An environmental data monitoring processing method and system, an electronic device and a storage medium

Abstract

The embodiment of the application relates to an environmental data monitoring processing method and system, electronic equipment and a storage medium, and belongs to the technical field of electric digital data processing. The method steps comprise the following: acquiring a target monitoring area and generating corresponding codes, connecting adjacent topological graph node areas and forming a closed loop link, sending a supplementary sampling instruction to a monitoring sensor and detecting whether there is missing transmission information, establishing a corresponding detection path, generating a patrol topological route and outputting early warning information. The embodiment of the application constructs a closed loop link of an environmental data monitoring sensor signal network, provides intelligent planning of a patrol topological route and a redundancy checking function, reduces the communication cost overhead of directional supplementary sampling, automatically generates a patrol route, realizes intelligent repair of a fault node, reduces the cost of manual patrol, and significantly improves the reliability, real-time performance and operation and maintenance efficiency of a large-scale distributed monitoring network.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to an environmental data monitoring processing method and system, electronic equipment and storage medium, and belongs to the technical field of digital data processing. BACKGROUND

[0002] In the field of environmental monitoring, the traditional data collection method usually adopts centralized monitoring stations or simple distributed sensor networks. Although the existing technology can provide certain monitoring capabilities, there are still the following problems in data collection in a wide range and complex environment:

[0003] Insufficient data integrity and reliability: the existing environmental monitoring system usually relies on a single or a small number of monitoring sites, and the data coverage is limited, which is difficult to fully reflect the real environmental conditions of the monitoring area. Although the distributed sensor network can improve the data collection density, due to the lack of intelligent collaboration mechanism between nodes, it is difficult to find and repair in time when data is lost or transmission is abnormal, resulting in incomplete monitoring data.

[0004] Low efficiency of fault detection and recovery: the existing technology usually adopts periodic polling or simple heartbeat detection to determine whether the node is working normally, but the periodic polling or heartbeat detection method has slow response speed and cannot accurately locate the fault node. When a sensor node fails, the system may only record the fault, but cannot automatically plan the optimal inspection path, resulting in low maintenance efficiency and affecting the continuity of monitoring.

[0005] The network topology structure of the existing technology relies on fixed network topology (such as star, mesh or tree structure), which is difficult to adapt to the dynamically changing monitoring environment (such as temporary increase or decrease of monitoring points or node movement scene), lacks effective topology coding mechanism, and causes difficulty in node management and data association, which affects the accuracy of data analysis.

[0006] In summary, the existing technology cannot meet people's requirements and needs to be improved. SUMMARY

[0007] The embodiment of the present application aims to provide an environmental data monitoring processing method, system, electronic equipment and storage medium, which adopts closed-loop link detection, dynamic inspection planning and other technical means to solve the shortcomings of the existing technology.

[0008] The embodiment of the present application provides the following scheme:

[0009] According to one aspect of the embodiments of this application, an environmental data monitoring and processing method is provided, applied to an environmental data monitoring and processing system, comprising: acquiring a target monitoring area; deploying distributed acquisition nodes within the target monitoring area, the distributed acquisition nodes including monitoring sensors and acquisition nodes; encoding the distributed acquisition nodes to generate a first code and a second code; the first code corresponds to a topology map graphic area of ​​the monitoring area, the second code corresponds to a topology map node area; connecting adjacent topology map node areas to form a node link; if the node link is a closed loop link, acquiring sensor information of the acquisition nodes on the closed loop link and detecting the integrity of the sensor information; if sensor information is detected to be missing on the closed loop link, sending a supplementary acquisition command to the monitoring sensor to acquire the location of the fault node with missing sensor information, and recording the first code and the second code corresponding to the fault node location; repeatedly detecting the node location with missing sensor information and the supplementary acquisition command; if sensor information is still missing at the fault node location when the number of detections reaches a threshold, establishing a corresponding detection path, generating an inspection topology route, and outputting early warning information.

[0010] According to at least one specific embodiment of the present application, the process of deploying distributed acquisition nodes within the target monitoring area includes: acquiring a monitoring dataset, the monitoring dataset including at least the node's communication radius, node power consumption, and the two-dimensional plane coordinate range of the area to be monitored; based on the monitoring dataset, generating an initial candidate node coordinate list within the two-dimensional plane coordinate range with the node's communication radius as a constraint; calling an optimization algorithm module and setting a corresponding threshold to optimize the node coordinate list, iteratively outputting the optimized node coordinate list, and generating a node deployment instruction file based on the optimized node coordinate list; and distributing the node deployment instruction file line by line to the nodes to be deployed in each node coordinate list through a broadcast channel, and completing the deployment of the distributed acquisition nodes after the nodes to be deployed send back an instruction file confirmation frame.

[0011] According to at least one specific implementation of the embodiments of this application, in the process of optimizing the node coordinate list by calling the optimization algorithm module and setting the corresponding threshold, the corresponding threshold is set based on minimizing the total power consumption of the nodes and in combination with the redundancy of the communication links between adjacent nodes; when the node to be deployed sends back the instruction file confirmation frame, if any node to be deployed in the node coordinate list does not send back the confirmation frame within the preset window period, the node to be deployed is confirmed to be in the "to be filled" state, and the coordinates of the node to be deployed are recalculated in the initial candidate node coordinate list.

[0012] According to at least one specific embodiment of this application, the first code corresponds to a topology graph region of the monitoring area, and the second code corresponds to a topology graph node region. Adjacent topology graph node regions are connected to form node links. If the node link is a closed-loop link, sensor information of the acquisition nodes on the closed-loop link is obtained, and the integrity of the sensor information is detected. The method further includes: parsing the first code to generate a list of polygon boundary coordinates of the topology graph region; parsing the second code using the list of polygon boundary coordinates to extract node identifiers and their center coordinates of adjacent topology graph node regions; and detecting whether the Euclidean distance between the topology node regions is less than a preset threshold based on the node identifiers and their center coordinates. If the Euclidean distance is less than a preset threshold, an undirected edge is established between node identifiers to form a node link, and a depth-first traversal algorithm is called to detect whether a closed loop exists in the node link. If the closed loop is detected, a sensor information acquisition instruction is executed. The sensor information acquisition instruction is used to acquire each acquisition node on the closed loop. The actual number of sensor data frames received in the buffer queue of the communication link is calculated through the sensor information acquisition instruction. The number of sensor data frames is compared with the total number of nodes in the closed loop. If the two are equal, the sensor information is determined to be complete and the closed loop is marked as valid. Or, if the two are not equal, a supplementary acquisition process is triggered, and the acquisition command is resent to the faulty node until the sensor information meets the integrity requirements.

[0013] According to at least one specific embodiment of the present application, during the execution of the sensor information acquisition instruction, when a closed-loop link is detected, a distributed sensor information acquisition protocol is initiated. An improved Byzantine fault-tolerant algorithm is used to verify the authenticity of the node, and a sliding window statistical model of data arrival time is established based on time series analysis to identify abnormal nodes. The feature matching degree between the actual received data frame and the expected data frame in the buffer queue is calculated. The calculation process includes constructing a hash fingerprint feature vector of the data frame and / or using an SVM classifier to determine the integrity probability. The current feature matching degree is calculated based on the integrity probability. When the feature matching degree is lower than a threshold, an adaptive acknowledgment frame return strategy is initiated, and the sending parameters of the supplementary acquisition instruction are dynamically adjusted based on network quality.

[0014] According to at least one specific embodiment of the present application, if a missing sensing information is detected on the closed-loop link, a supplementary sampling command is sent to the monitoring sensor to obtain the location of the fault node with missing sensing information, and the first and second codes corresponding to the location of the fault node are recorded. This further includes: obtaining the fault node ID; writing the fault node ID into the register of the control system; calling the coordinate mapping table to extract its planar coordinates as the location of the fault node; sequentially querying the topology graph graphic area index table and the node area table based on the coordinates of the fault node to obtain the first and second codes respectively and storing them in the cache; constructing a message with the fault node ID, synchronization timestamp, and wake-up offset field; appending the first and second codes to the extended field of the register; retransmitting via the broadcast channel until an acknowledgment frame is received; or: if retransmission exceeds a certain number of times, determining that the fault node has no processing value.

[0015] According to at least one specific embodiment of the present application, the repeated detection of the node location with missing sensor information and the supplementary acquisition command, if the faulty node location still has missing sensor information when the number of detections reaches a threshold, then a corresponding detection path is established, an inspection topology route is generated, and an early warning information is output. This further includes: when data loss is detected, establishing a faulty node list and controlling the frequency of supplementary acquisition command transmission; marking nodes whose missing counters reach a threshold as faulty nodes; generating a closed-loop detection path for the faulty nodes; updating the topological connection relationship of the topology graph area; extracting the corresponding location coordinates and node identifiers for the confirmed faulty nodes; generating a multi-dimensional early warning information package; pushing the multi-dimensional early warning information package via the MQTT protocol and storing the fault log locally, while simultaneously establishing an inspection topology route.

[0016] According to another aspect of the embodiments of this application, an environmental data monitoring and processing system is provided for implementing the environmental data monitoring and processing method, comprising: a data acquisition node encoding generation module, configured to acquire a target monitoring area, deploy distributed data acquisition nodes within the target monitoring area, the distributed data acquisition nodes including monitoring sensors and data acquisition nodes, encoding the distributed data acquisition nodes to generate a first code and a second code; and a topology region node generation module, wherein the first code corresponds to a topology map graphic area of ​​the monitoring area, the second code corresponds to a topology map node area, and adjacent topology map node areas are connected to form node links, if the... If the node link is a closed-loop link, then the sensor information of the acquisition nodes on the closed-loop link is acquired, and the integrity of the sensor information is detected; if the closed-loop link detection module detects that the sensor information on the closed-loop link is missing, it sends a supplementary acquisition command to the monitoring sensor, acquires the location of the fault node with missing sensor information, and records the first code and second code corresponding to the location of the fault node; the inspection and early warning output module repeatedly detects the location of the node with missing sensor information and the supplementary acquisition command. If the fault node still has missing sensor information when the number of detections reaches a threshold, then a corresponding detection path is established, an inspection topology route is generated, and an early warning information is output.

[0017] According to another aspect of the embodiments of this application, an electronic device is provided, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method.

[0018] According to other aspects of embodiments of this application, a computer-readable storage medium is provided that stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method.

[0019] The embodiments of this application have the following advantages compared with the prior art:

[0020] This application embodiment constructs a closed-loop link for an environmental data monitoring sensor signal network. First, hierarchical coding is used to divide the monitoring area into a topology map and nodes. Then, the closed-loop link is used as the smallest redundancy unit for integrity verification. Once a data gap is detected, targeted data acquisition is triggered. If acquisition fails, an inspection route is automatically generated and an early warning is issued, forming a self-healing process from fault detection to path repair. The integrity of the closed-loop link is verified through the mapping relationship between coding and the topology structure, and targeted data acquisition and recording are performed. If the acquisition attempts reach a threshold and still fail, the "fault node coordinates + coding" are automatically input into the path planning module to generate the shortest inspection topology route, achieving intelligent repair of the fault node. The environmental data monitoring system utilizes topology coding to provide spatial consistency of the topology structure and nodes. The closed-loop link provides intelligent planning of inspection topology routes and redundancy verification functions. Targeted acquisition reduces communication costs, and automatic route generation enables intelligent repair of fault nodes, shortening fault response time to the level of the closed-loop detection cycle and reducing the cost of manual inspection. This significantly improves the reliability, real-time performance, and operational efficiency of large-scale distributed monitoring networks. Attached Figure Description

[0021] To more clearly illustrate the specific implementation methods of the embodiments of this application or the technical solutions in the prior art, the drawings used in the description of the specific implementation methods or the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of environmental data monitoring and processing methods.

[0023] Figure 2 This is a flowchart of the optimization technical solutions provided in steps S11 to S14.

[0024] Figure 3 This is a flowchart of the optimized technical solutions provided in steps S21 to S23.

[0025] Figure 4 This is a flowchart of the optimization technical solution provided in steps S231 to S233.

[0026] Figure 5 This is a flowchart of the optimization technical solution provided in steps S31 to S32.

[0027] Figure 6 This is a flowchart of the optimization technical solution provided in steps S41 to S42.

[0028] Figure 7 This is an architecture diagram of an environmental data monitoring and processing system.

[0029] Figure 8 This is a schematic diagram of the electronic device. Detailed Implementation

[0030] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the embodiments of this application.

[0031] The environmental data monitoring and processing method and system provided in this application are applicable to large-scale distributed environmental monitoring scenarios, such as air pollution monitoring, water quality monitoring, soil monitoring, or meteorological data acquisition. By optimizing the deployment, coding, and fault detection mechanisms of data acquisition nodes, this application improves the integrity and reliability of environmental monitoring data and achieves efficient fault location and early warning. It can be widely applied to various scenarios with high requirements for data integrity and real-time operation and maintenance. Typical application scenarios are illustrated below:

[0032] Smart city infrastructure monitoring: Deploy distributed sensor networks in key infrastructure such as urban roads, bridges, tunnels and underground utility tunnels. Verify structural health monitoring data (stress, vibration, temperature and humidity, etc.) in real time through closed-loop links. If a data gap is found, start supplementary data collection immediately. If supplementary data collection fails, automatically generate an inspection path to guide inspection robots or maintenance personnel directly to the fault node, shorten road closure time and ensure the safety of urban operation.

[0033] Industrial environmental monitoring: Applicable to complex industrial scenarios such as chemical industrial parks, steel plants, and data centers. In this application scenario, the embodiments of this application can perform closed-loop monitoring of air quality, temperature and humidity, and harmful gas concentrations. Dual coding is used to quickly locate leak sources or abnormal equipment, avoiding the high costs of traditional manual inspections. Dynamic inspection routes can be coordinated with AGVs / drones to achieve precise operation and maintenance.

[0034] Ecological protection and natural resource monitoring: Low-power wireless sensor networks are deployed in vast or topographically complex areas such as wetlands, forests, rivers, and mining areas. A closed-loop link mechanism allows for timely replenishment of missing ecological data when nodes are low on power or communication is disrupted. Ecological data can include water quality, soil moisture, biodiversity indicators, etc., ensuring the continuous reliability of both research and monitoring data. When replenishment fails multiple times, this embodiment can also generate an optimal inspection route, reducing the intensity of manual inspections and improving the efficiency of ecological protection.

[0035] Emergency monitoring in extreme environments or disasters: In the event of sudden disasters such as earthquakes, floods, and landslides, temporary sensor arrays can be quickly deployed to verify the integrity of data from key monitoring points in real time. If data is interrupted due to node damage, the embodiments of this application will immediately output early warning information including coordinates, scope of impact, and disposal suggestions to assist emergency command departments in making rapid decisions, shorten the rescue cycle, and improve rescue efficiency.

[0036] Definitions:

[0037] Distributed data acquisition nodes: These are field data acquisition units composed of two physical entities: monitoring sensors and acquisition nodes. The monitoring sensors are responsible for sensing environmental parameters such as temperature, humidity, gas concentration, vibration, etc. The acquisition nodes are responsible for data preprocessing, local caching, and communication forwarding, possessing both data processing and communication interaction capabilities.

[0038] Topology Graph Region: The region corresponding to the first code. The topology graph region is used to form an undirected graph of the actual monitoring area. An undirected graph is a mathematical structure consisting of vertices and edges, where none of the edges have directional arrows. The physical space covered by an undirected graph is the topology graph region. It is identified by the first code in the coding system corresponding to the topology graph region, allowing for granular management of the region. The graph region can be further subdivided into several node regions for algorithmic operations and logical control related to loop closure detection and path planning.

[0039] Distributed acquisition nodes: Field data acquisition units composed of two types of physical entities, monitoring sensors and acquisition nodes. The monitoring sensors and acquisition nodes are connected by wired or wireless means and can be deployed as needed to achieve distributed coverage.

[0040] Topological graph region: The region corresponding to the first code, which is the physical space covered by the entire graph when the actual monitoring area is abstracted into an undirected graph.

[0041] In the coding system, the first code is used as an identifier, which can correspond to the macro-management granularity such as floor area subsystem.

[0042] The graphic area can be further subdivided into several node areas for easy hierarchical management.

[0043] Node link: A communication line between two adjacent node regions on the topology diagram, reflecting the feasibility of transmission and the direction of data flow between nodes. When multiple node links are connected end-to-end to form a closed path, a closed-loop link is constituted. Each link can transmit data packets bidirectionally. In the embodiments of this application, node links are used for link-level integrity verification.

[0044] Supplementary Acquisition Command: A triggered acquisition command sent by the acquisition node to the monitoring sensor that is missing sensing information via the node link. The supplementary acquisition command may include: target node code, list of missing parameters, number of retries, and expected transmission time slot. If the supplementary acquisition is successful, the data is backfilled into the local cache; if the supplementary acquisition fails, the subsequent inspection process begins.

[0045] Inspection topology route: After multiple failed data collection attempts, the system automatically generates the optimal inspection path based on factors such as the coordinates of the faulty node, node links, and transmission feasibility constraints. This path can be, for example, a directed graph, a GIS coordinate sequence, or a mobile navigation task package, etc. An example is: starting point - faulty node - backup node - destination. This inspection topology route can be used for intelligent operation and maintenance.

[0046] like Figure 1 The environmental data monitoring and processing method shown is applied to an environmental data monitoring and processing system, including:

[0047] Step S1: Obtain the target monitoring area, deploy distributed acquisition nodes within the target monitoring area, the distributed acquisition nodes include monitoring sensors and acquisition nodes, encode the distributed acquisition nodes, and generate a first code and a second code.

[0048] Step S2: The first code corresponds to the topology map graphic area of ​​the monitoring area, and the second code corresponds to the topology map node area. Connect the adjacent topology map node areas to form a node link. If the node link is a closed loop link, obtain the sensing information of the acquisition node on the closed loop link and check the integrity of the sensing information.

[0049] Step S3: If a missing sensor information is detected on the closed-loop link, a supplementary sampling command is sent to the monitoring sensor to obtain the location of the fault node with missing sensor information, and the first and second codes corresponding to the fault node location are recorded.

[0050] Step S4: Repeatedly detect the location of nodes with missing sensor information and the supplementary acquisition command. If the faulty node still has missing sensor information when the number of detections reaches the threshold, then establish the corresponding detection path, generate the inspection topology route and output the early warning information.

[0051] In the technical solutions provided in steps S1 to S4, efficient and reliable monitoring of the target area is achieved through topology coding management, closed-loop link detection, and inspection planning. Spatial topology relationships are constructed using the first coding (graphical area) and the second coding (node ​​area), transforming the physical sensor network into a topology graphical area, forming a computable logical structure. Then, closed-loop verification is performed using closed-loop links to detect the integrity of the sensor data. Faulty nodes are quickly located and data is modified through supplementary sampling commands and inspection path planning, achieving closed-loop monitoring and data processing from detection to maintenance.

[0052] In the technical solutions provided in steps S1 to S4, step S2 provides closed-loop link detection based on step S1, and repairs faulty nodes in the closed-loop link through the supplementary data acquisition command in step S3. It also eliminates transient interference by repeatedly verifying the corresponding thresholds, ensuring data integrity. The inspection topology route provided in step S4 is based on the faulty nodes in step S3 and the topology relationship diagram and closed-loop link of steps S1 and S2. This allows for precise location of faulty areas, shortening fault response time, and improving operational efficiency. Furthermore, it uses the closed-loop link and judgment to implement supplementary data acquisition and modification measures for temporary faults, and employs early warning notification measures for persistent faults that cannot be automatically repaired. This not only prevents the spread of single-point faults but also ensures the long-term stable operation of the system.

[0053] like Figure 2 As shown, in a preferred embodiment of this application, step S1, in the process of deploying distributed acquisition nodes within the target monitoring area, includes:

[0054] Step S11: Obtain the monitoring dataset. The monitoring dataset includes at least the node's communicable radius, node power consumption, and the two-dimensional plane coordinate range of the area to be monitored.

[0055] Step S12: Based on the monitoring dataset, generate an initial list of candidate node coordinates within the two-dimensional plane coordinate range, using the communicable radius of the nodes as a constraint.

[0056] Step S13: Invoke the optimization algorithm module and set the corresponding threshold to optimize the node coordinate list. Iterate and output the optimized node coordinate list. Based on the optimized node coordinate list, generate a node deployment instruction file. The instruction file includes the coordinates, wake-up time, and synchronization beacon period of each node.

[0057] Step S14: The node deployment instruction file is sent out one by one to the nodes to be deployed in the coordinate list of each node through the broadcast channel. When the node to be deployed sends back the instruction file confirmation frame, the deployment of the distributed acquisition nodes is completed.

[0058] The optimization solutions provided in steps S11 to S14 take the monitoring dataset as input. By generating a list of node coordinates and a node deployment instruction file, and downloading the node deployment instruction file, the optimal spatial layout and time slot synchronization of distributed acquisition nodes are achieved. Step S11 quantifies the communicable radius, power consumption, and area boundary of the nodes into a unified dataset, providing calculable constraint boundaries for subsequent coordinate optimization. Steps S12 to S13 call the optimization algorithm in the two-dimensional plane with the communication radius as a hard constraint, iteratively eliminate redundant coordinates, and output a list of coordinates with the maximum coverage and the fewest nodes. The wake-up time and synchronization beacon period are embedded synchronously to ensure that the nodes achieve optimal configuration in both space and time, reduce the power consumption of the entire network, and reduce the probability of communication collisions. Finally, the instruction file is sent out one by one through the broadcast channel, and the confirmation frame is sent back to ensure that the actual position of all nodes is consistent with the optimization result, forming a distributed acquisition network that can be put into operation immediately. The optimization solutions provided in steps S11 to S14 optimize space and time slot synchronization by establishing a dataset and constructing a mathematical model. Finally, they confirm the frame by broadcasting the confirmation instruction file. Under the premise of ensuring full coverage of the monitoring area, the solution minimizes the number of nodes, minimizes power consumption, and synchronizes communication, which significantly improves the reliability and energy efficiency of the subsequent environmental data monitoring and processing stage.

[0059] For example, in step S13, during the process of optimizing the node coordinate list by calling the optimization algorithm module and setting the corresponding threshold, the threshold is set based on minimizing the total power consumption of the nodes and in combination with the redundancy of the communication links between adjacent nodes. When the node to be deployed sends back the instruction file confirmation frame, if any node to be deployed in the node coordinate list fails to send back the confirmation frame within the preset window period, the node to be deployed is confirmed to be in the "to be filled" state, and the coordinates of the node to be deployed are recalculated in the initial candidate node coordinate list.

[0060] In this specific embodiment, as a further optimization of step S13, further optimizations were made to address issues such as network lifecycle, robustness, and coverage quality in step S13. Through the combined effect of the optimization algorithm and redundancy threshold, uneven energy consumption caused by excessive node communication or coverage overlap is avoided, achieving balanced node load and reducing power depletion. Even if some nodes fail, the overall environmental data monitoring and processing system can still maintain functionality through supplementary data collection commands, reducing the risk of single-point failure. By further optimizing step S13 and combining it with real-time enhancement of the coordination of distributed acquisition nodes deployed within the target monitoring area, the initial candidate list is re-called when issuing supplementary data collection commands, ensuring that the new coordinates both meet the optimization objectives and adapt to the current network state.

[0061] like Figure 3As shown, as a preferred technical solution of this application embodiment, step S2 can be further improved: the first code corresponds to the topology map graphic area of ​​the monitoring area, the second code corresponds to the topology map node area, adjacent topology map node areas are connected to form node links, if the node link is a closed loop link, the sensing information of the acquisition node on the closed loop link is obtained, and the integrity of the sensing information is detected, further including:

[0062] Step S21: Parse the first code to generate a list of polygon boundary coordinates of the topology graph region. Parse the second code using the list of polygon boundary coordinates to extract the node identifiers and center coordinates of adjacent topology graph node regions.

[0063] Step S22: Detect whether the Euclidean distance of the topological node region is less than a preset threshold based on the node identifier and its center coordinates. If the Euclidean distance is less than the preset threshold, establish undirected edges between the node identifiers to form node links and call the depth-first traversal algorithm to detect whether there is a closed loop link in the node links.

[0064] Step S23: If a closed-loop link is detected, a sensor information acquisition command is executed. This command acquires information from each data acquisition node on the closed-loop link. The actual number of sensor data frames received in the buffer queue of the communication link is calculated using this command. The number of sensor data frames is compared with the total number of nodes in the closed-loop link. If they are equal, the sensor information is considered complete and the closed-loop link is marked as valid.

[0065] If the two are not equal, a re-sampling process is triggered, and the acquisition command is resent to the faulty node until the sensor information meets the integrity requirements.

[0066] The optimized technical solution provided in steps S21 to S23 divides the topology of the monitoring area into graphical regions and node regions. Using a joint geometry-graph theory algorithm, it analyzes boundary coordinates and extracts nodes, establishes undirected edges using Euclidean distance as a criterion, and then uses depth-first traversal to find closed-loop links. Verification of the integrity of sensor information is only initiated when a closed-loop link is formed. If sensor information is missing, it is identified as a faulty node, and a supplementary sampling command is sent to the monitoring sensor. The optimized technical solution provided in steps S21 to S23 combines geometry-graph theory with data integrity detection, ensuring that only nodes adjacent in the topology graph that can form a closed-loop link are included in the scope of sending supplementary sampling commands, avoiding interference from invalid data. Based on the closed-loop link, it achieves integrated closed-loop control from the topology graph structure to the fault repair of missing data, enabling monitoring data to be detected based on the topology graph and targeted supplementary sampling commands to be sent.

[0067] like Figure 4As shown, as a further improvement to step S23, during the execution of the sensor information acquisition instruction:

[0068] Step S231: When a closed-loop link is detected, a distributed sensor information acquisition protocol is started, the improved Byzantine fault-tolerant algorithm is used to verify the authenticity of the node, and a sliding window statistical model of data arrival time is established based on time series analysis to identify abnormal nodes.

[0069] Step S232: Calculate the feature matching degree between the actual received data frames and the expected data frames in the buffer queue. The calculation process includes constructing the hash fingerprint feature vector of the data frames and / or using an SVM classifier to determine the integrity probability.

[0070] Step S233: Calculate the current feature matching degree based on the integrity probability. When the feature matching degree is lower than the threshold, start the adaptive confirmation frame return strategy and dynamically adjust the sending parameters of the supplementary sampling command based on the network quality.

[0071] In the optimized technical solution provided in steps S231 to S233, a closed-loop link detection and multi-step collaborative verification approach is adopted. A node authenticity verification model is established through the Byzantine fault-tolerant algorithm and time series analysis in step S231. This is combined with the data frame feature matching degree calculation and SVM classifier integrity assessment in step S232, and the adaptive confirmation frame dynamic adjustment mechanism in step S233, achieving the goal of efficiently identifying abnormal nodes and ensuring data transmission integrity. The distributed verification in step S231 and the feature vector analysis in step S232 form a dual verification. Step S233 dynamically adjusts the supplementary sampling parameters based on the integrity probability in step S232, coordinating with the abnormal node identification in step S231 to improve network resource utilization. The sliding window model in step S231 combined with the hash fingerprint feature vector in step S232 solves the problem of decreased system security caused by unreliable network nodes, data frame tampering, or loss, significantly improving transmission efficiency.

[0072] like Figure 5 As shown, as a further improvement to the embodiment of this application, if a lack of sensing information is detected on the closed-loop link in step S3, a supplementary sampling command is sent to the monitoring sensor to obtain the location of the fault node with missing sensing information, and the first code and the second code corresponding to the fault node location are recorded, further including:

[0073] Step S31: Obtain the fault node ID, write the fault node ID into the register of the control system, and call the coordinate mapping table to extract its planar coordinates as the location of the fault node. Based on the coordinates of the fault node, query the topology graph graphic area index table and the node area table in sequence to obtain the first code and the second code respectively and store them in the cache.

[0074] Step S32: Construct a message using the fault node ID, synchronization timestamp, and wake-up offset fields, append the first and second codes to the extended fields of the register, and retransmit it via the broadcast channel until an acknowledgment frame is received; or: if the retransmission exceeds a certain number of times, determine that the fault node has no processing value.

[0075] The optimized technical solution provided in steps S31 to S32 adopts the principle of identifying faulty nodes and issuing supplementary data acquisition instructions through closed-loop link missing detection and encoding mapping. Step S31 is used to map the coordinates of the faulty node ID, query the topology map index, and perform encoding mapping. Step S32 constructs a fault message, broadcasts extended fields, and performs retransmission control, thereby achieving the goal of accurately locating faulty nodes and efficiently acquiring supplementary data.

[0076] The coordinate mapping table in step S31 works in conjunction with the topology map index to quickly associate the physical location and logical code of the faulty node, forming a mapping relationship between the first and second codes and the faulty node, thus improving the efficiency of fault tracing. The message construction and retransmission mechanism in step S32 is based on the dual-code information (first and second codes) in step S31 to ensure the integrity of the supplementary sampling instruction.

[0077] The encoding buffer in step S31 and the confirmation frame feedback in step S32 corroborate each other, and can be integrated with the optimization technical solutions provided in steps S231 to S233 to form a new implementation method, constituting a multi-level fault-tolerant system. The integrated optimization technical solution solves the problems of ambiguous fault node positioning and low re-sampling efficiency caused by missing sensor information.

[0078] As a further improvement to the optimized technical solution for steps S31 to S32, in order to prevent the problem of insufficient real-time performance and fault tolerance of coordinate mapping in step S31, and to prevent the repetition mechanism in step S32 from causing broadcast storms (exacerbating conflicts during network congestion), the following steps can be added to some implementations for improvement:

[0079] Before querying the coordinate mapping table, the version number of the topology software and the hash value of the topology graph are verified. If the version number of the topology software does not match, the topology synchronization protocol is used to update the local coordinate mapping table before the query is executed.

[0080] The BEB algorithm based on IEEE 802.11 dynamically adjusts the retransmission delay according to the current channel load, limits the maximum lifespan or maximum number of transmissions of IP packets, DNS records or cached data, and performs retransmission only after determining the threshold of the maximum lifespan or maximum number of transmissions.

[0081] In the further improvements to steps S31 and S32 described above, a pre-step is added. This pre-step employs consistency verification and dynamic conflict backoff. Before querying the coordinate mapping table, a consistency verification is performed on the topology software version number and the topology graph hash value. If a mismatch is found, the local coordinate mapping table is immediately updated using the topology synchronization protocol, thus ensuring the real-time performance and fault tolerance of the mapping information. Simultaneously, during the data retransmission phase, based on the IEEE 802.11 BEB algorithm, the backoff window is dynamically adjusted according to the real-time channel load, and a threshold is set before retransmission. This threshold is used to record the longest survival time or maximum number of transmissions for IP packets, DNS records, or cached data, effectively suppressing broadcast storms and congestion conflicts. The improved technical solution ensures that the coordinate mapping upon which retransmission decisions rely is always accurate, and reduces the frequency and duration of retransmissions when the network is congested. This achieves multiple technical effects, improving both the real-time performance and fault tolerance of the mapping while avoiding retransmissions that exacerbate network conflicts. It solves the problems of coordinate mapping failures caused by inconsistent topology versions and broadcast storms and increased network congestion caused by indiscriminate retransmissions.

[0082] like Figure 6 As shown, as a further improvement to the embodiment of this application, in step S4, the location of the node with missing sensor information and the supplementary acquisition command are repeatedly detected. If the faulty node still has missing sensor information when the number of detections reaches a threshold, a corresponding detection path is established, an inspection topology route is generated, and an early warning information is output. This further includes:

[0083] Step S41: When data loss is detected, a list of faulty nodes is established and the frequency of data acquisition command transmission is controlled. Nodes whose missing data counter reaches a threshold are marked as faulty nodes. A closed-loop detection path for the faulty nodes is generated, and the topological connection relationship of the topology graph region is updated. In some implementations, the frequency of data acquisition command transmission and the generation of closed-loop detection paths for faulty nodes can be controlled using the exponential backoff algorithm and Dijkstra's algorithm, respectively.

[0084] Step S42: Extract the corresponding location coordinates and node identifiers of the confirmed faulty nodes to generate a multi-dimensional early warning information packet; push the multi-dimensional early warning information packet via the MQTT protocol and store the fault log locally, while establishing an inspection topology route. In step S42, the multi-dimensional early warning information packet includes map coordinates. MQTT is a collision avoidance strategy. The lightweight publish / subscribe messaging protocol based on MQTT can run on top of the TCP / IP protocol. After each retransmission failure, the retransmission interval is extended exponentially (2^n), with an upper limit capped. Over time, the retransmission frequency is exponentially reduced, effectively suppressing network congestion.

[0085] The optimized technical solution provided in steps S41 to S42 implements an intelligent inspection and early warning method for fault nodes. Steps S41 to S42 adopt a dynamic detection path reconstruction and multi-dimensional information collaborative push approach to control the frequency of supplementary sampling and reduce network load. The distribution pattern of fault nodes is discovered through the established closed-loop path, and the consistency between the generated inspection topology route and the actual distribution of fault nodes is ensured by dynamically updating the topology map. The real-time push of early warning information achieves the purpose of automated fault isolation and precise inspection scheduling, solving the problems caused by fault propagation due to the lack of repetitive sensor information, low efficiency of manual inspection, and delayed operation and maintenance response.

[0086] As a further improvement to steps S41 to S42, some implementations employ an exponential backoff algorithm to establish a fault point list and regenerate the closed-loop detection path of the fault node based on the Dijkstra algorithm. In step S41, the exponential backoff algorithm is used in conjunction with the retransmission mechanism in step S32 to avoid invalid supplementary sampling commands. The detection path generated by the Dijkstra algorithm, in conjunction with the coordinate mapping table in step S31, ensures optimal path after the topology map is updated. The fault node list and the inspection topology route are formed based on the closed-loop link, which can guide on-site personnel to quickly locate fault coordinates and achieve real-time early warning. The specific applications of the exponential backoff algorithm and the Dijkstra algorithm in steps S41 to S42 can be summarized as follows:

[0087] Step S43: Input data into the algorithm model, receive the closed-loop link list L of the current topology graph, the actual frame count vector C of the buffer queue, and the expected frame count vector E; if there exists C[i]≠E[i], then add the node i to the list of faulty nodes F, and initialize the missing counter m[i]=1 for each faulty node.

[0088] Step S44, Exponential backoff frequency control: For each node i in F, calculate the backoff interval d[i] = base × 2^(min(m[i], maxBackOff)) based on m[i], where base is the preset base time slot and maxBackOff is the maximum backoff power. The supplementary sampling instruction of node i is issued at time t_i = t_0 + Σd[i], where t_0 is the time when the missing data is first detected.

[0089] Step S45: Generate a closed-loop path using Dijkstra's algorithm: Taking the faulty node i as the source, run Dijkstra's algorithm on the topology graph G=(V,E,w), where the edge weight w(u,v) = Euclidean distance(u,v) + λ·link failure probability(u,v), and λ is the reliability weight coefficient. The algorithm outputs the shortest closed loop P[i] starting from i and returning to i, and the path length is denoted as D[i]. It is worth noting that although it is possible to weight and sum variables with different dimensions in engineering, for greater rigor, in some implementations, the physical meaning of λ in step S45 needs to be defined as: how many meters of distance is equivalent to every 1% failure probability. By adding a rigorous definition of the physical meaning of λ, the formula will be more reasonable when deriving.

[0090] Step S46, Topology update: Merge the edge set of P[i] into the original topology graph E to form the updated E′. If P[i] introduces a new edge, update the list of polygon boundary coordinates of the graph region and synchronize it to the global topology library of the property system.

[0091] In step S47, if the data is still missing after each supplementary sampling instruction is sent, (m[i]+1) is assigned to m[i], and steps S44 to S46 are repeated. When m[i] ≥ the fault threshold T_fault, node i is marked as a permanent fault, and i and its associated edges are deleted from the topology graph.

[0092] The Exponential Backoff algorithm controls the interval between retry operations to avoid network congestion or resource contention caused by frequent requests. The core mechanism of the Exponential Backoff algorithm includes an initial delay, exponential growth, an upper limit, and a termination condition. In the Exponential Backoff algorithm, an initial waiting time (e.g., `T=1s`) is set. After each failed retry, the delay time increases exponentially (`T = T * 2^n`, where `n` is the number of failures). A maximum delay time (e.g., `T_max=32s`) and a maximum number of retries (e.g., `N_max=5`) are set. If the termination condition is met, retries stop upon receiving a response; otherwise, the operation is abandoned after reaching the maximum number of retries.

[0093] Dijkstra's algorithm is used to calculate the single-source shortest path in a weighted graph, finding the optimal path between two points. The computation steps of Dijkstra's algorithm include initialization, iterative processing, and a termination condition. Initialization sets the distance to the starting point to 0 and the distances to other nodes to ∞. All nodes are added to the set to be processed. The node with the shortest current distance is selected from the set. The adjacent nodes of the node with the shortest current distance are traversed, and the shortest distance of each node is updated. The algorithm continues until all nodes have been processed or the target node is marked as having a determined shortest path.

[0094] The optimized technical solution provided in steps S43 to S47 employs a hierarchical processing approach for faulty nodes and a self-repairing method for closed-loop paths. It accurately detects and locates faulty nodes and intelligently sends supplementary sampling commands. A highly reliable closed-loop path is generated using an improved Dijkstra algorithm, and the topology is dynamically updated. A fault escalation mechanism enables resource recovery, achieving rapid fault isolation and continuous stable system operation. The improved technical solution controls the supplementary sampling frequency for fault detection through exponential backoff and Dijkstra's algorithm, avoiding network overload. The two algorithms work together to reconstruct the optimal detection path after a fault occurs in the environmental data monitoring and processing system, ensuring long-term continuous and stable system operation.

[0095] For the method steps disclosed in the above embodiments, the method steps are described as a series of actions for the purpose of simplicity. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily necessary for the embodiments of this application.

[0096] Any flowchart or other description of a process or method can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a specific logical function or process. Furthermore, the scope of preferred embodiments of this application includes additional implementations in which functions may be performed and implemented not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, or in accordance with program structures such as loops, branches, etc., to execute computer instructions and implement corresponding functions. This is something that those skilled in the art would readily understand when implementing embodiments of this application.

[0097] like Figure 7 The environmental data monitoring and processing system shown is used to implement the environmental data monitoring and processing method described in any specific embodiment of the present application, including:

[0098] The data acquisition node encoding generation module is used to acquire the target monitoring area, deploy distributed data acquisition nodes within the target monitoring area, the distributed data acquisition nodes including monitoring sensors and data acquisition nodes, and encode the distributed data acquisition nodes to generate a first code and a second code.

[0099] The topology region node generation module has a topology map graphic area corresponding to the monitoring area with the first code and a topology map node area corresponding to the second code. It connects adjacent topology map node areas to form a node link. If the node link is a closed loop link, it acquires the sensing information of the acquisition node on the closed loop link and detects the integrity of the sensing information.

[0100] If the closed-loop link detection module detects missing sensing information on the closed-loop link, it sends a supplementary sampling command to the monitoring sensor to obtain the location of the fault node with missing sensing information and records the first code and the second code corresponding to the location of the fault node.

[0101] The inspection and early warning output module repeatedly detects the location of nodes with missing sensor information and the supplementary sampling command. If the faulty node still has missing sensor information when the number of detections reaches a threshold, a corresponding detection path is established, an inspection topology route is generated, and an early warning information is output.

[0102] The implementation methods of the system described above are merely illustrative. For example, the various functional modules, units, or subsystems within the system may or may not be physically separate, or they may or may not be physical units; that is, they may be located in the same place or distributed across multiple different systems and their subsystems or modules. Those skilled in the art can select some or all of the functional modules, units, or subsystems to achieve the objectives of the embodiments of the present invention according to actual needs. Those skilled in the art can understand and implement the above-described situations without any creative effort.

[0103] like Figure 8 As shown, in addition to providing an environmental data monitoring and processing method and system, this application also provides corresponding electronic devices and storage media:

[0104] An electronic device includes: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of an environmental data monitoring and processing method.

[0105] A computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of an environmental data monitoring and processing method.

[0106] Explanation of reference numerals in the attached drawings: processor 710, memory 720, input device 730, output device 740.

[0107] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. For example... Figure 8 The structure shown in this embodiment of the invention includes an electronic device comprising one or more processors 710 and a memory 720; the processors 710 in this electronic device may be one or more. Figure 8Taking a processor 710 as an example; a memory 720 is used to store one or more programs; the one or more programs are executed by the one or more processors 710, so that the one or more processors 710 implement the environmental data monitoring and processing method as described in any one embodiment of the present invention.

[0108] The electronic device may also include an input device 730 and an output device 740.

[0109] The processor 710, memory 720, input device 730, and output device 740 in this electronic device can be connected via a bus or other means. Figure 8 Taking the example of a connection between China and Israel via a bus.

[0110] The memory 720 in this electronic device serves as a computer-readable storage medium, capable of storing one or more programs. These programs can be software programs, computer-executable programs, or modules, such as the program instructions / modules corresponding to the environmental data monitoring and processing method provided in this embodiment of the invention. The processor 710 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory 720, thereby implementing the environmental data monitoring and processing method described in the above embodiment.

[0111] The memory 720 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device. Furthermore, the memory 720 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 720 may further include memory remotely located relative to the processor 710, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0112] Input device 730 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 740 may include display devices such as a display screen.

[0113] Furthermore, when one or more programs included in the aforementioned electronic device are executed by one or more processors 710, the programs perform all the steps of the environmental data monitoring and processing method.

[0114] In the description of the embodiments of this application, the reference to terms such as "an embodiment," "example," "specific example," etc., means that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0115] Furthermore, the technical solutions of the various implementation methods in this application can be combined with each other, but only if they are based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the embodiments of this application.

[0116] All features disclosed in the embodiments of this application, or all steps in the disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps. Any feature disclosed in the specification of the embodiments of this application, unless specifically stated otherwise, may be replaced by other equivalent or similar alternative features. That is, unless specifically stated otherwise, each feature is merely one example of a series of equivalent or similar features. Throughout the specification, the same reference numerals indicate the same elements.

[0117] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification of embodiments (including the corresponding claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification of embodiments (including the corresponding claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of this application, and are not intended to limit them. Although the embodiments of this application have been described in detail with reference to the foregoing specific embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing specific embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this invention.

Claims

1. An environmental data monitoring and processing method, applied to an environmental data monitoring and processing system, characterized in that, include: The target monitoring area is obtained, and distributed acquisition nodes are deployed within the target monitoring area. The distributed acquisition nodes include monitoring sensors and acquisition nodes. The distributed acquisition nodes are encoded to generate a first code and a second code. The first code corresponds to the topology map graphic area of ​​the monitoring area, and the second code corresponds to the topology map node area. Adjacent topology map node areas are connected to form a node link. If the node link is a closed loop link, the sensing information of the acquisition node on the closed loop link is obtained, and the integrity of the sensing information is detected. If a missing sensor information is detected on the closed-loop link, a supplementary sampling command is sent to the monitoring sensor to obtain the location of the fault node with missing sensor information, and the first code and the second code corresponding to the fault node location are recorded. Repeatedly detect the location of the node with missing sensor information and the supplementary sampling command. If the faulty node still has missing sensor information when the number of detections reaches a threshold, then establish a corresponding detection path, generate an inspection topology route, and output early warning information.

2. The environmental data monitoring and processing method according to claim 1, characterized in that, The process of deploying distributed acquisition nodes within the target monitoring area includes: Acquire a monitoring dataset, which includes at least the node's communicable radius, node power consumption, and the two-dimensional plane coordinate range of the area to be monitored. Based on the monitoring dataset, an initial list of candidate node coordinates is generated within the two-dimensional plane coordinate range, with the communicable radius of the nodes as a constraint. The optimization algorithm module is invoked and the corresponding threshold is set to optimize the node coordinate list. The optimized node coordinate list is iteratively output, and a node deployment instruction file is generated based on the optimized node coordinate list. The node deployment instruction file is sent out one by one to the nodes to be deployed in the coordinate list of each node through the broadcast channel. When the node to be deployed sends back the instruction file confirmation frame, the deployment of the distributed acquisition nodes is completed.

3. The environmental data monitoring and processing method according to claim 2, characterized in that, In the process of optimizing the node coordinate list by calling the optimization algorithm module and setting the corresponding threshold, the corresponding threshold is set based on minimizing the total power consumption of the nodes and in combination with the redundancy of the communication links between adjacent nodes. When a node to be deployed sends back a confirmation frame of the instruction file, if any node to be deployed in the node coordinate list fails to send back a confirmation frame within a preset window period, the node to be deployed is confirmed to be in a "pending replacement" state, and the coordinates of the node to be deployed are recalculated in the initial candidate node coordinate list.

4. The environmental data monitoring and processing method according to claim 1, characterized in that, The first code corresponds to a topology map area of ​​the monitoring area, and the second code corresponds to a topology map node area. Adjacent topology map node areas are connected to form node links. If the node link is a closed loop link, the sensor information of the acquisition nodes on the closed loop link is obtained, and the integrity of the sensor information is detected. Further, this includes: Parse the first code to generate a list of polygon boundary coordinates for the topology graph region. Parse the second code using the list of polygon boundary coordinates to extract the node identifiers and center coordinates of adjacent topology graph node regions. Based on the node identifier and its center coordinates, detect whether the Euclidean distance of the topological node region is less than a preset threshold. If the Euclidean distance is less than the preset threshold, establish undirected edges between the node identifiers to form a node link and call the depth-first traversal algorithm to detect whether there is a closed loop link in the node link. If the closed-loop link is detected, a sensor information acquisition instruction is executed. This instruction acquires information from each data acquisition node on the closed-loop link. The actual number of sensor data frames received in the buffer queue of the communication link is calculated using this instruction. This number of sensor data frames is compared with the total number of nodes in the closed-loop link. If they are equal, the sensor information is deemed complete and the closed-loop link is marked as valid. If the two are not equal, a re-sampling process is triggered, and the acquisition command is resent to the faulty node until the sensor information meets the integrity requirements.

5. The environmental data monitoring and processing method according to claim 4, characterized in that, During the execution of the sensor information acquisition command, when a closed-loop link is detected, the distributed sensor information acquisition protocol is initiated, the improved Byzantine fault-tolerant algorithm is used to verify the authenticity of the node, and a sliding window statistical model of data arrival time is established based on time series analysis to identify abnormal nodes. Calculate the feature matching degree between the actual received data frames and the expected data frames in the buffer queue. The calculation process includes constructing the hash fingerprint feature vector of the data frames and / or using an SVM classifier to determine the integrity probability. The current feature matching degree is calculated based on the integrity probability. When the feature matching degree is lower than the threshold, an adaptive confirmation frame return strategy is initiated, and the sending parameters of the supplementary sampling command are dynamically adjusted based on network quality.

6. The environmental data monitoring and processing method according to claim 1, characterized in that, If a missing sensor information is detected on the closed-loop link, a supplementary sampling command is sent to the monitoring sensor to obtain the location of the fault node with missing sensor information, and the first and second codes corresponding to the fault node location are recorded, further including: Obtain the fault node ID, write it into the control system register, and use the coordinate mapping table to extract its planar coordinates as the location of the fault node. Based on the coordinates of the fault node, query the topology graph graphic area index table and the node area table in sequence to obtain the first code and the second code respectively and store them in the cache. Construct a message with the fault node ID, synchronization timestamp, and wake-up offset field, append the first and second codes to the extended field of the register, and retransmit it through the broadcast channel until an acknowledgment frame is received. Alternatively, if the retransmission exceeds a certain number of times, the fault node is determined to be of no value for processing.

7. The environmental data monitoring and processing method according to claim 1, characterized in that, The repeated detection of node locations with missing sensor information and the supplementary sampling command, if the faulty node location still has missing sensor information when the number of detections reaches a threshold, then a corresponding detection path is established, an inspection topology route is generated, and an early warning information is output, further including: When data loss is detected, a list of faulty nodes is established and the frequency of sending supplementary data collection instructions is controlled. Nodes whose missing data counters reach a threshold are marked as faulty nodes, closed-loop detection paths for faulty nodes are generated, and the topological connection relationships of the topology graph area are updated. Extract the corresponding location coordinates and node identifiers of the confirmed fault nodes to generate a multi-dimensional early warning information package; push the multi-dimensional early warning information package through the MQTT protocol and store the fault log locally, while establishing an inspection topology route.

8. An environmental data monitoring and processing system for implementing the environmental data monitoring and processing method according to any one of claims 1 to 7, characterized in that, include: The data acquisition node encoding generation module is used to acquire the target monitoring area, deploy distributed data acquisition nodes within the target monitoring area, the distributed data acquisition nodes including monitoring sensors and data acquisition nodes, and encode the distributed data acquisition nodes to generate a first code and a second code. The topology region node generation module has a topology map graphic area corresponding to the monitoring area with the first code and a topology map node area corresponding to the second code. It connects adjacent topology map node areas to form a node link. If the node link is a closed loop link, it acquires the sensing information of the acquisition node on the closed loop link and detects the integrity of the sensing information. If the closed-loop link detection module detects missing sensing information on the closed-loop link, it sends a supplementary sampling command to the monitoring sensor to obtain the location of the fault node with missing sensing information and records the first code and the second code corresponding to the location of the fault node. The inspection and early warning output module repeatedly detects the location of nodes with missing sensor information and the supplementary sampling command. If the faulty node still has missing sensor information when the number of detections reaches a threshold, a corresponding detection path is established, an inspection topology route is generated, and an early warning information is output.

9. An electronic device, characterized in that, include: The system includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method according to any one of claims 1 to 7.

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