A one-stop environment perception management method and device based on mesh networking

Abstract

The present invention discloses a one-stop environment perception management method and device based on mesh networking, which relates to the field of self-organizing network technology. The method includes: through mesh networking, arranging perception nodes in the target space to build a perception topology network; collecting environmental feature data, parsing in the edge processing unit, analyzing the degree of change; analyzing the communication delay; calculating the change parameter according to the degree of change and the delay; the central node receives the data, the analysis result and the parameter, and obtains the analysis coefficient through the processing center integrated auxiliary analysis; selecting the central environment analysis path, integrating the analysis data, combining the edge analysis and the change parameter, calculating the analysis result, and performing management. The method solves the technical problems of scattered data collection points, high data transmission delay, and difficulty in realizing real-time perception and intelligent management in traditional environmental perception, achieves comprehensive coverage of the monitoring area, improves the stability and reliability of data transmission, and achieves the effect of accurate and effective environmental management.

Description

Technical Field

[0001] The present application relates to the technical field of self-organizing networks, and specifically to a one-stop environment perception management method and device based on mesh networking. Background Art

[0002] With the acceleration of urbanization and the improvement of environmental protection requirements, the importance of environmental perception and governance technologies has become increasingly prominent. However, traditional environmental perception and governance methods have problems such as scattered data collection points and high data transmission delays, which makes it difficult to achieve real-time environmental perception and intelligent governance decisions. At the same time, although the Mesh network structure has the advantages of wide coverage and stable connection, its relatively high latency and high network complexity also limit its application in the field of environmental perception and governance. Summary of the invention

[0003] This application solves the technical problems of scattered data collection points, high data transmission delay, and difficulty in achieving real-time perception and intelligent management in traditional environmental perception by providing a one-stop environmental perception and management method and device based on mesh networking. It achieves comprehensive coverage of the monitoring area, improves the stability and reliability of data transmission, and realizes accurate and effective environmental management.

[0004] The present application provides a one-stop environmental perception management method based on mesh networking, the method comprising: through mesh networking, arranging multiple perception nodes in multiple target areas of a target space to construct a perception topology network, wherein the multiple perception nodes include perception units and edge processing units, and the perception topology network includes a central node and a processing center; through the multiple perception nodes, the environmental feature data in the multiple target areas are perceived and collected, and the multiple environmental feature data are parsed and processed in the multiple edge processing units to obtain multiple edge parsing results, and multiple degrees of change of the multiple environmental feature data are obtained by analysis; in the multiple perception nodes, based on the multiple environmental feature data, the multiple perception nodes and the central processing units are analyzed to obtain the multiple degree of change of the multiple environmental feature data; multiple communication delays of the node; according to the multiple degrees of change and the multiple communication delays, calculate and obtain multiple change parameters of the multiple environmental feature data transmitted to the central node; the central node receives the multiple environmental feature data, multiple edge analysis results and multiple change parameters, and performs integrated auxiliary analysis decisions on the multiple environmental feature data according to the multiple change parameters through the processing center to obtain multiple integrated auxiliary analysis coefficients; according to the multiple integrated auxiliary analysis coefficients, select a corresponding number of central environmental analysis paths in the processing center, perform integrated auxiliary analysis on the multiple environmental feature data, obtain multiple central analysis results, combine the multiple edge analysis results and the multiple change parameters, calculate and obtain multiple analysis results, and perform governance.

[0005] The present application also provides a one-stop environment perception management device based on mesh networking, including: a perception topology network construction module, the perception topology network construction module is used to arrange multiple perception nodes in multiple target areas of the target space through mesh networking to build a perception topology network, wherein the multiple perception nodes include perception units and edge processing units, and the perception topology network includes a central node and a processing center; an analysis processing module, the analysis processing module is used to perceive and collect environmental feature data in the multiple target areas through the multiple perception nodes, perform analysis processing on the multiple environmental feature data in the multiple edge processing units, obtain multiple edge analysis results, and analyze and obtain multiple degrees of change of the multiple environmental feature data; a communication delay analysis module, the communication delay analysis module is used to analyze the communication delay between the multiple perception nodes and the multiple perception nodes based on the multiple environmental feature data. A plurality of communication delays of the central node; a change parameter calculation module, the change parameter calculation module is used to calculate and obtain a plurality of change parameters of the plurality of environmental feature data transmitted to the central node according to the plurality of change degrees and the plurality of communication delays; an analysis decision module, the analysis decision module is used for the central node to receive the plurality of environmental feature data, a plurality of edge analysis results and a plurality of change parameters, and to perform integrated auxiliary analysis decisions on the plurality of environmental feature data according to the plurality of change parameters through the processing center to obtain a plurality of integrated auxiliary analysis coefficients; a governance module, the governance module is used to select a corresponding number of central environmental analysis paths in the processing center according to the plurality of integrated auxiliary analysis coefficients, perform integrated auxiliary analysis on the plurality of environmental feature data, obtain a plurality of central analysis results, and calculate and obtain a plurality of analysis results in combination with the plurality of edge analysis results and a plurality of change parameters for governance.

[0006] The one-stop environment perception management method and device based on mesh networking proposed in this application, through mesh networking, multiple perception nodes are arranged in multiple target areas of the target space to build a perception topology network, wherein the multiple perception nodes include perception units and edge processing units, and the perception topology network includes central nodes and processing centers; through the multiple perception nodes, the environmental feature data in the multiple target areas are perceived and collected, and the multiple environmental feature data are parsed and processed in the multiple edge processing units to obtain multiple edge parsing results, and multiple degrees of change of the multiple environmental feature data are obtained by analysis; in the multiple perception nodes, based on the multiple environmental feature data, the multiple perception nodes and the central processing units are analyzed to obtain the multiple degree of change of the multiple environmental feature data. The multiple communication delays of the nodes; according to the multiple change degrees and multiple communication delays, the multiple change parameters of the multiple environmental feature data transmitted to the central node are calculated; the central node receives the multiple environmental feature data, multiple edge analysis results and multiple change parameters, and the processing center performs integrated auxiliary analysis decisions on the multiple environmental feature data according to the multiple change parameters to obtain multiple integrated auxiliary analysis coefficients; according to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environmental analysis paths are selected in the processing center, and the multiple environmental feature data are integrated and analyzed to obtain multiple central analysis results, and the multiple edge analysis results and multiple change parameters are combined to calculate and obtain multiple analysis results for governance. The technical problems of scattered data collection points, high data transmission delays, and difficulty in achieving real-time perception and intelligent governance in traditional environmental perception are solved, and the comprehensive coverage of the monitoring area is achieved, the stability and reliability of data transmission are improved, and the effect of accurate and effective environmental governance is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the device according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0008] Figure 1 A schematic diagram of a one-stop environment perception management method based on mesh networking provided in an embodiment of the present application;

[0009] Figure 2 A schematic diagram of the structure of a one-stop environment perception management device based on mesh networking provided in an embodiment of the present application.

[0010] Explanation of the accompanying drawings: perception topology network construction module 1, analysis and processing module 2, communication delay analysis module 3, change parameter calculation module 4, analysis and decision module 5, governance module 6. DETAILED DESCRIPTION

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0012] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0013] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0014] The present application embodiment provides a one-stop environment perception management method based on mesh networking, such as Figure 1 As shown, the method includes:

[0015] Through mesh networking, multiple perception nodes are arranged in multiple target areas of the target space to build a perception topology network, wherein the multiple perception nodes include perception units and edge processing units, and the perception topology network includes a central node and a processing center.

[0016] In an embodiment of the present application, the system terminal deploys multiple sensing nodes in different areas of the target space through Mesh networking technology, and these nodes are interconnected to form a sensing topology network. Each sensing node is equipped with a sensing unit and an edge processing unit. The sensing unit is responsible for collecting data about the surrounding environment, such as air quality, temperature, humidity, etc.; while the edge processing unit performs preliminary processing and analysis on these data. This sensing topology network includes a central node and a processing center. As the core of the network, the central node is responsible for receiving data from each sensing node and transmitting it to the processing center. The processing center is a powerful data processing and analysis platform that can integrate, analyze and process data from each node to derive the environmental conditions of the target space, and integrate multiple environmental data to assist in analytical decision-making.

[0017] The environmental feature data in the multiple target areas are sensed and collected through the multiple sensing nodes, and the multiple environmental feature data are analyzed and processed in the multiple edge processing units to obtain multiple edge analysis results, and multiple degrees of change of the multiple environmental feature data are obtained by analysis.

[0018] In one embodiment, in multiple target areas within the already arranged target space, the system terminal collects environmental feature data in each area in real time through the sensing node, such as air quality, temperature, humidity, soil conditions, etc. These collected data are transmitted to the edge processing unit in the node for parsing and processing. The edge processing unit is responsible for receiving the original data and performing preliminary parsing and analysis. During the parsing and analysis process, the edge processing unit calls the internal edge parser to parse multiple environmental feature data and obtain multiple edge parsing results. At the same time, the edge processing unit also analyzes the degree of change of multiple environmental feature data, that is, calculates the probability of change of these data at different time points through the internal data change analyzer. This helps the system terminal understand the change trend and stability of the environmental feature data, so as to more accurately judge the environmental conditions of the target space. In this way, multiple edge processing units process environmental feature data from different target areas in parallel to obtain multiple edge parsing results. These results not only contain the parsed value of the data, but also the degree of change information of the data. This information provides strong support for subsequent decision-making and governance, helping to more accurately identify and solve environmental problems.

[0019] Furthermore, the present application provides a method of sensing and collecting environmental feature data in the multiple target areas through the multiple sensing nodes, performing analysis and processing of the multiple environmental features in the multiple edge processing units, and obtaining multiple edge analysis results, including:

[0020] Environmental characteristic data within the multiple target areas are sensed and collected through the multiple sensing nodes, wherein each environmental characteristic data includes hydrological characteristic data, air characteristic data and soil characteristic data; multiple sample environmental characteristic data sets are obtained based on the environmental data perception records within the multiple target areas, the same sample environmental characteristic data are classified, and the proportion and analysis results of each sample environmental characteristic data are used to identify them, thereby obtaining multiple classified environmental characteristic data sets and multiple classified edge analysis result sets.

[0021] Preferably, in multiple target areas, the system terminal uses multiple sensing nodes to collect environmental characteristic data. These environmental characteristic data cover hydrological characteristic data, air characteristic data and soil characteristic data. Among them, hydrological characteristic data involves various parameters related to water bodies, such as water level, water flow velocity, water quality composition, etc. Air characteristic data involves various properties and states of air, such as air quality index, temperature, humidity, gas concentration, etc. Soil characteristic data involves various physical and chemical properties of soil, such as soil moisture, nutrient content, pH, etc. Taking lakes as an example, the system terminal arranges multiple sensing nodes in the lake and its surrounding areas. These nodes will automatically collect water temperature, pH, dissolved oxygen, conductivity, turbidity and other detection items according to the preset collection frequency and parameter settings. Specifically, sensing nodes are arranged at the sewage outlets and rivers entering the lake to monitor the water temperature, pH, flow rate of the inflowing water quality, as well as the water temperature, pH and flow rate of the lake water quality. Sensing nodes are arranged near residential areas and industrial areas to also monitor the water temperature, pH and flow rate of the external source and lake water quality. Sensing nodes are deployed in key areas to monitor the water level of the lake. Sensing nodes are deployed in high-incidence bands such as garbage dumping, illegal occupation and abuse, and unlicensed water extraction in the lake to monitor the shoreline. Through these sensing nodes deployed around and inside the lake, the system terminal can collect hydrological characteristic data about the lake, namely water temperature, pH, flow rate, water level, etc. Subsequently, the system terminal divides the environmental data perception records in these target areas according to the location to form multiple sample environmental characteristic data sets. Each set contains environmental characteristic data collected in a target area. This environmental data perception record is a historical record database that covers the historical status data of these target areas. In order to process and analyze these data more effectively, the system terminal classifies the data in each sample environmental characteristic data set. Classification is based on data type. For the same type of environmental characteristic data, it is classified into one category. For example, all temperature-related data are classified into one category, or data of the same pollutant are classified into one category. After classification, the proportion of each type of data in each sample environmental characteristic data set is calculated. The proportion represents the relative frequency of the data of this type in the set. Afterwards, each classified environmental feature data is identified in combination with its corresponding parsing result. The identification process is to associate the parsing result with the corresponding environmental feature data category to facilitate subsequent analysis and query. After the above steps, the system terminal obtains multiple classified environmental feature data sets and multiple classified edge parsing result sets. These sets contain various types of environmental feature data and their corresponding parsing results, as well as the proportion of each type of data in the sample set. These sets provide strong data support for the subsequent construction of multiple edge parsers.

[0022] According to the computing power information of the multiple edge processing units, a decision is made to obtain multiple construction data volumes; according to the multiple construction data volumes, the classified environment feature data and the classified edge parsing results with the largest proportion are selected from the multiple classified environment feature data sets and the multiple classified edge parsing result sets, and multiple edge parsers are constructed and configured in the multiple edge processing units; based on the multiple edge parsers, multiple environmental feature data are parsed to obtain multiple edge parsing results.

[0023] Preferably, in the environment perception network, in order to better parse multiple environmental feature data, the system terminal first analyzes the computing power information of each edge processing unit. This is because different edge processing units may have different data processing capabilities. Based on these computing power information, a reasonable amount of construction data can be determined for each unit. Subsequently, the system terminal analyzes the previously classified and sorted multiple environmental feature data sets and the corresponding edge parsing result sets. According to the determined amount of construction data, the data with the largest proportion, that is, the highest frequency of occurrence, are selected from these sets. These data will be used to build multiple edge parsers, and each parser will be configured in the corresponding edge processing unit. Specifically, the system terminal designs the input layer, hidden layer, and output layer of the edge parser according to the complexity of the problem and the characteristics of the data. Subsequently, the weights and bias items of the initial edge parser are randomly initialized, and multiple environmental feature data sets are input into the neural network, and the output results are obtained by calculation of each layer. Afterwards, the mean square error is used to calculate the difference between the prediction result of the edge parser and the corresponding edge parsing result set, and the weights and bias items of the edge parser are updated by the back propagation algorithm according to the calculated gradient information. Repeat this process until the preset maximum number of iterations. Through the above steps, the system terminal can generate a targeted edge parser for each type of environmental feature data to obtain multiple edge parsers. Once the edge parser is built, the system terminal will configure the built edge parser into the corresponding edge processing unit to ensure that the edge processing unit can read the new environmental feature data normally and output the corresponding parsing results. Then, the system terminal inputs the obtained multiple environmental feature data into the edge parser in the edge processing unit. The edge parser can perform real-time parsing and processing on the input environmental feature data based on the learned knowledge, thereby obtaining multiple edge parsing results. These results can not only help the system terminal quickly understand the current environmental status, but also provide strong data support for subsequent governance decisions.

[0024] Further, the present application provides a method for analyzing and obtaining multiple degrees of variation of multiple environmental characteristic data, including:

[0025] According to the change speed of the environmental characteristic data in the multiple target areas, multiple area change degrees are obtained; multiple sample environmental characteristic data sets in the multiple target areas are obtained, and according to the change of each sample environmental characteristic data after it appears, multiple data change degree sets are obtained.

[0026] Preferably, the system terminal analyzes the speed of change of the environmental characteristic data in multiple target areas. These data will change in different time periods. In order to quantify these changes, the system terminal calculates the degree of change of the environmental characteristic data in each area, which is achieved by comparing the amount of change of the data in a period of time, that is, subtracting the data at the initial time from the data at the last moment in a period of time. This degree of change can help the system terminal understand the speed of change of the environmental characteristic data in each area. Subsequently, the system terminal uses the same two methods mentioned above to obtain multiple sample environmental characteristic data sets in multiple target areas from the environmental data perception records in multiple target areas again. For each sample environmental characteristic data, the system terminal changes the sample environmental characteristic data after it appears. This includes analyzing how the sample environmental characteristic data changes within a period of time after it appears, as well as the data at the beginning and end moments. Through this process, a data change degree can be calculated for each sample data, and this change degree reflects the contribution of the sample data to the change of the environmental characteristic data. Afterwards, the system terminal can obtain multiple data change degree sets, each set corresponding to a target area, containing the data change degrees of all sample environmental characteristic data in the area. These collections can help the system terminal fully understand the changes in environmental characteristic data in each target area, thereby providing a scientific basis for the subsequent construction of multiple data change analyzers.

[0027] Using the multiple sample environment feature data sets and multiple data change degree sets, multiple data change analyzers are constructed and configured in the multiple edge processing units; based on the multiple data change analyzers, data change analysis is performed on the multiple environment feature data to obtain multiple data change degrees.

[0028] Preferably, after obtaining multiple sample environmental feature data and multiple data change degree sets, the system terminal uses the same method as the aforementioned construction of multiple edge parsers to train the initialized data change analyzer using multiple sample environmental feature data and multiple data change degree sets to construct multiple data change analyzers. These analyzers are used to specifically analyze the changes in environmental feature data in a specific area, and are configured in the corresponding edge processing unit, so that the system terminal can quickly and accurately analyze the collected environmental feature data. When multiple environmental feature data enter the edge processing unit, the corresponding data change analyzer will be immediately started and analyzed. These analyzers will evaluate the degree of change of the environmental feature data based on the learned knowledge and the current data situation, and generate multiple data change degrees. These change degrees can not only help the system terminal understand the changing trend of the environmental feature data, but also provide an important reference for the subsequent change degree calculation.

[0029] A plurality of variation degrees are calculated based on the plurality of region variation degrees and the plurality of data variation degrees.

[0030] Preferably, the system terminal obtains multiple regional change degrees and multiple data change degrees, wherein the regional change degree reflects the overall trend of environmental change in a region. The data change degree reflects the trend of change of a certain type of data in a region. In order to obtain more comprehensive change degree information, the system terminal combines the regional change degree and the data change degree. Taking air characteristic data as an example, the system terminal determines the importance of air characteristic data in the region based on historical experience and expert advice, and assigns a weight, which reflects the degree of influence of air characteristic data on the environmental change of the entire region. When calculating the comprehensive change degree, the system terminal first multiplies this weight by the regional change degree to obtain a weighted regional change degree. Subsequently, the weighted regional change degree is added to the data change degree of the air characteristic data, and the result of the addition is divided by 2 to obtain the final change degree. Afterwards, for the data change degrees of the remaining features, the system terminal repeats the above process to calculate multiple change degrees. These change degrees correspond to the environmental characteristic data one by one. In this way, the system terminal can not only take into account the environmental change trend of the entire region, but also pay attention to the changes in specific data categories, and perform weighted processing according to their importance in the region. The multiple degrees of change calculated in this way can provide the system terminal with more comprehensive and accurate environmental change information, which helps to better understand and respond to the challenges brought about by environmental changes.

[0031] In the plurality of sensing nodes, based on the plurality of environmental feature data, a plurality of communication delays between the plurality of sensing nodes and the central node are analyzed.

[0032] In one embodiment, in a perception topology network of multiple perception nodes and a central node, environmental feature data is an important reference factor for analyzing communication delays. When analyzing the communication delays between multiple perception nodes and a central node, the system terminal first determines the basic delay between the perception node and the central node based on the distance between the perception node and the central node and its own conditions. Subsequently, this basic delay is added to the delay caused by the environmental feature data itself to obtain the communication delay between each perception node and the central node. By obtaining the communication delay, the network performance can be evaluated more accurately, providing strong support for improving communication efficiency.

[0033] Further, the present application provides, within a plurality of sensing nodes, analyzing a plurality of communication delays between the plurality of sensing nodes and the central node based on the plurality of environmental feature data, including:

[0034] Based on the perception topology network, basic communication delays between the multiple perception nodes and the central node are obtained; the data volume of the multiple environmental feature data is obtained; based on the multiple data volumes, multiple data transmission delays are obtained through analysis, and multiple communication delays are obtained through calculation in combination with the multiple basic communication delays.

[0035] Preferably, in a perception topology network, in order to accurately evaluate the communication performance of the entire network, the system terminal analyzes the communication delay between multiple perception nodes and the central node. This delay mainly includes two parts, namely, basic communication delay and data transmission delay. First, the basic communication delay refers to the time required to establish a communication connection between the perception node and the central node without data transmission load. This time depends on the hardware configuration of the network, the communication protocol, and the distance between the nodes, and is obtained by means of network testing. Subsequently, the system terminal analyzes the data transmission delay. This delay is closely related to the amount of data transmitted. The environmental feature data collected by each perception node has different amounts of data, and the size of these amounts of data will affect the time required for data transmission. For example, if a node collects a large amount of data, it will take longer to transmit these data. In order to obtain the data transmission delay, the system terminal counts the amount of environmental feature data collected by each perception node, and obtains multiple amounts of data corresponding to multiple environmental feature data. After that, the system terminal obtains the transmission rate of the current network, and then divides each amount of data by this transmission rate to estimate the time required for each node to transmit data. This time is the data transmission delay. Then, the system terminal adds the basic communication delay and the data transmission delay to obtain the total communication delay between the sensing node and the central node. This total delay can fully reflect the communication performance of the network and provide strong support for the subsequent calculation of the change parameters transmitted to the central node.

[0036] Based on the multiple degrees of change and the multiple communication delays, multiple change parameters of the multiple environmental feature data transmitted to the central node are calculated and obtained.

[0037] In one embodiment, when multiple sensing nodes transmit environmental characteristic data to a central node, in order to comprehensively evaluate the quality and efficiency of data transmission, the system terminal calculates multiple change parameters by combining multiple degrees of change and multiple communication delays. This calculation process is that the system terminal inputs the degree of change of the environmental characteristic data that each sensing node needs to transmit and the communication delay during transmission into a constructed change parameter analyzer, performs data change analysis, and calculates the change parameters of each sensing node. This change parameter can reflect the probability of change of these environmental characteristic data being sent to the central node. The larger the probability, the greater the probability that the transmitted data will have problems such as packet loss, resulting in inaccurate data received by the central node.

[0038] Further, the present application provides a method for calculating and obtaining a plurality of change parameters of the plurality of environmental feature data transmitted to the central node according to the plurality of change degrees and the plurality of communication delays, including:

[0039] Based on the perception records of environmental feature data in multiple target areas, multiple sample change degree sets and multiple sample communication delay sets are obtained, and multiple sample change parameter sets are obtained; using the multiple sample change degree sets, multiple sample communication delay sets and multiple sample change parameter sets, multiple change parameter analyzers are constructed and configured in the multiple edge processing units; based on the multiple change parameter analyzers, data change analysis is performed on the multiple change degrees and multiple communication delays to obtain multiple change parameters.

[0040] Preferably, the system terminal extracts the data in the environmental data perception record again to obtain multiple sample change degree sets, multiple sample communication delay sets, and multiple sample change parameter sets. Subsequently, using these sample sets, a change parameter analyzer is constructed using the same method as the aforementioned data change analyzer. This analyzer is also configured in multiple edge processing units so that the data from the perception node can be processed and analyzed in real time. Once the change parameter analyzer is configured, the system terminal inputs multiple change degrees and multiple communication delays into the change parameter analyzer, and the change parameter analyzer performs data change analysis based on the learned knowledge to obtain multiple change parameters. These parameters can reflect the probability of change of environmental feature data during transmission to the central node. If the value of a certain change parameter is large, it means that the data corresponding to this change parameter is more likely to be lost, distorted or other problems when it is transmitted to the central node, resulting in inaccurate data received by the central node.

[0041] The central node receives the multiple environmental feature data, multiple edge analysis results and multiple change parameters, and performs integrated auxiliary analysis decisions on the multiple environmental feature data according to the multiple change parameters through the processing center to obtain multiple integrated auxiliary analysis coefficients.

[0042] In one embodiment, the environmental feature data is first sensed and recorded by multiple edge processing units. Due to the limited computing power of edge analysis, although these edge processing units can perform preliminary data analysis, the accuracy is relatively low. Therefore, in order to obtain more accurate analysis results, the system terminal transmits the environmental feature data to the central node for integrated auxiliary analysis. The central node receives multiple environmental feature data from the edge processing unit, as well as the corresponding edge analysis results and change parameters. Subsequently, the processing center makes an integrated auxiliary analysis decision on the multiple environmental feature data according to the multiple change parameters received by the central node. This decision-making process is to input the received multiple change parameters into the constructed auxiliary analysis decision maker, and the auxiliary analysis decision maker makes an integrated auxiliary analysis decision based on the learned knowledge to obtain multiple integrated auxiliary analysis coefficients. The size of the generated integrated auxiliary analysis coefficient decreases with the increase of the change parameter. This is because when the change parameter is large, it indicates that the data may have undergone a large change. At this time, the accuracy of the integrated auxiliary analysis will be reduced, so the integrated auxiliary analysis coefficient generated by the decision maker is small. In this way, the system terminal can further improve the accuracy and reliability of data analysis through the integrated auxiliary analysis of the central node on the basis of the preliminary analysis of the edge processing unit.

[0043] Furthermore, the present application provides an integrated auxiliary analysis decision for multiple environmental feature data according to the multiple change parameters, including:

[0044] A set of sample change parameters is obtained, and according to the set of sample change parameters, a set of sample integrated auxiliary analytical coefficients is obtained by processing, wherein the size of the sample change parameters is negatively correlated with the size of the sample integrated auxiliary analytical coefficients; an integrated auxiliary analytical decision maker is constructed using the sample change parameter set and the set of sample integrated auxiliary analytical coefficients, and is configured in the processing center; based on the integrated auxiliary analytical decision maker, integrated auxiliary analytical decisions are made on the multiple change parameters to obtain multiple integrated auxiliary analytical coefficients.

[0045] Preferably, the system terminal continues to extract a set of sample change parameters from the environmental data perception record. Subsequently, the system terminal determines the sample integrated auxiliary analysis coefficient corresponding to each sample change parameter by evaluating the size of these change parameters. Specifically, after obtaining the sample change parameter, the system terminal quantitatively adjusts the value of the corresponding analysis coefficient according to the relationship between the sample integrated auxiliary analysis coefficient and the sample change parameter, that is, the size of the sample change parameter is negatively correlated with the size of the sample integrated auxiliary analysis coefficient. When the change parameter is large, it means that the possibility of data change is high. At this time, the system terminal will reduce the value of the sample integrated auxiliary analysis coefficient to reflect the possible inaccuracy of the analysis result; conversely, when the change parameter is small, the value of the analysis coefficient will be increased, indicating that the analysis result is more reliable. According to the above relationship, the system terminal calculates a sample integrated auxiliary analysis coefficient for each sample change parameter. Subsequently, the integrated auxiliary analysis coefficients of each sample are combined into a set to obtain a sample integrated auxiliary analysis coefficient set. After obtaining enough sample change parameters and corresponding analysis coefficients, the system terminal uses the same method as the aforementioned construction of the change parameter analyzer to construct an integrated auxiliary analysis decision maker. This decision maker is configured in the processing center to make a fast and accurate integrated auxiliary analysis decision based on the received data change parameters when the central node receives the data transmitted by the edge processing unit. After that, the system terminal uses the integrated auxiliary analysis decision maker to make an integrated auxiliary analysis decision on the change parameters and generate an integrated auxiliary analysis coefficient. These coefficients reflect the system terminal's assessment of the accuracy of the analysis of each environmental feature data after considering the possibility of data change.

[0046] According to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environmental analysis paths are selected in the processing center, and integrated auxiliary analysis is performed on the multiple environmental feature data to obtain multiple central analysis results. The multiple edge analysis results and multiple change parameters are combined to calculate and obtain multiple analysis results for governance.

[0047] In one embodiment, in the data processing center, the system terminal pre-builds a set of basic auxiliary parsing paths, which are divided based on the centrally constructed data set and are used to parse the environmental feature data. When the processing center obtains multiple integrated auxiliary parsing coefficients, the system terminal selects the same number of central environmental parsing paths for integrated auxiliary parsing according to the number of these coefficients. These parsing processes are to filter out the features with the most occurrences from the environmental feature data. Subsequently, the system terminal assigns weights to the central parsing results and edge parsing results of each area according to the size of the changing parameters of each area, and then performs weighted summation on the central parsing results and edge parsing results of each area to obtain the parsing results of each area. By comprehensively considering this information, the system terminal can better understand the laws behind the data, thereby forming a comprehensive, accurate and flexible data parsing and governance plan to govern the environment.

[0048] Further, the present application provides that according to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environment analysis paths are selected in the processing center, the multiple environmental feature data are integrated and assisted to obtain multiple central analysis results, and the multiple edge analysis results and multiple change parameters are combined to calculate and obtain multiple analysis results, including:

[0049] Based on the environmental perception data records of the target space, a sample environmental feature data set is obtained, and a sample central analysis result set is obtained as a central construction data set; according to a preset ratio, a first construction data set is randomly selected from the central construction data set to construct a first central analysis branch; and according to the preset ratio, a construction data set is continuously randomly selected from the central construction data set to construct multiple central environmental analysis paths, and a central analyzer is obtained, which is configured in the processing center.

[0050] Preferably, the system terminal extracts a set of sample environmental feature data sets based on the environmental perception data records. At the same time, a sample central analysis result set corresponding to the sample environmental feature data set is also obtained, and this set of data will serve as the basis for the central construction data set. Subsequently, according to a preset ratio, a portion of data is randomly selected from the central construction data set, namely the first construction data set, and this data set is used to construct the first central analysis branch. This branch will serve as a path for the subsequent analysis process. After that, continue to randomly select more data from the central construction data set according to the same preset ratio to construct multiple different central environmental analysis paths. These paths represent different analysis methods for processing and analyzing environmental feature data. After completing the above steps, the system terminal integrates these analysis paths to construct a central analyzer. This analyzer is configured in the data processing center to parse and process the received environmental feature data.

[0051] According to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environmental analysis paths are selected in the central analyzer, and integrated auxiliary analysis is performed on the multiple environmental feature data respectively, and the analysis results with the highest probability of occurrence are output respectively to obtain multiple central analysis results; according to the sizes of the multiple change parameters, the multiple central analysis results and the multiple edge analysis results are weighted to obtain multiple analysis results, wherein the size of the change parameter is positively correlated with the weight of the edge analysis result.

[0052] Preferably, inside the central resolver, the system terminal determines the number of central environmental resolution paths that need to be activated based on the multiple integrated auxiliary resolution coefficients obtained. Subsequently, the environmental feature data to be resolved are respectively input into the selected central environmental resolution paths. In each selected central environmental resolution path, the system terminal resolves the environmental feature data. This resolution process is to compare the environmental feature data with the sample environmental feature data in this path, and select the environmental feature data with the highest frequency of occurrence as the central resolution result of this path. Afterwards, the system terminal assigns weights to the central resolution result and edge resolution result of the area according to the size of the change parameter of each area. The size of the change parameter is positively correlated with the weight of the edge resolution result, that is, the larger the change parameter, the higher the weight of the edge resolution result, and the smaller the weight of the corresponding central resolution result, because the larger the change parameter, the greater the probability of change during the transmission process, and the less accurate the data transmitted. Then, the system terminal performs weighted summation on the central resolution result and edge resolution result of each area. This process is to perform weighted calculation on the central resolution result and edge resolution result according to their respective weights to obtain a weighted sum as the resolution result of the area. Finally, the system terminal obtains multiple analysis results for multiple areas, which are used for subsequent environmental governance.

[0053] In the above, refer to Figure 1 A one-stop environment-aware governance method based on mesh networking according to an embodiment of the present invention is described in detail. Figure 2 A one-stop environment perception management device based on mesh networking according to an embodiment of the present invention is described.

[0054] A one-stop environment perception and management device based on mesh networking according to an embodiment of the present invention is used to solve the technical problems of scattered data collection points, high data transmission delay, and difficulty in achieving real-time perception and intelligent management in traditional environment perception, thereby achieving comprehensive coverage of the monitoring area, improving the stability and reliability of data transmission, and achieving the effect of accurate and effective environmental management. A one-stop environment perception and management device based on mesh networking includes: a perception topology network construction module 1, an analysis and processing module 2, a communication delay analysis module 3, a change parameter calculation module 4, an analysis and decision module 5, and a management module 6.

[0055] Perception topology network construction module 1: the perception topology network construction module 1 is used to arrange multiple perception nodes in multiple target areas of the target space through mesh networking to build a perception topology network, wherein the multiple perception nodes include perception units and edge processing units, and the perception topology network includes a central node and a processing center;

[0056] Analysis and processing module 2: the analysis and processing module 2 is used to sense and collect the environmental feature data in the multiple target areas through the multiple sensing nodes, perform analysis and processing on the multiple environmental feature data in the multiple edge processing units, obtain multiple edge analysis results, and analyze and obtain multiple degrees of change of the multiple environmental feature data;

[0057] Communication delay analysis module 3: the communication delay analysis module 3 is used to analyze multiple communication delays between the multiple sensing nodes and the central node based on the multiple environmental feature data in the multiple sensing nodes;

[0058] The change parameter calculation module 4 is used to calculate and obtain multiple change parameters of the multiple environmental feature data transmitted to the central node according to the multiple change degrees and multiple communication delays;

[0059] Analysis and decision module 5: the analysis and decision module 5 is used for the central node to receive the multiple environmental feature data, multiple edge analysis results and multiple change parameters, and to perform integrated auxiliary analysis and decision on the multiple environmental feature data according to the multiple change parameters through the processing center to obtain multiple integrated auxiliary analysis coefficients;

[0060] Governance module 6: The governance module 6 is used to select a corresponding number of central environmental analysis paths in the processing center according to the multiple integrated auxiliary analysis coefficients, perform integrated auxiliary analysis on the multiple environmental feature data, obtain multiple central analysis results, combine the multiple edge analysis results and multiple change parameters, calculate and obtain multiple analysis results, and perform governance.

[0061] Furthermore, the analysis processing module 2 also includes:

[0062] Environmental characteristic data in the multiple target areas are sensed and collected through the multiple sensing nodes, wherein each environmental characteristic data includes hydrological characteristic data, air characteristic data and soil characteristic data; based on the environmental data sensing records in the multiple target areas, multiple sample environmental characteristic data sets are obtained, the same sample environmental characteristic data are classified, and the proportion of each sample environmental characteristic data and the analysis result are used to identify them, so as to obtain multiple classified environmental characteristic data sets and multiple classified edge analysis result sets; based on the computing power information of the multiple edge processing units, it is decided to obtain multiple constructed data volumes; according to the multiple constructed data volumes, the classified environmental characteristic data and the classified edge analysis results with the largest proportion are selected from the multiple classified environmental characteristic data sets and the multiple classified edge analysis result sets, and multiple edge analyzers are constructed and configured in the multiple edge processing units; based on the multiple edge analyzers, multiple environmental characteristic data are analyzed to obtain multiple edge analysis results.

[0063] Furthermore, the analysis processing module 2 also includes:

[0064] According to the change speed of the environmental characteristic data in the multiple target areas, multiple regional change degrees are obtained; multiple sample environmental characteristic data sets in the multiple target areas are obtained, and according to the change situation after each sample environmental characteristic data appears, multiple data change degree sets are obtained; using the multiple sample environmental characteristic data sets and the multiple data change degree sets, multiple data change analyzers are constructed and configured in the multiple edge processing units; based on the multiple data change analyzers, data change analysis is performed on the multiple environmental characteristic data to obtain multiple data change degrees; based on the multiple regional change degrees and the multiple data change degrees, multiple change degrees are calculated to obtain.

[0065] Furthermore, the communication delay analysis module 3 also includes:

[0066] Based on the perception topology network, basic communication delays between the multiple perception nodes and the central node are obtained; the data volume of the multiple environmental feature data is obtained; based on the multiple data volumes, multiple data transmission delays are obtained through analysis, and multiple communication delays are obtained through calculation in combination with the multiple basic communication delays.

[0067] Furthermore, the variation parameter calculation module 4 further includes:

[0068] Based on the perception records of environmental feature data in multiple target areas, multiple sample change degree sets and multiple sample communication delay sets are obtained, and multiple sample change parameter sets are obtained; using the multiple sample change degree sets, multiple sample communication delay sets and multiple sample change parameter sets, multiple change parameter analyzers are constructed and configured in the multiple edge processing units; based on the multiple change parameter analyzers, data change analysis is performed on the multiple change degrees and multiple communication delays to obtain multiple change parameters.

[0069] Furthermore, the analysis decision module 5 also includes:

[0070] A set of sample change parameters is obtained, and according to the set of sample change parameters, a set of sample integrated auxiliary analytical coefficients is obtained by processing, wherein the size of the sample change parameters is negatively correlated with the size of the sample integrated auxiliary analytical coefficients; an integrated auxiliary analytical decision maker is constructed using the sample change parameter set and the set of sample integrated auxiliary analytical coefficients, and is configured in the processing center; based on the integrated auxiliary analytical decision maker, integrated auxiliary analytical decisions are made on the multiple change parameters to obtain multiple integrated auxiliary analytical coefficients.

[0071] Furthermore, the governance module 6 also includes:

[0072] Based on the environmental perception data records of the target space, a sample environmental feature data set is obtained, and a sample central analysis result set is obtained as a central construction data set; according to a preset ratio, a first construction data set is randomly selected from the central construction data set to construct a first central analysis branch; continuing to randomly select a construction data set from the central construction data set according to the preset ratio, a plurality of central environmental analysis paths are constructed to obtain a central analyzer, which is configured in the processing center; according to the plurality of integrated auxiliary analysis coefficients, a corresponding number of central environmental analysis paths are selected in the central analyzer, and integrated auxiliary analysis is performed on the plurality of environmental feature data respectively, and analysis results with the highest probability of occurrence are output respectively to obtain a plurality of central analysis results; according to the size of the plurality of change parameters, the plurality of central analysis results and the plurality of edge analysis results are weighted to obtain a plurality of analysis results, wherein the size of the change parameter is positively correlated with the weight of the edge analysis result.

[0073] A one-stop environment perception management device based on mesh networking provided in an embodiment of the present invention can execute a one-stop environment perception management method based on mesh networking provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0074] Although the present application makes various references to certain modules in the device according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0075] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A one-stop environment perception management method based on mesh networking, characterized in that: The method comprises: Through mesh networking, multiple sensing nodes are arranged in multiple target areas of the target space to build a sensing topology network, wherein the multiple sensing nodes include sensing units and edge processing units, and the sensing topology network includes a central node and a processing center; The environmental feature data in the multiple target areas are sensed and collected through the multiple sensing nodes, the multiple environmental feature data are analyzed and processed in the multiple edge processing units to obtain multiple edge analysis results, and multiple degrees of change of the multiple environmental feature data are obtained by analysis; In the plurality of sensing nodes, based on the plurality of environmental feature data, analyzing a plurality of communication delays between the plurality of sensing nodes and the central node; Calculate and obtain multiple change parameters of the multiple environmental feature data transmitted to the central node according to the multiple change degrees and multiple communication delays; The central node receives the multiple environmental feature data, multiple edge analysis results and multiple change parameters, and performs integrated auxiliary analysis decision of the multiple environmental feature data according to the multiple change parameters through the processing center to obtain multiple integrated auxiliary analysis coefficients; According to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environment analysis paths are selected in the processing center, the multiple environmental feature data are integrated and assisted to obtain multiple central analysis results, and the multiple edge analysis results and multiple change parameters are combined to calculate and obtain multiple analysis results for treatment; According to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environment analysis paths are selected in the processing center, and the multiple environmental feature data are integrated and assisted to obtain multiple central analysis results, and the multiple edge analysis results and multiple change parameters are combined to calculate and obtain multiple analysis results, including: Based on the environmental perception data record of the target space, a sample environmental feature data set is obtained, and a sample center analysis result set is obtained as a center construction data set; According to a preset ratio, a first construction data set is randomly selected from the central construction data set to obtain a first central parsing branch; Continue to randomly select a constructed data set in the central constructed data set according to a preset ratio, construct multiple central environment parsing paths, obtain a central parser, and configure it in the processing center; According to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environment analysis paths are selected in the central analyzer, and integrated auxiliary analysis is performed on the multiple environmental feature data respectively, and the analysis results with the highest probability of occurrence are output respectively to obtain multiple central analysis results; According to the sizes of the multiple change parameters, the multiple center analysis results and the multiple edge analysis results are weighted to obtain multiple analysis results, wherein the size of the change parameter is positively correlated with the weight of the edge analysis result.

2. The method according to claim 1, characterized in that The environmental feature data in the multiple target areas are sensed and collected through the multiple sensing nodes, and the multiple environmental features are analyzed and processed in the multiple edge processing units to obtain multiple edge analysis results, including: Sensing and collecting environmental characteristic data in the multiple target areas through the multiple sensing nodes, wherein each environmental characteristic data includes hydrological characteristic data, air characteristic data and soil characteristic data; According to the environmental data perception records in the multiple target areas, multiple sample environmental feature data sets are obtained, the same sample environmental feature data are classified, and the proportion and analysis results of each sample environmental feature data are used to identify them, so as to obtain multiple classified environmental feature data sets and multiple classified edge analysis result sets; According to the computing power information of the plurality of edge processing units, decide to obtain a plurality of construction data volumes; According to the multiple constructed data amounts, select the largest proportion of the classified environment feature data sets and the classified edge parsing results from the multiple classified environment feature data sets and the multiple classified edge parsing result sets, construct multiple edge parsers, and configure them in the multiple edge processing units; Based on the multiple edge parsers, multiple environmental feature data are parsed to obtain multiple edge parsing results.

3. The method according to claim 1, characterized in that Analyze and obtain multiple degrees of change of multiple environmental characteristic data, including: Acquire multiple area change degrees according to the change speed of the environmental characteristic data in the multiple target areas; Acquire multiple sets of sample environmental characteristic data in multiple target areas, and acquire multiple sets of data change degrees according to the changes of each sample environmental characteristic data after it appears; Using the plurality of sample environment feature data sets and the plurality of data change degree sets, construct a plurality of data change analyzers, and configure them in the plurality of edge processing units; Based on the multiple data change analyzers, performing data change analysis on the multiple environmental feature data to obtain multiple data change degrees; A plurality of variation degrees are calculated based on the plurality of region variation degrees and the plurality of data variation degrees.

4. The method according to claim 1, characterized in that: In the plurality of sensing nodes, based on the plurality of environmental feature data, analyzing a plurality of communication delays between the plurality of sensing nodes and the central node comprises: Based on the sensing topology network, obtaining basic communication delays between the plurality of sensing nodes and the central node; Acquire the data volume of the plurality of environmental characteristic data; Based on multiple data volumes, multiple data transmission delays are analyzed and obtained, and multiple communication delays are calculated and obtained by combining multiple basic communication delays.

5. The method according to claim 1, characterized in that Calculating and obtaining a plurality of change parameters of the plurality of environmental feature data transmitted to the central node according to the plurality of change degrees and the plurality of communication delays includes: Based on the perception records of environmental feature data in multiple target areas, multiple sample change degree sets and multiple sample communication delay sets are obtained, and multiple sample change parameter sets are obtained; Using the multiple sample change degree sets, the multiple sample communication delay sets and the multiple sample change parameter sets, construct multiple change parameter analyzers, and configure them in the multiple edge processing units; Based on the multiple change parameter analyzers, data change analysis is performed on the multiple change degrees and multiple communication delays to obtain multiple change parameters.

6. The method according to claim 1, characterized in that The integrated auxiliary analysis and decision making of multiple environmental feature data is performed according to the multiple change parameters, including: Acquire a set of sample variation parameters, and process and acquire a set of sample integration auxiliary analysis coefficients according to the set of sample variation parameters, wherein the size of the sample variation parameters is negatively correlated with the size of the sample integration auxiliary analysis coefficients; Using the sample variation parameter set and the sample integrated auxiliary analysis coefficient set, an integrated auxiliary analysis decision maker is constructed and configured in the processing center; Based on the integrated auxiliary analytical decision maker, integrated auxiliary analytical decisions are performed on the multiple change parameters to obtain multiple integrated auxiliary analytical coefficients.

7. A one-stop environment perception management device based on mesh networking, characterized in that: The device is used to implement a one-stop environment perception management method based on mesh networking as described in any one of claims 1 to 6, comprising: A sensing topology network construction module: through mesh networking, multiple sensing nodes are arranged in multiple target areas of the target space to build a sensing topology network, wherein the multiple sensing nodes include sensing units and edge processing units, and the sensing topology network includes a central node and a processing center; The analysis and processing module senses and collects the environmental feature data in the multiple target areas through the multiple sensing nodes, performs analysis and processing on the multiple environmental feature data in the multiple edge processing units, obtains multiple edge analysis results, and analyzes and obtains multiple degrees of change of the multiple environmental feature data; Communication delay analysis module: in multiple sensing nodes, based on the multiple environmental feature data, analyzing multiple communication delays between the multiple sensing nodes and the central node; A change parameter calculation module: according to the multiple change degrees and multiple communication delays, calculates and obtains multiple change parameters of the multiple environmental feature data transmitted to the central node; Analysis and decision module: the central node receives the multiple environmental feature data, multiple edge analysis results and multiple change parameters, and performs integrated auxiliary analysis and decision making of the multiple environmental feature data according to the multiple change parameters through the processing center to obtain multiple integrated auxiliary analysis coefficients; Governance module: According to the multiple integrated auxiliary analysis coefficients, a corresponding number of central environment analysis paths are selected in the processing center, and the multiple environmental feature data are integrated and assisted to obtain multiple central analysis results. The multiple edge analysis results and multiple change parameters are combined to calculate and obtain multiple analysis results for governance.

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