A humidity sensor monitoring method and system for moisture-proof performance evaluation

Abstract

The present invention discloses a humidity sensor monitoring method and system for moisture-proof performance evaluation, belonging to the field of environmental monitoring technology. The method includes: obtaining humidity sensor monitoring performance data, determining the initial layout position of the humidity sensor in the target area and performing redundancy analysis, and constructing a humidity monitoring system after optimizing the layout position; obtaining humidity change data under different environmental characteristics and humidity conditions through the monitoring system, and constructing a humidity difference map; analyzing moisture diffusion characteristics based on the humidity difference map, and establishing a humidity change prediction model; monitoring humidity information and environmental condition data in real time, and importing them into the prediction model to predict humidity changes and obtain prediction results; and determining the monitoring weight and monitoring strategy of the humidity sensor based on the prediction results. The present invention optimizes sensor layout and monitoring methods, can efficiently evaluate the moisture-proof performance of the target area, and improve the accuracy and efficiency of humidity monitoring.

Description

Technical Field

[0001] The present invention relates to the field of sensor monitoring technology, and in particular to a humidity sensor monitoring method and system for moisture-proof performance evaluation. Background Art

[0002] Humidity monitoring plays a vital role in environmental control, storage management, and building protection. Humidity fluctuations not only affect the preservation of items but can also cause structural damage to facilities. Traditional humidity monitoring methods typically rely on single humidity sensors or fixed sensor networks, which are difficult to adapt to complex environmental characteristics and dynamic humidity fluctuations. Furthermore, improper monitoring system placement or insufficient sensor performance can result in incomplete humidity information and low monitoring accuracy.

[0003] In recent years, with the advancement of environmental monitoring technology, the performance and variety of humidity sensors have continued to improve. However, optimizing monitoring systems by fully utilizing existing sensor resources remains a pressing challenge. On the one hand, the complex diffusion characteristics of moisture make it difficult for traditional sensor deployments to fully capture humidity changes in the target area. On the other hand, redundant monitoring data can lead to wasted resources and reduced monitoring efficiency. Furthermore, existing methods lack the ability to predict dynamic moisture diffusion characteristics, making it difficult to promptly respond to humidity fluctuations and assess moisture-proof performance.

[0004] Therefore, there is an urgent need for a method and system that can optimize the layout of humidity sensors and improve the efficiency and accuracy of humidity monitoring, especially for the moisture diffusion characteristics in complex environments. By building a prediction model, the analysis and prediction capabilities of humidity changes can be improved, thereby achieving more efficient moisture-proof performance evaluation. Summary of the Invention

[0005] In order to solve at least one of the above technical problems, the present invention proposes a humidity sensor monitoring method and system for moisture-proof performance evaluation.

[0006] A first aspect of the present invention provides a humidity sensor monitoring method for moisture-proof performance evaluation, comprising:

[0007] Acquiring monitoring performance data of humidity sensors, determining initial placement locations of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement locations, optimizing the placement of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area;

[0008] Acquire humidity change data at each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, and construct a humidity difference map of the target area according to the humidity change data;

[0009] Determining the moisture diffusion characteristics of the target area under different humidity conditions and various environmental characteristics according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics;

[0010] The humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result;

[0011] A humidity sensor monitoring weight for the target area is determined according to the humidity change prediction result, and a humidity sensor monitoring strategy is determined according to the monitoring weight.

[0012] In this solution, the monitoring performance data of the humidity sensors is obtained, the initial layout positions of the humidity sensors in the target area to be evaluated for moisture-proof performance are determined based on the monitoring performance data, redundancy analysis is performed on the humidity sensors in the initial layout positions, and the positions of the humidity sensors are optimized based on the redundancy analysis to construct a humidity monitoring system for the target area. Specifically,

[0013] Acquiring monitoring performance data of humidity sensors, and determining, based on the monitoring performance data, the humidity sensor layout spacing in the target area to be evaluated for moisture-proof performance;

[0014] Acquiring spatial structure information of the target area, and determining initial layout positions of the humidity sensors according to the spatial structure information and the layout spacing of the humidity sensors;

[0015] By sequentially placing moisture release devices at multiple preset locations in the target area, operating the moisture release devices at a preset power for a preset time, and obtaining humidity information at each initial location in the target area using humidity sensors at the initial locations;

[0016] constructing a humidity distribution map of the target area based on the humidity information, calculating the Euclidean distance of the humidity information between the monitoring areas of each humidity sensor based on the humidity distribution map, performing similarity analysis based on the Euclidean distance, and constructing a similarity matrix;

[0017] Classifying monitoring areas whose similarity is greater than a preset similarity according to the similarity matrix to obtain similarity monitoring classification areas;

[0018] Performing data monitoring repeatability analysis on the humidity information of each similarity monitoring classification area, determining the humidity information data repetition rate of each similarity monitoring classification area, calculating the humidity information acquisition redundancy based on the data repetition rate, and merging areas with redundancy greater than a preset value to obtain a merged monitoring area;

[0019] The initial layout positions of humidity sensors are optimized according to the combined monitoring areas, and a humidity monitoring system for the target area is constructed based on the humidity sensors with optimized positions.

[0020] In this solution, the humidity monitoring system obtains humidity change data at each location in the target area under various environmental characteristics and different humidity conditions, and constructs a humidity difference map of the target area based on the humidity change data, specifically:

[0021] Acquire humidity change data and timestamp data for each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, wherein the environmental characteristics include temperature, airflow velocity, air pressure, and light intensity, and the different humidity conditions include the location and range of the humidity source and the humidity value;

[0022] Constructing a data matrix based on the timestamp data for each environmental feature and humidity data of the target area under humidity conditions acquired by the humidity monitoring system at each time point;

[0023] Obtaining the layout location information of the humidity sensors in the target area, performing a humidity spatial interpolation operation on the layout location information and the humidity data of each location at each time point in the target area based on the Kriging interpolation algorithm, and constructing a humidity distribution map of the target area at each time point;

[0024] Performing data annotation on the humidity distribution map, wherein the data annotation includes a timestamp annotation, an environmental feature annotation, and a humidity condition annotation, to obtain a data-annotated humidity distribution map;

[0025] Setting a reference humidity value for the target area, assigning a reference color value to the reference humidity value, analyzing the reference humidity value and the reference color value according to histogram homogenization, and constructing a color mapping table for different humidity values;

[0026] Color mapping is performed on the data-annotated humidity distribution map according to the color mapping table to construct a humidity difference map of the target area.

[0027] In this solution, the humidity diffusion characteristics of the target area under different humidity conditions and the environmental characteristics are determined according to the humidity difference map, and a humidity change prediction model for the target area is constructed according to the humidity diffusion characteristics, specifically:

[0028] According to the humidity difference map, the humidity difference maps under the same environmental characteristics and the same humidity conditions are sorted in time series to obtain a time series humidity difference map under each environmental characteristic and humidity condition;

[0029] Determine the humidity change at each location in the target area under each environmental characteristic and humidity condition based on the time series humidity difference map, analyze the humidity change at each location based on a gradient field algorithm, and construct a gradient field of humidity distribution;

[0030] Identifying moisture diffusion directions and trends in a target area under various environmental characteristics and different humidity conditions based on the gradient field of the moisture distribution, and identifying moisture diffusion characteristics based on the moisture diffusion directions and trends, wherein the moisture diffusion characteristics include moisture diffusion path characteristics, diffusion rate characteristics, and diffusion degree characteristics;

[0031] A humidity change prediction model for the target area is constructed based on a decision tree algorithm, a feature vector is constructed by combining the environmental characteristics, humidity conditions, and corresponding moisture diffusion characteristics, and the feature vector is divided into training set features and test set features according to a preset ratio;

[0032] The training set features are imported into the humidity change prediction model to construct a decision tree, the humidity change prediction model is trained according to the decision tree, and the test set features are imported into the humidity change prediction model after training to optimize the model parameters, so as to obtain a humidity change prediction model with prediction capabilities for each location in the target area.

[0033] In this solution, the humidity information of the target area is monitored in real time according to the humidity monitoring system, and the environmental condition data of the target area is obtained. The humidity information and environmental condition data are imported into the humidity change prediction model to predict the humidity change of the target area, and the humidity change prediction result is obtained, which is specifically:

[0034] According to the humidity monitoring system, the humidity information of the target area is obtained in real time, wherein the humidity information includes the location and range of the humidity source and the humidity value, and the environmental condition data of the target area is obtained in real time;

[0035] Importing the humidity information and environmental condition data into the humidity change prediction model, predicting moisture diffusion information in the target area within a future preset time period, and obtaining moisture diffusion prediction information;

[0036] The humidity change at each location in the target area is predicted based on the moisture diffusion prediction information to obtain a humidity change prediction result.

[0037] In this solution, the humidity sensor monitoring weight of the target area is determined according to the humidity change prediction result, and the humidity sensor monitoring strategy is determined according to the monitoring weight, specifically:

[0038] Acquire humidity control demand data of a target area, and mark areas where the humidity is greater than the humidity control demand in a future preset time period according to the humidity change prediction result and the humidity control demand data to obtain marked areas;

[0039] Adjusting the humidity sensor monitoring weight of the marked area according to the humidity change prediction result, and determining the sampling frequency of each humidity sensor in the target area according to the humidity sensor monitoring weight;

[0040] Obtaining data transmission performance data of the humidity monitoring system, and calculating performance consumption information of the humidity monitoring system for data sampling according to the sampling frequency;

[0041] determining a humidity monitoring response speed of the humidity monitoring system for the target area based on the performance consumption information and the data transmission performance data;

[0042] Obtaining humidity monitoring response speed requirement data for the target area; if the humidity monitoring response speed is less than the humidity monitoring response speed requirement, determining the data transmission priority of each humidity monitoring sensor according to the humidity sensor monitoring weight; and constructing a humidity sensor monitoring strategy based on the sampling frequency and data transmission priority;

[0043] The target area is monitored for humidity in real time according to the monitoring strategy to obtain real-time humidity information of the target area, and the moisture-proof performance of the target area is evaluated according to the real-time humidity information to obtain a moisture-proof performance evaluation result.

[0044] A second aspect of the present invention further provides a humidity sensor monitoring system for moisture-proof performance evaluation, the system comprising: a memory and a processor, the memory including a humidity sensor monitoring method program for moisture-proof performance evaluation, and the humidity sensor monitoring method program for moisture-proof performance evaluation, when executed by the processor, implementing the following steps:

[0045] Acquiring monitoring performance data of humidity sensors, determining initial placement locations of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement locations, optimizing the placement of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area;

[0046] Acquire humidity change data at each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, and construct a humidity difference map of the target area according to the humidity change data;

[0047] Determining the moisture diffusion characteristics of the target area under different humidity conditions and various environmental characteristics according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics;

[0048] The humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result;

[0049] A humidity sensor monitoring weight for the target area is determined according to the humidity change prediction result, and a humidity sensor monitoring strategy is determined according to the monitoring weight.

[0050] The present invention discloses a humidity sensor monitoring method and system for moisture-proof performance evaluation, belonging to the field of environmental monitoring technology. The method includes: obtaining humidity sensor monitoring performance data, determining the initial layout position of the humidity sensor in the target area and performing redundancy analysis, and constructing a humidity monitoring system after optimizing the layout position; obtaining humidity change data under different environmental characteristics and humidity conditions through the monitoring system, and constructing a humidity difference map; analyzing moisture diffusion characteristics based on the humidity difference map, and establishing a humidity change prediction model; monitoring humidity information and environmental condition data in real time, and importing them into the prediction model to predict humidity changes and obtain prediction results; and determining the monitoring weight and monitoring strategy of the humidity sensor based on the prediction results. The present invention optimizes sensor layout and monitoring methods, can efficiently evaluate the moisture-proof performance of the target area, and improve the accuracy and efficiency of humidity monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A flow chart of a humidity sensor monitoring method for moisture-proof performance evaluation according to the present invention is shown;

[0052] Figure 2 A flow chart showing the present invention for constructing a humidity change prediction model for a target area is shown;

[0053] Figure 3 A flow chart showing the humidity change prediction results obtained by the present invention is shown;

[0054] Figure 4 A block diagram of a humidity sensor monitoring system for moisture-proof performance evaluation according to the present invention is shown. DETAILED DESCRIPTION

[0055] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0056] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0057] Figure 1 The flowchart of the humidity sensor monitoring method for moisture-proof performance evaluation of the present invention is shown.

[0058] like Figure 1 As shown, the first aspect of the present invention provides a humidity sensor monitoring method for moisture-proof performance evaluation, comprising:

[0059] S102, obtaining monitoring performance data of humidity sensors, determining initial placement positions of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement positions, optimizing the positions of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area;

[0060] S104, obtaining humidity change data at each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, and constructing a humidity difference map of the target area according to the humidity change data;

[0061] S106, determining each environmental characteristic and moisture diffusion characteristics of the target area under different humidity conditions according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics;

[0062] S108, monitoring the humidity information of the target area in real time according to the humidity monitoring system, obtaining environmental condition data of the target area, importing the humidity information and environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtaining a humidity change prediction result;

[0063] S110 , determining a humidity sensor monitoring weight for a target area according to the humidity change prediction result, and determining a humidity sensor monitoring strategy according to the monitoring weight.

[0064] It should be noted that by collecting humidity sensor performance data (such as accuracy, response speed, and measurement range), combined with the spatial structure of the target area, the humidity sensor placement is preliminarily determined to effectively cover the monitoring area. Redundancy analysis and optimized placement reduce monitoring blind spots and data redundancy, ensuring a rational sensor distribution and building an efficient and accurate humidity monitoring system. The humidity monitoring system records humidity variation data under multiple environmental characteristics (such as temperature, airflow, pressure, and light) and humidity conditions (such as humidity source location and humidity range), forming a humidity data set in both temporal and spatial dimensions. Based on this data, a humidity difference map is constructed to visually demonstrate the spatial differences in humidity distribution within the target area. The humidity difference map identifies characteristics such as the path, rate, and degree of moisture diffusion within the target area, revealing patterns in humidity variation. Based on these diffusion characteristics, a humidity change prediction model is constructed using machine learning algorithms (such as decision trees) to accurately predict dynamic humidity changes in complex environments. By combining real-time humidity monitoring information with environmental condition data and the humidity change prediction model, humidity trends are dynamically analyzed to provide early warning of potential moisture diffusion issues. This step enhances the system's dynamic response to moisture diffusion. Based on the humidity change predictions, it determines the monitoring weights (e.g., importance and priority) for each humidity sensor and optimizes the monitoring strategy (e.g., sampling frequency and data transmission priority). This adaptive monitoring strategy improves resource utilization of the humidity monitoring system, reduces energy consumption and costs, while ensuring monitoring accuracy in high-risk areas and providing efficient support for moisture-proofing performance assessments in target areas.

[0065] According to an embodiment of the present invention, the steps of obtaining monitoring performance data of humidity sensors, determining initial placement positions of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement positions, optimizing the positions of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area are as follows:

[0066] Acquiring monitoring performance data of humidity sensors, and determining, based on the monitoring performance data, the humidity sensor layout spacing in the target area to be evaluated for moisture-proof performance;

[0067] Acquiring spatial structure information of the target area, and determining initial layout positions of the humidity sensors according to the spatial structure information and the layout spacing of the humidity sensors;

[0068] By sequentially placing moisture release devices at multiple preset locations in the target area, operating the moisture release devices at a preset power for a preset time, and obtaining humidity information at each initial location in the target area using humidity sensors at the initial locations;

[0069] constructing a humidity distribution map of the target area based on the humidity information, calculating the Euclidean distance of the humidity information between the monitoring areas of each humidity sensor based on the humidity distribution map, performing similarity analysis based on the Euclidean distance, and constructing a similarity matrix;

[0070] Classifying monitoring areas whose similarity is greater than a preset similarity according to the similarity matrix to obtain similarity monitoring classification areas;

[0071] Performing data monitoring repeatability analysis on the humidity information of each similarity monitoring classification area, determining the humidity information data repetition rate of each similarity monitoring classification area, calculating the humidity information acquisition redundancy based on the data repetition rate, and merging areas with redundancy greater than a preset value to obtain a merged monitoring area;

[0072] The initial layout positions of humidity sensors are optimized according to the combined monitoring areas, and a humidity monitoring system for the target area is constructed based on the humidity sensors with optimized positions.

[0073] It should be noted that the initial placement of humidity sensors within the target area is determined by analyzing their performance data. Moisture release devices are then placed at multiple preset locations within the target area to simulate the moisture diffusion process. This process, combined with humidity change information collected by the humidity sensors at the initial placement locations, creates a humidity distribution map for the target area. This process can intuitively demonstrate moisture diffusion characteristics and humidity change trends. Environmental characteristics (such as temperature, airflow velocity, and pressure) within certain target areas may be relatively uniform, resulting in less spatial variation in humidity changes. In this case, the humidity data collected by multiple sensors may be highly consistent, resulting in information redundancy. Therefore, by calculating the Euclidean distance of humidity information, analyzing the similarity between humidity monitoring areas, and generating a similarity matrix, the similarity of humidity characteristics between monitoring areas can be quantified, which helps to identify data redundant areas, classify monitoring areas with higher similarity, merge areas with redundancy exceeding a preset threshold, optimize the layout of humidity sensors, and reduce excessive deployment of sensors; only adjacent areas with redundancy exceeding a preset threshold can be merged, and only one humidity sensor is set in the merged area for monitoring. Through the optimization of layout positions and the merging of monitoring areas, an efficient humidity monitoring system is finally constructed to ensure that humidity sensors can comprehensively monitor the target area with the optimal number and distribution pattern.

[0074] According to an embodiment of the present invention, the humidity monitoring system obtains humidity change data at each location in the target area under various environmental characteristics and different humidity conditions, and constructs a humidity difference map of the target area based on the humidity change data, specifically:

[0075] Acquire humidity change data and timestamp data for each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, wherein the environmental characteristics include temperature, airflow velocity, air pressure, and light intensity, and the different humidity conditions include the location and range of the humidity source and the humidity value;

[0076] Constructing a data matrix based on the timestamp data for each environmental feature and humidity data of the target area under humidity conditions acquired by the humidity monitoring system at each time point;

[0077] Obtaining the layout location information of the humidity sensors in the target area, performing a humidity spatial interpolation operation on the layout location information and the humidity data of each location at each time point in the target area based on the Kriging interpolation algorithm, and constructing a humidity distribution map of the target area at each time point;

[0078] Performing data annotation on the humidity distribution map, wherein the data annotation includes a timestamp annotation, an environmental feature annotation, and a humidity condition annotation, to obtain a data-annotated humidity distribution map;

[0079] Setting a reference humidity value for the target area, assigning a reference color value to the reference humidity value, analyzing the reference humidity value and the reference color value according to histogram homogenization, and constructing a color mapping table for different humidity values;

[0080] Color mapping is performed on the data-annotated humidity distribution map according to the color mapping table to construct a humidity difference map of the target area.

[0081] It should be noted that humidity changes are not only affected by spatial position, but also closely related to environmental conditions (such as temperature, airflow velocity, air pressure, light intensity) and humidity sources (such as humidity source location and humidity value). By integrating timestamps, environmental characteristics (such as temperature, airflow velocity, air pressure, light intensity) and humidity conditions (such as humidity source location, range and humidity value), a humidity change data matrix of the target area is constructed. By constructing a humidity distribution map of the target area at each time point, since the layout locations of humidity sensors in the target area are sparse and humidity sensors are not deployed at every location, it is necessary to spatially interpolate the humidity sensor data through the Kriging interpolation algorithm to generate a humidity distribution map of the target area at each time point, which improves the resolution of the humidity distribution, compensates for the monitoring blind spots that may be caused by the large spacing of sensors, and makes the humidity data coverage more comprehensive and accurate. By constructing a color mapping table, the humidity distribution map is converted into a humidity difference map. Different humidity values ​​are intuitively presented as different colors, which can quickly identify areas or change trends that exceed the baseline humidity.

[0082] Figure 2 The flowchart of the present invention for constructing a humidity change prediction model for a target area is shown.

[0083] According to an embodiment of the present invention, determining the environmental characteristics and the moisture diffusion characteristics of the target area under different humidity conditions according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics, specifically:

[0084] S202, sorting the humidity difference maps under the same environmental characteristics and the same humidity conditions in time series according to the humidity difference maps, to obtain a time series humidity difference map under each environmental characteristic and humidity condition;

[0085] S204, determining the humidity change at each location in the target area under each environmental characteristic and humidity condition based on the time series humidity difference map, analyzing the humidity change at each location based on a gradient field algorithm, and constructing a gradient field of humidity distribution;

[0086] S206, identifying moisture diffusion directions and trends in the target area under various environmental characteristics and different humidity conditions based on the gradient field of the moisture distribution, and identifying moisture diffusion characteristics based on the moisture diffusion directions and trends, the moisture diffusion characteristics including moisture diffusion path characteristics, diffusion rate characteristics, and diffusion degree characteristics;

[0087] S208, constructing a humidity change prediction model for the target area based on a decision tree algorithm, constructing a feature vector based on the environmental characteristics, humidity conditions, and corresponding moisture diffusion characteristics, and dividing the feature vector into training set features and test set features according to a preset ratio;

[0088] S210, importing the training set features into the humidity change prediction model to construct a decision tree, training the humidity change prediction model according to the decision tree, and importing the test set features into the humidity change prediction model after training to optimize the model parameters, so as to obtain a humidity change prediction model with prediction capabilities for each location in the target area.

[0089] It should be noted that by analyzing moisture diffusion data under different environmental characteristics and humidity conditions in the humidity difference map, combined with a gradient field algorithm and identification of moisture diffusion direction and trends, it is possible to accurately determine the diffusion path, diffusion rate, and diffusion extent of moisture in the target area. This means that we can fully understand how moisture propagates under different conditions. By constructing a time-series-based humidity change prediction model that combines the humidity difference map, environmental characteristics, and moisture diffusion characteristics, we can achieve dynamic predictions of humidity changes in the target area. Using a gradient field algorithm to analyze humidity changes and combining it with a decision tree algorithm to train and optimize the humidity change prediction model, we can achieve high-precision predictions of humidity changes in the target area. By partitioning the feature vectors and optimizing the training and test sets, we ensure that the model can adapt to different environmental conditions and humidity change patterns. The gradient field represents the spatial variation of humidity within the target area.

[0090] Figure 3 The flowchart of the humidity change prediction result obtained by the present invention is shown.

[0091] According to an embodiment of the present invention, the humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result, which is specifically:

[0092] S302, obtaining humidity information of the target area in real time according to the humidity monitoring system, wherein the humidity information includes the location and range of the humidity source and the humidity value, and obtaining environmental condition data of the target area in real time;

[0093] S304, importing the humidity information and environmental condition data into the humidity change prediction model, predicting moisture diffusion information in the target area within a future preset time period, and obtaining moisture diffusion prediction information;

[0094] S306 , predicting the humidity change at each location in the target area according to the moisture diffusion prediction information to obtain a humidity change prediction result.

[0095] It's important to note that by monitoring the target area's humidity information (such as the location, range, and humidity value of the humidity source) and environmental conditions (such as temperature, airflow, and air pressure) in real time, and integrating these real-time humidity information and environmental conditions into the humidity change prediction model, it's possible to predict moisture diffusion in the target area, including its path, rate, and range. This prediction isn't limited to the current moment; it can also accurately estimate humidity changes over time.

[0096] According to an embodiment of the present invention, determining the humidity sensor monitoring weight of the target area according to the humidity change prediction result, and determining the humidity sensor monitoring strategy according to the monitoring weight, are specifically as follows:

[0097] Acquire humidity control demand data of a target area, and mark areas where the humidity is greater than the humidity control demand in a future preset time period according to the humidity change prediction result and the humidity control demand data to obtain marked areas;

[0098] Adjusting the humidity sensor monitoring weight of the marked area according to the humidity change prediction result, and determining the sampling frequency of each humidity sensor in the target area according to the humidity sensor monitoring weight;

[0099] Obtaining data transmission performance data of the humidity monitoring system, and calculating performance consumption information of the humidity monitoring system for data sampling according to the sampling frequency;

[0100] determining a humidity monitoring response speed of the humidity monitoring system for the target area based on the performance consumption information and the data transmission performance data;

[0101] Obtaining humidity monitoring response speed requirement data for the target area; if the humidity monitoring response speed is less than the humidity monitoring response speed requirement, determining the data transmission priority of each humidity monitoring sensor according to the humidity sensor monitoring weight; and constructing a humidity sensor monitoring strategy based on the sampling frequency and data transmission priority;

[0102] The target area is monitored for humidity in real time according to the monitoring strategy to obtain real-time humidity information of the target area, and the moisture-proof performance of the target area is evaluated according to the real-time humidity information to obtain a moisture-proof performance evaluation result.

[0103] It should be noted that in areas with higher humidity (marked areas), more frequent humidity monitoring is required. In areas with lower humidity, frequent monitoring may be redundant, wasting computing and transmission resources. By adjusting the monitoring weights and sampling frequency, resources can be concentrated in areas with greater humidity fluctuations, improving sensor monitoring efficiency, avoiding ineffective data collection, reducing unnecessary data collection and transmission, and improving overall system performance while also reducing energy consumption. Data transmission performance is crucial in wireless humidity monitoring systems. Excessively high sampling frequencies can overload the system, increase data transmission latency, reduce monitoring response speed, and even affect system stability. Humidity monitoring systems must respond promptly to humidity changes in target areas. This is particularly true in moisture prevention assessments and moisture diffusion predictions, where response speed is crucial for ensuring effective early warning and decision-making. If the system's response speed is too slow, moisture prevention measures may not be initiated promptly, increasing risk. By dynamically adjusting the sensor priority and sampling frequency, humidity changes in important areas can be monitored in a timely manner, avoiding response delays when moisture risks are higher. Based on the humidity monitoring response speed requirements of the target area, the monitoring strategy can be flexibly adjusted so that the system can provide fast and accurate humidity change data at critical moments. Based on real-time humidity information and optimization of the monitoring strategy, the moisture-proof performance of the target area can be evaluated efficiently and accurately, and potential problems of excessive humidity can be discovered in a timely manner.

[0104] Figure 4 A block diagram of a humidity sensor monitoring system for moisture-proof performance evaluation according to the present invention is shown.

[0105] A second aspect of the present invention further provides a humidity sensor monitoring system 4 for moisture-proof performance evaluation, the system comprising: a memory 41 and a processor 42, wherein the memory includes a humidity sensor monitoring method program for moisture-proof performance evaluation, and when the humidity sensor monitoring method program for moisture-proof performance evaluation is executed by the processor, the following steps are implemented:

[0106] Acquiring monitoring performance data of humidity sensors, determining initial placement locations of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement locations, optimizing the placement of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area;

[0107] Acquire humidity change data at each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, and construct a humidity difference map of the target area according to the humidity change data;

[0108] Determining the moisture diffusion characteristics of the target area under different humidity conditions and various environmental characteristics according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics;

[0109] The humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result;

[0110] A humidity sensor monitoring weight for the target area is determined according to the humidity change prediction result, and a humidity sensor monitoring strategy is determined according to the monitoring weight.

[0111] The present invention discloses a humidity sensor monitoring method and system for moisture-proof performance evaluation, belonging to the field of environmental monitoring technology. The method includes: obtaining humidity sensor monitoring performance data, determining the initial layout position of the humidity sensor in the target area and performing redundancy analysis, and constructing a humidity monitoring system after optimizing the layout position; obtaining humidity change data under different environmental characteristics and humidity conditions through the monitoring system, and constructing a humidity difference map; analyzing moisture diffusion characteristics based on the humidity difference map, and establishing a humidity change prediction model; monitoring humidity information and environmental condition data in real time, and importing them into the prediction model to predict humidity changes and obtain prediction results; and determining the monitoring weight and monitoring strategy of the humidity sensor based on the prediction results. The present invention optimizes sensor layout and monitoring methods, can efficiently evaluate the moisture-proof performance of the target area, and improve the accuracy and efficiency of humidity monitoring.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0113] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0114] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0115] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0116] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0117] 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 modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A humidity sensor monitoring method for moisture-proof performance evaluation, characterized in that: The following steps are involved: Acquiring monitoring performance data of humidity sensors, determining initial placement locations of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement locations, optimizing the placement of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area; Acquire humidity change data at each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, and construct a humidity difference map of the target area according to the humidity change data; Determining the moisture diffusion characteristics of the target area under different humidity conditions and various environmental characteristics according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics; The humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result; Determining a humidity sensor monitoring weight for a target area based on the humidity change prediction result, and determining a humidity sensor monitoring strategy based on the monitoring weight; The humidity sensor monitoring weight of the target area is determined according to the humidity change prediction result, and the humidity sensor monitoring strategy is determined according to the monitoring weight, specifically: Acquire humidity control demand data of a target area, and mark areas where the humidity is greater than the humidity control demand in a future preset time period according to the humidity change prediction result and the humidity control demand data to obtain marked areas; Adjusting the humidity sensor monitoring weight of the marked area according to the humidity change prediction result, and determining the sampling frequency of each humidity sensor in the target area according to the humidity sensor monitoring weight; Obtaining data transmission performance data of the humidity monitoring system, and calculating performance consumption information of the humidity monitoring system for data sampling according to the sampling frequency; determining a humidity monitoring response speed of the humidity monitoring system for the target area based on the performance consumption information and the data transmission performance data; Obtaining humidity monitoring response speed requirement data for the target area; if the humidity monitoring response speed is less than the humidity monitoring response speed requirement, determining the data transmission priority of each humidity monitoring sensor according to the humidity sensor monitoring weight; and constructing a humidity sensor monitoring strategy based on the sampling frequency and data transmission priority; The target area is monitored for humidity in real time according to the monitoring strategy to obtain real-time humidity information of the target area, and the moisture-proof performance of the target area is evaluated according to the real-time humidity information to obtain a moisture-proof performance evaluation result.

2. A humidity sensor monitoring method for moisture-proof performance evaluation according to claim 1, characterized in that: The method includes obtaining monitoring performance data of humidity sensors, determining initial placement positions of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement positions, optimizing the positions of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area, specifically: Acquiring monitoring performance data of humidity sensors, and determining, based on the monitoring performance data, the humidity sensor layout spacing in the target area to be evaluated for moisture-proof performance; Acquiring spatial structure information of the target area, and determining initial layout positions of the humidity sensors according to the spatial structure information and the layout spacing of the humidity sensors; By sequentially placing moisture release devices at multiple preset locations in the target area, operating the moisture release devices at a preset power for a preset time, and obtaining humidity information at each initial location in the target area using humidity sensors at the initial locations; constructing a humidity distribution map of the target area based on the humidity information, calculating the Euclidean distance of the humidity information between the monitoring areas of each humidity sensor based on the humidity distribution map, performing similarity analysis based on the Euclidean distance, and constructing a similarity matrix; Classifying monitoring areas whose similarity is greater than a preset similarity according to the similarity matrix to obtain similarity monitoring classification areas; Performing data monitoring repeatability analysis on the humidity information of each similarity monitoring classification area, determining the humidity information data repetition rate of each similarity monitoring classification area, calculating the humidity information acquisition redundancy based on the data repetition rate, and merging areas with redundancy greater than a preset value to obtain a merged monitoring area; The initial layout positions of humidity sensors are optimized according to the combined monitoring areas, and a humidity monitoring system for the target area is constructed based on the humidity sensors with optimized positions.

3. The humidity sensor monitoring method for moisture-proof performance evaluation according to claim 1, characterized in that: The humidity monitoring system obtains humidity change data at each location in the target area under various environmental characteristics and different humidity conditions, and constructs a humidity difference map of the target area based on the humidity change data, specifically: Acquire humidity change data and timestamp data for each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, wherein the environmental characteristics include temperature, airflow velocity, air pressure, and light intensity, and the different humidity conditions include the location and range of the humidity source and the humidity value; Constructing a data matrix based on the timestamp data for each environmental feature and humidity data of the target area under humidity conditions acquired by the humidity monitoring system at each time point; Obtaining the layout location information of the humidity sensors in the target area, performing a humidity spatial interpolation operation on the layout location information and the humidity data of each location at each time point in the target area based on the Kriging interpolation algorithm, and constructing a humidity distribution map of the target area at each time point; Performing data annotation on the humidity distribution map, wherein the data annotation includes a timestamp annotation, an environmental feature annotation, and a humidity condition annotation, to obtain a data-annotated humidity distribution map; Setting a reference humidity value for the target area, assigning a reference color value to the reference humidity value, analyzing the reference humidity value and the reference color value according to histogram homogenization, and constructing a color mapping table for different humidity values; Color mapping is performed on the data-annotated humidity distribution map according to the color mapping table to construct a humidity difference map of the target area.

4. The humidity sensor monitoring method for moisture-proof performance evaluation according to claim 1, characterized in that: The method further comprises determining the humidity diffusion characteristics of the target area under different humidity conditions and the environmental characteristics according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the humidity diffusion characteristics. Specifically, the method comprises: According to the humidity difference map, the humidity difference maps under the same environmental characteristics and the same humidity conditions are sorted in time series to obtain a time series humidity difference map under each environmental characteristic and humidity condition; Determine the humidity change at each location in the target area under each environmental characteristic and humidity condition based on the time series humidity difference map, analyze the humidity change at each location based on a gradient field algorithm, and construct a gradient field of humidity distribution; Identifying moisture diffusion directions and trends in a target area under various environmental characteristics and different humidity conditions based on the gradient field of the moisture distribution, and identifying moisture diffusion characteristics based on the moisture diffusion directions and trends, wherein the moisture diffusion characteristics include moisture diffusion path characteristics, diffusion rate characteristics, and diffusion degree characteristics; A humidity change prediction model for the target area is constructed based on a decision tree algorithm, a feature vector is constructed by combining the environmental characteristics, humidity conditions, and corresponding moisture diffusion characteristics, and the feature vector is divided into training set features and test set features according to a preset ratio; The training set features are imported into the humidity change prediction model to construct a decision tree, the humidity change prediction model is trained according to the decision tree, and the test set features are imported into the humidity change prediction model after training to optimize the model parameters, so as to obtain a humidity change prediction model with prediction capabilities for each location in the target area.

5. The humidity sensor monitoring method for moisture-proof performance evaluation according to claim 1, characterized in that: The humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result, which is specifically: According to the humidity monitoring system, the humidity information of the target area is obtained in real time, wherein the humidity information includes the location and range of the humidity source and the humidity value, and the environmental condition data of the target area is obtained in real time; Importing the humidity information and environmental condition data into the humidity change prediction model, predicting moisture diffusion information in the target area within a future preset time period, and obtaining moisture diffusion prediction information; The humidity change at each location in the target area is predicted based on the moisture diffusion prediction information to obtain a humidity change prediction result.

6. A humidity sensor monitoring system for moisture-proof performance evaluation, characterized in that: The humidity sensor monitoring system for moisture-proof performance evaluation includes a storage device and a processor. The storage device includes a humidity sensor monitoring method program for moisture-proof performance evaluation. When the humidity sensor monitoring method program for moisture-proof performance evaluation is executed by the processor, the following steps are implemented: Acquiring monitoring performance data of humidity sensors, determining initial placement locations of humidity sensors in a target area for moisture-proof performance evaluation based on the monitoring performance data, performing redundancy analysis on the humidity sensors at the initial placement locations, optimizing the placement of the humidity sensors based on the redundancy analysis, and constructing a humidity monitoring system for the target area; Acquire humidity change data at each location in the target area under various environmental characteristics and different humidity conditions according to the humidity monitoring system, and construct a humidity difference map of the target area according to the humidity change data; Determining the moisture diffusion characteristics of the target area under different humidity conditions and various environmental characteristics according to the humidity difference map, and constructing a humidity change prediction model for the target area according to the moisture diffusion characteristics; The humidity monitoring system monitors the humidity information of the target area in real time, obtains the environmental condition data of the target area, imports the humidity information and the environmental condition data into the humidity change prediction model to predict the humidity change of the target area, and obtains the humidity change prediction result; Determining a humidity sensor monitoring weight for a target area based on the humidity change prediction result, and determining a humidity sensor monitoring strategy based on the monitoring weight; The humidity sensor monitoring weight of the target area is determined according to the humidity change prediction result, and the humidity sensor monitoring strategy is determined according to the monitoring weight, specifically: Acquire humidity control demand data of a target area, and mark areas where the humidity is greater than the humidity control demand in a future preset time period according to the humidity change prediction result and the humidity control demand data to obtain marked areas; Adjusting the humidity sensor monitoring weight of the marked area according to the humidity change prediction result, and determining the sampling frequency of each humidity sensor in the target area according to the humidity sensor monitoring weight; Obtaining data transmission performance data of the humidity monitoring system, and calculating performance consumption information of the humidity monitoring system for data sampling according to the sampling frequency; determining a humidity monitoring response speed of the humidity monitoring system for the target area based on the performance consumption information and the data transmission performance data; Obtaining humidity monitoring response speed requirement data for the target area; if the humidity monitoring response speed is less than the humidity monitoring response speed requirement, determining the data transmission priority of each humidity monitoring sensor according to the humidity sensor monitoring weight; and constructing a humidity sensor monitoring strategy based on the sampling frequency and data transmission priority; The target area is monitored for humidity in real time according to the monitoring strategy to obtain real-time humidity information of the target area, and the moisture-proof performance of the target area is evaluated according to the real-time humidity information to obtain a moisture-proof performance evaluation result.

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