Multi-data acquisition and image transmission method and system based on wireless network

Abstract

The present invention discloses a multi-data acquisition and image transmission method and system based on a wireless network, which relates to the field of image data acquisition and transmission technology, including: building a wireless network architecture, and determining a central node, an acquisition node and an edge node, using the acquisition node to obtain real-time image data, determining the position information of the acquisition node based on application scenario information, then determining the edge dynamic point based on a three-dimensional space coordinate system, and determining the coordinates of the edge node through the edge dynamic point and the coordinate point of the acquisition device, and then determining the coordinates of the central node in the three-dimensional space coordinate system through the edge node basic coordinates and transmission quality index of each edge node, so as to realize the determination of suitable acquisition nodes, edge nodes and central nodes in areas with numerous network devices and complex terrain, and avoid the edge node transmitting the image data to the central node after receiving the image data from the acquisition node and being affected by factors such as the environment.

Description

Technical Field

[0001] The present invention relates to the technical field of image data acquisition and transmission, and in particular to a method and system for multi-data acquisition and image transmission based on a wireless network. Background Art

[0002] Wireless network-based multi-data acquisition and image transmission technology leverages wireless communication to achieve real-time acquisition, processing, and remote transmission of multiple data sources, breaking the limitations of traditional wired networks and enhancing system flexibility and adaptability. This technology has broad applications in remote monitoring, intelligent transportation, environmental monitoring, and other fields. Through efficient data and image transmission, it improves response speed and data update frequency, reduces the need for manual intervention, and promotes the automation and intelligent development of systems. Its application not only promotes the popularization of IoT technology but also drives innovation and technological advancement across various industries, possessing significant social and economic value.

[0003] Existing wireless network-based multi-data acquisition and image transmission methods and systems are difficult to implement in the case of a large number of network devices.

[0004] In areas with complex terrain, it is difficult for the wireless network architecture to determine suitable edge nodes and central nodes because the collection devices and edge devices are easily affected by the environment. At the same time, because different collection nodes are equipped with different collection devices, it is difficult to ensure time synchronization of the image data transmitted to the edge nodes, which affects the efficiency of subsequent image processing. Therefore, it is necessary to provide a multi-data collection and image transmission method and system based on a wireless network to solve the above-mentioned problems. Summary of the Invention

[0005] In order to solve the above technical problems, a multi-data acquisition and image transmission method and system based on a wireless network are provided. This technical solution solves the existing multi-data acquisition and image transmission method and system based on a wireless network proposed in the above background technology. In areas with numerous network devices and complex terrain, the acquisition devices and edge devices are easily affected by the environment, which makes it difficult for the wireless network architecture to determine suitable edge nodes and central nodes. At the same time, since different acquisition nodes are equipped with different acquisition devices, it is difficult to ensure time synchronization of the image data transmitted to the edge nodes, affecting the efficiency of subsequent image processing.

[0006] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0007] The multi-data collection and image transmission method based on wireless network includes:

[0008] Build wireless network architecture and determine central nodes, collection nodes, and edge nodes;

[0009] Use acquisition nodes to obtain real-time image data, and use edge nodes to obtain real-time time information;

[0010] Based on the acquisition nodes, edge nodes and real-time time information, clock synchronization is performed on the real-time acquired image data to obtain synchronized image data;

[0011] Transmitting synchronized image data to the central node via the edge node;

[0012] Performing wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data;

[0013] Obtain the data attribute matrix of the classified image data and construct a data attribute pie chart based on the data attribute matrix;

[0014] Based on the data attribute pie chart, the image transmission parameters are determined, and the classified image data is transmitted to the cloud platform for storage.

[0015] In an optional embodiment, the step of constructing a wireless network architecture and determining a central node, a collection node, and an edge node specifically includes:

[0016] Obtain application scenario information, and determine the location information of the collection node based on the application scenario information;

[0017] According to the location information of the collection node, the environmental information of the collection node is obtained, and the corresponding collection device is set and the type information of the collection device is obtained;

[0018] Classify the collection devices based on their type information, and obtain location information of the same type of collection devices respectively;

[0019] Determine the maximum distance information of the collection device using the location information of the same type of collection device;

[0020] Determine the farthest distance line segment using the farthest distance information of the acquisition device, and construct a three-dimensional space coordinate system with the center point of the farthest distance line segment as the origin;

[0021] Determine the edge dynamic points based on the three-dimensional space coordinate system;

[0022] Determine the coordinate points of the same type of acquisition devices in a three-dimensional space coordinate system based on the position information of the same type of acquisition devices;

[0023] Connect the edge dynamic points with the coordinate points of the same type of acquisition devices in the three-dimensional space coordinate system to obtain edge dynamic line segments;

[0024] The length values ​​of the edge dynamic line segments corresponding to the same type of acquisition devices are summed to obtain the edge node dynamic decision value;

[0025] The coordinates of the edge dynamic point when the edge node dynamic decision value is the minimum are used as the coordinates of the edge node;

[0026] The central node is determined based on the environmental information of the edge nodes and collection nodes corresponding to each type of collection device.

[0027] In an optional embodiment, determining the central node based on the environmental information of the edge nodes and collection nodes corresponding to each type of collection device specifically includes:

[0028] Based on the three-dimensional space coordinate system, the coordinates of the edge nodes corresponding to each type of acquisition device are determined as the basic coordinates of the edge nodes;

[0029] Using the environmental information of the collection node, determine the temperature information, humidity information, electromagnetic interference information, airflow information, vibration information and noise information of the collection node corresponding to the same type of collection device;

[0030] Obtaining the collection quality influence coefficient corresponding to the collection node based on the temperature information, humidity information, electromagnetic interference information, airflow information, vibration information, and noise information of the collection node corresponding to the same type of collection device;

[0031] determining specification information of each type of collection device based on the type information of the collection device;

[0032] Obtaining the collection quality index of the collection node based on the type information, specification information and collection quality impact coefficient of the collection device;

[0033] The collection nodes are graded based on the collection quality index;

[0034] Perform correlation analysis on the hierarchically divided collection nodes and edge nodes, and set up multi-level edge devices on the edge nodes;

[0035] Obtaining the operating status information and multi-level environment information of the multi-level edge devices set for each edge node, and obtaining the operating status quality index corresponding to the multi-level edge devices set for each edge node;

[0036] Obtaining a transmission quality index for each edge node based on the operating status quality index and multi-level environment information corresponding to the multi-level edge devices set for each edge node;

[0037] The coordinates of the central node in the three-dimensional space coordinate system are determined by the edge node basic coordinates and the transmission quality index of each edge node.

[0038] In an optional embodiment, performing clock synchronization on the real-time collected image data based on the collection node, the edge node and the real-time time information to obtain the synchronized image data specifically includes:

[0039] Determine the level information of the acquisition node and extract the timestamp information in the real-time acquisition image data transmitted by the acquisition node through the edge node;

[0040] The edge node determines whether the timestamp information is empty, determines the timestamp transmission non-empty rate of the same-level collection node, and sets the timestamp transmission non-empty rate threshold based on the edge node;

[0041] If the timestamp transmission non-empty rate of the acquisition node at the same level is greater than or equal to the timestamp transmission non-empty rate threshold, then the standard time information of the real-time acquisition image data is determined based on the timestamp information and real-time time information of the acquisition node at the same level;

[0042] If the timestamp transmission non-empty rate of the same-level acquisition nodes is less than the timestamp transmission non-empty rate threshold, the standard time information of the real-time acquisition image data is determined based on the real-time time information.

[0043] In an optional embodiment, transmitting the synchronized image data to the central node through the edge node specifically includes:

[0044] Determine the central node with which the edge nodes interact, and generate a pre-shared key by combining the edge nodes and the central node;

[0045] Based on the pre-shared key, the central node determines whether to allow the edge node to transmit images. If not, the acquisition node continues to collect real-time images. If yes, the transmission quality threshold is set based on the edge node's transmission quality index.

[0046] Setting data processing information of the edge node for the synchronous image data according to the transmission quality index and the transmission quality threshold;

[0047] Based on the data processing information and the pre-shared key, the synchronized image data of the edge node is transmitted to the central node.

[0048] In an optional embodiment, performing wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data specifically includes:

[0049] Determine the standard time information of the synchronized image data based on the standard time information of the real-time collected image data; construct a time wheel based on the standard time information to classify the synchronized image data according to time periods;

[0050] Extract the feature information of the synchronized image data and construct features based on the feature information of the synchronized image data

[0051] Roulette, classifying the synchronized image data after time roulette classification according to image features;

[0052] Determine the task priority index based on the edge node corresponding to the synchronized image data, and construct a task priority wheel to classify the synchronized image data after feature wheel classification according to the task priority;

[0053] Data processing is performed on the synchronous image data classified by the completion time wheel, the feature wheel, and the task priority wheel to obtain classified image data.

[0054] In an optional embodiment, determining image transmission parameters based on the data attribute pie chart and transmitting the classified image data to the cloud platform for storage specifically includes:

[0055] According to the data attribute pie chart, determine the bandwidth requirement information, data compression information, transmission protocol information, transmission frequency information and transmission encryption information of the image transmission;

[0056] Determine image transmission parameters based on image transmission bandwidth requirement information, data compression information, transmission protocol information, transmission frequency information, and transmission encryption information;

[0057] Through the image transmission parameters, the classified image data are sequentially transmitted to the cloud platform for storage.

[0058] Furthermore, a wireless network-based multi-data acquisition and image transmission system is proposed, which is used to implement any of the above transmission methods, including:

[0059] An edge processing module, which is used to acquire real-time collected image data using an acquisition node, and to acquire real-time time information using the edge node. Based on the acquisition node, the edge node, and the real-time time information, the module is used to perform clock synchronization on the real-time collected image data to obtain synchronized image data, and transmit the synchronized image data to the central node via the edge node.

[0060] A central management module, the central management module is used to synchronize the clock of the real-time collected image data based on the collection nodes, edge nodes and real-time time information to obtain synchronized image data;

[0061] The cloud platform module is used to monitor and manage the cloud platform, and is also used to build a wireless network architecture, determine the central node, collection node and edge node, determine the central node for edge node interaction, and generate a pre-shared key in combination with the edge node and the central node.

[0062] In an optional embodiment, the central management module includes:

[0063] A central receiving unit, configured to receive data and information transmitted from the edge processing module;

[0064] a classification unit, the classification unit being configured to perform wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data;

[0065] The data sending unit is used to obtain a data attribute matrix of the classified image data, and construct a data attribute pie chart based on the data attribute matrix, determine the image transmission parameters based on the data attribute pie chart, and transmit the classified image data to the cloud platform for storage.

[0066] In an optional embodiment, the edge processing module includes:

[0067] An acquisition unit, configured to acquire real-time image data using an acquisition node and acquire real-time time information using an edge node;

[0068] A data processing unit, configured to perform clock synchronization on real-time collected image data based on the collection nodes, edge nodes, and real-time time information to obtain synchronized image data;

[0069] A transmission unit is used to transmit the synchronous image data to the central node through the edge node.

[0070] Compared with the prior art, the present invention has the following beneficial effects:

[0071] In the multi-data acquisition and image transmission method and system based on a wireless network proposed in this solution, the location information of the acquisition node is determined based on the application scenario information, and then the edge dynamic point is determined based on the three-dimensional space coordinate system. The coordinates of the edge node are determined by the edge dynamic point and the coordinate point of the acquisition device. Then, the coordinates of the central node in the three-dimensional space coordinate system are determined by the edge node basic coordinates and transmission quality index of each edge node. This realizes the determination of suitable acquisition nodes, edge nodes and central nodes in areas with numerous network devices and complex terrain, and avoids the influence of environmental factors on the edge node when transmitting image data to the central node after receiving the image data from the acquisition node.

[0072] In the multi-data acquisition and image transmission method and system based on a wireless network proposed in this solution, the level information of the acquisition node is determined, and the timestamp information in the real-time acquired image data transmitted by the acquisition node is extracted through the edge node. Then, the edge node is used to determine whether the timestamp information is empty, and the timestamp transmission non-empty rate of the acquisition nodes of the same level is determined. A timestamp transmission non-empty rate threshold is set based on the edge node. Through the timestamp transmission non-empty rate threshold and the timestamp transmission non-empty rate, it is ensured that the image data transmitted from different acquisition nodes to the edge node maintains time synchronization, thereby improving the efficiency of subsequent image processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1Flowchart of the multi-data acquisition and image transmission method based on wireless network proposed by the present invention;

[0074] Figure 2 A flowchart of the construction of the wireless network architecture in the present invention;

[0075] Figure 3 This is a flow chart for determining the central node in the present invention;

[0076] Figure 4 This is a system framework diagram of the wireless network-based multi-data acquisition and image transmission system proposed by the present invention. DETAILED DESCRIPTION

[0077] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0078] Reference Figure 1 - Figure 4 As shown, the multi-data collection and image transmission method based on a wireless network includes:

[0079] Build wireless network architecture and determine central nodes, collection nodes, and edge nodes;

[0080] Use acquisition nodes to obtain real-time image data, and use edge nodes to obtain real-time time information;

[0081] Based on the acquisition nodes, edge nodes and real-time time information, clock synchronization is performed on the real-time acquired image data to obtain synchronized image data;

[0082] Transmitting synchronized image data to the central node via the edge node;

[0083] Performing wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data;

[0084] Obtain the data attribute matrix of the classified image data and construct a data attribute pie chart based on the data attribute matrix;

[0085] Based on the data attribute pie chart, the image transmission parameters are determined, and the classified image data is transmitted to the cloud platform for storage.

[0086] Specifically, the wireless network architecture is the overall structure and design module diagram of the multi-data acquisition and image transmission system built by the cloud platform module through various data and information, including the location information of the central node, acquisition node and edge node determined later. The acquisition node is responsible for collecting image data and sending the image data to the edge node. The edge node processes the image data and performs preprocessing, and passes important information to the central node, or makes local decisions. The central node conducts in-depth analysis and storage of all data, makes global decisions, and issues instructions to downstream nodes for in-depth analysis and storage to make global decisions.

[0087] Furthermore, the data attribute matrix of the classified image data is obtained, and a data attribute pie chart is constructed based on the data attribute matrix. The classified image data is loaded through common Python libraries such as PIL (Pillow) and torchvision.

[0088] Furthermore, a wireless network architecture is constructed and the central node, collection node, and edge node are determined, including:

[0089] Obtain application scenario information, and determine the location information of the collection node based on the application scenario information;

[0090] According to the location information of the collection node, the environmental information of the collection node is obtained, and the corresponding collection device is set and the type information of the collection device is obtained;

[0091] Classify the collection devices based on their type information, and obtain location information of the same type of collection devices respectively;

[0092] Determine the maximum distance information of the collection device using the location information of the same type of collection device;

[0093] Determine the farthest distance line segment using the farthest distance information of the acquisition device, and construct a three-dimensional space coordinate system with the center point of the farthest distance line segment as the origin;

[0094] Determine the edge dynamic points based on the three-dimensional space coordinate system;

[0095] Determine the coordinate points of the same type of acquisition devices in a three-dimensional space coordinate system based on the position information of the same type of acquisition devices;

[0096] Connect the edge dynamic points with the coordinate points of the same type of acquisition devices in the three-dimensional space coordinate system to obtain edge dynamic line segments;

[0097] The length values ​​of the edge dynamic line segments corresponding to the same type of acquisition devices are summed to obtain the edge node dynamic decision value;

[0098] The coordinates of the edge dynamic point when the edge node dynamic decision value is the minimum are used as the coordinates of the edge node;

[0099] The central node is determined based on the environmental information of the edge nodes and collection nodes corresponding to each type of collection device.

[0100] Specifically, based on the application scenario information, the location information of the collection node is determined. First, it is necessary to understand the environmental characteristics of the scene, such as terrain, buildings, obstacles, communication conditions, etc., and then clarify the type of application scenario, such as urban environment, indoor environment, agricultural monitoring, industrial environment, etc. Different types of scenarios have different impacts on the requirements and location of the collection nodes. Then determine the type of data that needs to be collected, such as temperature and humidity, gas concentration, light intensity, motion monitoring, etc. Different types of data collection requirements may have different requirements for the layout of sensors. At the same time, determine the area and range that each collection node needs to cover. Based on the three-dimensional space coordinate system, determine the edge dynamic point. The edge dynamic point is a dynamic coordinate set in the three-dimensional space coordinate system to determine the coordinates of the edge node.

[0101] Furthermore, the central node is determined based on the environmental information of the edge nodes and collection nodes corresponding to each type of collection device, specifically including:

[0102] Based on the three-dimensional space coordinate system, the coordinates of the edge nodes corresponding to each type of acquisition device are determined as the basic coordinates of the edge nodes;

[0103] Using the environmental information of the collection node, determine the temperature information, humidity information, electromagnetic interference information, airflow information, vibration information and noise information of the collection node corresponding to the same type of collection device;

[0104] Obtaining the collection quality influence coefficient corresponding to the collection node based on the temperature information, humidity information, electromagnetic interference information, airflow information, vibration information, and noise information of the collection node corresponding to the same type of collection device;

[0105] determining specification information of each type of collection device based on the type information of the collection device;

[0106] Obtaining the collection quality index of the collection node based on the type information, specification information and collection quality impact coefficient of the collection device;

[0107] The collection nodes are graded based on the collection quality index;

[0108] Perform correlation analysis on the hierarchically divided collection nodes and edge nodes, and set up multi-level edge devices on the edge nodes;

[0109] Obtaining the operating status information and multi-level environment information of the multi-level edge devices set for each edge node, and obtaining the operating status quality index corresponding to the multi-level edge devices set for each edge node;

[0110] Obtaining a transmission quality index of each edge node according to the operating status quality index and multi-level environment information corresponding to the multi-level edge devices set for each edge node;

[0111] The coordinates of the central node in the three-dimensional space coordinate system are determined by the edge node basic coordinates and the transmission quality index of each edge node.

[0112] Specifically, the collection quality index is an indicator that comprehensively measures the performance of collection nodes in multiple dimensions. The collection quality index is used to classify collection nodes. Different collection nodes are divided into different levels based on factors such as node performance, data quality, and stability, so as to optimize network resource management and improve data collection efficiency. Collection nodes with a collection quality index close to 1 are classified as high-quality nodes, indicating that the node performs very well in all aspects, with accurate data collection and stable communication, etc., and are suitable for tasks with extremely high data quality requirements. Collection nodes with a collection quality index between 0.5 and 0.8 are classified as medium-quality nodes, indicating that the node's performance is at a medium level and may be lacking in some aspects (such as slightly poor communication quality or low energy efficiency), and are suitable for tasks with general data quality requirements. Collection nodes with a collection quality index lower than 0.5 are classified as low-quality nodes, indicating that the node has problems in multiple aspects, such as inaccurate data collection, poor communication quality, etc., and are not suitable for high-precision or high-requirement tasks and may need to be replaced or optimized.

[0113] The calculation formula of the acquisition quality influence coefficient is:

[0114] ;

[0115] Where, is the collection quality influence coefficient, For the The influence function of the factors, For the The actual value of the factor, For the The weight of the factors, Indicates the The correction function related to environmental factors, is the strength coefficient;

[0116] The calculation formula of the acquisition quality index is:

[0117] ;

[0118] Where, is the collection quality index, is the collection quality influence coefficient, For the The type coefficient of the acquisition device at the moment, For the Specification factor of the acquisition device at the time, For the Equipment influence coefficient of the time acquisition device, For the The configuration influence coefficient of the acquisition device at the moment, is the correction factor, for The weight of the influence coefficient at the moment.

[0119] Furthermore, the operating status information and multi-level environmental information of the multi-level edge devices set for each edge node are obtained, and the operating status quality index corresponding to the multi-level edge devices set for each edge node is obtained. The multi-level edge devices are multiple edge devices set for each edge node, which are used to perform multi-batch processing on the image data transmitted by the acquisition node. The calculation steps of the operating status quality index corresponding to the multi-level edge devices set for each edge node are as follows:

[0120] S1. Define various parameters required to calculate the operating status quality index, including edge device operating status parameters, multi-level device interaction influence coefficients, multi-level environmental influence coefficients, multi-level edge device configuration quality coefficients, and multi-level device health;

[0121] S2. Input the above parameters in sequence , calculate and obtain the operating status quality index corresponding to the multi-level edge devices set for each edge node, where, Represents the edge device operating status parameters of device m on edge node n (such as device load, response time, processing power, stability, etc.). These status parameters can be quantified based on the device's real-time monitoring data (such as CPU usage, memory usage, response delay, etc.). Representation device For equipment The interaction coefficients between multiple devices at the same edge node n (reflecting the impact of device interaction, resource sharing, or conflict on quality). These coefficients can be determined based on historical data, dependencies between devices, resource allocation, etc. is the multi-level environmental impact coefficient of the edge node n (including temperature, humidity, air quality, network bandwidth and other factors). Environmental factors will affect the working stability and reliability of the device. Indicates the multi-level edge device configuration quality coefficient of edge node n (such as the robustness of node hardware, configuration optimization degree, etc.), Multi-level device health of device m on edge node n (such as device failure rate, service life, etc.).

[0122] Furthermore, based on the acquisition nodes, edge nodes and real-time time information, clock synchronization is performed on the real-time acquired image data to obtain synchronized image data, specifically including:

[0123] Determine the level information of the acquisition node and extract the timestamp information in the real-time acquisition image data transmitted by the acquisition node through the edge node;

[0124] The edge node determines whether the timestamp information is empty, determines the timestamp transmission non-empty rate of the same-level collection node, and sets the timestamp transmission non-empty rate threshold based on the edge node;

[0125] If the timestamp transmission non-empty rate of the acquisition node at the same level is greater than or equal to the timestamp transmission non-empty rate threshold, then the standard time information of the real-time acquisition image data is determined based on the timestamp information and real-time time information of the acquisition node at the same level;

[0126] If the timestamp transmission non-empty rate of the same-level acquisition nodes is less than the timestamp transmission non-empty rate threshold, the standard time information of the real-time acquisition image data is determined based on the real-time time information.

[0127] Furthermore, the synchronized image data is transmitted to the central node through the edge node, specifically including:

[0128] Determine the central node with which the edge nodes interact, and generate a pre-shared key by combining the edge nodes and the central node;

[0129] Based on the pre-shared key, the central node determines whether to allow the edge node to transmit images. If not, the acquisition node continues to collect real-time images. If yes, the transmission quality threshold is set based on the edge node's transmission quality index.

[0130] Setting data processing information of the edge node for the synchronous image data according to the transmission quality index and the transmission quality threshold;

[0131] Based on the data processing information and the pre-shared key, the synchronized image data of the edge node is transmitted to the central node.

[0132] Specifically, data processing information for synchronized image data is set for the edge node based on a transmission quality index and a transmission quality threshold. When the transmission quality index is greater than or equal to the transmission quality threshold, indicating high transmission quality at the edge node, lossless data transmission is adopted to ensure image quality. When the transmission quality index is lower than the transmission quality threshold, indicating low transmission quality at the edge node, lossy compression (e.g., using JPEG compression or video encoding compression) is performed on the image data during transmission to reduce data volume and increase transmission speed. Based on the data processing information and a pre-shared key, the synchronized image data from the edge node is transmitted to the central node. When the edge node uses the data processing information for data transmission, a key is set in the synchronized image data using the pre-shared key to encrypt the data transmission and ensure data transmission security.

[0133] Furthermore, the synchronous image data received by the central node is subjected to wheel classification and data processing to obtain classified image data, specifically including:

[0134] Determine the standard time information of the synchronized image data based on the standard time information of the real-time collected image data; construct a time wheel based on the standard time information to classify the synchronized image data according to time periods;

[0135] Extract the feature information of the synchronized image data and construct features based on the feature information of the synchronized image data

[0136] Roulette, classifying the synchronized image data after time roulette classification according to image features;

[0137] Determine the task priority index based on the edge node corresponding to the synchronized image data, and construct a task priority wheel to classify the synchronized image data after feature wheel classification according to the task priority;

[0138] Data processing is performed on the synchronous image data classified by the completion time wheel, the feature wheel, and the task priority wheel to obtain classified image data.

[0139] Specifically, a time wheel is constructed based on standard time information, dividing image data into time periods. Each time period is a "sector" on the wheel, corresponding to the image data collected within that time period. Within one of the "sectors" of the time wheel, a feature wheel is constructed based on the extracted image feature information. This wheel classifies images according to the extracted features. Feature classification can be based on image similarity or through unsupervised learning algorithms (such as clustering). Image feature information includes color features and content features. First, synchronized image data with the same color features are divided into the same "sector" of the feature wheel based on color features. Then, synchronized image data with the same content are divided into the same "sector" of the feature wheel based on content features. Based on the processing power and task priority of each edge node (based on information such as edge node load, network bandwidth, and task type), each synchronized image data is assigned a priority index. Then, the task priority index is mapped to a task priority wheel, where each sector represents a priority interval.

[0140] Furthermore, based on the data attribute pie chart, the image transmission parameters are determined, and the classified image data is transmitted to the cloud platform for storage, specifically including:

[0141] According to the data attribute pie chart, determine the bandwidth requirement information, data compression information, transmission protocol information, transmission frequency information and transmission encryption information of the image transmission;

[0142] Determine image transmission parameters based on image transmission bandwidth requirement information, data compression information, transmission protocol information, transmission frequency information, and transmission encryption information;

[0143] Through the image transmission parameters, the classified image data are sequentially transmitted to the cloud platform for storage.

[0144] Furthermore, a wireless network-based multi-data acquisition and image transmission system is proposed, which is used to implement any of the above transmission methods, including:

[0145] The edge processing module is used to obtain real-time collected image data through the collection node and obtain real-time time information through the edge node. Based on the collection node, the edge node and the real-time time information, the edge processing module is used to synchronize the clock of the real-time collected image data to obtain synchronized image data, and transmit the synchronized image data to the central node through the edge node;

[0146] The central management module is used to synchronize the clock of the real-time collected image data based on the collection nodes, edge nodes and real-time time information to obtain synchronized image data;

[0147] The cloud platform module is used to monitor and manage the cloud platform, and is also used to build a wireless network architecture, determine the central node, collection node and edge node, determine the central node for edge node interaction, and generate a pre-shared key in combination with the edge node and the central node.

[0148] Furthermore, the central management module includes:

[0149] A central receiving unit, which is used to receive data and information transmitted from the edge processing module;

[0150] The classification unit is used to perform wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data;

[0151] The data sending unit is used to obtain the data attribute matrix of the classified image data, and construct a data attribute pie chart based on the data attribute matrix. Based on the data attribute pie chart, the image transmission parameters are determined, and the classified image data is transmitted to the cloud platform for storage.

[0152] Furthermore, the edge processing module includes:

[0153] The acquisition unit is used to acquire real-time image data using an acquisition node and to acquire real-time time information using an edge node;

[0154] The data processing unit is used to synchronize the clock of the real-time collected image data based on the collection node, the edge node and the real-time time information to obtain synchronized image data;

[0155] The transmission unit is used to transmit the synchronous image data to the central node through the edge node.

[0156] The advantages of the present invention are that: based on the type information, specification information and collection quality impact coefficient of the collection device, the collection quality index of the collection node is obtained, and then the collection nodes are graded according to the collection quality index. Then, the graded collection nodes are associated with the edge nodes. Multi-level edge devices are set at the edge nodes, and the operating status information and multi-level environmental information of the multi-level edge devices set at each edge node are obtained. The operating status quality index corresponding to the multi-level edge devices set at each edge node is obtained. Based on the operating status quality index and multi-level environmental information corresponding to the multi-level edge devices set at each edge node, the transmission quality index of each edge node is obtained. By gradually analyzing each link, such as collection quality, node status, and environmental impact, comprehensive optimization from device performance to transmission quality is ensured, avoiding the risk of one-sided dependence on a single factor. Real-time monitoring of environmental factors and device status enables the system to self-adjust and adapt to different operating conditions, thereby improving the flexibility and reliability of the system. By quantifying indicators such as node quality and transmission performance, the system can intelligently schedule resources and load balance, optimize device configuration, and improve data transmission efficiency and systematicity. A multi-dimensional evaluation method ensures that even if some nodes fail, the stable operation of the entire system can be guaranteed. At the same time, the model has good scalability and can adapt to changes in different scales and needs;

[0157] Based on the application scenario information, the location information of the acquisition node is determined. Then, based on the three-dimensional space coordinate system, the edge dynamic point is determined. The coordinates of the edge node are determined by the edge dynamic point and the coordinate point of the acquisition device. Then, the coordinates of the central node in the three-dimensional space coordinate system are determined by the edge node basic coordinates and transmission quality index of each edge node. This allows the determination of appropriate acquisition nodes, edge nodes, and central nodes in areas with numerous network devices and complex terrain, avoiding the influence of environmental factors when the edge node transmits image data to the central node after receiving the image data from the acquisition node.

[0158] By determining the level information of the acquisition node and extracting the timestamp information in the real-time image data transmitted by the acquisition node through the edge node, the edge node is used to determine whether the timestamp information is empty. At the same time, the timestamp transmission non-empty rate of the acquisition node at the same level is determined, and the timestamp transmission non-empty rate threshold is set based on the edge node. Through the timestamp transmission non-empty rate threshold and the timestamp transmission non-empty rate, the image data transmitted from different acquisition nodes to the edge node are ensured to maintain time synchronization, thereby improving the efficiency of subsequent image processing.

[0159] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-data acquisition and image transmission method based on a wireless network, characterized in that: include: Build wireless network architecture and determine central nodes, collection nodes, and edge nodes; Use acquisition nodes to obtain real-time image data, and use edge nodes to obtain real-time time information; Based on the acquisition nodes, edge nodes and real-time time information, clock synchronization is performed on the real-time acquired image data to obtain synchronized image data; Transmitting synchronized image data to the central node via the edge node; Performing wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data; Obtain the data attribute matrix of the classified image data and construct a data attribute pie chart based on the data attribute matrix; Based on the data attribute pie chart, the image transmission parameters are determined, and the classified image data is transmitted to the cloud platform for storage; The construction of the wireless network architecture and the determination of the central node, collection node, and edge node specifically include: Obtain application scenario information, and determine the location information of the collection node based on the application scenario information; According to the location information of the collection node, the environmental information of the collection node is obtained, and the corresponding collection device is set and the type information of the collection device is obtained; Classify the collection devices based on their type information, and obtain location information of the same type of collection devices respectively; Determine the maximum distance information of the collection device using the location information of the same type of collection device; Determine the farthest distance line segment using the farthest distance information of the acquisition device, and construct a three-dimensional space coordinate system with the center point of the farthest distance line segment as the origin; Determine the edge dynamic points based on the three-dimensional space coordinate system; Determine the coordinate points of the same type of acquisition devices in a three-dimensional space coordinate system based on the position information of the same type of acquisition devices; Connect the edge dynamic points with the coordinate points of the same type of acquisition device in the three-dimensional space coordinate system to obtain edge dynamic line segments; The length values ​​of the edge dynamic line segments corresponding to the same type of acquisition devices are summed to obtain the edge node dynamic decision value; The coordinates of the edge dynamic point when the edge node dynamic decision value is the minimum are used as the coordinates of the edge node; Determine the central node based on the environmental information of the edge nodes and collection nodes corresponding to each type of collection device; The determining of the central node based on the environmental information of the edge nodes and collection nodes corresponding to each type of collection device specifically includes: Based on the three-dimensional space coordinate system, the coordinates of the edge nodes corresponding to each type of acquisition device are determined as the basic coordinates of the edge nodes; Using the environmental information of the collection node, determine the temperature information, humidity information, electromagnetic interference information, airflow information, vibration information and noise information of the collection node corresponding to the same type of collection device; Obtaining the collection quality influence coefficient corresponding to the collection node based on the temperature information, humidity information, electromagnetic interference information, airflow information, vibration information, and noise information of the collection node corresponding to the same type of collection device; determining specification information of each type of collection device based on the type information of the collection device; Obtaining the collection quality index of the collection node based on the type information, specification information and collection quality impact coefficient of the collection device; The collection nodes are graded based on the collection quality index; Perform correlation analysis on the hierarchically divided collection nodes and edge nodes, and set up multi-level edge devices on the edge nodes; Obtaining the operating status information and multi-level environment information of the multi-level edge devices set for each edge node, and obtaining the operating status quality index corresponding to the multi-level edge devices set for each edge node; Obtaining a transmission quality index for each edge node based on the operating status quality index and multi-level environment information corresponding to the multi-level edge devices set for each edge node; Determine the coordinates of the central node in the three-dimensional space coordinate system through the edge node basic coordinates and transmission quality index of each edge node; The clock synchronization of the real-time collected image data based on the collection node, the edge node and the real-time time information to obtain the synchronized image data specifically includes: Determine the level information of the acquisition node and extract the timestamp information in the real-time acquisition image data transmitted by the acquisition node through the edge node; The edge node determines whether the timestamp information is empty, determines the timestamp transmission non-empty rate of the same-level collection node, and sets the timestamp transmission non-empty rate threshold based on the edge node; If the timestamp transmission non-empty rate of the acquisition node at the same level is greater than or equal to the timestamp transmission non-empty rate threshold, then the standard time information of the real-time acquisition image data is determined based on the timestamp information and real-time time information of the acquisition node at the same level; If the timestamp transmission non-empty rate of the same-level acquisition nodes is less than the timestamp transmission non-empty rate threshold, the standard time information of the real-time acquisition image data is determined based on the real-time time information.

2. The method for multi-data acquisition and image transmission based on a wireless network according to claim 1, characterized in that: The transmitting of the synchronized image data to the central node through the edge node specifically includes: Determine the central node with which the edge nodes interact, and generate a pre-shared key by combining the edge nodes and the central node; Based on the pre-shared key, the central node determines whether to allow the edge node to transmit images. If not, the acquisition node continues to collect real-time images. If yes, the transmission quality threshold is set based on the edge node's transmission quality index. Setting data processing information of the edge node for the synchronous image data according to the transmission quality index and the transmission quality threshold; Based on the data processing information and the pre-shared key, the synchronized image data of the edge node is transmitted to the central node.

3. The method for multi-data acquisition and image transmission based on a wireless network according to claim 2, characterized in that: The performing wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data specifically includes: Determine the standard time information of the synchronized image data based on the standard time information of the real-time collected image data; construct a time wheel based on the standard time information to classify the synchronized image data according to time periods; Extract the feature information of the synchronized image data and construct features based on the feature information of the synchronized image data Roulette, classifying the synchronized image data after time roulette classification according to image features; Determine the task priority index based on the edge node corresponding to the synchronized image data, and construct a task priority wheel to classify the synchronized image data after feature wheel classification according to the task priority; Data processing is performed on the synchronous image data classified by the completion time wheel, the feature wheel, and the task priority wheel to obtain classified image data.

4. The method for multi-data acquisition and image transmission based on a wireless network according to claim 3, characterized in that: The method of determining image transmission parameters based on the data attribute pie chart and transmitting the classified image data to the cloud platform for storage specifically includes: According to the data attribute pie chart, determine the bandwidth requirement information, data compression information, transmission protocol information, transmission frequency information and transmission encryption information of the image transmission; Determine image transmission parameters based on image transmission bandwidth requirement information, data compression information, transmission protocol information, transmission frequency information, and transmission encryption information; Through the image transmission parameters, the classified image data are sequentially transmitted to the cloud platform for storage.

5. A multi-data acquisition and image transmission system based on a wireless network, used to implement the transmission method according to any one of claims 1 to 4, characterized in that: include: An edge processing module, which is used to acquire real-time collected image data using an acquisition node, and to acquire real-time time information using the edge node. Based on the acquisition node, the edge node, and the real-time time information, the module is used to perform clock synchronization on the real-time collected image data to obtain synchronized image data, and transmit the synchronized image data to the central node via the edge node. A central management module, the central management module is used to synchronize the clock of the real-time collected image data based on the collection nodes, edge nodes and real-time time information to obtain synchronized image data; The cloud platform module is used to monitor and manage the cloud platform, and is also used to build a wireless network architecture, determine the central node, collection node and edge node, determine the central node for edge node interaction, and generate a pre-shared key in combination with the edge node and the central node.

6. The wireless network-based multi-data acquisition and image transmission system according to claim 5, characterized in that: The central management module includes: A central receiving unit, configured to receive data and information transmitted from an edge processing module; a classification unit, the classification unit being configured to perform wheel classification and data processing on the synchronous image data received by the central node to obtain classified image data; The data sending unit is used to obtain a data attribute matrix of the classified image data, and construct a data attribute pie chart based on the data attribute matrix, determine the image transmission parameters based on the data attribute pie chart, and transmit the classified image data to the cloud platform for storage.

7. The wireless network-based multi-data acquisition and image transmission system according to claim 5, characterized in that: The edge processing module includes: An acquisition unit, configured to acquire real-time image data using an acquisition node and acquire real-time time information using an edge node; A data processing unit, configured to perform clock synchronization on real-time collected image data based on the collection nodes, edge nodes, and real-time time information to obtain synchronized image data; A transmission unit is used to transmit the synchronous image data to the central node through the edge node.

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