135 results about "Wireless sensor networking" patented technology

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.

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 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 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.

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.

A node deployment method for time difference positioning and direction finding of internal and external field targets, which takes the weighted sum of the average positioning accuracy improvement of the internal field area positioning and the average direction finding accuracy improvement of the external field area as the objective function of the station deployment optimization, takes the wireless sensor sensing capability as the constraint condition, improves the coverage rate of the internal field area, and deploys the distributed nodes for time difference positioning and direction finding of internal and external field targets; after the optimization deployment of the application, in the case of the change of the external field target source position and RDOA measurement error, the average positioning accuracy of the internal field area, the average direction finding accuracy of the external field target, and the coverage rate performance of the internal field area are all significantly improved, which improves the coverage range of the wireless sensor network while taking into account the internal field target positioning and external field target direction finding of the key area.

The invention discloses a soil environment monitoring system based on a wireless sensor network, and relates to the technical field of soil environment monitoring, and the system comprises a sensing node module which is used for being installed in a to-be-monitored soil environment and is responsible for collecting environment data in soil; the interior of each sensing node is integrated with a sensor set through different sensors, the sensor sets are used for sensing various data in soil, and data transmission is carried out between the sensing nodes through a wireless sensor network. According to the soil environment monitoring system based on the wireless sensor network, the reliability of data transmission is ensured through redundancy transmission and automatic path switching, the data transmission delay condition is monitored in real time, a regulation and control decision is generated, and the timeliness of data transmission is ensured; when signals are attenuated in the transmission process, the monitoring system can automatically adjust the transmitting power and the receiving sensitivity, the signal quality and stability are improved, and the reliability of data transmission is ensured.

Provided in the present application is a lightweight encryption and authentication method for a wireless sensor network. The method comprises: a gateway node respectively generating a sensor ephemeral key and a user ephemeral key on the basis of a one-way hash function and a preconfigured physically unclonable function, and respectively sending to a user end and a sensor node the sensor ephemeral key, the user ephemeral key, a preconfigured sensor long-term key and a preconfigured user long-term key; and after the user end and the sensor node are registered, the user end performing identity authentication on identity information currently input by a user, and performing, on the basis of the identity information, mutual authentication between the user end, the gateway node and the sensor node, so as to send a sensor hash-based message authentication code and a user hash-based message authentication code to the sensor node on the basis of the authentication result, such that the sensor node and the gateway node perform key agreement and authentication to obtain a session key, and wireless sensor network communication can thus be performed on the basis of the session key, thereby effectively solving the problem of authenticating the security of a wireless sensor network.

The invention discloses a multi-source data-driven ecological protection and restoration method and system, and aims to solve the technical problems of contradiction between wetland and forest environment monitoring precision and cost, poor data transmission adaptability, and weak analysis model over-fitting and generalization ability. According to the method, a heterogeneous wireless ad hoc network driven by multi-source data is constructed, and a wireless sensor network and a Mesh network are fused, so that efficient sensing and reliable transmission of wetland and forest land environments are realized; low-cost sensor data is processed by adopting a machine learning and optimization theory, a lightweight environment intelligent detection model is established, an environment-sensitive wireless sensor MAC protocol is optimally designed, and the data transmission efficiency and reliability in a complex environment are improved. According to the method, the monitoring cost can be remarkably reduced, the accuracy and efficiency of ecological environment assessment and pest control and prevention are improved, technical support is provided for ecological protection and restoration, healthy tourism development and digital forest protection, and the method has important application value and social benefits.

The invention discloses a wireless sensor network scheduling method under DoS attack and a related device. The method comprises the following steps: initializing a network environment, evaluating a deep Q network, a target network and an experience playback buffer area; acquiring a state vector of each sensor node, and selecting a to-be-scheduled sensor node by adopting a scheduling strategy based on a deep Q network; modeling interaction between the selected node and a DoS attacker as a two-person zero sum game, solving Nash equilibrium and calculating a real-time channel packet loss probability; calculating an instant reward of the scheduling action based on the state vector, and updating the retention time of each node to obtain a new state after the action is executed; and storing the empirical data into a buffer area, updating and evaluating network parameters, periodically synchronizing to a target network, and determining an optimal scheduling strategy. According to the method, adaptive channel access control of the sensor nodes is realized, so that the state estimation precision of the wireless sensor network system is effectively guaranteed in an attack environment, and network resources and energy consumption are optimized at the same time.

The invention discloses a Cuckoo search algorithm-based network node interaction method and system, and the method comprises the steps: setting wireless sensor network parameters, constructing a node energy consumption model containing a free space and a multipath attenuation mode, and adaptively selecting an energy consumption mode according to the relation between a transmission distance and a threshold value; selecting a single-hop or multi-hop transmission mode according to the distance between the cluster head nodes and the base station, determining the optimal number of cluster heads, and optimally selecting the cluster head nodes by using a cuckoo search algorithm; and optimizing a data transmission path, and selecting a relay node through a fitness function to realize interaction with a core network control function node. The system comprises a network initialization and parameter configuration module, an energy consumption modeling module, a cluster head selection and optimization module and a path optimization and core network interaction module. According to the invention, network energy consumption can be effectively reduced, network life is prolonged, data transmission efficiency and network adaptability are improved, and intelligent network management is realized.

The application discloses a DV-Hop positioning method and system based on hop count and hop distance optimization, and relates to the technical field of wireless sensor network positioning. The method comprises the following steps: an anchor node broadcasts by using multiple communication radii to obtain an anchor node distribution degree variable and determine a hop count correction coefficient; the minimum hop count is corrected by using the hop count correction coefficient to obtain an optimized average hop distance of the anchor node; the average hop distance of an unknown node is calculated according to the optimized average hop distance of the anchor node; the estimated distance between the unknown node and the anchor node is calculated according to the calculated average hop distance of the unknown node and the corrected minimum hop count; and the position coordinates of the unknown node are calculated by using the least square method according to the estimated distance. The application can solve the problem that the node positioning error is relatively large in a network area with uneven distribution (such as a C-shaped or Z-shaped irregular network area), and meets the actual application requirements.

This invention relates to the field of transformer condition monitoring technology, specifically a transformer condition monitoring and protection system utilizing a wireless sensor network. The system includes a sensor optimization deployment module for determining the optimal physical installation location of each wireless sensor node within the wireless sensor network based on thermal imaging analysis of the transformer; and a data acquisition module for collecting transformer condition data through multiple wireless sensor nodes deployed at the optimal physical installation locations. This condition data includes at least temperature data, vibration data, and electrical parameter data. This invention obtains a continuous temperature change map of the transformer through thermal imaging analysis and employs algorithms for calculating the deflection angle and distance. Using the hotspot area with the largest temperature change rate as a benchmark, and combining this with the physical offset of the thermal field propagation, the optimal sensor installation location is calculated, overcoming the shortcomings of traditional manual sensor placement that relies on experience.

The application discloses a kind of identification methods of node in wireless sensor network, comprising: from wireless sensor network, any node is selected and recorded as main node;Through the broadcast RTS signal of main node, traverse all other nodes in wireless sensor network;The node that the back CTS signal received by main node is recorded as participant node is obtained;The interaction parameter between main node and each participant node is obtained;Based on cross-layer fuzzy algorithm, the initial evaluation value of each participant node is generated by processing interaction parameter, and initial evaluation total value is calculated based on initial evaluation value;Based on the Bi-LSTM+BBMO model pre-constructed, the transfer trust value of each participant node is generated by processing interaction parameter;The trust value of each participant node is calculated based on the trust value of main node, and trust total value is calculated based on trust value;According to initial evaluation total value and trust total value, the comprehensive evaluation of each participant node is calculated, and each participant node is judged and identified according to comprehensive evaluation;The application can identify node with high accuracy.

The application discloses a wireless sensor network distributed elastic clock synchronization method based on dynamic weight value updating, and comprises the following steps: step 1, each node of the wireless sensor network sends its current relevant parameter information to all neighbor nodes, and meanwhile, receives the information sent by the neighbor nodes; step 2, a distributed weighted clock synchronization algorithm is designed; step 3, a false data injection (FDI) network attack is identified; step 4, a time-varying reputation value rep is introduced ij (k) dynamically updating the weight value w ij , a security defense mechanism is designed to repair the communication channel disconnected due to the FDI attack, and elastic clock synchronization is realized; and step 5, the above steps 2-4 are repeated until the clock synchronization is finished. The application has good robustness and expandability, can be used for enriching the theory and application of the wireless sensor network clock synchronization, and provides a new idea for realizing clock synchronization.

This invention discloses a method for optimizing resource allocation in wireless sensor networks based on millimeter-wave wireless power transmission. The method includes the following steps: constructing a single-cell wireless sensor network model based on millimeter-wave energy harvesting; fixing power allocation coefficients and, with the objective of maximizing the total energy received by all wireless sensors, using coalition formation game theory to obtain the optimal wireless sensor grouping and antenna allocation; employing linear programming optimization to obtain the optimal power allocation for each wireless sensor within the energy harvesting time, maximizing the total harvested energy of all sensors; and utilizing the Lagrange dual multiplier method and KKT conditions to maximize system energy efficiency, obtaining the optimal allocation between uplink and downlink transmissions in the single-cell wireless sensor network model. This invention not only enables flexible beamforming to enhance the total received energy of wireless sensors in multi-sensor application scenarios but also improves the overall energy efficiency of the system.

The invention discloses a multi-agent system elastic consensus method and system with privacy protection capability, and relates to the technical field of computers. The method comprises the steps that in an initial security window period, privacy protection of an initial state of an intelligent agent is achieved through state decomposition, sub-state mixed updating and merging operation, in an environment with spoofing attack, a conventional intelligent agent filters malicious information in a mode of sorting and removing suspicious extreme values based on a weighted mean value sub-sequence reduction algorithm, and the privacy protection of the initial state of the intelligent agent is achieved. And updating the state based on the trusted neighbor set until a consensus is reached. According to the method, the privacy of the initial state of the intelligent agent can be protected while the unconstrained spoofing attack is resisted, the communication overhead is not increased, the calculation complexity is low, the convergence speed is high, and the method is suitable for resource-limited collaborative scenes such as an unmanned aerial vehicle cluster and a wireless sensor network.

The application discloses a bridge tunnel line shape and rigidity detection method and system based on an optical fiber sensing technology, relates to the technical field of bridge displacement monitoring, and comprises a fiber grating strain sensor, a fiber grating displacement sensor, a rigidity detection module, an acceleration sensor, an analog-digital conversion module, an amplification circuit module, a filter circuit module, a data processing module, a data transmission module, an interface module, a memory module, a display module, an alarm module, a clock module and a power module. The application realizes the functions of real-time monitoring of physical parameters such as bridge stress, bridge main bridge tower displacement, bridge vibration quantity, bridge vertical distance change quantity and displacement, data analysis and processing, bridge health state evaluation, bridge structure health early warning and the like by monitoring various parameters of the bridge in real time through a wireless sensor network, and effectively avoids various accidents.

The invention relates to the technical field of mine pressure monitoring, and discloses a novel mine pressure monitoring method based on a wireless sensor network and intelligent data analysis, and the method comprises the steps: collecting mine pressure data in a mine environment through the wireless sensor network; transmitting the encrypted data of the mine pressure data to a local data processing position through wireless communication; decrypting and analyzing the encrypted data at the local data processing position to obtain an analysis result of the encrypted data; performing mine pressure anomaly analysis on the analysis result to obtain a mine pressure risk level of the analysis result; performing early warning strategy matching on the mine pressure risk grade to obtain graded early warning information of the mine environment; by optimizing wireless sensor network deployment and a data acquisition process, mine pressure data can be efficiently acquired, timeliness and pertinence of mine pressure early warning are effectively improved, and powerful guarantee is provided for mine safety prevention and control.

The application discloses a method for extracting a stable clock from an indoor LED light signal, characterized in that a photodiode is used as a photoelectric detector to receive a light signal emitted by an indoor LED lamp, then photoelectric conversion is performed on the light signal to obtain a current signal, the current signal is subjected to current-voltage conversion and voltage amplification to obtain a low-voltage power distribution network double-frequency signal containing a direct current component and high-frequency noise, through band-pass filtering processing, setting of a voltage reference and a voltage comparator, a sinusoidal 100Hz clock signal extracted can be optionally shaped into a 100Hz square wave signal, which is used as a reference signal for calibration of a physical clock of a wireless sensor network node. The circuit is simple in implementation, the extracted sinusoidal and square wave clock signals have clear waveforms, and the frequency is accurate and stable.

This invention provides a dynamic networking anti-interference diagnostic method for GIS sensors based on the K-nearest neighbor algorithm, belonging to the field of power Internet of Things (IoT) communication technology. The method includes: collecting raw data of multi-dimensional communication link characteristics between GIS sensor nodes within a time sliding window of a set size and sliding step, and performing Z-score standardization; calling a dynamic anti-interference training sample library with online incremental learning and forgetting mechanisms; using an improved K-nearest neighbor classification model that incorporates a time decay factor, determining the current communication link status category in real time by calculating weighted Euclidean distance, employing an adaptive K-value selection strategy based on sample density, and using Gaussian kernel function weighted voting; and finally triggering targeted adaptive frequency selection networking strategies or hierarchical fault warning operations based on the determined category. This invention can effectively distinguish between environmental interference and hardware faults in strong electromagnetic environments of GIS, significantly improving the communication reliability and self-healing capability of wireless sensor networks.