The method involves calculating (S1) the optimal cluster number of the current round. The size of the competition radius is determined (S2) according to the candidate cluster head. The cluster head is selected (S3) after considering the residual energy value of the node and the degree of node connectivity. The adjacent cluster heads are screened and removed (S4) to complete final cluster head selection. The non-cluster first cognitive node is selected (S5) based on the cluster head distance and connection degree with respect to the cognitive node. The clustering is determined (S6) by data sensor node based on the distance to the cluster head, the degree of connectivity with respect to the data node, and the distance from the sink node. Heterogeneous nodes based low-energy adaptive clustering method for wireless cognitive sensor networks. The distribution of the cognitive nodes in each cluster is effectively balanced. The number of the cognitive nodes can be reduced as much as possible on the premise that enough high channel detection rate is guaranteed, so that the deployment cost is reduced to the maximum extent. The drawing shows a flowchart illustrating a heterogeneous nodes based low-energy adaptive clustering method for wireless cognitive sensor networks. (Drawing includes non-English language text) S1Step for calculating the optimal cluster number of the current roundS2Step for determining size of the competition radius according to the candidate cluster headS3Step for selecting cluster headS4Step for screening and removing adjacent cluster heads to complete final cluster head selectionS5Step for selecting non-cluster first cognitive nodeS6Step for determining clustering by data sensor node
The system has a wireless sensor network connected with a monitoring center that is connected with a mobile terminal and a satellite communication terminal. The wireless sensor network is provided with a convergent node and multiple sensor nodes. The sensor node collects an environment parameter. The convergent node collects the environment parameter from the sensor nodes and sends the environment parameter to the monitoring center. The sensor node is divided into multiple clusters, where the cluster is selected as a cluster head node. The sensor node is provided with a micro processor unit, a communication unit and a power supply management unit. Intelligent ocean vessel monitoring system. The drawing shows a block diagram of an intelligent ocean vessel monitoring system. '(Drawing includes non-English language text)'
The method involves constructing an initial scale free wireless sensor network topology. The initial scale free wireless sensor network topology is optimized to obtain the preliminary optimization of the wireless sensor network topology, according to the degree of each connection of independent edge nodes. The difference of three kinds of different connection modes of independent edge is accessed. The connection mode with the least degree difference is selected. The preliminary optimization of wireless sensor network topology is obtained. Wireless sensor network topology construction method. The topology construction of wireless sensor network is performed efficiently, and the robustness of the wireless sensor network is improved. The drawing shows a block diagram illustrating the wireless sensor network topology construction method. (Drawing includes non-English language text)
The system has a meteorological information acquiring device for acquiring meteorological information within an ocean monitoring area. The meteorological information acquiring device is provided with a wireless sensor network, where a sink node establishes the wireless sensor network. The meteorological information acquiring device is fixed with wireless sensor nodes, where the wireless sensor nodes are deployed in the ocean monitoring area. The wireless sensor node collects the meteorological information of the monitoring area. The sink node gathers the meteorological information collected by the wireless sensor nodes. The sink node sends the meteorological information to a visualization device to realize storage and display processes. Meteorological information visualization system. The drawing shows a block diagram of a meteorological information visualization system. '(Drawing includes non-English language text)'
The method involves calculating theoretical detection distance of a detection system at different directions according to sonar equation. Actual detection distance is obtained at the different direction through experimental measurement. Detection capacity coefficient is calculated according to the theoretical detection distance and the actual detection distance. Two nodes are selected in a network. A communication capacity coefficient is obtained according to communication delay between the nodes. Marine environment representation capability coefficient is obtained according to propagation loss between the nodes. Target characteristic characterization ability coefficient is obtained according to radiation noise level of cooperation target in different directions in test water. A detection performance evaluation value of a detection system is calculated. Method for evaluating underwater sound detection efficiency of a networking detecting system. The method enables evaluating system performance, and providing scientific reference evidence for optimizing configuration of the detection system. The drawing shows a flow diagram illustrating a method for evaluating underwater sound detection efficiency of networking detecting system. '(Drawing includes non-English language text)'
The method involves determining whether a candidate node is normally working in a cluster node. A rest spare node is selected as a user node for collecting and transmitting sensing data to a cluster head. The sensing data is transmitted to a base station by the cluster head. Determination is made to check whether the candidate node satisfies a cluster selection condition. Cluster coverage proportion is calculated when cluster coverage proportion is greater than first preset threshold. A cluster head node is selected when the candidate node satisfies the cluster selection condition. A current cluster node is selected from a cluster when cluster coverage proportion is less than second preset threshold. Wireless sensor network area coverage monitoring cluster head selecting method. The method enables improving selection of clusters and lifetime of a wireless sensor network, reducing area consumption, facilitates cluster node energy consumption, enhances sensor node sensing range to completely overlap characteristic and sensing range and efficiently completes related work of cluster head selecting. The drawing shows a schematic view of a wireless sensor network area coverage monitoring cluster head.
The method involves dividing (S1) original data packet into multiple data blocks in first underwater communication node. The data block is encoded to obtain a coded packet by performing a predetermined encoding operation (S2). Data window size is measured (S3). The coded packet is transmitted in a data window in a second underwater acoustic communication node (S4). State and setting time threshold value is received in the first underwater communication node (S5). Acknowledgement information of the coded packet is obtained to reconstruct the original data packet in the second underwater communication node until the original data packet is generated (S6). INDEPENDENT CLAIMS are also included for the following:a reliable underwater wireless communication systema wireless remote control underwater robot system. Underwater reliable wireless communication method. The method enables improving channel utilization ratio and transmission efficiency, and reducing transmission data time cost. The drawing shows a flow diagram illustrating an underwater reliable wireless communication method. '(Drawing includes non-English language text)' S1Step for dividing original data packet into multiple data blocksS2Step for encoding data blockS3Step for measuring data window sizeS4Step for transmitting coded packetS5Step for receiving state and setting time threshold valueS6Step for obtaining acknowledgement information
The method involves selecting a relay step for clusters according to a remaining energy information of nodes and a distance associated with a cluster head node and a base station, and selecting a relay node from nodes by a particle swarm algorithm. The cluster head node or the relay node is selected as a normal node, and communication rules including schedules are established by receiving a data sent by a common node and by performing a fusion by the cluster head node. The fused data is sent to the relay node by the cluster head node. The fused data is sent to the base station by the relay node. An INDEPENDENT CLAIM is also included for a particle swarm-based wireless sensor network hierarchical clustering system. Particle swarm-based wireless sensor network hierarchical clustering method. The method enables considering the influence of residual energy and distance while selecting the cluster head node and the relay node, so that a reasonable selection of the relay node reduces the influence of energy depletion and improves the network work performance and stability. The drawing shows a flow diagram illustrating a particle swarm-based wireless sensor network hierarchical clustering method. '(Drawing includes non-English language text)'
The device has a damage detection subsystem (1) that is provided with wireless sensor network composed of a sink node and sensor nodes. The sensor nodes monitor and sense dangerous portions of the long-span bridge. The sink node gathers large span bridge dangerous portion data collected by sensor node and sends the gathered data to a data storage subsystem (2). A data analyzing sub-system (3) obtains the dangerous portion large-span bridge sensing data from the data storage subsystem, analyzes and processes the large-span bridge dangerous portion sensing data. Intelligent monitoring device for large-span bridge structure damage. The safety monitoring of the long-span bridge structure can be realized, and the collected data processed through the data analysis subsystem. The system structure is simple, the monitoring precision is high, and the human and material resources can be effectively saved. The drawing shows a block diagram of the intelligent monitoring device for large-span bridge structure damage. (Drawing includes non-English language text) 1Damage detection subsystem2Data storage subsystem3Data analyzing sub-system
The system has sensor nodes (1) that are set in underwater environment. The underwater base stations are set with sensor nodes in centralized manner, for collecting underwater information detected by sensor nodes. Underwater base station control unit is set for centrally managing underwater base stations installed in underwater environment. The control unit is set for estimating distance between underwater base station and underwater sensor node, and controlling specific frequency bands (41-48) selection to-be-assigned to arbitrary sensor node, based on estimated distance value. Underwater communication system for monitoring marine exploration of resources, marine environment and underwater military affairs defence. The communication with number of several sensor nodes can be efficiently performed. The underwater base stations are centrally managed by underwater base station control station, so that different frequencies are used in underwater communication between the underwater base station control station and the underwater base station. Thus the underwater sensor nodes and underwater base stations can be efficiently controlled by using different frequencies. The satisfaction of the user can be increased by allowing larger number of underwater sensor nodes to-be-utilized. The drawing shows a schematic diagram of underwater communication system. (Drawing includes non-English language text) 1Sensor node3Intermediate node41-48Frequency bands