollutant concentration and humidity data of the disinfection area to evaluate the disinfection needs of each disinfection area, sorts the areas with higher humidity or higher pollutant concentration, determines the areas that need to be disinfected first based on the area pollution situation, calculates the disinfection execution order according to the disinfection needs, and generates the area disinfection priority value.

[0055] The path planning and resource scheduling module plans disinfection paths based on regional disinfection priority values, combined with geographic information and pollution conditions. It determines the disinfection needs of each path, assesses the required concentration and amount of iodine solution for each path, adjusts the amount of disinfectant sprayed according to the spraying path and equipment distribution, optimizes the path coverage effect, and generates a disinfection resource path allocation plan.

[0056] The disinfection effect feedback module acquires and analyzes the concentration of pollutants in the area after disinfection, and monitors the changes in pollutant concentration in the disinfection area in real time by combining the changes in the concentration of iodine solution. It determines whether the concentration of pollutants after disinfection meets the standards, compares the pollutant data before and after disinfection, calculates the actual coverage of the disinfectant in the area, and generates a disinfection effect evaluation report.

[0057] The resource dynamic scheduling module optimizes and adjusts the allocation of disinfectant and the spraying method within the area based on the disinfection resource path allocation plan and disinfection effect evaluation report. It monitors the usage of disinfectant in real time and dynamically adjusts the concentration of iodine solution and the amount of resources used according to the actual effect and needs, generating a resource scheduling adjustment plan.

[0058] The results of the iodine disinfection activation conditions include environmental compliance indicators, humidity influence parameters, and iodine concentration thresholds. The regional disinfection priority values ​​include demand level parameters, urgency parameters, and execution order parameters. The disinfection resource path allocation plan includes path coverage indicators, resource allocation parameters, and spraying adjustment parameters. The disinfection effect evaluation report includes pollutant change data, coverage effect data, and compliance data. The resource scheduling and adjustment plan includes allocation optimization parameters, spraying adjustment parameters, and concentration control parameters.

[0059] Please see Figure 2 The environmental data monitoring module includes:

[0060] The humidity acquisition submodule acquires humidity data of the disinfection area collected by the smart sensor, organizes the humidity data in chronological order and by area number, compares the humidity data of the corresponding area at each time point with the humidity activation threshold, records the areas that do not meet the activation conditions and the corresponding time points, and determines the humidity segments that meet the activation conditions by combining the area and time dimensions, and obtains a list of humidity activation segments.

[0061] Based on the humidity data of the disinfection areas collected by intelligent sensors, the data was first organized. Specifically, referring to Table 1, the original environmental data of three disinfection areas (R01 - emergency room, R02 - outpatient hall, R03 - inpatient ward) in a hospital were collected at four consecutive time points (T1-T4, with an interval of 1 hour). The humidity data was associated with the area number in chronological order. For example, at time point T2, the humidity value of area R01 was 71%, the humidity value of area R02 was 73%, and the humidity value of area R03 was 75%. Next, a humidity threshold was set. This threshold was based on a 30-day controlled experiment. In a simulated hospital environment, the survival rate of suspended particles of common pathogens (such as Staphylococcus aureus) was monitored by adjusting the air humidity. The experimental data showed that when the relative humidity increased from 65% to 70%, the bacterial survival rate increased by 15%, and when the humidity increased from 70% to 75%, the increase reached 42%. Therefore, the humidity threshold was set to 70%. Subsequently, the humidity data of each area at each time point was analyzed. The humidity data for each region is compared with the threshold of 70%. For example, at time point T2, the humidity of region R01 (71%) is greater than 70%, the humidity of region R02 (73%) is greater than 70%, and the humidity of region R03 (75%) is greater than 70%, all meeting the condition. However, at time point T1, the humidity of region R01 (65%) and region R02 (68%) do not meet the condition. Therefore, these two regions and their corresponding time points are recorded as records that do not meet the activation condition, specifically recorded as (T1, R01, 65%) and (T1, Finally, by combining the regional and time dimensions, records that continuously meet the start-up conditions are grouped into humidity start-up segments. For example, if region R01 meets the conditions at two consecutive time points T2 and T3, its segment is [T2, T3]; if region R02 meets the conditions at two consecutive time points T2 and T3, its segment is [T2, T3]; and if region R03 meets the conditions at four consecutive time points T1, T2, T3, and T4, its segment is [T1, T4]. Finally, a list of humidity start-up segments is obtained.

[0062] Table 1: Initial Environmental Data of the Disinfection Area

[0063] Time point Area code humidity(%) <![CDATA[Pollutant concentration (μg / m 3 )]]> Iodine solution concentration (mg / L) T1 R01 65 120 450 T1 R02 68 150 455 T1 R03 72 90 440 T2 R01 71 180 452 T2 R02 73 210 458 T2 R03 75 130 445 T3 R01 74 250 449 T3 R02 76 280 460 T3 R03 78 180 448 T4 R01 68 150 451 T4 R02 70 190 455 T4 R03 72 110 442

[0064] As shown in Table 1, this table lists the environmental parameter monitoring values ​​of the three disinfection areas, which are in the initial state in this embodiment, at four time points.

[0065] The pollutant concentration assessment submodule calls the area number of each time point in the humidity start-up zone list, matches the pollutant concentration data recorded by the pollutant sensor at the same time point, groups the concentration data and humidity data together, and determines the pollutant concentration response rate corresponding to the humidity change by calculating the average rate of change of pollutant concentration in the group, and obtains the pollutant response rate list.

[0066] The humidity start-up zone list includes zones [T2,T3] of region R01, [T2,T3] of region R02, and [T1,T4] of region R03. For each zone in the list, the region number and time point are extracted. For example, for zone [T2,T3] of region R01, (R01,T2) and (R01,T3) are extracted. Then, based on the extracted region number and time point, the corresponding pollutant concentration data recorded by the pollutant sensor are matched from Table 1. Specifically, the concentration value matched for (R01,T2) is 180 μg / m³. 3 The concentration value matched by (R01,T3) is 250 μg / m³. 3 Next, the matched concentration data and the corresponding humidity data are jointly grouped to form a set of data pairs. For example, the joint grouping for region R01 is {(71%, 180μg / m²)}. 3 ), (74%, 250 μg / m 3 Then, for the joint grouped data of each region, the average rate of change of pollutant concentration is calculated. The calculation process is as follows: take the pollutant concentration at the end of the segment and subtract the pollutant concentration at the beginning of the segment, and then divide the difference by the corresponding time span. The time span is calculated in 1 hour / time point. For example, the average rate of change of region R01 is (250-180) / (3-2)=70 / 1=70μg / m 3 / h, similarly, the average rate of change of region R02 is (280-210) / (3-2)=70 / 1=70μg / m 3 / h, the average rate of change of R03 in the region is (110-90) / (4-1)=20 / 3≈6.67μg / m 3 / h, and finally, the calculated rate values ​​are associated with the region number and time segment to obtain a list of pollutant response rates.

[0067] The iodine concentration judgment submodule calls the corresponding concentration data of the iodine concentration sensor according to the region number of each time point in the pollutant response rate list, constructs a set of mapping relationships between iodine concentration and pollutant response rate, compares the iodine concentration with the preset start concentration threshold, and combines the consistency of the pollutant response rate change value with the humidity start time point to determine whether iodine meets the disinfection start requirements under the current conditions, and generates the iodine disinfection start condition judgment result.

[0068] Based on the pollutant response rate list generated by the aforementioned steps, this list records that the response rate of region R01 in the interval [T2, T3] is 70 μg / m³. 3 / h, the response rate of region R02 in the interval [T2,T3] is 70 μg / m 3 / h, and the response rate of region R03 in the interval [T1,T4] is 6.67 μg / m 3 For each entry in the list, extract its region number and corresponding time point, and retrieve the concentration data recorded by the iodine concentration sensor at the corresponding time point from Table 1. For example, for region R01 at time point T3, its response rate is 70 μg / m³. 3 / h, the concentration of iodine tincture is 449 mg / L. Next, a mapping relationship set between iodine tincture concentration and pollutant response rate is constructed. This set has the form {(region number, time point):(iodine tincture concentration, response rate)}. For example, the set contains the entry {(R01,T3):(449 mg / L,70 μg / m 3 / h)} and {(R02,T3):(460mg / L,70μg / m 3 Then, a preset activation concentration threshold is set. This threshold is determined based on disinfection efficacy tests of different concentrations of povidone-iodine solution at different contaminant levels. Experiments show that when the concentration of povidone-iodine solution is below 450 mg / L, it is effective against concentrations exceeding 150 μg / m³. 3 The inactivation rate of pollutants decreased by more than 30%, so the activation concentration threshold was set to 450 mg / L. Then, the iodine concentration of each entry in the mapping set was compared with this threshold of 450 mg / L. For example, the concentration of region R01 at T3 was 449 mg / L, which was less than 450 mg / L, thus not meeting the condition. However, the concentration of region R02 at T3 was 460 mg / L, which was greater than 450 mg / L, thus meeting the condition. Finally, the consistency between the pollutant response rate change value and the time point of the humidity activation zone was used for judgment. That is, it was checked whether the response rate of the regions meeting the iodine concentration condition was within the corresponding humidity activation zone. The response rate of region R02 was 70 μg / m³. 3 / h is calculated within its humidity start-up zone [T2,T3], and its iodine concentration of 460mg / L at T3 also meets the conditions. Therefore, it is determined that region R02 meets the disinfection start-up requirements at time point T3, while region R01 does not start due to insufficient iodine concentration at time T3, and region R03 does not start due to too low response rate. Finally, the iodine disinfection start-up condition judgment result is generated.

[0069] The disinfection priority calculation module includes:

[0070] The conditional filtering submodule, based on the area number and time point recorded in the iodine disinfection start condition judgment result, calls the pollutant concentration data and humidity data of each area within the corresponding time period, compares the pollutant concentration value with the pollutant concentration benchmark threshold, filters the area data with a concentration greater than the threshold, then compares its corresponding humidity value with the humidity benchmark threshold, filters the area data with a humidity greater than the threshold, obtains the area number that meets both filtering conditions at the same time, and generates a list of high-demand area numbers.

[0071] The region that met the activation conditions for iodine disinfection, as recorded in the iodine disinfection activation condition judgment results, was R02, and the time point was T3. Based on this, the pollutant concentration data of 280 μg / m³ for region R02 at time point T3 was retrieved from Table 1. 3 With a humidity level of 76%, baseline thresholds for pollutant concentration and humidity were then set. These thresholds were determined in accordance with the "Hospital Air Purification Management Standard" GB 19258-2003, which stipulates that the total airborne bacteria count for Class II environments (outpatient clinics) should be ≤200 cfu / m³. 3 Through conversion and safety redundancy, the baseline threshold for pollutant concentration is set at 200 μg / m³. 3 Meanwhile, to avoid equipment damage from operation in excessively humid environments, the humidity baseline threshold was set to 75%. Then, the retrieved contaminant concentration value was compared with the baseline threshold of 200 μg / m³. 3 For comparison, the concentration of R02 in region 280 μg / m 3 Greater than 200 μg / m 3 If the first screening condition is met, the humidity value of 76% corresponding to the region is compared with the humidity baseline threshold of 75%. The humidity of region R02 is greater than 75%, thus meeting the second screening condition. Since region R02 meets both screening conditions, its region number R02 is extracted. If other regions such as R01 and R03 also meet the activation conditions at other times, they are also screened and compared. Finally, all region numbers that meet the conditions simultaneously are summarized to generate a list of high-demand region numbers.

[0072] The demand assessment submodule, based on each area number in the list of high-demand areas, calls the pollutant concentration value and humidity value of the corresponding time period, normalizes the two values ​​and weights them, sets the pollutant concentration weight coefficient and humidity weight coefficient as the pollutant coefficient value and humidity coefficient value respectively, and calculates the area demand value based on the weighted sum value to obtain the list of area disinfection demand values.

[0073] Based on the list of high-demand areas, this embodiment only includes area number R02, and retrieves its pollutant concentration value of 280 μg / m³ at time point T3. 3 The humidity value was set to 76%. Then, both values ​​were normalized. The normalization method was (current value - minimum value of the interval) / (maximum value of the interval - minimum value of the interval). The reference interval for pollutant concentration was set to [50, 500] μg / m³ based on historical monitoring data. 3With the humidity reference range set at [40, 90]%, the normalized value of pollutant concentration in region R02 is (280-50) / (500-50) = 230 / 450 ≈ 0.511, and the normalized value of humidity is (76-40) / (90-40) = 36 / 50 = 0.72. Next, the weighting coefficients for pollutant concentration and humidity are set based on a regression analysis that studies the combined effects of pollutant concentration and humidity on disinfectant consumption. The analysis results show that the influence coefficient of pollutant concentration is 0.68, and the influence coefficient of humidity... The influence coefficient is 0.32. Therefore, the pollutant concentration weighting coefficient (pollutant coefficient value) is set to 0.7, and the humidity weighting coefficient (humidity coefficient value) is set to 0.3. Then, the regional demand value is calculated based on the weighted summation value. The calculation method is to multiply each normalized parameter value with its corresponding weighting coefficient and then sum them up. That is, the demand value of region R02 = 0.511 × 0.7 + 0.72 × 0.3 = 0.3577 + 0.216 = 0.5737. The demand values ​​calculated for all high-demand regions are associated with their region numbers to obtain a list of regional disinfection demand values.

[0074] The sequential calculation submodule sorts all regions in descending order of their required values ​​based on the required values ​​of each region in the regional disinfection requirement value list. It then assigns sequential numbers to the sorted regions, pairs the region numbers with their sorting numbers, obtains the corresponding sorting number for each region as the disinfection priority value, and generates the regional disinfection priority value.

[0075] In this embodiment, the list of regional disinfection requirements contains only one entry (R02, 0.5737). If there are multiple regions, for example, region R01 has a requirement value of 0.6521 and region R03 has a requirement value of 0.4899, then the list would be {(R01, 0.6521), (R02, 0.5737), (R03, 0.4899)}. First, the requirement values ​​of all regions in the list are compared and arranged in descending order. The sorted order is R01 (0.6521), R02 (0.5737), etc. R03(0.4899), then, assign sequential numbers to the sorted area numbers in sequence, where the first in the sequence is assigned a value of 1, the second is assigned a value of 2, and so on, that is, the sequential number of R01 is 1, the sequential number of R02 is 2, the sequential number of R03 is 3. Finally, pair each area number with its corresponding sequence number to form a set containing the area number and its value as the disinfection priority, specifically {(R01,1),(R02,2),(R03,3)}. This set is the generated area disinfection priority value.

[0076] The path planning and resource scheduling module includes:

[0077] The path generation submodule, based on the order of the area numbers in the area disinfection priority value, calls the geographical location information of the corresponding area, calculates the geographical coordinate distance and connection direction between areas, plans a set of continuous path segments by traversing the shortest distance path between areas after priority value sorting, and establishes a correspondence between each path segment and its connected area number to generate a priority path number list.

[0078] In this extended scenario, the regional disinfection priority values ​​are {(R01,1),(R02,2),(R03,3)}. First, the regional numbers are extracted from 1 to 3 according to priority order, i.e., R01, R02, R03. The preset geographical location information of these regions is then retrieved, as shown in Table 2. This table records the central geographical coordinates and area of ​​each region. Next, the geographical coordinate distance between adjacent priority regions is calculated. For example, the distance between R01(10,20) and R02(30,15) is... The distance between R02(30,15) and R03(25,30) is Next, by traversing all possible region connection sequences and calculating the total distance, the shortest path between regions after priority sorting is found. In this example, since the priority is already determined, the path sequence is fixed as R01->R02->R03, and the total path is 20.62 + 15.81 = 36.43 meters. This path is divided into two path segments: path segment 1 is from R01 to R02, and path segment 2 is from R02 to R03. Finally, a correspondence is established between each path segment and the region number it connects to. For example, path segment 1 corresponds to (R01, R02), and path segment 2 corresponds to (R02, R03). After summarizing, a priority path number list is generated.

[0079] Table 2: Geographic and Environmental Information of Disinfection Area

[0080] Area code Center coordinates (m) <![CDATA[Area (m 2 )]]> <![CDATA[Pollutant concentration (μg / m 3 )]]> humidity(%) R01 (10,20) 100 260 75 R02 (30,15) 120 280 76 R03 (25,30) 80 190 78

[0081] As shown in Table 2, this table contains core information for three high-demand areas under the extended scenario, which is used for path planning and resource calculation.

[0082] The demand calculation submodule, based on the area numbers connected by each path segment in the priority path number list, calls the pollutant concentration value and humidity value corresponding to each area number, performs a weighted average of the pollutant concentration and humidity by path segment, compares the average value with the iodine concentration demand benchmark value, calculates the iodine solution demand per meter of path segment, and obtains the solution demand of the path segment.

[0083] The priority path number list includes path segment 1 (R01, R02) and path segment 2 (R02, R03). For each path segment in the list, the pollutant concentration and humidity values ​​of its connected area numbers at the corresponding time point (T3) are retrieved, as shown in Table 2. The pollutant concentrations of R01 and R02 connected by path segment 1 are 260 μg / m³, respectively. 3 and 280μg / m 3 The humidity levels were 75% and 76%, respectively. Then, a weighted average of pollutant concentration and humidity was calculated for each path segment, with the weights determined based on the area. The average pollutant concentration for path segment 1 was calculated as follows: (260×100+280×120) / (100+120) = (26000+33600) / 220 = 59600 / 220 ≈ 270.91 μg / m³ 3 The average humidity is calculated as follows: (75×100+76×120) / (100+120) = (7500+9120) / 220 = 16620 / 220 ≈ 75.55%. Next, a baseline value for the required iodine concentration is established. This baseline value is experimentally determined and corresponds to the complete inactivation of 100 μg / m³ at standard humidity (60%). 3 The required amount of iodine solution per unit length (1 meter) for pollutants was set at 10 mL / m. Subsequently, the baseline value was corrected based on actual environmental parameters, with the correction factor calculated by dividing the average pollutant concentration by the standard concentration of 100 μg / m. 3 The solution requirement is determined by multiplying the average humidity by the standard humidity of 60%. Therefore, the unit requirement for path segment 1 is 10 × (270.91 / 100) × (75.55 / 60) ≈ 10 × 2.7091 × 1.2592 ≈ 34.11 mL / m. This is the solution requirement for path segment 1. Finally, the solution requirements for all path segments are obtained.

[0084] The spraying adjustment submodule calls the unit demand data corresponding to each path segment in the solution demand data of the path segment, matches the spraying equipment number and spraying radius value in the current path segment, calculates the overlap between the actual coverage area of ​​the spraying equipment and the area of ​​the path segment, multiplies the overlap with the unit solution demand of the path segment, obtains the adjusted spraying amount of each equipment in the path segment, and obtains the equipment spraying adjustment value.

[0085] The system retrieves the required solution volume for each path segment. Path segment 1 requires 34.11 mL / m with a path length of 20.62 meters, while path segment 2 requires (assumed to be 25.15 mL / m) with a path length of 15.81 meters. First, it matches the spraying equipment within path segment 1, assuming that equipment D01 is responsible for path segment 1 with a preset spray radius of 2 meters. Then, it calculates the overlap between the actual coverage area of ​​the spraying equipment on the path segment and the area of ​​the path segment. Assuming path segment 1 is a corridor with a width of 2 meters, the area of ​​the path segment is 20.62 × 2 = 41.24 m². 2 The spray coverage width of device D01 is 4 meters. The overlap is calculated as the ratio of the spray width to the path width, i.e., 4 / 2 = 2. When the overlap is greater than 1, a correction factor is set. The correction factor is the reciprocal of the overlap, i.e., 1 / 2 = 0.5. Next, the correction factor is multiplied by the unit solution requirement of the path segment to obtain the adjusted spray volume of the device in that path segment. That is, the adjusted spray volume of device D01 in path segment 1 = 34.11 × 0.5 = 17.06 mL / m. This value is the spray adjustment value of device D01. Finally, the spray adjustment values ​​of all devices on all path segments are obtained.

[0086] The resource allocation submodule matches the remaining liquid volume of the adjustable equipment number with the current reserve iodine concentration based on the path segment number and spray volume requirement value corresponding to each equipment number in the equipment spraying adjustment value, filters the equipment numbers whose reserve volume can cover the required spray volume, constructs a corresponding mapping set of path segments and equipment numbers, establishes the resource equipment number allocation relationship under each path segment, and generates a disinfection resource path allocation scheme.

[0087] Based on the generated equipment spraying adjustment values, the adjusted spraying volume of equipment D01 in path segment 1 is 17.06 mL / m, and the total length of path segment 1 is 20.62 meters. Therefore, the total required spraying volume is 17.06 × 20.62 ≈ 351.75 mL. First, the available equipment numbers and their statuses are matched. Assuming that equipment D01 and D02 are currently available for adjustment, D01 has a remaining liquid volume of 1000 mL and a reserve iodine concentration of 500 mg / L, while D02 has a remaining liquid volume of 200 mL and a reserve iodine concentration of 500 mg / L. Then, equipment numbers whose reserve volumes can cover the required spraying volume are screened. The required volume of 351.75 mL in path segment 1 is compared with the remaining liquid volumes of each equipment. D01's 1000 mL... The amount is greater than 351.75 mL, which meets the condition. The amount of 200 mL for D02 is less than 351.75 mL, which does not meet the condition. Therefore, device D01 is selected. Next, a mapping set of path segments and device numbers is constructed. Path segment 1 is mapped to the selected device D01. If the required amount for path segment 2 is 15.81 × 25.15 ≈ 397.62 mL, and D01 has 1000 - 351.75 = 648.25 mL remaining after executing path segment 1, which can still meet the requirement of path segment 2, then path segment 2 is also mapped to device D01. Finally, the resource device number allocation relationship under each path segment is established, that is, path segment 1 is executed by D01, path segment 2 is executed by D01, thereby generating a disinfection resource path allocation scheme.

[0088] The disinfection effect feedback module includes:

[0089] The concentration acquisition submodule acquires the pollutant concentration values ​​recorded by the pollutant sensors in each area after disinfection, and organizes them according to the area number and the acquisition time. It compares the acquired concentration values ​​with the pollutant baseline concentration threshold, filters out records with concentration values ​​less than or equal to the threshold and marks them as compliant area records, and marks the rest as non-compliant area records, generating a list of pollution compliance mark values.

[0090] After disinfection, the pollutant concentration values ​​recorded by the pollutant sensors in each area are obtained. For example, the pollutant concentration value of area R02 at time T5 after disinfection is 45 μg / m³. 3 The region R01 is 55 μg / m 3 First, the collected concentration values ​​were compared with the pollutant baseline concentration threshold, which was set at 50 μg / m³ according to the "Hospital Air Purification Management Standard". 3 Then, the concentration values ​​after disinfection in each area were screened and labeled. The concentration of RO2 in area 45 μg / m² was recorded. 3 Less than or equal to 50 μg / m 3 Therefore, it was marked as a compliant area record, with a concentration of 55 μg / m³ in area R01. 3 Greater than 50 μg / m3 The area is marked as a non-compliant area. Finally, the marking results of all areas are summarized to generate a list of pollution compliance marking values.

[0091] The pollution change submodule, based on the area number in the pollution compliance marker value list, calls the pollutant concentration value before disinfection and the concentration value collected after iodine disinfection under the corresponding area number, calculates the difference between the concentration values ​​of the two time periods, and then divides the difference by the concentration value before disinfection to obtain the change ratio value, records the change ratio corresponding to each area number, and obtains the pollution concentration change rate list.

[0092] The pollution compliance label list records R02 as compliant and R01 as non-compliant. Each area in the list is numbered, and its pollutant concentration values ​​before and after disinfection are retrieved. The concentration values ​​before disinfection are taken from Table 2, and the concentration of R02 before disinfection is 280 μg / m³. 3 After disinfection, the concentration was 45 μg / m³. 3 R01 concentration before disinfection was 260 μg / m³. 3 After disinfection, the concentration was 55 μg / m³. 3 Then, the difference between the concentration values ​​of the two time periods was calculated, and the difference in R02 was 280-45=235μg / m³. 3 The difference in R01 is 260-55=205μg / m 3 Next, the difference is divided by the concentration value before disinfection to obtain the change ratio value. The change ratio value of R02 is 235 / 280≈0.8393, which is 83.93%, and the change ratio value of R01 is 205 / 260≈0.7885, which is 78.85%. Finally, the area number and its corresponding change ratio value are recorded to obtain a list of pollution concentration change rates.

[0093] The coverage assessment submodule calls the area number and change rate value in the pollution concentration change rate list, combines the spraying amount, spraying location and spraying equipment number in the iodine solution spraying record, calculates the cross ratio of the spraying area and the area area, and then weights and summarizes the cross ratio and the pollution concentration change rate to calculate the actual impact of iodine solution in the target pollution area under each area, and generates a disinfection effect assessment report.

[0094] The generated list of pollution concentration change rates was retrieved, showing a change rate of 83.93% for R02 and 78.85% for R01. Combined with the iodine solution spraying record, which includes a total spray volume of 351.75 mL from device D01 along path segment 1 (primarily affecting R01 and R02), the spraying location is the line connecting R01 and R02. First, the overlap ratio between the sprayed area and the area is calculated. Assuming the length of path segment 1 within area R01 is 10 meters, its length within area R02 is 10.62 meters, and the spraying width is 4 meters, then the sprayed area within R01 is 40 m².2 The crossover ratio is 40 / 100 = 0.4, and the spraying area within R02 is 10.62 × 4 = 42.48 m². 2 The crossover percentage is 42.48 / 120 = 0.354. Then, the crossover percentage and the pollution concentration change rate are weighted and summarized to calculate the actual impact. The weighting coefficient is set based on the importance of the crossover percentage, with the crossover percentage weight set at 0.6 and the change rate weight set at 0.4. Then, the actual impact of region R01 = 0.4 × 0.6 + 0.7885 × 0.4 = 0.24 + 0.3154 = 0.5554, and the actual impact of region R02 = 0.354 × 0.6 + 0.8393 × 0.4 = 0.2124 + 0.3357 = 0.5481. The calculation results of all regions are summarized to generate a disinfection effect assessment report.

[0095] The resource dynamic scheduling module includes:

[0096] The dosage collection submodule, based on the equipment number and spray path number in the disinfection resource path allocation scheme, calls the real-time liquid volume record data and spray start and end time data during the spraying process, accumulates the total amount of spraying per unit time and collects it into the path number dimension, and then calculates the spraying rate value by combining the spraying duration under the path number to obtain a list of path spraying rate values.

[0097] Based on the disinfection resource path allocation scheme, device D01 is assigned to path segment 1 and path segment 2, and its real-time liquid volume record data during the spraying process is called. For example, the initial liquid volume of device D01 in path segment 1 is 1000mL, the ending liquid volume is 648.25mL, the spraying start time is 14:00:00, the end time is 14:10:00, and the duration is 10 minutes. First, the total spraying volume per unit time is accumulated and aggregated to the path number dimension. The total spraying volume of path segment 1 is 1000-648.25=351.75mL. Then, combined with the spraying duration of 10 minutes under the path number, the spraying rate value is calculated, that is, the spraying rate of path segment 1 = 351.75mL / 10min = 35.175mL / min. The calculation results of all path segments are summarized to obtain the path spraying rate value list.

[0098] The concentration adjustment submodule, based on the rate value corresponding to each path number in the path spraying rate value list, calls the pollutant concentration change value under the path number in the disinfection effect evaluation results, compares the difference between the spraying rate and the pollutant change value, records the path numbers where the spraying rate and the pollutant concentration change trend are opposite, and sets the adjustment range in combination with the iodine reserve concentration value under the current path number, obtains the iodine concentration adjustment value corresponding to each path, and obtains the path concentration adjustment value list.

[0099] According to the list of spraying rate values ​​along the path, the rate for path segment 1 is 35.175 mL / min. The pollutant concentration change values ​​for the main affected area of ​​this path segment are then used from the disinfection effectiveness assessment results. For example, the average change rate of R01 and R02 is taken as (83.93% + 78.85%) / 2 = 81.39%. First, the spraying rate is compared with the pollutant change value to establish an ideal rate-effect relationship benchmark. This benchmark is derived through historical data regression analysis. Under the current pollutant level, the ideal change rate of 85% corresponds to a spraying rate of 40 mL / min. The current actual rate... The actual rate of spraying (35.175 mL / min) is lower than the ideal rate of 40 mL / min, and the actual rate of change (81.39%) is also lower than the ideal rate of change (85%). The trend is consistent, and no adjustment is needed. If there is a situation where the spraying rate is higher than the ideal rate but the rate of change is lower than the ideal rate of change, then record the path number as the path to be adjusted. Then, for the path that needs to be adjusted, set the adjustment range based on the current iodine reserve concentration (500 mg / L). If the effect needs to be improved, increase the concentration by 5%, that is, the adjustment range is +25 mg / L; otherwise, decrease it. Summarize the adjustment values ​​of all paths to obtain a list of path concentration adjustment values.

[0100] The resource reallocation submodule calls all path numbers and concentration adjustment value data in the path concentration adjustment value list, matches the path number with the corresponding adjustable equipment number and the remaining liquid volume of the equipment, constructs a resource transfer matrix based on the current resource allocation and concentration adjustment value under the path number, and adjusts the resource allocation ratio of each equipment under the current path through the ratio difference between the remaining resource volume and the demand volume in the matrix, generating a resource scheduling adjustment plan;

[0101] The path concentration adjustment value list is invoked. Assuming path segment 1 requires increasing the concentration of iodine tincture by 25 mg / L, and the current reserve concentration of equipment D01 is 500 mg / L with a remaining volume of 648.25 mL, firstly, the available equipment corresponding to the path number is matched, i.e., equipment D01 corresponds to path segment 1. Then, a resource transfer matrix is ​​constructed based on the current resource allocation and concentration adjustment value under the path number. This matrix aims to calculate the required amount of stock solution (high-concentration iodine tincture) and diluent to achieve the target concentration. Assuming the stock solution is stored in equipment D03 with a concentration of 1000 mg / L, to increase the 648.25 mL solution in D01 from 500 mg / L to 525 mg / L, the required amount of stock solution V to be added is... add According to the concentration mixing formula (V current ×C current +V add ×C add ) / (V current +V add ) = C final Substituting the value, we get (648.25×500+V). add×1000) / (648.25+V add )=525, solving this equation gives 324125+1000×V add =340331.25 + 525 × V add The result is 475×V. add =16206.25, then V add ≈34.12mL. Finally, based on the ratio difference between the remaining amount of resources (D03) and the demand (D01) in the matrix, a specific resource scheduling instruction is generated, that is, 34.12mL of raw liquid is transferred from equipment D03 to equipment D01, thereby generating a resource scheduling adjustment plan.

[0102] Please see Figure 3 A smart environmental disinfection method based on iodine tincture includes the following steps:

[0103] S1: Acquire data collected by humidity sensor, pollutant concentration data detected by air quality sensor, and iodine solution concentration data collected by solution concentration sensor within the disinfection area. Timestamp the three types of data and establish a unified sequence to generate iodine disinfection start condition judgment results.

[0104] S2: Based on the iodine disinfection activation condition judgment result, call the pollutant concentration data and humidity data of each area, compare the pollutant concentration data with the air quality standard to obtain the exceedance difference, compare the humidity data with the set humidity threshold to obtain the exceedance difference, perform a weighted calculation on the exceedance difference and exceedance difference to obtain the disinfection demand data of each area, and then sort the disinfection demand data of all areas to generate the regional disinfection priority value.

[0105] S3: Call the regional disinfection priority value and combine it with the geographical location information of each disinfection area to calculate the path of priority order, compare the path length with the spray coverage of the spraying equipment, convert it into iodine consumption data, and generate a disinfection resource path allocation scheme.

[0106] S4: Based on the disinfection resource path allocation scheme, call the post-disinfection data collected by the pollutant concentration sensor, compare it with the pre-disinfection pollutant concentration data, calculate the pollutant concentration reduction, and combine it with the iodine solution concentration change data to obtain the coverage data and generate a disinfection effect evaluation report.

[0107] S5: Based on the disinfection effect assessment report, retrieve the data on the usage of iodine solution and the spraying method, adjust the regional iodine solution allocation, calculate the difference in spraying concentration after adjustment, and generate a resource scheduling adjustment plan.

[0108] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An intelligent environmental disinfection system based on iodine tincture, characterized in that, The system includes: The environmental data monitoring module collects data on humidity, pollutant concentration, and iodine solution concentration in the disinfection area, monitors environmental changes in real time, determines whether the disinfection start-up conditions are met, analyzes the impact of humidity on pollutant concentration, determines whether the iodine concentration meets the start-up conditions, and generates the iodine disinfection start-up condition judgment result. The disinfection priority calculation module assesses the disinfection needs of each disinfection area based on the iodine disinfection activation condition judgment result, sorts the areas with high humidity or high pollution concentration, calculates the execution order according to the demand, and generates the area disinfection priority value. The path planning and resource scheduling module plans disinfection paths based on the regional disinfection priority value, combined with geographical information and pollution status, assesses the required concentration of iodine solution and resource amount for each path, adjusts the spraying amount according to the spraying path and equipment distribution, and generates a resource and path allocation plan. The disinfection effect feedback module obtains the changes in the concentration of contaminants and the concentration of iodine solution after disinfection, determines whether the concentration of contaminants after disinfection meets the standards, compares the contaminant data before and after disinfection, calculates the actual coverage of the disinfectant in the area, and generates a disinfection effect evaluation report.

2. The intelligent environmental disinfection system based on iodine tincture according to claim 1, characterized in that: The iodine disinfection activation condition judgment results include environmental compliance indicators, humidity influence parameters, and iodine concentration thresholds. The regional disinfection priority values ​​include demand level parameters, urgency level parameters, and execution order parameters. The disinfection resource path allocation scheme includes path coverage indicators, resource allocation parameters, and spraying adjustment parameters. The disinfection effect evaluation report includes pollutant change data, coverage effect data, and compliance data.

3. The intelligent environmental disinfection system based on iodine tincture according to claim 1, characterized in that, The environmental data monitoring module includes: The humidity acquisition submodule acquires humidity data of the disinfection area collected by the smart sensor, organizes the humidity data in chronological order and by area number, compares the humidity data of the corresponding area at each time point with the humidity activation threshold, records the areas that do not meet the activation conditions and the corresponding time points, and determines the humidity segments that meet the activation conditions by combining the area and time dimensions, and obtains a list of humidity activation segments. The pollutant concentration assessment submodule calls the area number of each time point in the humidity start-up zone list, matches the pollutant concentration data recorded by the pollutant sensor at the same time point, groups the concentration data and humidity data together, and determines the pollutant concentration response rate corresponding to the humidity change by calculating the average rate of change of pollutant concentration in the group, and obtains the pollutant response rate list. The iodine concentration judgment submodule, based on the region number of each time point in the pollutant response rate list, calls the corresponding concentration data of the iodine concentration sensor to construct a set of mapping relationships between iodine concentration and pollutant response rate. By comparing the iodine concentration with the preset start-up concentration threshold and combining the consistency between the pollutant response rate change value and the time point of the humidity start-up zone, it determines whether the iodine meets the disinfection start-up requirements under the current conditions and generates the iodine disinfection start-up condition judgment result.

4. The intelligent environmental disinfection system based on iodine tincture according to claim 1, characterized in that, The disinfection priority calculation module includes: The conditional filtering submodule, based on the area number and time point recorded in the iodine disinfection start condition judgment result, calls up the pollutant concentration data and humidity data of each area within the corresponding time period, compares the pollutant concentration value with the pollutant concentration benchmark threshold, filters the area data with a concentration greater than the threshold, then compares its corresponding humidity value with the humidity benchmark threshold, filters the area data with a humidity greater than the threshold, obtains the area number that meets both filtering conditions at the same time, and generates a list of high-demand area numbers. The demand assessment submodule, based on each area number in the list of high-demand areas, calls the pollutant concentration value and humidity value of its corresponding time period, normalizes the two values ​​and weights them, sets the pollutant concentration weight coefficient and humidity weight coefficient as the pollutant coefficient value and humidity coefficient value respectively, and calculates the area demand value based on the weighted sum value to obtain the list of area disinfection demand values. The sequential calculation submodule, based on the demand value of each region in the regional disinfection demand value list, arranges all regions in descending order of demand value, assigns sequential numbers to the arranged region numbers, pairs the region numbers with their sorting numbers, obtains the corresponding sorting number for each region as the disinfection priority value, and generates the regional disinfection priority value.

5. The intelligent environmental disinfection system based on iodine tincture according to claim 1, characterized in that, The path planning and resource scheduling module includes: The path generation submodule, based on the order of the area numbers in the area disinfection priority value, calls the geographical location information of the corresponding area, calculates the geographical coordinate distance and connection direction between areas, plans a set of continuous path segments by traversing the shortest distance path between areas after priority value sorting, and establishes a correspondence between each path segment and its connected area number to generate a priority path number list. The demand calculation submodule, based on the area numbers connected by each path segment in the priority path number list, calls the pollutant concentration value and humidity value corresponding to each area number, performs a weighted average of the pollutant concentration and humidity by path segment, compares the average value with the iodine concentration demand benchmark value, calculates the iodine solution demand per meter of path segment, and obtains the solution demand of the path segment. The spraying adjustment submodule calls the unit demand data corresponding to each path segment in the solution demand of the path segment, matches the spraying equipment number and spraying radius value in the current path segment, calculates the overlap between the actual coverage area of ​​the spraying equipment and the area of ​​the path segment, multiplies the overlap with the unit solution demand of the path segment, obtains the adjusted spraying amount of each equipment in the path segment, and obtains the equipment spraying adjustment value. The resource allocation submodule matches the remaining liquid volume of the adjustable equipment number with the current reserve iodine concentration based on the path segment number and spray volume requirement value corresponding to each equipment number in the equipment spray adjustment value, filters the equipment numbers whose reserve volume can cover the required spray volume, constructs a corresponding mapping set of path segments and equipment numbers, establishes the resource equipment number allocation relationship under each path segment, and generates a disinfection resource path allocation scheme.

6. The intelligent environmental disinfection system based on iodine tincture according to claim 1, characterized in that, The disinfection effect feedback module includes: The concentration acquisition submodule acquires the pollutant concentration values ​​recorded by the pollutant sensors in each area after disinfection, and organizes them according to the area number and the acquisition time. It compares the acquired concentration values ​​with the pollutant baseline concentration threshold, filters out records with concentration values ​​less than or equal to the threshold and marks them as compliant area records, and marks the rest as non-compliant area records, generating a list of pollution compliance mark values. The pollution change submodule, based on the area number in the pollution compliance marker value list, calls the pollutant concentration value before disinfection and the concentration value collected after iodine disinfection under the corresponding area number, calculates the difference between the concentration values ​​of the two time periods, divides the difference by the concentration value before disinfection to obtain the change ratio value, records the change ratio corresponding to each area number, and obtains the pollution concentration change rate list. The coverage assessment submodule calls up the area number and change rate value in the pollution concentration change rate list, combines the spraying amount, spraying location and spraying equipment number in the iodine solution spraying record, calculates the cross ratio of the sprayed area and the area, and then weights and summarizes the cross ratio and the pollution concentration change rate to calculate the actual impact of iodine solution in the target polluted area under each area, and generates a disinfection effect assessment report.

7. The intelligent environmental disinfection system based on iodine tincture according to claim 1, characterized in that, The system also includes: The resource dynamic scheduling module optimizes and adjusts the allocation of disinfectant and the spraying method within the area based on the disinfection resource path allocation scheme and disinfection effect evaluation report, monitors the use of disinfectant in real time, and dynamically adjusts the concentration of iodine solution and the amount of resources used according to the actual effect and needs, generating a resource scheduling adjustment scheme. The resource scheduling and adjustment scheme includes allocation optimization parameters, spraying adjustment parameters, and concentration control parameters.

8. The intelligent environmental disinfection system based on iodine tincture according to claim 7, characterized in that, The resource dynamic scheduling module includes: The dosage collection submodule, based on the equipment number and spray path number in the disinfection resource path allocation scheme, calls the real-time liquid volume record data and spray start and end time data during the spraying process, accumulates the total amount of spraying per unit time and collects it into the path number dimension, and then calculates the spraying rate value by combining the spraying duration under the path number to obtain a list of path spraying rate values. The concentration adjustment submodule, based on the rate value corresponding to each path number in the path spraying rate value list, calls the pollutant concentration change value under the path number in the disinfection effect evaluation result, compares the difference between the spraying rate and the pollutant change value, records the path number where the spraying rate and the pollutant concentration change trend are opposite, and sets the adjustment range in combination with the iodine reserve concentration value under the current path number, obtains the iodine concentration adjustment value corresponding to each path, and obtains the path concentration adjustment value list. The resource reallocation submodule calls all path numbers and concentration adjustment value data in the path concentration adjustment value list, matches the path number with the corresponding adjustable equipment number and the remaining liquid volume of the equipment, constructs a resource transfer matrix based on the current resource allocation and concentration adjustment value under the path number, and adjusts the resource allocation ratio of each equipment under the current path by the ratio difference between the remaining resource quantity and the demand quantity in the matrix, and generates a resource scheduling adjustment plan.

9. A smart environmental disinfection method based on iodine tincture, characterized in that, The method, used in the iodine-based intelligent environmental disinfection system according to any one of claims 1-8, includes the following steps: S1: Acquire data collected by humidity sensor, pollutant concentration data detected by air quality sensor, and iodine solution concentration data collected by solution concentration sensor within the disinfection area. Timestamp the three types of data and establish a unified sequence to generate iodine disinfection start condition judgment results. S2: Based on the judgment result of the iodine disinfection start condition, call the pollutant concentration data and humidity data of each area, compare the pollutant concentration data with the air quality standard to obtain the exceedance difference, compare the humidity data with the set humidity threshold to obtain the exceedance difference, perform a weighted calculation on the exceedance difference and exceedance difference to obtain the disinfection demand data of each area, and then sort the disinfection demand data of all areas to generate the area disinfection priority value. S3: Call the regional disinfection priority value and combine it with the geographical location information of each disinfection area to calculate the path of the priority order, compare the path length with the spray coverage of the spraying equipment, convert it into iodine consumption data, and generate a disinfection resource path allocation scheme. S4: Based on the disinfection resource path allocation scheme, call the post-disinfection data collected by the pollutant concentration sensor, compare it with the pre-disinfection pollutant concentration data, calculate the pollutant concentration reduction, and combine it with the iodine solution concentration change data to obtain the coverage data, and generate a disinfection effect evaluation report. S5: Based on the disinfection effect evaluation report, retrieve the data on the amount of iodine solution used and the spraying method, adjust the regional iodine solution allocation, calculate the difference in spraying concentration after adjustment, and generate a resource scheduling adjustment plan.

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