Multifunctional Water Drop Energy Harvesting and Human Motion Sensor Based on Flexible Dual-Mode Nanogenerator Incorporated with Polymer Nanotubes

Huang, Long; Xu, Weiting; Zhao, Chenghan; Zhang, Yong Liang; Yung, Kai Leung; Diao, Dongfeng; Fung, Kin Hung; Hao, Jian

doi:10.1021/acsami.0c05136

Cited by 52 publications

(30 citation statements)

References 46 publications

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“…This leads to the loss of data received from the cluster head, which increases power consumption and network latency. 24,25 In addition, the cluster head component protects the base station and communicates with it, which consumes more energy than the member nodes, resulting in uneven power consumption. 26 Multi-hop data transmission methods between nodes can be combined during data transmission, sharing the weight of the cluster head and achieving the purpose of extending the life of the network.…”

Section: Energy-saving Scale-free Topology Model Eaem Methodsmentioning

confidence: 99%

Scale‐free topology security mechanism of wireless sensor network against cascade failure

Gao

Liu

et al. 2021

Int J Communication

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As the basic architecture of the Internet of things, wireless sensor networks are the most important technical means to detect data on the Internet of things, and their security is essential to the development and implementation of the Internet of things. The wireless sensor network based on the scale-free theory has strong fault tolerance when random nodes fail and can better adapt to the unsupervised and complex environment of wireless sensor networks.However, in a wireless sensor network with scale-free function, the unevenness of its degree distribution causes some nodes to be very critical in the network. Once attacked, it will cause major damage to the network. Selective promotion attacks are relatively common. At the network level, the attacker destroys the normal collection of network data by selectively losing information or not forwarding sensitive information, which is extremely harmful to the network using this function. In order to overcome the influence of excessive dependence on a single path on the balance performance of the network, starting from the entire network, a secure multi-path routing algorithm for wireless sensor networks based on scale-free topology is proposed. Through the analysis of the network topology, the highest degree network node can be found. Optimize the load factor, use digital watermarking technology to locate the network path packet loss rate, and perform Gaussian modeling on the packet loss rate. Then the routing loading function and the routing packet loss rate are used as the confidence model factors to create the routing confidence model. We must first establish a model, select the transmission path according to the received function, and then obtain the global optimal security sensor routing algorithm. Through the algorithm in this thesis, the security of the wireless sensor network is improved by 17%.

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Section: Energy-saving Scale-free Topology Model Eaem Methodsmentioning

confidence: 99%

Scale‐free topology security mechanism of wireless sensor network against cascade failure

Gao

Liu

et al. 2021

Int J Communication

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“…If the value is between TðnÞ and 1, then the node is a normal node; otherwise, this node is the cluster head node [10]. TðnÞ is calculated using the following method [11,12]:…”

Section: Wireless Sensor Network Algorithmmentioning

confidence: 99%

Simulation Training of E‐Sports Players Based on Wireless Sensor Network

Qian

2021

Wireless Communications and Mobile Computing

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The application of wireless sensors in sports competitions is becoming more and more common. This research mainly discusses the simulation training of e-sports players based on a wireless sensor network. Under the same experimental conditions, in order to avoid mutual influence and interference between the hand grip test and continuous endurance load, the exercise experiment for each subject was repeated twice. At the same time, the EMG signal collection and reaction time test during the endurance load are performed. All tests are data records before and after 40 minutes of the DOTA game competition. Before the start of each experimental test, the experimental equipment is calibrated and the parameters of the required indicators are set; the software was opened to run and checked whether it is normal; before the measurement, let the subjects perform simple preparation activities, train the subjects, and understand and be familiar with the action essentials required by the test to reduce the error. The original surface EMG signal recorded directly uses the built-in signal processing function in the MR-XP 1.08 master edition software to perform full-wave rectification and smoothing. Processing of original EMG data: firstly, the EMG signal during endurance contraction is intercepted. In order to exclude individual differences in sEMG indicators of different subjects, the starting point is the first rise of each subject to 60% MVC or 25% MVC. The arrival time is the end point. In e-sports, the reaction speed when the prompt is effective is significantly faster than when the prompt is invalid ( p < 0.05 ). At this time, the time interval between the cue prompt and the target stimulus is 500 ms. This study is helpful to improve the athletes’ technical and tactical level.

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“…Among them, c is the speed in vacuum [8]. Assuming that the node has unlimited energy storage capacity, the energy collected by the node in the time period [t 0 , t 0 + ΔT] is:…”

Section: Wireless Sensormentioning

confidence: 99%

Computer simulation algorithm of gymnastics formation change path based on wireless sensor

Chen

Kuang

2021

EURASIP J. Adv. Signal Process.

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Today with the rapid development of the information age, the exchange of science and technology has brought closer the closeness of countries, and our country has also begun to conduct in-depth research on WSN. This research mainly discusses the computer simulation algorithm of gymnastics formation change path based on wireless sensor. In this research, an improved Leader-Follower method is designed. In the research of gymnastics formation transformation of mobile nodes in the wireless sensor network environment, the traditional three types of nodes are divided into four categories according to the different formation responsibilities, namely, coordinator, beacon node, master mobile node (Leader), slave mobile node (Follower). After it accurately locates itself with the help of the information of the beacon node, the information should be sent out in the form of broadcast, and the coordinator sends the information to the host computer through the serial port for tracking display. In order to enable the mobile nodes in the network to keep the current gymnastic formation moving toward the target point after completing the gymnastic formation transformation, this paper uses the l-φ closed-loop control method to modify the gymnastic formation in real time. The method based on the received signal strength is selected to realize the positioning of the beacon node to the mobile node, and combined with the positioning engine in the core processor CC2431 of the mobile node, efficient and low-energy wireless positioning can be realized. Multiple mobile nodes coordinate with each other to control communication between each node in a wireless manner, and sense their own heading angle information through geomagnetic sensors, so as to make judgments and adjustments on the maintenance and transformation of the current gymnastics formation. During the formation change, after analysis, it is concluded that the maximum offset of Follower2 from the ideal path in the process of traveling to the desired position in the triangular queue is + 0.28 m. This research effectively realized the computer simulation of autonomous formation.

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Multifunctional Water Drop Energy Harvesting and Human Motion Sensor Based on Flexible Dual-Mode Nanogenerator Incorporated with Polymer Nanotubes

Cited by 52 publications

References 46 publications

Scale‐free topology security mechanism of wireless sensor network against cascade failure

Scale‐free topology security mechanism of wireless sensor network against cascade failure

Simulation Training of E‐Sports Players Based on Wireless Sensor Network

Computer simulation algorithm of gymnastics formation change path based on wireless sensor

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