Intelligent linkage monitoring system of ecological garden environment information based on Internet of Things technology

Abstract

The present invention relates to the technical field of data transmission, and in particular to an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology, including: obtaining the transmission probability of each category according to the compressibility coefficient and transmission priority of the block of monitoring data, and obtaining the transmission category and the category to be transmitted; adjusting the transmission priority of the block in the category to be transmitted and re-clustering it into several new categories according to the validity of the monitoring data to which each block in the linkage data set belongs; in all new categories, any two different blocks are recorded as A and B, the transmission probability of the new category to which A and B belong is recorded as fA and fB, the validity of the monitoring data to which A and B belong is recorded as kA and kB, and the adjusted transmission priority makes the difference between fA and fB positively correlated with the difference between kA and kB. The present invention reduces the delay phenomenon during linkage monitoring or the problem that the linkage monitoring result cannot be obtained as much as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology. Background Art

[0002] In the Internet of Things technology, in order to achieve all-round intelligent monitoring, a large number of terminal devices are often required to work together. For example, multiple monitoring devices, VOCs monitoring devices, and environmental monitoring sensors such as temperature, wind speed, etc. are needed to monitor air quality. For example, microphone devices, monitoring equipment, inspection robots or drones are needed to monitor the ecological environment. However, when a large number of terminal devices communicate with the server, due to limited communication resources (such as the number of communication frequency bands, communication bandwidth, etc.), some data cannot be obtained in time during the linkage monitoring or the acquisition process is delayed, causing the server to enter a thread blocking state to wait for data transmission, or exit related processes, and terminate the linkage analysis and monitoring process with other data in advance, which ultimately leads to abnormalities or delays in the linkage monitoring results on the server side. Summary of the invention

[0003] In order to solve the above problems, the present invention provides an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology.

[0004] The ecological garden environment information intelligent linkage monitoring system based on Internet of Things technology of the present invention adopts the following technical solutions:

[0005] An embodiment of the present invention provides an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology, which includes the following modules:

[0006] Data acquisition module, used to collect monitoring data output by terminal equipment;

[0007] The edge computing module includes multiple edge devices, each edge device reads the monitoring data of several terminal devices, divides each monitoring data into blocks, and each block has a transmission priority; any block of all monitoring data constitutes a data set to be transmitted; according to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block, all blocks in the data set to be transmitted are clustered into several categories; according to the compressibility coefficients and transmission priorities of all blocks in each category, the transmission probability of each category is obtained; according to the transmission probabilities of all categories, a category is randomly selected as the transmission category, and other categories outside the transmission category are recorded as the categories to be transmitted;

[0008] Data transmission module: used to transmit the blocks of the transmission category in each edge device to the server;

[0009] The transmission priority allocation module runs on the server and is used to treat the monitoring data with linkage monitoring function as a linkage data set; after receiving the blocks of all edge devices, the server adjusts the transmission priority of the blocks in the category to be transmitted in each edge device according to the validity of the monitoring data belonging to each block in each linkage data set, and re-cluster all the blocks in the category to be transmitted into several new categories according to the compressibility coefficient of any two blocks in all the blocks in the category to be transmitted and the adjusted transmission priority of each block;

[0010] Among all new categories of blocks of all edge devices, any two different blocks are denoted as A and B, the transmission probability of the new categories to which A and B belong is denoted as fA and fB, and the validity of the monitoring data to which A and B belong is denoted as kA and kB. The adjusted transmission priority makes the difference between fA and fB positively correlated with the difference between kA and kB.

[0011] Preferably, the specific steps of obtaining the compressibility coefficients of any two blocks are as follows:

[0012] Splice any two blocks together to obtain a splicing result, obtain the data volume K0 of the splicing result, encode and compress the splicing result to obtain a compressed result, the data volume of the compressed result is recorded as K1, and the ratio of (K0-K1) to K0 is taken as the compressibility coefficient of any two blocks.

[0013] Preferably, the clustering of all the blocks in the data set to be transmitted into several categories according to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block comprises the following specific steps:

[0014] The average of the transmission priorities of any two blocks is recorded as the comprehensive transmission priority, and the product of the comprehensive transmission priority and the compressibility coefficient of any two blocks is recorded as the metric distance of any two blocks; according to the metric distance of any two blocks in the data set to be transmitted, the K-Means algorithm is used to cluster all the blocks in the data set to be transmitted to obtain several categories.

[0015] Preferably, the specific steps for obtaining the validity of the monitoring data belonging to each block in each linkage data set are as follows:

[0016] In the transmission priority allocation module on the server side, for all monitoring data in each linkage data set, all blocks belonging to the same monitoring data are obtained, and the ratio of the data volume of all blocks belonging to the same monitoring data to the data volume of the monitoring data is recorded as the integrity of each monitoring data;

[0017] The total amount of data in the blocks included in the monitoring data in each linkage data set and not received by the server is obtained, and the ratio of the total amount of data to the data transmission speed is recorded as the data completion pressure A1 of each linkage data set;

[0018] The mean of the completeness of all monitoring data in the linkage data set is obtained, recorded as A2, and the ratio of A2 to A1+1 is recorded as the validity of each linkage data set; all linkage data sets to which each monitoring data belongs are obtained, and the maximum validity among the availabilities of all the linkage data sets is taken as the validity of each monitoring data.

[0019] Preferably, the step of obtaining the transmission probability of each category according to the compressibility coefficients and transmission priorities of all blocks in each category includes the following specific steps:

[0020] Among all the blocks in each category, two blocks with the largest metric distance are obtained and recorded as a compression group; the two blocks with the largest metric distance are spliced ​​together and compressed to obtain a compression result; among all the remaining blocks, two blocks with the largest metric distance are obtained again and recorded as a compression group again; the two blocks with the largest distance are spliced ​​together again and compressed to obtain a compression result; and so on, until there are no remaining blocks or only one block is left and stop; according to the order in which the compression results are obtained, all the obtained compression groups are recorded as a compression group sequence of each category; the average value of the transmission priority of all blocks in the compression group sequence is recorded as the initial transmission probability of each category; the initial transmission probabilities of all categories are normalized to obtain the transmission probability of each category.

[0021] Preferably, the transmission priority after adjustment is such that the difference between fA and fB is positively correlated with the difference between kA and kB, and the specific steps included are as follows:

[0022] The set of blocks in all new categories of all edge devices is denoted as S; , ;

[0023] make ; mA represents the compression index of the new category to which A belongs, and mB represents the compression index of the new category to which B belongs; the compression index of the new category is obtained according to the compression group sequence of the new category;

[0024] The transmission priority corresponding to when F is minimum is used as the adjusted transmission priority of each block in S.

[0025] Preferably, the specific steps of obtaining the compression index of the new category to which A belongs and the compression index of the new category to which B belongs are as follows:

[0026] For the new category to which any block in A or B belongs, a compression group sequence of the new category is obtained. For each compression group in the compression group sequence, the compressibility coefficients of the two blocks in each compression group are simply recorded as the compressibility coefficient of each compression group. The mean of the effectiveness of the monitoring data to which the two blocks in the compression group belong respectively is obtained, and the mean of the effectiveness corresponding to each compression group is normalized to obtain the compression attention of each compression group. The compression attention of each compression group is used as a weight, and the compressibility coefficients of all compression groups in the compression group sequence are weighted and summed to obtain the compression index of the new category to which any block in A or B belongs.

[0027] Preferably, the block transmission of the transmission category in each edge device to the server includes the following specific steps:

[0028] According to the order in which the compression results are obtained, all the compression results are concatenated together and compressed to obtain the final compression result of each category, and the final compression result is transmitted to the server.

[0029] Preferably, the step of dividing each monitoring data into blocks includes the following specific steps:

[0030] The monitoring data in each edge device is flattened into a one-dimensional sequence; the one-dimensional sequence is equally divided into several subsequences, and the data volume of each subsequence is N; each subsequence is regarded as a block, and N is a preset value.

[0031] Preferably, after the transmission priority allocation module adjusts the transmission priority of the blocks in the to-be-transmitted category in each edge device, the specific steps included are as follows:

[0032] All blocks in the to-be-transmitted category in each edge device constitute the to-be-transmitted data set again. According to the compressibility coefficient of any two blocks in the to-be-transmitted data set and the adjusted transmission priority of each block, all blocks in the to-be-transmitted data set are clustered into several categories again, and the transmission category and the to-be-transmitted category are regained. The data transmission module transmits the transmission category of each edge device to the server again. After receiving the blocks, the server uses the transmission priority allocation module to re-assign transmission priorities to the blocks in the to-be-transmitted category of the edge device. And so on, continuously transmit the blocks of all monitoring data of the edge device to the server. When all blocks of the monitoring data are transmitted to the server, the edge device reads new monitoring data from the terminal device again and blocks them, and adds the blocks to the to-be-transmitted data set.

[0033] The beneficial effects of the technical solution of the present invention are:

[0034] According to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block, all blocks in the data set to be transmitted are clustered into several categories; the transmission probability of each category is obtained according to the compressibility coefficients and transmission priority of all blocks in each category; a category is randomly selected according to the transmission probability of all categories and recorded as the transmission category, and then only the blocks in the transmission category are transmitted each time. The present invention ensures that when all edge devices transmit data to the server, there will not be too serious network congestion, and avoids the situation where the same edge device occupies too many network resources.

[0035] Further, according to the validity of the monitoring data belonging to each block in each linkage data set, the transmission priority of the blocks in the category to be transmitted in each edge device is adjusted, and the transmission priority after adjustment makes the difference between fA and fB positively correlated with the difference between kA and kB. The present invention can ensure that the remaining monitoring data that has not been transmitted in the edge device (that is, the blocks in the category to be transmitted) can be transmitted or network resources can be allocated according to the demand of the monitoring data in the linkage data set on the server side when determining the transmission order or allocating network resources (that is, transmitting or allocating network resources according to the difference in the validity of the monitoring data), so that in the case of limited network resources, the linkage monitoring can be ensured to be carried out smoothly as much as possible, reducing the obvious delay phenomenon of the linkage monitoring and the problem of not being able to obtain the monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A structural diagram of an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation method, structure, characteristics and effects of the intelligent linkage monitoring system of ecological garden environment information based on Internet of Things technology proposed by the present invention are described in detail as follows in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0039] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0040] The specific scheme of the intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology provided by the present invention is described in detail below with reference to the accompanying drawings.

[0041] See also Figure 1 , which shows a structural diagram of an ecological garden environment information intelligent linkage monitoring system based on Internet of Things technology provided by an embodiment of the present invention, the system includes the following modules:

[0042] The data acquisition module is used to collect monitoring data output by the terminal device. The terminal device includes monitoring cameras and various sensor devices, such as temperature sensors, humidity sensors, and wind speed and wind force sensors for monitoring ambient temperature, humidity, and wind speed and force, turbidity sensors for monitoring water quality, VOCs sensors for monitoring VOCs in the air, and microphone devices for monitoring vibration or noise and other sounds; it also includes other terminal devices, such as robots and drones for inspection, and terminal devices for user login and interaction.

[0043] There are many terminal devices, of different types, installed in different locations, and the formats of the output monitoring data are also different, including image data, sequence data, and text data. In this embodiment, the text data of non-numeric data is encoded into decimal numerical data using the UTF-8 encoding method, and the image data and sequence data are also represented by decimal numerical data to facilitate subsequent calculations. In addition, each terminal device needs to communicate with the server to transmit the monitoring data of each terminal device to the server.

[0044] The specific type, quantity and installation location of the terminal device are determined by the specific IoT scenario and are not specifically limited in this embodiment.

[0045] The edge computing module plays the role of data transfer and data computing. It includes multiple edge devices, each of which includes at least a data storage device for storing data and a processor for data computing.

[0046] Specifically, considering the large number of terminal devices, when a large number of terminal devices communicate directly with the server, the server needs to access multiple terminal devices at the same time, resulting in the need to pay a large amount of network resources, such as more communication ports and network frequency bands, and sufficient network bandwidth, while network resources in the Internet of Things are very limited. In this embodiment, several terminal devices are connected to an edge device, and the monitoring data of multiple terminal devices are transmitted to the edge device. The edge device summarizes and calculates the received monitoring data for subsequent transmission to the server.

[0047] In this embodiment, a large amount of monitoring data of terminal devices is first aggregated and then sent to the server through multiple edge devices, which further saves network resources. In this embodiment, the terminal device uses a WIFI network to communicate with the edge device. In other embodiments, a network cable can also be used to achieve communication between the terminal device and the edge device. In addition, the terminal device connected to each edge device is determined by the specific Internet of Things scenario. For example, in this embodiment, each edge device is connected to at least 4 surveillance cameras. In other embodiments, each edge device can be connected to other numbers and types of terminal devices.

[0048] The data transmission module is used to realize the communication between each edge device and the server. Specifically, the monitoring data summarized by each edge device is transmitted to the server. In this embodiment, each edge device communicates with the server via a wireless network (such as a 5g network).

[0049] Considering that the number of edge devices is still relatively large, and network resources are also limited, for example, the number of communication frequency bands is far less than the number of edge devices, or the communication bandwidth has a certain upper limit, it is impossible to transmit all the monitoring data summarized by all edge devices to the server at the same time. In this embodiment, the monitoring data in each edge device is divided into blocks, and each edge device transmits each block to the server with a certain transmission probability.

[0050] The transmission priority allocation module runs on the server. After receiving the blocks of monitoring data transmitted by all edge devices, the blocks are merged into complete monitoring data, and then different monitoring data are used for linkage monitoring. For example, the monitoring data output by monitoring equipment, VOCs monitoring equipment and temperature, wind speed and wind speed sensors at different locations are used to monitor the air quality, pollution sources or traffic exhaust emissions in and around the park; for example, microphone equipment, monitoring equipment, inspection robots or drones are used to monitor the ecological environment of the park. The above are just some example descriptions, and the specific linkage monitoring process is determined by the Internet of Things, which will not be described in detail in this embodiment.

[0051] However, when the blocks received by the server cannot be merged into complete monitoring data, for example, due to limited network resources, some blocks of monitoring data have not yet been transmitted to the server, this may cause the server to enter a thread blocking state waiting for data transmission, affecting or blocking the calculation and analysis process of other data; the server may also exit the relevant process and end the linkage monitoring process with other data ahead of schedule, ultimately resulting in abnormalities or delays in the linkage monitoring results on the server side; in summary, after the edge device transmits the monitoring data in blocks, the server will still be unable to perform correct and smooth linkage monitoring due to network resource limitations.

[0052] Specifically, in the edge computing module, the monitoring data collected by each edge device is obtained. These monitoring data need to be sent to the server for linkage monitoring and processing. When the amount of these monitoring data is large, if these monitoring data are to be transmitted to the server at one time, the edge device needs to maintain a long-term connection with the server, resulting in the edge device occupying more communication resources, and other edge devices may not be able to seize communication resources and communicate with the server, which in turn causes the server to be unable to read the required monitoring data in time and perform linkage monitoring. Therefore, this embodiment uses each edge device to divide the monitoring data therein into blocks.

[0053] As an example, the monitoring data of each edge device is divided into blocks, including the following steps:

[0054] Flatten the monitoring data in each edge device into a one-dimensional sequence. If the monitoring data is one-dimensional, then there is no need to flatten it (for example, the monitoring data output by the sensor). If the monitoring data is two-dimensional, such as image-type monitoring data, then flatten it into a one-dimensional sequence from top to bottom and from left to right. Divide the one-dimensional sequence into several subsequences, and the amount of data in each subsequence is N. Each subsequence is regarded as a block.

[0055] When the data is not evenly divided, the last remaining subsequence does not require the data size to be N.

[0056] In this embodiment, N=512KB is used for description. In other embodiments, N may be set to other values, which are not specifically limited in this embodiment. In addition, if the amount of some monitoring data is less than N, the monitoring data is treated as a separate block.

[0057] So far, each monitoring data corresponds to one or more blocks.

[0058] Furthermore, this embodiment randomly selects a block from each monitoring data, and the blocks selected from all monitoring data on each edge device constitute a data set to be transmitted, and the blocks in the data set to be transmitted are the data that the edge device needs to transmit to the server. The purpose of this process is to transmit only one block of each monitoring data at a time, on the one hand to avoid excessive network resource occupation when transmitting the entire monitoring data, and on the other hand to enable the monitoring data in all edge devices to be transmitted to the server, so that the server can subsequently use different terminal devices for linkage monitoring.

[0059] Furthermore, for any two blocks in the data set to be transmitted, the compressibility coefficients of the two blocks are obtained. The compressibility coefficient indicates the degree to which the two blocks can be compressed when they are compressed and transmitted together. The larger the value, the more the two blocks need to be compressed and transmitted together, thereby reducing the amount of data during transmission, speeding up the transmission speed, and reducing the occupation of network resources. The smaller the value, the less compression the two blocks will have if they are compressed and transmitted together, which is not conducive to reducing the occupation of network resources during transmission.

[0060] As an example, the compressibility coefficients of any two blocks are obtained by:

[0061] Splice any two blocks together to form a sequence, obtain the data volume K0 of the sequence, encode and compress the sequence using the LZW encoding algorithm, and obtain a compression result. The data volume of the compression result is recorded as K1, and the ratio of (K0-K1) to K0 is used as the compressibility coefficient of any two blocks. It should be noted that there are two splicing methods when splicing two blocks together. One splicing method is to put one block in front and the other block in the back, and then splice the two blocks together. Another splicing method is to put one of the blocks in the back and the other block in the front, and then splice the two blocks together. Each splicing method corresponds to a compressibility coefficient. This embodiment only retains the largest compressibility coefficient and the corresponding splicing method.

[0062] In addition, for the data set to be transmitted in each edge device, an initial transmission priority is assigned to each block in the data set to be transmitted. In this embodiment, the initial transmission priority of each block is the same, that is, assuming that there are n blocks in the data set to be transmitted, then the initial transmission priority of each block is 1 / n.

[0063] According to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block, all blocks in the data set to be transmitted are clustered into several categories, each category contains multiple blocks, and blocks in the same category have larger compressibility coefficients and transmission priorities.

[0064] As an example, according to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block, all blocks in the data set to be transmitted are clustered into several categories, including the following methods:

[0065] The average of the transmission priorities of any two blocks is recorded as the comprehensive transmission priority, and the product of the comprehensive transmission priority and the compressibility coefficient of any two blocks is recorded as the metric distance of any two blocks. According to the metric distance of any two blocks in the data set to be transmitted, the K-Means algorithm is used to cluster all the blocks in the data set to be transmitted, and the number of clusters is set to: one third of the number of all blocks in the data set to be transmitted (rounded up to retain the integer part). In other embodiments, the number of clusters can also be set to other values, which is not specifically limited in this embodiment.

[0066] Furthermore, it should be noted that in the data transmission module, when each edge device transmits data to the server, it only transmits all blocks in one category at a time, and all categories need to be transmitted to the server in multiple times to ensure that there will not be too serious network congestion when all edge devices transmit data to the server, and to avoid the situation where the same edge device occupies too many network resources.

[0067] Specifically, this embodiment obtains the transmission probability of each category according to the compressibility coefficient and transmission priority between all blocks in each category, and randomly selects a category according to the transmission probabilities of all categories, which is recorded as the transmission category; the category with a larger transmission probability has a greater possibility of being used as the transmission category; in other embodiments, the category with the largest transmission probability can also be used as the transmission category. Other categories other than the transmission category are recorded as categories to be transmitted.

[0068] Transfer chunks in the transfer category to the server.

[0069] The greater the transmission probability, the greater the transmission priority among all blocks in each category, and the greater the compressibility, the less network resources are occupied during transmission, and the more priority transmission is needed.

[0070] As an example, the transmission probability of each category is obtained according to the compressibility coefficient and transmission priority between all blocks in each category, including the following method:

[0071] The mean of the transmission priorities of all blocks in each category is used as the initial transmission probability of each category. The initial transmission probabilities of all categories in each edge device are normalized, and the normalized initial transmission probabilities are used as the transmission probability of each category. This embodiment uses the softmax algorithm for normalization so that the sum of the transmission probabilities of all categories in each edge device is equal to 1.0.

[0072] As another example, the transmission probability of each category is obtained according to the compressibility coefficient and the transmission priority between all the blocks in each category, including the following method:

[0073] Among all the blocks in each category, obtain the two blocks with the largest metric distance, and these two blocks are recorded as a compression group; splice these two blocks together and then compress them using the LZW algorithm to obtain a compression result; among all the remaining blocks, obtain the two blocks with the largest metric distance, and these two blocks are also recorded as a compression group; splice these two blocks together and then compress them using the LZW algorithm to obtain a compression result; among all the remaining blocks, obtain the two blocks with the largest metric distance again, and these two blocks are again recorded as a compression group; splice these two blocks together and then compress them using the LZW algorithm to obtain a compression result; and so on, stop when there are no remaining blocks or only one block left; in the order of obtaining the compression results, splice all the obtained compression results together from beginning to end (the remaining block is spliced ​​at the end), and then use the LZW algorithm to compress them again to obtain the final compression result of each category.

[0074] In other embodiments, the LZW algorithm may be replaced by a Huffman coding algorithm.

[0075] The multiple compression groups obtained in the above process are recorded as the compression group sequence of each category, and the average of the transmission priorities of all blocks in the compression group sequence is recorded as the initial transmission probability of each category. Then, the initial transmission probabilities of all categories in each edge device are normalized to obtain the transmission probability of each category.

[0076] The blocks in the transmission category are transmitted to the server, including the method of transmitting the final compressed result in the transmission category to the server.

[0077] It should be noted that, due to limited network resources, such as fewer frequency bands, even if each edge device transmits only one category, there will be the following problem: when all edge devices transmit together, some edges may not be able to seize the appropriate frequency band for transmission. At this time, this embodiment first sends the transmission probability of the transmission category of each edge device to the server in sequence. It should be noted that the transmission probability of the transmission category is a numerical value, and its data volume is small. Therefore, only sending the transmission probability of the transmission category of each edge device does not occupy too many network resources. After the server receives the transmission probability of the transmission category of all edge devices, these transmission probabilities are softmax normalized to obtain the transmission probability of each edge device. Assuming that there are only N0 available frequency bands, then N0 edge devices are randomly selected according to the transmission probability of the edge device to seize these N0 available frequency bands for transmission.

[0078] In the transmission priority allocation module, it is considered that the server of this embodiment needs to perform linkage monitoring through a large number of terminal devices, such as monitoring equipment at different locations, VOCs monitoring equipment, and environmental monitoring sensors such as temperature, wind speed, etc. to monitor the air quality, pollution sources, or traffic exhaust emissions in and around the park; another example is the use of microphone equipment, monitoring equipment, inspection robots, or drones to monitor the ecological environment of the park. In summary, in order to achieve linkage monitoring, the monitoring data of multiple terminal devices need to be analyzed together at the same time.

[0079] This embodiment uses the monitoring data with linkage monitoring as a linkage data set, that is, the server needs to obtain all the monitoring data in a linkage data set at the same time before completing a monitoring. For example, the monitoring data output by monitoring equipment, VOCs monitoring equipment, temperature, wind speed and other environmental monitoring sensors at different locations are used as a linkage data set for linkage monitoring of air quality; the monitoring data output by microphone equipment, monitoring equipment, inspection robots, etc. are used as another linkage data set for linkage monitoring of the ecological environment.

[0080] If the monitoring data in a linkage data set is missing or incomplete, the server will enter a thread blocking state or directly exit the corresponding program process, causing the server to consume computing resources or network resources without obtaining the expected monitoring results, or the monitoring results will be delayed. Especially when there are many terminal devices and limited network resources, it is difficult for the server to use different terminal devices for smooth and fast linkage monitoring.

[0081] In this embodiment, the blocks on each monitoring data in each linkage data set are recorded as the blocks in each linkage data set. After receiving the blocks of all edge devices, the server obtains the validity of the monitoring data to which each block in each linkage data set belongs.

[0082] The validity of monitoring data indicates the server's demand for monitoring data in the linkage data set. The greater the validity of monitoring data, the more all blocks of monitoring data need to occupy network resources in a timely manner and be transmitted to the server in a timely manner to achieve linkage monitoring. The smaller the validity, the less likely the linkage data set where the monitoring data is located can achieve linkage monitoring quickly. At this time, the monitoring data does not need to occupy network resources, so that the monitoring data in other linkage data sets can be transmitted in a timely manner and linked monitoring can be performed.

[0083] As an example, the validity of the monitoring data belonging to each block in each linkage data set is obtained, including the specific method as follows:

[0084] In the transmission priority allocation module on the server side, the server has received the blocks transmitted from the edge device. For all the monitoring data in each linkage data set, all the blocks belonging to the same monitoring data are obtained. The ratio of the data volume of all the blocks belonging to the same monitoring data to the data volume of the monitoring data is recorded as the completeness of each monitoring data.

[0085] The total amount of block data contained in the monitoring data in each linkage data set and not received by the server is obtained. The ratio of the total amount of data to the data transmission speed is recorded as the data completion pressure A1 of each linkage data set. The larger the value, the more block data remaining in each linkage data set that has not been received by the server, and the greater the transmission pressure.

[0086] In this embodiment, the data transmission speed refers to the average value of the network upload speed in the last 30 seconds.

[0087] The mean of the completeness of all monitoring data in the linkage data set is obtained, recorded as A2, and the ratio of A2 to A1+1 is recorded as the effectiveness of each linkage data set. The greater the effectiveness of the linkage data set, the more complete the data in the linkage data set is and the less pressure is placed on the transmission of missing data. Adding 1 to the formula A1+1 is to avoid the situation where the denominator is zero.

[0088] One piece of monitoring data may be in different linkage data sets. All linkage data sets to which each piece of monitoring data belongs are obtained. Among the validity of all linkage data sets, the maximum validity is taken as the validity of each piece of monitoring data.

[0089] It should be noted that when each edge device communicates with the server, in addition to the blocks in the transmission category, it also needs to transmit additional data, including: the compressibility coefficient between any two blocks in the transmission category of each edge device, the transmission priority of each block, and the monitoring data to which each block belongs. Since these additional data do not include the block data itself, the amount of these data is relatively small compared to the amount of data in the transmission category, and will not significantly occupy network resources.

[0090] It should also be noted that when some edge devices fail to seize network resources (for example, when they are not allocated a network frequency band for communication), the block data in the transmission category of the edge device will not be transmitted, and the corresponding additional data will not be transmitted to the server.

[0091] After the server receives the blocks transmitted by the edge device (including additional data), it adjusts the transmission priority of the blocks of the category to be transmitted in each edge device according to the validity of the monitoring data to which the blocks belong. For the blocks of the category to be transmitted in each edge device, these blocks are used as the data set to be transmitted. According to the compressibility coefficient of any two blocks in the data set to be transmitted and the adjusted transmission priority of each block, all the blocks in the data set to be transmitted are clustered into several new categories again. In all new categories of all edge devices, any two different blocks are denoted as A and B, and the transmission probability of obtaining the new category to which A belongs is denoted as fA, and the transmission probability of obtaining the new category to which B belongs is denoted as fB. The validity of the monitoring data to which A belongs is denoted as kA, and the validity of the monitoring data to which B belongs is denoted as kB. The adjusted transmission priority makes the difference between fA and fB positively correlated with the difference between kA and kB.

[0092] The transmission priority after adjustment in the above process makes the difference between fA and fB positively correlated with the difference between kA and kB, which can ensure that the remaining monitoring data that has not been transmitted in the edge device (that is, the blocks in the category to be transmitted) can be transmitted or allocated network resources according to the demand for monitoring data in the linkage data set on the server when determining the transmission order or allocating network resources (that is, transmit or allocate network resources according to the difference in the validity of the monitoring data). This ensures that the linkage monitoring can be carried out smoothly as much as possible when network resources are limited, reducing the obvious delay in the linkage monitoring and the problem of not being able to obtain monitoring results.

[0093] As an example, the transmission priority after adjustment is such that the difference between fA and fB is positively correlated with the difference between kA and kB, including:

[0094] make .

[0095] when When the minimum value is taken, the transmission priority after adjustment can be made such that the difference between fA and fB is positively correlated with the difference between kA and kB.

[0096] In other embodiments, Replace with .

[0097] Furthermore, for the new category to which A belongs, a compression group sequence of the new category is obtained. For each compression group in the compression group sequence, the mean of the effectiveness of the monitoring data to which the two blocks in the compression group belong respectively is obtained. The mean of the effectiveness corresponding to each compression group is normalized (normalized using softmax) to obtain the compression attention of each compression group. The compression attention of each compression group is used as a weight, and the compressibility coefficients of all compression groups in the compression group sequence are weighted and summed to obtain the compression index of the new category to which A belongs, denoted as mA. The larger the compression index, the more the new category to which A belongs can meet the server's urgent demand for monitoring data in the linkage data set and also has greater compressibility.

[0098] Similarly, the compression index of the new category to which B belongs is obtained, which is recorded as mB; the specific method only requires replacing A with B in the above-mentioned method.

[0099] For all new categories of blocks in all edge devices, the set of these blocks is denoted as S; , ;

[0100] make .

[0101] When each block in S corresponds to a different transmission priority Taking different values, when F is the smallest, the transmission priority corresponding to each block in S is used as the transmission priority after adjustment. This embodiment uses a simulated annealing algorithm to obtain the minimum value of F.

[0102] In the above formula, when the compression index of the new category to which A belongs is greater than the compression index of the new category to which B belongs, that is, When the value is small, compared with B and for A, the block compressibility of the new category to which A belongs is relatively high, and it does not occupy too many network resources. At this time, it is not necessary to strictly transmit according to the demand of the monitoring data in the server-side linkage data set (that is, there is no need to pay attention to the condition that the difference between fA and fB is positively correlated with the difference between kA and kB), and the server can also smoothly perform linkage monitoring; on the contrary, when the compression index of the new category to which A belongs is less than or equal to the compression index of the new category to which B belongs, that is, When the value is large, compared with B and for A, the compressibility of the new category of blocks to which A belongs is relatively low. At this time, the blocks in A occupy more network resources during transmission. At this time, in order to be able to transmit according to the demand of the monitoring data in the linkage data set on the server side, so that the server side can smoothly perform linkage monitoring, it is necessary to make the difference between fA and fB as positively correlated as possible with the difference between kA and kB, so that the data that the server side urgently needs for linkage monitoring (that is, the blocks of monitoring data with high effectiveness) are transmitted to the server first, and the data that is not urgently needed for linkage monitoring (that is, the blocks of monitoring data with low effectiveness) does not have to occupy limited network resources compared with server data.

[0103] The above process is executed on the server side. The server adjusts the transmission priority of each block in the transmission category according to the validity of the monitoring data in the linkage data set. The server sends the adjusted transmission priority to the blocks of each edge device, and all additional data on the server side is deleted.

[0104] Then the remaining blocks in each edge device (that is, all blocks in the category to be transmitted) constitute the data set to be transmitted again. According to the compressibility coefficient of any two blocks in the data set to be transmitted and the adjusted transmission priority of each block, all blocks in the data set to be transmitted are clustered into several categories again, and the transmission category is regained. Then the data transmission module transmits the transmission category of each edge device to the server again. After receiving the blocks, the server uses the transmission priority allocation module to re-assign transmission priorities to the blocks in the category to be transmitted of the edge device. And so on, all monitoring data blocks of the edge device are continuously transmitted to the server, so that when network resources are limited, network resources can be reasonably allocated, so that the linkage monitoring of the server can proceed smoothly, and the delay phenomenon during linkage monitoring or the problem of not being able to obtain linkage monitoring results can be minimized as much as possible.

[0105] It should be noted that after all the blocks in the data set to be transmitted are transmitted, a block is randomly selected from all the monitoring data of the edge device to form the data set to be transmitted. In particular, when there is only one block in the data set to be transmitted, the block is treated as a separate category. There is a block with a value of 0 in the category by default, and its initial transmission priority is set to 1 / 2. After all the blocks of a certain monitoring data are transmitted, the edge device obtains new monitoring data from the terminal device again and divides it into blocks, and adds the randomly selected block to the data set to be transmitted.

[0106] In addition, it takes a certain amount of calculation time for the server to obtain the adjusted transmission priority. If the adjusted transmission priority is not calculated during this period, the original transmission priority is kept unchanged and data transmission is performed according to the above method.

[0107] As an example, when the server obtains the adjusted transmission priority, a method for quickly obtaining the adjusted transmission priority is: limit the value range of the transmission priority within a preset interval, such as the interval (0, 2), or limit the value range of the transmission priority to several values, such as 0.05, 0.1, 0.15, ..., 2.00, so that the minimum value of F can be quickly obtained, but the minimum value at this time is not the most accurate, but the calculation speed is fast, and it can still ensure the smooth linkage monitoring of the server.

[0108] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology, characterized in that: The system includes the following modules: Data acquisition module, used to collect monitoring data output by terminal equipment; The edge computing module includes multiple edge devices, each edge device reads the monitoring data of several terminal devices, divides each monitoring data into blocks, and each block has a transmission priority; any block of all monitoring data constitutes a data set to be transmitted; according to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block, all blocks in the data set to be transmitted are clustered into several categories; according to the compressibility coefficients and transmission priorities of all blocks in each category, the transmission probability of each category is obtained; according to the transmission probabilities of all categories, a category is randomly selected as the transmission category, and other categories outside the transmission category are recorded as the categories to be transmitted; A data transmission module, used to transmit the blocks of the transmission category in each edge device to the server; The transmission priority allocation module runs on the server and is used to treat the monitoring data with linkage monitoring function as a linkage data set; after receiving the blocks of all edge devices, the server adjusts the transmission priority of the blocks in the category to be transmitted in each edge device according to the validity of the monitoring data belonging to each block in each linkage data set, and re-cluster all the blocks in the category to be transmitted into several new categories according to the compressibility coefficient of any two blocks in all the blocks in the category to be transmitted and the adjusted transmission priority of each block; Among all new categories of blocks of all edge devices, any two different blocks are denoted as A and B, the transmission probability of the new categories to which A and B belong is denoted as fA and fB, and the validity of the monitoring data to which A and B belong is denoted as kA and kB. The transmission priority after adjustment makes the difference between fA and fB positively correlated with the difference between kA and kB. The specific steps for obtaining the compressible coefficients of any two blocks are as follows: Splice any two blocks together to obtain a splicing result, obtain the data volume K0 of the splicing result, encode and compress the splicing result to obtain a compressed result, the data volume of the compressed result is recorded as K1, and the ratio of (K0-K1) to K0 is taken as the compressibility coefficient of any two blocks; The specific steps for obtaining the validity of the monitoring data belonging to each block in each linkage data set are as follows: In the transmission priority allocation module on the server side, for all monitoring data in each linkage data set, all blocks belonging to the same monitoring data are obtained, and the ratio of the data volume of all blocks belonging to the same monitoring data to the data volume of the monitoring data is recorded as the integrity of each monitoring data; The total amount of data in the blocks included in the monitoring data in each linkage data set and not received by the server is obtained, and the ratio of the total amount of data to the data transmission speed is recorded as the data completion pressure A1 of each linkage data set; The mean of the completeness of all monitoring data in the linkage data set is obtained, recorded as A2, and the ratio of A2 to A1+1 is recorded as the validity of each linkage data set; all linkage data sets to which each monitoring data belongs are obtained, and the maximum validity among the availabilities of all the linkage data sets is taken as the validity of each monitoring data.

2. According to claim 1, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: The method of clustering all the blocks in the data set to be transmitted into several categories according to the compressibility coefficients of any two blocks in the data set to be transmitted and the transmission priority of each block includes the following specific steps: The average of the transmission priorities of any two blocks is recorded as the comprehensive transmission priority, and the product of the comprehensive transmission priority and the compressibility coefficient of any two blocks is recorded as the metric distance of any two blocks; According to the metric distance between any two blocks in the data set to be transmitted, the K-Means algorithm is used to cluster all the blocks in the data set to be transmitted to obtain several categories.

3. According to claim 2, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: The specific steps of obtaining the transmission probability of each category according to the compressibility coefficients and transmission priorities of all blocks in each category are as follows: Among all the blocks in each category, two blocks with the largest metric distance are obtained and recorded as a compression group; the two blocks with the largest metric distance are spliced ​​together and compressed to obtain a compression result; Among all the remaining blocks, two blocks with the largest measured distance are obtained again and recorded as a compression group again; the two blocks with the largest distance are spliced ​​together again and compressed to obtain a compression result; And so on, until there are no remaining blocks or only one block is left; according to the order in which the compression results are obtained, all the obtained compression groups are recorded as the compression group sequence of each category; The mean of the transmission priorities of all chunks in the compressed group sequence is recorded as the initial transmission probability of each category; The initial transmission probabilities of all categories are normalized to obtain the transmission probability of each category.

4. According to claim 3, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: The transmission priority after adjustment is such that the difference between fA and fB is positively correlated with the difference between kA and kB, and the specific steps are as follows: The set of blocks in all new categories of all edge devices is denoted as S; , ; make ; mA represents the compression index of the new category to which A belongs, and mB represents the compression index of the new category to which B belongs; the compression index of the new category is obtained according to the compression group sequence of the new category; The transmission priority corresponding to when F is minimum is used as the adjusted transmission priority of each block in S.

5. According to claim 4, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: The specific steps of obtaining the compression index of the new category to which A belongs and the compression index of the new category to which B belongs are as follows: For the new category to which any block in A or B belongs, a compression group sequence of the new category is obtained. For each compression group in the compression group sequence, the compressibility coefficients of the two blocks in each compression group are simply recorded as the compressibility coefficient of each compression group. The mean of the effectiveness of the monitoring data to which the two blocks in the compression group belong respectively is obtained, and the mean of the effectiveness corresponding to each compression group is normalized to obtain the compression attention of each compression group. The compression attention of each compression group is used as a weight, and the compressibility coefficients of all compression groups in the compression group sequence are weighted and summed to obtain the compression index of the new category to which any block in A or B belongs.

6. According to claim 3, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: The specific steps of transmitting the blocks of the transmission category in each edge device to the server include the following: According to the order in which the compression results are obtained, all the compression results are concatenated together and compressed again to obtain the final compression result of each category, and the final compression result is transmitted to the server.

7. According to claim 1, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: The specific steps of dividing each monitoring data into blocks are as follows: The monitoring data in each edge device is flattened into a one-dimensional sequence; the one-dimensional sequence is equally divided into several subsequences, and the data volume of each subsequence is N; each subsequence is regarded as a block, and N is a preset value.

8. According to claim 1, an intelligent linkage monitoring system for ecological garden environment information based on Internet of Things technology is characterized in that: After the transmission priority allocation module adjusts the transmission priority of the blocks in the to-be-transmitted category in each edge device, the specific steps included are as follows: All the blocks in the to-be-transmitted category in each edge device constitute the to-be-transmitted data set again. According to the compressibility coefficient of any two blocks in the to-be-transmitted data set and the adjusted transmission priority of each block, all the blocks in the to-be-transmitted data set are clustered into several categories again, and the transmission category and the to-be-transmitted category are re-obtained. The data transmission module transmits the transmission category of each edge device to the server again. After receiving the blocks, the server uses the transmission priority allocation module to re-allocate the transmission priority to the blocks in the to-be-transmitted category of the edge device. By analogy, all monitoring data blocks of the edge device are continuously transmitted to the server; when all the monitoring data blocks are transmitted to the server, the edge device reads new monitoring data from the terminal device again and divides them into blocks, and adds the blocks to the data set to be transmitted.

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