310 results about "Wireless sensor network" patented technology

The invention discloses a traditional Chinese medicinal material standard base intelligent irrigation and fertilization method based on the Internet of Things and a decision making system, and relates to the technical field of agricultural informatization. Through multi-source data acquisition and intelligent analysis, the limitation of an existing irrigation and fertilization method is solved, accurate decision making and resource optimization are realized, comprehensive data are acquired by utilizing a soil moisture content sensor, a meteorological station and plant image acquisition equipment, and by combining principal component analysis, a long-short-term memory neural network and a block chain technology, the intelligent irrigation and fertilization method is realized. According to the system, the water and fertilizer requirements are accurately predicted, an irrigation and fertilization scheme is optimized, data credibility and traceability are ensured, meanwhile, real-time control and collaborative operation of equipment are achieved through edge calculation and a wireless sensor network, the resource utilization efficiency is improved, the production cost is reduced, and scientificity and sustainability of traditional Chinese medicine planting are remarkably improved.

The invention discloses a cable defect detection method of a binocular intelligent inspection robot, and relates to the field of image processing, and the method comprises the steps: firstly obtaining the state information of a cable, then carrying out the preprocessing and stereo matching of the image information of the cable, and then constructing a target detection and segmentation model; the target detection and segmentation model is adopted to detect and segment cable defects, and model sample data is updated in real time in an incremental learning mode; fusing the cable state information acquired by the infrared camera, the thermal imager and the wireless sensor network by using a multi-sensor data information fusion model; the cable is maintained and managed based on a detection result; according to the invention, the detection precision and accuracy can be improved, cables of different types and specifications can be handled, the adaptability and stability are ensured, and the real-time performance and accuracy of detection can be improved.

The invention relates to the technical field of component quality control, and discloses a remote component quality control system based on digital twin and wireless communication. A component data acquisition module of the system obtains multi-dimensional data of a to-be-monitored component through a wireless sensor network, and a component identification code is associated to generate a quality basic data set; the regional association analysis module establishes association mapping of adjacent components according to a spatial topological relation to form a quality association partition map; the environmental response evaluation module analyzes the influence degree of environmental factors on the performance of the component and generates an environmental response analysis report; the defect positioning module identifies problem points and constructs a defect distribution map; and the quality early warning module integrates the problem points and the associated parameters, marks the position of the potential safety hazard, and outputs a quality evaluation and risk early warning report. The system realizes remote and comprehensive control of component quality, and assists in timely finding and dealing with quality problems.

The invention discloses a wireless sensor network (WSN) target coverage method and device based on a chaos adaptive bat algorithm, and belongs to the technical field of wireless sensor network coverage. Aiming at the problems of limited communication range, poor adaptive capability and the like of the existing WSN, the method comprises the following steps of: initializing parameters, constructing a monitoring relation matrix to determine a fitness value, designing an adaptive inertia weight strategy, updating various parameters of a bat individual, and carrying out operations such as local search, adaptive adjustment of loudness and pulse emissivity and the like. And judging a termination condition to obtain an optimal solution in combination with an elitist strategy and chaos updating. The device comprises a network model construction module and the like and is used for executing the method. According to the method, the adaptive bat algorithm is adopted to establish the target coverage model, the elite strategy and chaos updating are combined, the algorithm is prevented from falling into local optimum, the stability is improved, the sensor node coverage area is effectively increased, the convergence speed is higher, the optimization capacity is stable, and the method is suitable for a WSN target coverage scene.

The invention discloses an evacuation path dynamic planning method and system based on an HPSO-IGWO algorithm, and relates to the technical field of fire safety and emergency evacuation. The system mainly comprises a fire information acquisition module, a data processing coordination module, a path planning module and an evacuation indication module. The fire information acquisition module acquires information such as the position, smoke concentration and temperature of a fire through a sensor, and transmits the acquired data to the data processing coordination module; the data processing coordination module sends the data to the path planning module, so that the evacuation path is planned and optimized by using an HPSO-IGWO algorithm, the path is dynamically adjusted according to the real-time condition of the fire, and the safety and optimality of the evacuation path are ensured; and finally, the path planning module sends the planned evacuation path information to each LED evacuation indicator through the wireless sensor network, and the indicators display the evacuation direction in real time according to the information sent by the server to guide people to evacuate along the planned path.

The invention discloses a positionable electrical fire wireless sensor network alarm system, and relates to the technical field of electrical fire monitoring, and the system comprises a fire positioning alarm platform, and the fire positioning alarm platform is in communication connection with the following modules: a wireless sensor network node module, a wireless sensor network node module and a wireless sensor network node module, electrical parameters and environmental data are collected in real time, sensor data are analyzed, environmental interference signals are filtered, and a front-end sensing data set is constructed; and the wireless communication transmission module is used for fusing a multi-source positioning technology of NB-IoT and wireless networking. According to the method, RSSI fingerprint positioning, TDOA time difference positioning and BIM map constraints are fused, the positioning precision in a complex building environment is improved, in addition, the system verifies the alarm position of an independent fire sensor in real time, if the deviation exceeds a threshold value, a secondary optimization process is automatically triggered, it is ensured that the positioning result meets the fire emergency standard, the fire confirmation time is remarkably shortened, and the fire emergency safety is improved. And a reliable basis is provided for rapid evacuation and fire extinguishing.

The invention relates to the technical field of wireless sensor networks, and discloses a transformer substation ground deformation sensor monitoring signal collecting and monitoring method, system and device and a medium, and the method comprises the steps: dividing monitoring areas and selecting corresponding types of sensors according to ground deformation risks of different functional areas of a transformer substation; constructing a multi-channel synchronous signal acquisition system, synchronously acquiring sensor signals through a clock synchronization technology, and dynamically adjusting the sampling frequency; a wireless communication network is adopted to transmit the collected data, and data transmission is carried out; processing and analyzing the data transmitted to the monitoring center, and establishing a ground deformation prediction system comprising a finite element model, a neural network model and a time sequence model; and setting an early warning threshold based on the real-time analysis result, triggering a corresponding early warning signal, and displaying the monitoring data and the early warning state through a visual interface. According to the method, a data transmission and processing mechanism is improved, rapid and stable data transmission is ensured, the ground deformation trend is analyzed in time through an efficient algorithm, a reliable basis is provided for safe operation of a transformer substation, and potential risks are early warned in advance.

The invention relates to the technical field of intelligent agriculture, in particular to an intelligent agricultural water-saving irrigation control system based on a wireless sensor network, which comprises the steps of acquiring crop information, judging an irrigation regulation and control stage, marking land parcels, reading marks, extracting serial numbers of associated acquisition points to divide data transmission priorities, humidity measurement values of different depths are extracted based on the priority list and compared with a crop root layer demand threshold value to identify a water layer needing to be supplemented, root layer types are distinguished according to the soil layer depth, intervals or continuous irrigation periods are set, and the water supply rhythm is arranged; water supply arrangement is read, and instruction contents such as plot numbers, starting and ending time and water supply depth are generated and combined into tasks capable of being continuously called. By monitoring the crop growth and the soil humidity in real time, the irrigation strategy can be accurately judged and dynamically adjusted to meet the water requirement of each stage, the crop root depth and the soil humidity are accurately matched, the irrigation periods of deep and shallow soil layers are optimized, and a flexible scheme is provided to improve the water resource utilization efficiency.

The invention provides a distributed anti-interference collaborative optimization method under a mine wireless network based on multi-agent reinforcement learning, and provides a distributed routing and interference suppression collaborative optimization solution for solving the problem that the communication reliability of a wireless sensor network is reduced due to transient electromagnetic interference generated by large-scale electrical equipment under a mine. According to the method, typical mine electromagnetic interference characteristics such as impulse noise and sweep frequency interference are integrated through multi-mode interference, a multi-agent reinforcement learning (MARL) architecture is designed, collaborative optimization of distributed routing and interference suppression is achieved, and interference source positioning, dynamic channel hopping and intelligent rerouting strategies based on spectrum sensing are included. The anti-interference routing protocol is intelligently and dynamically optimized, an interference area is effectively avoided while the shortest path is guaranteed, the anti-interference capability and the communication stability of the mine wireless sensor network are remarkably improved, and an interpretable and extensible intelligent communication solution is provided for a complex industrial environment.

The invention discloses an environmental pollution detection method and system based on a wireless sensor network, and relates to the technical field of environmental pollution monitoring, and the method comprises the steps: deploying a sensing node set in a to-be-monitored region, collecting and establishing node collection data, and analyzing and establishing self-calibration observation data through an edge calculation unit; configuring adjacent node communication to construct a wireless sensor network and form a temporary cluster; and according to the cluster reconstruction communication topology and the sampling frequency, executing data reconstruction acquisition, inputting a result and self-calibration observation data into a causal backtracking channel for verification, and outputting an environmental pollution detection result. The technical problems that a traditional air pollution detection method is difficult to adapt to a dynamically changing monitoring environment, monitoring coverage is incomplete, data collection precision is insufficient, and pollution sources cannot be traced are solved, air pollution detection coverage is more comprehensive, data are more reliable, the pollution sources can be traced, a complete process from detection to management is formed, and the detection efficiency is improved. And the technical effects of accurate evaluation and effective management and control are achieved.

The invention relates to the technical field of wireless sensor networks, in particular to a heterogeneous wireless sensor network coverage method for a mountain new energy construction site, which comprises the following steps of: constructing a three-dimensional mountain monitoring area, inputting related parameters and establishing a multi-target optimization model taking the non-coverage rate, the reciprocal of the connectivity rate and the minimum total energy consumption as targets; initializing a dung beetle population, dividing the dung beetle population into four classes, obtaining an initial coverage scheme, and screening a non-dominated coverage scheme solution set for storage; iteratively updating the positions of various types of dung beetles based on a multi-target dung beetle optimization algorithm; the current coverage scheme and the archive set are combined, the archive set is updated after non-dominated sorting, and dense solutions are discarded to guarantee diversity when the scale is over-scale; and outputting a solution set after the maximum number of iterations is reached, and selecting a target scheme to complete node deployment. The method is adaptive to complex mountain scenes, network coverage and communication quality are improved, energy consumption is reduced, local optimum is avoided, and mountain monitoring effects of high coverage, low energy consumption and strong adaptation are achieved.

This utility model discloses a low-power wireless sensor network monitoring device, including a housing, a signal transmitting mechanism, and a vibration monitoring mechanism. A fixed base is fixedly installed at the lower end of the housing, and the signal transmitting mechanism is fixedly installed at the upper end of the housing. The probe moves up and down along the inner wall of the fixed base due to the amplitude of the vibration. During the movement of the fixed base, the magnet at its upper end moves along the trajectory, thereby moving up and down inside the induction coil boss. In this process, electrical energy is generated. At the same time, the vibration monitoring mechanism detects the vibration signal. The electrical energy generated by the triggering mechanism and the vibration signal detected by the vibration monitoring mechanism are both transmitted to the signal transmitting mechanism. The electrical energy is used to wake up the signal transmitting mechanism and enable it to transmit the signal detected by the vibration monitoring mechanism. After the signal is transmitted, the signal transmitting mechanism enters sleep mode again, so that the device only transmits signals when vibration occurs, which greatly reduces the energy consumption of the device and allows the device to monitor for a long time.

Provided are a method and a device for reconstructing lost data of marine wireless sensor networks (MWSNs). The data reconstruction method includes following steps: establishing an initial topological structure of the MWSNs; using an improved hierarchical energy balance multipath (IHEBM) routing protocol to cluster network nodes; using an improved radial basis function neural network (RBFNN) to predict lost data of nodes in the cluster based on a clustering of the nodes; and using a centralized principal component analysis (PCA) method to compress and reconstruct data of a cluster head node in a process of data transmission from a cluster head to a ship base station.

This invention discloses a management system comprising access points, a plurality of expansion base devices, and a backend server. Each expansion base device includes an interface, a sensor, a wireless sensor network transceiver circuit, a wireless network transceiver circuit, and control circuitry. The interface is used to couple electronic devices. The sensor is used to measure values. The wireless sensor network transceiver circuit is used to receive and transmit data to other expansion base devices. The wireless network transceiver circuit is used to receive and transmit data to the access point. The backend server is communicatively connected to one or more of the access points and expansion base devices. The expansion base devices are interconnected to form a mesh network. The expansion base devices achieve efficient data transmission through the mesh network and wireless network.

The invention discloses a coal mine methane leakage early warning method and system based on a wireless sensor network, and relates to the technical field of leakage early warning. The method comprises the following steps: deploying a sparse sensor network in a coal mine area, and constructing a coal mine cloud picture; real-time data of a coal mine area are collected and transmitted back to the central control processor; if the real-time data represents that no leakage exists, but the real-time data is in a metastable critical state, carrying out directional sensing management by calling a mobile sensing component in the sparse sensing network; if the real-time data represents that leakage exists, a leakage verification assembly is triggered, the data are synchronized to a coal mine cloud picture, cloud picture network screening and superposition state definition based on leakage events are carried out, and leakage data are determined and leakage early warning management is carried out based on superposition state collapse of candidate leakage paths by introducing a walking operator. The technical problem that in the prior art, coal mine methane leakage monitoring depends on a fixed sensing point, and the leakage state cannot be dynamically tracked is solved, and the technical effect of coal mine methane leakage dynamic positioning is achieved.

This invention provides an energy-saving clustering routing method for wireless sensor networks based on improved multi-target ant colony optimization, comprising: Step 1, initialization; Step 2, determining the set of active sensor nodes in the current round; Step 3, completing network clustering; Step 4, maintaining the Pareto optimal path solution set; Step 5, repeating steps 2 to 4 until the maximum number of iterations is reached or the solution set converges, outputting the Pareto optimal path solution set as the routing scheme for network data transmission. This invention improves network energy efficiency and extends network lifetime by constructing a globally collaborative energy management framework that integrates sleep scheduling, cluster head election, and routing optimization, while ensuring the real-time performance and reliability of data transmission.

The application relates to a wireless sensor network hierarchical routing optimization method and system based on a quantum mound beetle mechanism, relates to the technical field of wireless communication, and aims to solve the technical problems of unbalanced energy consumption and short network life of a wireless sensor network in a traditional method. The technical points of the application include the following steps: establishing a wireless sensor network system model; determining the number of clusters and dynamically clustering, and simultaneously establishing a network node dynamic clustering cost function; initializing quantum mound beetle groups and setting parameters, and calculating the organic matter decomposition degree of all quantum mound beetles to determine the global optimal quantum position of the quantum mound beetle groups; quantum position evolution of the quantum mound beetles and obtaining the global optimal quantum position by using a selection mechanism; quantum mound beetle mechanism evolution termination judgment, outputting the current wireless sensor network cluster center; wireless sensor network dynamic cluster head election; and the wireless sensor network performing stable data transmission while updating the network state. The application effectively improves the energy consumption efficiency of the wireless sensor network and effectively prolongs the network life.

The invention discloses a multi-field coupling intelligent inclination angle plane physical similar simulation experiment system and method. The system comprises an experiment platform with a controllable inclination angle, a stress monitoring module, an optical deformation monitoring module and an acoustic emission monitoring module. The experiment platform realizes high-precision adjustment and stable maintenance of an inclination angle of + / -0.1 degree through cooperation of hydraulic drive and a mechanical lock. The stress module adopts a wireless sensor network to monitor a stress field; the optical module is used for measuring full-field displacement strain based on a CCD camera and a digital image related technology; and the acoustic emission module positions a rock stratum fracture signal through the probe array. The method comprises the steps of platform deployment, inclination angle adjustment, system debugging, synchronous mining monitoring and the like. According to the invention, inclination angle accurate control and multi-physical field information synchronous integrated acquisition are realized, and the system is suitable for inclined coal seam mining rock stratum movement and disaster mechanism research.

The application relates to the technical field of Internet of Things data processing, and discloses a local reasoning and abnormality detection method for a wireless sensor network, which comprises the following steps: constructing a hypergraph model according to a sensor node set in the sensor network and corresponding association relations, and defining an energy function; applying a sensitivity constraint to the potential function, so that the potential function satisfies a bounded difference condition; determining a constraint range of coupling strength and a truncation order m; performing local deterministic approximate reasoning to obtain a conditional edge probability of a target sensor node; calculating an abnormality score of the target sensor node, and performing abnormality detection. In the wireless sensor network, a hypergraph Gibbs model with a sensitivity constraint is constructed, and based on strong spatial mixing ensured by theory, the application realizes the probability reasoning of a deterministic error bound only by relying on a limited-step local communication, so that the explainable abnormality detection and positioning are completed on a resource-limited edge device.

The application discloses a robot attack-resistant positioning method based on geometric consistency voting and adaptive M estimation, and belongs to the field of wireless sensor network positioning. The method comprises the following steps: obtaining anchor node coordinates and ranging, and initializing a global positioning solution; enumerating three-anchor combinations to generate a sub-positioning solution, performing geometric consistency voting according to the deviation of the sub-positioning solution from the global positioning solution, assigning a credibility weight to the anchor node, and eliminating low-score nodes; calculating a residual error, adaptively determining an M estimation threshold value by using a median absolute deviation, and generating a robust weight by using a Tukey double weight function; fusing the two weights to obtain a comprehensive weight; constructing a weighted least square problem to update the global solution; and iterating until convergence. The application does not explicitly estimate attack values, and malicious nodes are inhibited by a double mechanism of geometric constraint and residual error statistics, is robust to different attack modes, is adaptive in parameters, and is convenient to implement in engineering.

The invention discloses a planar broadband quasi-isotropic antenna based on parallel transmission line coupled feeding. The planar broadband quasi-isotropic antenna comprises a dielectric substrate, an antenna patch radiation unit attached to the upper surface of the dielectric substrate and parallel transmission lines attached to the lower surface of the dielectric substrate. The antenna patch radiation unit is a pair of L-shaped microstrip patches which are symmetrical to each other; the parallel transmission lines are a pair of parallel microstrip lines and are located right below the pair of symmetrical L-shaped microstrip patches; and the antenna is used for carrying out coupled feeding on the L-shaped microstrip patch. This allows the antenna to produce two operating modes. By adjusting the structural parameters of the L-shaped microstrip patch and the parallel transmission line, the frequency points corresponding to the two working modes of the antenna are close to each other and fused, so that the antenna has the broadband working characteristic. The antenna has the advantages of planar structure, easy processing and manufacturing, wide bandwidth and the like, can effectively transmit or receive signals from all directions, and can be used in the fields of Internet of Things, wireless sensor networks and the like.

The invention discloses a lightweight modulation identification method and system based on sparse graph construction, a medium, equipment and a product in the technical field of wireless communication and artificial intelligence. The method comprises the following steps: carrying out data preprocessing on a received wireless communication signal to obtain a complex field signal; carrying out modulation identification on the complex field signal by utilizing a lightweight modulation identification model; carrying out local feature extraction on the complex field signal by utilizing a feature extraction module to obtain amplitude and phase coupled local space-time features; performing dimension reconstruction on the local spatial-temporal features to obtain reconstructed local spatial-temporal features; according to the reconstructed local spatial-temporal features, performing graph convolution processing and feature enhancement by using a graph convolution network based on a multi-connection strategy to obtain enhanced features; and classifying the enhanced features by using a classifier to obtain a modulation type. The method can be widely applied to real-time signal identification tasks in Internet of Things data transmission nodes, low-power-consumption wireless sensor networks, unmanned systems and edge intelligent gateways.

The invention relates to industrial wireless sensor network communication, in particular to a wireless sensor network self-adaptive routing method and device based on intelligent decision making. The data transmission stability and the operation life of the industrial Internet of Things system in a complex environment are effectively improved. Comprising the following steps: S1, performing periodic and event-driven data acquisition on each monitoring node in the industrial wireless sensor network; and S2, calculating a cluster head opportunity value of the node, and electing to generate a cluster head set according to the cluster head opportunity value. And S3, by taking the minimum residual energy of the path, the hop count and the link quality as optimization targets, constructing a multi-hop transmission path from the cluster head to the sink node through a routing discovery mechanism based on multi-target cost evaluation. And S4, dynamic switching of node states is controlled according to data characteristics and task importance, and energy consumption of the nodes is monitored in real time to be fed back to subsequent cluster head election and path optimization, so that global energy balance is realized.

Security protocols and techniques are provided to reduce security risks posed by anomaly traffic in a WSN. The WSN includes a WSN base station that communicates with one or more IoT servers over a 5G network or other backbone network. The WSN is managed by a WSN Central Office. The WSN base station monitors IoT traffic based on a detection model trained at a central office and detects the presence of anomaly traffic. Responsive to the detection of the anomaly traffic, the WSBS triggers a reconfiguration of the WSN to create a special path for the anomaly traffic to minimize the impact of the anomaly traffic on the WSN. Additionally, the central office can request the 5G network to update the NSI allocation to dedicate a network slice instance (NSI) for the anomaly traffic to segregate the anomaly traffic from the normal IoT traffic in the 5G network.

This invention relates to the field of infrared spectroscopy detection technology, specifically an in-situ online infrared spectroscopy detection system and method. The system includes: a biomimetic dynamic response material module, used to enhance probe contact pressure through temperature-responsive deformation and specifically capture target molecules through a molecularly imprinted cavity; a quantum-enhanced detection module, composed of a quantum dot infrared enhancement array and an optical phased array spectral scanning module, used to complete spectral acquisition of the molecularly imprinted cavity capture region; an AI-driven closed-loop control module, used to predict reaction paths in real time, optimize temperature / pressure / flow rate parameters, and trigger millisecond-level emergency quenching in case of anomalies; and a self-powered wireless sensor network, used to collect vibrational energy and be self-powered by a supercapacitor, combined with terahertz wireless communication for data transmission. This invention solves the three major bottlenecks of traditional technologies—low sensitivity, high latency, and the need for perforated wiring—through a biomimetic interface quantum-enhanced detection → cableless power transmission → AI millisecond-level decision-making closed loop.

The application discloses a method, device and electronic equipment for defending wormhole attack in a wireless sensor network, and belongs to the technical field of wireless communication. The method for defending wormhole attack comprises the following steps: dividing a weighted undirected graph corresponding to nodes in the wireless sensor network into a plurality of communities; reconstructing the weighted undirected graph by using a key node set in each community to obtain a reconstructed graph; simplifying the original large-scale network into a simplified network containing only key nodes by graph reconstruction, while retaining the key topological information of the original network, thereby providing a basis for efficient high-risk node pair selection. Further, high-risk node pairs corresponding to wormhole attacks are found from the reconstructed graph; the high-risk node pairs thus found are prone to be used by attackers to implement wormhole attacks with high concealment by using a selective forwarding method. Further, the high-risk node pairs corresponding to the wormhole attacks are defended, which can significantly improve the defense effect of the wormhole attack nodes deployed.

The invention belongs to the field of wireless communication and Internet of Things, and provides a wireless sensor network system based on star flash MESH, which comprises a wireless Mesh network formed by a plurality of nodes, and the nodes at least comprise one or more of star flash common nodes, star flash relay nodes, star flash fusion nodes and star flash low-power consumption nodes. According to the invention, through a hybrid node architecture and a double-loader design, low power consumption and high bandwidth requirements are considered, and high-speed services such as audio and video, firmware upgrade and the like are supported; end-to-end encryption and identity authentication are realized by adopting a national cryptographic algorithm, so that the network security is improved, and replay and man-in-the-middle attack are prevented; meanwhile, the protocol stack is designed in a layered mode, the modularization degree is high, and dynamic role configuration and flexible service expansion are supported; a quick relay mark and a sliding window anti-replay mechanism are introduced into a network layer, so that the forwarding efficiency is improved while the safety is ensured; eCDH and PIN authentication are combined in the network distribution stage, and safe and credible equipment network access and key management are achieved.

The invention discloses a smart agriculture wireless sensor network adaptive routing optimization method, which belongs to the technical field of wireless sensor networks, and comprises the following steps: calculating multi-party coverage metrics of a candidate routing scheme set according to a multi-objective function system; when the multi-party coverage metric reaches a dynamic multi-party coverage metric threshold, executing an adaptive activation operation, screening out a high-quality routing scheme to perform an enhanced clone operation, and generating a clone routing scheme; selecting an agricultural scene adaptive operator to perform mutation operation on the cloned routing scheme, generating a mutation routing scheme, and merging the mutation routing scheme into a candidate routing scheme set; executing improved multi-party non-dominated sorting and selection operation according to the multi-objective function system, and screening out a new candidate routing scheme set; and repeating iteration until an iteration termination condition is reached, and outputting the latest candidate routing scheme set as an optimal routing scheme set. According to the method, double optimization of agricultural production and operation benefits and network operation and maintenance cost can be realized.

This invention discloses a drip irrigation system based on the Q-learning method. The system comprises: a data acquisition module for installing pressure sensors at each outlet of the drip irrigation pipeline to collect water pressure data and record the terrain information at the outlet location; a Q-learning module for receiving the water pressure data and terrain information collected by the data acquisition module, learning based on the Q-learning algorithm to establish a correlation model between outlet water pressure and terrain, and outputting adjustment commands based on the model; a distributed wireless sensor network module for constructing a distributed wireless sensor network based on the water pressure values ​​generated by the Q-learning module, where each sensor node dynamically adjusts the network topology according to its own water pressure value and the communication status of adjacent nodes, achieving adaptive network construction and node management; and a control module for receiving the water pressure adjustment commands output by the Q-learning module and controlling the flow regulation device of the drip irrigation pipeline to ensure that each outlet reaches a preset water pressure balance.