Journal articles on the topic 'Wireless recharge'
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Joe Louis Paul, I., S. Sasirekha, D. Naveen Kumar D, and P. S. Revanth. "A Working Model for Mobile Charging using Wireless Power Transmission." International Journal of Engineering & Technology 7, no. 3.12 (July 20, 2018): 584. http://dx.doi.org/10.14419/ijet.v7i3.12.16434.
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Portable electronic devices are very popular nowadays. Almost all portable devices are battery powered, meaning that eventually, they all must be recharged–using the wired chargers currently being used. As the usage of these portable electronic devices is increasing, the demands for longer battery life are also increasing. These batteries need to be recharged or replaced periodically. It is a hassle to charge or change the battery after a while, especially when there is no power outlet around. Now instead of plugging in a cell phone, Personal Digital Assistant (PDA), digital camera, voice recorder, mp3 player or laptop to recharge it, it could receive its power wirelessly. The technology for Wireless Power Transmission or Wireless Power Transfer or Transmission (WPT) is in the forefront of electronic development. WPT systems are designed to transmit power without using wires more efficient than transmitting it while using wires. There could be large number of applications for wireless power systems. Hence, in this work, a wireless battery charger has been proposed for mobile phone charging which is expected to eliminate all the hassles with today’s battery technology. The advantage of this device is that it can wirelessly charge up the batteries which can save time and money in a long run for the general public.
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Chen, Chi-Chang. "Node-Gosper Island-Based Data Collection Method with Recharge Plan for Rechargeable Wireless Sensor Networks." MATEC Web of Conferences 201 (2018): 03001. http://dx.doi.org/10.1051/matecconf/201820103001.
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Because of recent advances in wireless power transfer technologies, several key topics of wireless sensor networks (WSNs) need to be revisited. Traditional data collection methods for WSNs typically consider the balance of power consumption among sensors as a critical design criterion for avoiding uneven power depletion in the networks. I propose a solution for the uneven power consumption problem of data collection over WSNs. I designed a node-Gosper island-based scalable hierarchical cluster transmission method in conjunction with a wireless recharge plan for data collection over rechargeable WSNs. For the recharge plan, I used a mobile wireless charger to visit and recharge the batteries of sensors located on different levels of node-Gosper curves with various frequencies. The duration of each recharging process for each layer of sensors was calculated to verify the feasibility of the proposed recharge plan. The simulation results indicate that my proposed data collection method outperforms several well-known data collection methods in terms of energy consumption.
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Chen, Chi-Chang. "A Novel Data Collection Method with Recharge Plan for Rechargeable Wireless Sensor Networks." Wireless Communications and Mobile Computing 2018 (2018): 1–19. http://dx.doi.org/10.1155/2018/7419182.
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Because of recent advances in wireless power transfer technologies, several key topics of wireless sensor networks (WSNs) need to be revisited. Traditional data collection methods for WSNs typically consider the balance of power consumption among sensors as a critical design criterion for avoiding uneven power depletion in the networks. I propose a solution for the uneven power consumption problem of data collection over WSNs. I designed a node-Gosper island-based scalable hierarchical cluster transmission method in conjunction with a wireless recharge plan for data collection over rechargeable WSNs. For the recharge plan, I used mobile wireless chargers to visit and recharge the batteries of sensors located on different levels of node-Gosper curves with various frequencies. The duration of each recharging process for each layer of sensors was calculated to verify the feasibility of the proposed recharge plan. The simulation results indicate that my proposed data collection method outperforms several well-known data collection methods in terms of energy consumption and that my proposed recharge plan is more efficient than previous approaches in terms of charge path length, number of alive nodes, and traveling efficiency.
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Campi, Tommaso, Silvano Cruciani, Francesca Maradei, and Mauro Feliziani. "Efficient Wireless Drone Charging Pad for Any Landing Position and Orientation." Energies 14, no. 23 (December 6, 2021): 8188. http://dx.doi.org/10.3390/en14238188.
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A wireless charging pad for drones based on resonant magnetic technology to recharge the internal battery is presented. The goal of the study was to design a robust, reliable and efficient charging station where a drone can land to automatically recharge its battery. The components of the wireless power transfer (WPT) system on board the drone must be compact and light in order not to alter the payload of the drone. In this study, the non-planar receiving coil of the WPT system is integrated into the drone’s landing gear while the transmitting pad is designed to be efficient for any landing point and orientation of the drone in the charging pad area. To meet these requirements, power transmission is accomplished by an array of planar coils integrated into the ground base station. The configuration of the WPT coil system, including a three-dimensional receiving coil and a multicoil transmitter, is deeply analyzed to evaluate the performance of the WPT, considering potential lateral misalignment and rotation of the receiving coil due to imprecise drone landing. According to the proposed configuration, the battery of a light drone (2 kg in weight and 0.5 kg in payload) is recharged in less than an hour, with an efficiency always greater than 75%.
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Prakash, P. Suman, M. Janardhan, K. Sreenivasulu, Shaik Imam Saheb, Shaik Neeha, and M. Bhavsingh. "Mixed Linear Programming for Charging Vehicle Scheduling in Large-Scale Rechargeable WSNs." Journal of Sensors 2022 (September 9, 2022): 1–13. http://dx.doi.org/10.1155/2022/8373343.
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Because wireless sensor networks (WSNs) have low-constrained batteries, optimizing the network lifetime is a primary challenge. Rechargeable batteries are a solution to prolong the lifetime of a sensor node instead of restricting their functionalities to save energy. Wireless energy transmitters have the added benefit of providing a charger for the batteries of the sensor nodes in the WSN. However, scheduling one or more charging vehicles efficiently to recharge multiple sensor nodes is challenging. In this context, this paper provides a solution to recharge the sensor nodes using charging vehicle scheduling in WSNs through a mixed linear programming approach. Initially, we identify a heuristic value of each sensor node based on their residual energy, distance from a charging vehicle, available data packets, and other metrics. Further, a set of nodes is recharged by identifying the best charging vehicle to prolong their lifetimes, as well as the lifetime of the network as a whole. We simulated the proposed approach using a Python simulator, tested using different performance metrics, and compared using the recently published works. We notice the superior performance of the proposed work under various metrics in time and query-driven WSNs.
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Saravanan, S. V. "Efficient and Energy Scheme for Wireless Rechargeable Sensor Network." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 2 (February 1, 2018): 265. http://dx.doi.org/10.11591/ijeecs.v9.i2.pp265-266.
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<span lang="EN-US">The wireless rechargeable sensor network is attractive crucial and important in recent years for the advancement of wireless energy communication skill. The previous explore shown that not all of sensors can be recharged due to the limitation of power capacity to mobile chargers can carry. If a sensor playing a critical role in a sensing task cannot function as usual due to the exhausted energy, then the sensing task will be interrupted. Therefore, this paper proposes a novel recharging mechanism taking the priorities of sensors into consideration such that mobile chargers can recharge the sensor with a higher priority and the network lifetime can be efficiently sustained. The priority of each sensor depends on its contribution to the sensing task, including the coverage and connectivity capabilities. Based on the priority, the sensor with a higher priority will be properly recharged to extend the network lifetime. Simulation results show that the proposed mechanism performs better against the related work in network lifetime.</span>
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Ijemaru, Gerald K., Kenneth L. M. Ang, and Jasmine K. P. Seng. "Mobile Collectors for Opportunistic Internet of Things in Smart City Environment with Wireless Power Transfer." Electronics 10, no. 6 (March 16, 2021): 697. http://dx.doi.org/10.3390/electronics10060697.
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In the context of Internet of Things (IoT) for Smart City (SC) applications, Mobile Data Collectors (MDCs) can be opportunistically exploited as wireless energy transmitters to recharge the energy-constrained IoT sensor-nodes placed within their charging vicinity or coverage area. The use of MDCs has been well studied and presents several advantages compared to the traditional methods that employ static sinks. However, data collection and transmission from the hundreds of thousands of sensors sparsely distributed across virtually every smart city has raised some new challenges. One of these concerns lies in how these sensors are being powered as majority of the IoT sensors are extremely energy-constrained owing to their smallness and mode of deployments. It is also evident that sensor-nodes closer to the sinks dissipate their energy faster than their counterparts. Moreover, battery recharging or replacement is impractical and incurs very large operational costs. Recent breakthrough in wireless power transfer (WPT) technologies allows the transfer of energy to the energy-hungry IoT sensor-nodes wirelessly. WPT finds applications in medical implants, electric vehicles, wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs), mobile phones, and so on. The present study highlights the use of mobile collectors (data mules) as wireless power transmitters for opportunistic IoT-SC operations. Specifically, mobile vehicles used for data collection are further exploited as wireless power transmitters (wireless battery chargers) to wirelessly recharge the energy-constrained IoT nodes placed within their coverage vicinity. This paper first gives a comprehensive survey of the different aspects of wireless energy transmission technologies—architecture, energy sources, IoT energy harvesting modes, WPT techniques and applications that can be exploited for SC scenarios. A comparative analysis of the WPT technologies is also highlighted to determine the most energy-efficient technique for IoT scenarios. We then propose a WPT scheme that exploits vehicular networks for opportunistic IoT-SC operations. Experiments are conducted using simulations to evaluate the performance of the proposed model and to investigate WPT efficiency of a power-hungry opportunistic IoT network for different trade-off factors.
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Wang, Qin, Hua Chen, Junwei Tian, Jia Wang, and Yu Su. "Biobjective UAV/UGV Collaborative Rendezvous Planning in Persistent Intelligent Task-Based Wireless Communication." Wireless Communications and Mobile Computing 2021 (August 13, 2021): 1–12. http://dx.doi.org/10.1155/2021/9578783.
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This paper addresses a multiobjective Unmanned Aerial Vehicle (UAV) and Unmanned Ground Vehicle (UGVs) collaboration scheduling problem in which UAVs must be recharged periodically during a persistent task, such as wireless communication and making aerial panoramic VR video by UAV. The proposal is to introduce a UGV/UAV cooperative system in which UAVs should be recharged by UGVs periodically, and also, the UGVs have to visit their task points expect for the recharge points. The objective of the problem is to schedule and plan paths with the tradeoff of path length and makespan for UAVs and UGVs. The mathematical model which can be considered a combinatorial multiobjective optimization problem is presented firstly, and the solution of the problem is composed of presubsolution and postsubsolution. The multiobjective adaptive large neighborhood is hybrid with the Pareto local search (MOALP) to resolve the problem. The experimental result shows that the proposed algorithm outperforms the compared algorithms on the rendezvous planning problem for UAVs and UGVs working collaboratively in intelligent tasks.
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Lee, Byunghun, and Yaoyao Jia. "Wirelessly-Powered Cage Designs for Supporting Long-Term Experiments on Small Freely Behaving Animals in a Large Experimental Arena." Electronics 9, no. 12 (November 25, 2020): 1999. http://dx.doi.org/10.3390/electronics9121999.
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In modern implantable medical devices (IMDs), wireless power transmission (WPT) between inside and outside of the animal body is essential to power the IMD. Unlike conventional WPT, which transmits the wireless power only between fixed Tx and Rx coils, the wirelessly-powered cage system can wirelessly power the IMD implanted in a small animal subject while the animal freely moves inside the cage during the experiment. A few wirelessly-powered cage systems have been developed to either directly power the IMD or recharge batteries during the experiment. Since these systems adapted different power carrier frequencies, coil configurations, subject tracking techniques, and wireless powered area, it is important for designers to select suitable wirelessly-powered cage designs, considering the practical limitations in wirelessly powering the IMD, such as power transfer efficiency (PTE), power delivered to load (PDL), closed-loop power control (CLPC), scalability, spatial/angular misalignment, near-field data telemetry, and safety issues against various perturbations during the longitudinal animal experiment. In this article, we review the trend of state-of-the-art wirelessly-powered cage designs and practical considerations of relevant technologies for various IMD applications.
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Fuller, Micah. "Wireless charging in California: Range, recharge, and vehicle electrification." Transportation Research Part C: Emerging Technologies 67 (June 2016): 343–56. http://dx.doi.org/10.1016/j.trc.2016.02.013.
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Gaddam, Sindhu, Ruhie ., Siva Naga Chethana Yasam, and Ranjith Kumar N. "Wireless Electric Vehicle Battery Charging System using PV Array." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 1031–37. http://dx.doi.org/10.22214/ijraset.2022.43916.
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Abstract: The rapid emergence and evolution of wireless power transfer technology (WPT) have led to the development of various electrical vehicle applications. One of these is the exploitation of the power from a photovoltaic (PV) array. This paper proposes a system that can extract the power from the PV array and recharge the electric vehicle's battery using a Series-Series compensated network. The use of the resonance phenomenon in transferring power efficiently has been widely acknowledged. Due to the presence of various reactive components, a frequency analysis of a series-series compensator is performed. A proposed system for analyzing the frequency of a wireless power transmission system is simulated in MATLAB Simulink software. The results of the study and the simulation are presented in this paper, which helps in validating the proposed system. The proposed system can be used in various climatic conditions to recharge an electric vehicle. In addition, the proposed system can be developed with closed-loop controllers to improve its performance. Keywords: PV array, H-bridge inverter, Rectifier, wireless power transfer, series-series compensation, photovoltaic, Battery, Transmitter, Receiver.
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Amin, Azka, Xi-Hua Liu, Muhammad Asim Saleem, Shagufta Henna, Taseer-ul Islam, Imran Khan, Peerapong Uthansakul, Muhammad Zeshan Qurashi, Seyed Sajad Mirjavadi, and Masoud Forsat. "Collaborative Wireless Power Transfer in Wireless Rechargeable Sensor Networks." Wireless Communications and Mobile Computing 2020 (June 30, 2020): 1–13. http://dx.doi.org/10.1155/2020/9701531.
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Wireless power transfer techniques to transfer energy have been widely adopted by wireless rechargeable sensor networks (WRSNs). These techniques are aimed at increasing network lifetime by transferring power to end devices. Under these wireless techniques, the incurred charging latency to replenish the sensor nodes is considered as one of the major issues in wireless sensor networks (WSNs). Existing recharging schemes rely on rigid recharging schedules to recharge a WSN deployment using a single global charger. Although these schemes charge devices, they are not on-demand and incur higher charging latency affecting the lifetime of a WSN. This paper proposes a collaborative recharging technique to offload recharging workload to local chargers. Experiment results reveal that the proposed scheme maximizes average network lifetime and has better average charging throughput and charging latency compared to a global charger-based recharging.
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Chen, Yingjue, Yingnan Gu, Panfeng Li, and Feng Lin. "Minimizing the number of wireless charging PAD for unmanned aerial vehicle–based wireless rechargeable sensor networks." International Journal of Distributed Sensor Networks 17, no. 12 (December 2021): 155014772110559. http://dx.doi.org/10.1177/15501477211055958.
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In wireless rechargeable sensor networks, most researchers address energy scarcity by introducing one or multiple ground mobile vehicles to recharge energy-hungry sensor nodes. The charging efficiency is limited by the moving speed of ground chargers and rough environments, especially in large-scale or challenging scenarios. To address the limitations, researchers consider replacing ground mobile chargers with lightweight unmanned aerial vehicles to support large-scale scenarios because of the unmanned aerial vehicle moving at a higher speed without geographical limitation. Moreover, multiple automatic landing wireless charging PADs are deployed to recharge unmanned aerial vehicles automatically. In this work, we investigate the problem of introducing the minimal number of PADs in unmanned aerial vehicle–based wireless rechargeable sensor networks. We propose a novel PAD deployment scheme named clustering-with-double-constraints and disks-shift-combining that can adapt to arbitrary locations of the base station, arbitrary geographic distributions of sensor nodes, and arbitrary sizes of network areas. In the proposed scheme, we first obtain an initial PAD deployment solution by clustering nodes in geographic locations. Then, we propose a center shift combining algorithm to optimize this solution by shifting the location of PADs and attempting to merge the adjacent PADs. The simulation results show that compared to existing algorithms, our scheme can charge the network with fewer PADs.
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Perumal, P. Shunmuga, V. Rhymend Uthariaraj, and V. R. Elgin Christo. "Novel Steam Powered Gravity Assisted Standalone Power System (SP-GA-SP System) Design for Remote Wireless Sensor Networks." Applied Mechanics and Materials 440 (October 2013): 248–53. http://dx.doi.org/10.4028/www.scientific.net/amm.440.248.
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Uninterrupted power supply through electrical grid is not possible for many remote areas like dense forest, hill areas, and deserts. The objective of the proposed work is to generate stand alone electricity using steam powered gravity assisted SP system for remote WSN applications. The proposed design drives the generator by triggering gravity force using steam powered cylinders with high thermal efficiency. The proposed SP system is used to recharge the battery systems of UAVs in remote sites thereby the UAVs are further used to recharge the remote wireless sensor nodes using laser beam transmissions.
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Qian, Qiuchen, Akshayaa Y. S. Pandiyan, and David E. Boyle. "Optimal Recharge Scheduler for Drone-to-Sensor Wireless Power Transfer." IEEE Access 9 (2021): 59301–12. http://dx.doi.org/10.1109/access.2021.3073076.
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Mohamed, Naoui, Flah Aymen, and Mohammed Alqarni. "Inductive Power Transmission System for Electric Car Charging Phase: Modeling plus Frequency Analysis." World Electric Vehicle Journal 12, no. 4 (December 19, 2021): 267. http://dx.doi.org/10.3390/wevj12040267.
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The effectiveness of inductive power transfer (IPT) presents a serious challenge for improving the global recharge system performance. An electric vehicle (EVs) needs to be charged rapidly and have maximum power when it is charged with wireless technology. Based on various research, the performance of this recharge system is attached to several points and the frequency resonance is one of those parameters that can influence. In this paper, we try to explore the relationship between the obtained power and the signal input frequency for charging a lithium battery, solve the class imbalance problem and understand the maximum allowed frequency. To obtain the results, a mathematical model was first created to demonstrate the relationship, then the dynamic model was validated and tested using the Matlab Simulink platform. The performance of the worldwide wireless recharging system in terms of frequency variation is depicted in a summary graph.
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Mohamed, Naoui, Flah Aymen, Zaafouri Issam, Mohit Bajaj, Sherif S. M. Ghoneim, and Mahrous Ahmed. "The Impact of Coil Position and Number on Wireless System Performance for Electric Vehicle Recharging." Sensors 21, no. 13 (June 25, 2021): 4343. http://dx.doi.org/10.3390/s21134343.
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Recently, most transportation systems have used an integrated electrical machine in their traction scheme, resulting in a hybrid electrified vehicle. As a result, an energy source is required to provide the necessary electric power to this traction portion. However, this cannot be efficient without a reliable recharging method and a practical solution. This study discusses the wireless recharge solutions and tests the system’s effectiveness under various external and internal conditions. Moreover, the Maxwell tool is used in this research to provide a complete examination of the coils’ position, size, number, and magnetic flux evolution when the coils are translated. In addition, the mutual inductance for each of these positions is computed to determine the ideal conditions for employing the wireless recharge tool for every charging application. A thorough mathematical analysis is also presented, and the findings clearly demonstrate the relationship between the magnet flux and the various external conditions employed in this investigation.
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Joshi, Shubham, T. P. Anithaashri, Ravi Rastogi, Gaurav Choudhary, and Nicola Dragoni. "IEDA-HGEO: Improved Energy Efficient with Clustering-Based Data Aggregation and Transmission Protocol for Underwater Wireless Sensor Networks." Energies 16, no. 1 (December 28, 2022): 353. http://dx.doi.org/10.3390/en16010353.
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With the emerging technology in underwater wireless sensor networks (UWSN), many researchers are undergoing this field since it cannot maintain the batteries and recharge them manually. Network duration should be taken into account because they can easily be recharged by a non-conventional resource like solar energy. When coming to the data collection process, clustering is an effective method to construct vitality effective UWSNs. The clustering properties of UWSNs differ from those of terrestrial wireless sensor networks (TWSNs) due to the sparse deployment of nodes as well as the dynamic nature of the channel. This paper proposes improved efficient data aggregation in a Hexagonal grid with energy optimization (IEDA-HGEO) protocol for effective data transmission with an optimal clustering process. It is further compared with ERP2R n energy-efficient routing protocol and EGRC (Energy-efficiency Grid Routing based on 3D Cubes). The three techniques mentioned above are specifically examined for their applicability to underwater communication, and their performance is compared in terms of energy consumption, efficiency, throughput, packet delivery ratio, and delay. The proposed method achieved the following metrics: delay 41%, energy consumption 48%, efficiency 95%, throughput 95%, and PDR 92%.
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Bharathan, Abhijeet, J. Premkumar, T. Sudhakar, J. Bethanney Janney, and Sindu. "Prosthetic Arm with Functional Fingers and Wireless Recharge on Walk Function." Journal of Physics: Conference Series 2318, no. 1 (August 1, 2022): 012025. http://dx.doi.org/10.1088/1742-6596/2318/1/012025.
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Abstract The efficiency, tactile features, and weight of prosthetic limbs have all improved over time, but the long charging period that comes with these benefits reduces their overall appeal. The purpose of this study is to incorporate a portable power source into the prosthetic arm in order to decrease downtime and increase reliability. The use of special footwear that serves as a regenerative power source for the prosthetic arm’s battery, a piezoelectric generator that generates energy while walking, and a charging station that transfers power directly to the prosthetic arm while on the move. The complete device allows the user to comfortably use the prosthetic arm for longer periods of time.
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Rao, Xunpeng, Yubo Yan, Maotian Zhang, Wanru Xu, Xiaochen Fan, Hao Zhou, and Panlong Yang. "You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger." IEEE Access 6 (2018): 47–59. http://dx.doi.org/10.1109/access.2017.2741220.
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Li, He, Quan Liu, Xiaopu Ma, Qinglei Qi, Jinjiang Liu, Pan Zhao, Yang Yang, and Xingang Zhang. "Cooperative Recharge Scheme Based on a Hamiltonian Path in Mobile Wireless Rechargeable Sensor Networks." Mathematical Problems in Engineering 2022 (May 19, 2022): 1–20. http://dx.doi.org/10.1155/2022/6955713.
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The energy problem and limited capacity of batteries have been fundamental constraints in many wireless sensor network (WSN) applications. For WSN, the wireless energy transmission technology based on magnetic resonance coupling is a promising energy transmission technology. To reduce the cost and energy consumption during charging in mobile wireless rechargeable sensor networks (MWRSNs), a cooperative mobile charging mechanism based on the Hamiltonian path is proposed in this paper. To improve the charging task interval, we study the use of a mobile charger (MC) as a mobile sink node to collect the data in this paper. Then, we used the sink and the charging sensors selected by the MC to construct the undirected complete graph. Finally, the Euclidean distance between nodes is used as the edge weight and a Hamiltonian loop is found by using the improved Clark–Wright (C-W) saving algorithm to solve the problem of charging a rechargeable sensor network. In addition to the energy usage efficiency (EUE) and the network lifetime, the average energy loss per unit time is considered as the evaluation index according to the impact of the MC on the energy consumption during charging. The simulation results show that the proposed scheme increases the average network lifetime, decreases the average energy loss per unit time, and improves the EUE.
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Silva, Pedro E. Gória, Nicola Marchetti, Pedro H. J. Nardelli, and Rausley A. A. de Souza. "Enabling Semantic-Functional Communications for Multiuser Event Transmissions via Wireless Power Transfer." Sensors 23, no. 5 (March 1, 2023): 2707. http://dx.doi.org/10.3390/s23052707.
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A central concern for large-scale sensor networks and the Internet of Things (IoT) has been battery capacity and how to recharge it. Recent advances have pointed to a technique capable of collecting energy from radio frequency (RF) waves called radio frequency-based energy harvesting (RF-EH) as a solution for low-power networks where cables or even changing the battery is unfeasible. The technical literature addresses energy harvesting techniques as an isolated block by dealing with energy harvesting apart from the other aspects inherent to the transmitter and receiver. Thus, the energy spent on data transmission cannot be used together to charge the battery and decode information. As an extension to them, we propose here a method that enables the information to be recovered from the battery charge by designing a sensor network operating with a semanticfunctional communication framework. Moreover, we propose an event-driven sensor network in which batteries are recharged by applying the technique RF-EH. In order to evaluate system performance, we investigated event signaling, event detection, empty battery, and signaling success rates, as well as the Age of Information (AoI). We discuss how the main parameters are related to the system behavior based on a representative case study, also discussing the battery charge behavior. Numerical results corroborate the effectiveness of the proposed system.
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Yang, Zhixiang, Lei Feng, Zhengwei Chang, Jizhao Lu, Rongke Liu, Michel Kadoch, and Mohamed Cheriet. "Prioritized Uplink Resource Allocation in Smart Grid Backscatter Communication Networks via Deep Reinforcement Learning." Electronics 9, no. 4 (April 8, 2020): 622. http://dx.doi.org/10.3390/electronics9040622.
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With the rapid increase in the number of wireless sensor terminals in smart grids, backscattering has become a very promising green technology. By means of backscattering, wireless sensors can either reflect energy signals in the environment to exchange information with each other or capture the energy signals to recharge their batteries. However, the changing environment around wireless sensors, limited radio frequency and various service priorities in uplink communications bring great challenges in allocation resources. In this paper, we put forward a backscatter communication model based on business priority and cognitive network. In order to achieve optimal throughput of system, an asynchronous advantage actor-critic (A3C) algorithm is designed to tackle the problem of uplink resource allocation. The experimental results indicate that the presented scheme can significantly enhance overall system performance and ensure the business requirements of high-priority users.
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Vien, Nguyen Duy-Nhat. "A Beamforming Algorithm for MIMO SWIPT Systems." JOIV : International Journal on Informatics Visualization 2, no. 3 (April 20, 2018): 110. http://dx.doi.org/10.30630/joiv.2.3.127.
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Efficient usage of energy resources is a growing concern in today’s communication systems. Energy harvesting is a new paradigm and allows the nodes to recharge their batteries from the environment. In this paper, we focus on the design of optimal linear beamformer for multi- input multi-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system. We formulate the problem of maximizing the information rate while keeping the energy harvested at the energy receivers above given levels. Finally, simulation results demonstrate the efficiency of the proposed algorithm.
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Wu, Yin, Bowen Li, Yongjun Zhu, and Wenbo Liu. "Energy-Neutral Communication Protocol for Living-Tree Bioenergy-Powered Wireless Sensor Network." Mobile Information Systems 2018 (2018): 1–15. http://dx.doi.org/10.1155/2018/5294026.
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The purpose of this paper is to represent a living-tree biological energy powered wireless sensor system and introduce a novel energy aware MAC protocol based on remaining energy level, energy harvesting status, and application requirements. Conventional wireless sensor network (WSN) cannot have an infinite lifetime without battery recharge or replacement. Energy harvesting (EH), from environmental energy sources, is a promising technology to provide sustainable powering for WSN. In this paper, a sensor network system has been developed which uses living-tree bioenergy as harvesting resource and super capacitor as energy storage. Moreover, by analyzing the power recharging, task arrangement, and energy consumption rate, a novel duty cycle-based energy-neutral MAC protocol is proposed. It dynamically optimizes each wireless sensor node’s duty cycle to create a balanced, efficient, and continuous network. The scheme is implemented in a plant surface-mounted bioenergy power wireless sensor node system called PBN, which aims to monitoring the plant’s growth parameters. The results show that the proposed MAC protocol can provide sustainable and reliable data transmission under ultralow and dynamic power inputs; it also significantly improves the latency and packet loss probability compared with other MAC protocols for EH-WSN.
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Cheng, Rei-Heng, ChengJie Xu, and Tung-Kuang Wu. "A Genetic Approach to Solve the Emergent Charging Scheduling Problem Using Multiple Charging Vehicles for Wireless Rechargeable Sensor Networks." Energies 12, no. 2 (January 17, 2019): 287. http://dx.doi.org/10.3390/en12020287.
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Wireless rechargeable sensor networks (WRSNs) have gained much attention in recent years due to the rapid progress that has occurred in wireless charging technology. The charging is usually done by one or multiple mobile vehicle(s) equipped with wireless chargers moving toward sensors demanding energy replenishing. Since the loading of each sensor in a WRSN can be different, their time to energy exhaustion may also be varied. Under some circumstances, sensors may deplete their energy quickly and need to be charged urgently. Appropriate scheduling of available mobile charger(s) so that all sensors in need of recharge can be served in time is thus essential to ensure sustainable operation of the entire network, which unfortunately has been proven to be an NP-hard problem (Non-deterministic Polynomial-time hard). Two essential criteria that need to be considered concurrently in such a problem are time (the sensor’s deadline for recharge) and distance (from charger to the sensor demands recharge). Previous works use a static combination of these two parameters in determining charging order, which may fail to meet all the sensors’ charging requirements in a dynamically changing network. Genetic algorithms, which have long been considered a powerful tool for solving the scheduling problems, have also been proposed to address the charging route scheduling issue. However, previous genetic-based approaches considered only one charging vehicle scenario that may be more suitable for a smaller WRSN. With the availability of multiple mobile chargers, not only may more areas be covered, but also the network lifetime can be sustained for longer. However, efficiently allocating charging tasks to multiple charging vehicles would be an even more complex problem. In this work, a genetic approach, which includes novel designs in chromosome structure, selection, cross-over and mutation operations, supporting multiple charging vehicles is proposed. Two unique features are incorporated into the proposed algorithm to improve its scheduling effectiveness and performance, which include (1) inclusion of EDF (Earliest Deadline First) and NJF (Nearest Job First) scheduling outcomes into the initial chromosomes, and (2) clustering neighboring sensors demand recharge and then assigning sensors in a group to the same mobile charger. By including EDF and NJF scheduling outcomes into the first genetic population, we guarantee both time and distance factors are taken into account, and the weightings of the two would be decided dynamically through the genetic process to reflect various network traffic conditions. In addition, with the extra clustering step, the movement of each charger may be confined to a more local area, which effectively reduces the travelling distance, and thus the energy consumption, of the chargers in a multiple-charger environment. Extensive simulations and results show that the proposed algorithm indeed derives feasible charge scheduling for multiple chargers to keep the sensors/network in operation, and at the same time minimize the overall moving distance of the mobile chargers.
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Inman, Daniel J., Justin Farmer, and Benjamin L. Grisso. "Energy Harvesting for Autonomous Sensing." Key Engineering Materials 347 (September 2007): 405–10. http://dx.doi.org/10.4028/www.scientific.net/kem.347.405.
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Autonomous, wireless structural health monitoring is one of the key goals of the damage monitoring industry. One of the main roadblocks to achieving autonomous sensing is removing all wiring to and from the sensor. Removing external connections requires that the sensor have its own power source in order to be able to broadcast/telemetry information. Furthermore if the sensor is to be autonomous in any way, it must contain some sort of computing and requires additional power to run computational algorithms. The obvious choice for wireless power is a battery. However, batteries often need periodical replacement. The work presented here focuses on using ambient energy to power an autonomous sensor system and recharge batteries and capacitors used to run an active sensing system. In particular, we examine methods of harvesting energy to run sensor systems from ambient vibration energy using piezoelectric elements.
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Kamalpreet Kaur, Naveen Goyal and Deepinder Singh Wadhwa. "A Review: Trending Clustering Protocols In WSN With Analyzing Their Complexity And Disadvantages." International Journal for Modern Trends in Science and Technology 7, no. 07 (February 20, 2022): 44–50. http://dx.doi.org/10.46501/ijmtst050237.
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Wireless Sensor Networks are generally consists of various static or mobile sensor nodes that create a self-organized system in a multi-hop manner. Wireless Sensor Networks are considered as the main component to analyze the surroundings so as to utilize the sensor data for further processing such as weather prediction, health related predictions of a patient, traffic control and so forth. In these conditions, the network’s sensor nodes are estimated to perform individually in the field for a long time, as it is not possible to recharge or replace the battery of the sensor nodes. Therefore, the depletion of a single sensor node may affect the processing of the entire network. Due to early energy depletion of the nodes, the concept of Cluster Head (CH) selection have included.This concept has a major impact on energy utilization of the network. Several clustering protocols, and optimization techniques are used formaintaining the energy efficiency in wireless sensor network and few of them are discussed in this work. This paper offers an overviewof the work that has been done by many authors.
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Kim, Seon, and Gino Lim. "A Hybrid Battery Charging Approach for Drone-Aided Border Surveillance Scheduling." Drones 2, no. 4 (November 18, 2018): 38. http://dx.doi.org/10.3390/drones2040038.
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This paper proposes a new method to extend the flight capability of drones in real time. The new method combines two wireless charging methods (stationary wireless charging systems and dynamic wireless charging systems) into a hybrid mode. The drones must frequently return to a ground control center to replace or recharge its battery due to the limited performance of batteries mounted in the drones. To reduce the need of returning to the center, stationary wireless charging systems and dynamic wireless charging systems have been proposed. However, a few drawbacks of the two systems include the needs of landing/stopping on the stationary charging systems and the uncertainty of charging efficiency over the dynamic charging systems. Hence, to resolve the current limitations, we propose the hybrid approach for extending drone flight duration in real time. A mathematical formulation model is proposed to decide an optimal installation location and operating time of the hybrid mode. A case study is conducted to illustrate feasibility and effectiveness of the proposed method. Results from the case study show that we can lengthen the flight duration per charge from the initial launching point (30 min → 32–59 min), and if the value of charging efficiency of the dynamic charging systems is maintained above a certain level, the time spent on the stationary charging systems is significantly reduced (58 min → 22 min).
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Mebratu, Derssie D., and Charles Kim. "Combination of clustering algorithms to maximize the lifespan of distributed wireless sensors." Journal of Sensors and Sensor Systems 5, no. 1 (March 2, 2016): 63–72. http://dx.doi.org/10.5194/jsss-5-63-2016.
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Abstract. Increasing the lifespan of a group of distributed wireless sensors is one of the major challenges in research. This is especially important for distributed wireless sensor nodes used in harsh environments since it is not feasible to replace or recharge their batteries. Thus, the popular low-energy adaptive clustering hierarchy (LEACH) algorithm uses the “computation and communication energy model” to increase the lifespan of distributed wireless sensor nodes. As an improved method, we present here that a combination of three clustering algorithms performs better than the LEACH algorithm. The clustering algorithms included in the combination are the k-means+ + , k-means, and gap statistics algorithms. These three algorithms are used selectively in the following manner: the k-means+ + algorithm initializes the center for the k-means algorithm, the k-means algorithm computes the optimal center of the clusters, and the gap statistics algorithm selects the optimal number of clusters in a distributed wireless sensor network. Our simulation shows that the approach of using a combination of clustering algorithms increases the lifespan of the wireless sensor nodes by 15 % compared with the LEACH algorithm. This paper reports the details of the clustering algorithms selected for use in the combination approach and, based on the simulation results, compares the performance of the combination approach with that of the LEACH algorithm.
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Wu, Yin, Bowen Li, and Fuquan Zhang. "Predictive Power Management for Wind Powered Wireless Sensor Node." Future Internet 10, no. 9 (September 6, 2018): 85. http://dx.doi.org/10.3390/fi10090085.
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A conventional Wireless Sensor Network (WSN) cannot have an infinite lifetime without a battery recharge or replacement. Energy Harvesting (EH), from environmental energy sources, is a promising technology to provide sustainable powering for a WSN. In this paper, we propose and investigate a novel predictive energy management framework that combines the Maximal Power Transferring Tracking (MPTT) algorithm, a predictive energy allocation strategy, and a high efficiency transmission power control mechanism: First, the MPTT optimal working point guarantees minimum power loss of the EH-WSN system; Then, by exactly predicting the upcoming available energy, the power allocation strategy regulates EH-nodes’ duty cycle accurately to minimize the power failure time; Ultimately, the transmission power control module further improves energy efficiency by dynamically selecting the optimum matching transmission power level with minimum energy consumption. A wind energy powered wireless sensor system has been equipped and tested to validate the effectiveness of the proposed scheme. Results indicate that compared with other predictive energy managers, the proposed mechanism incurs relatively low power failure time while maintaining a high-energy conversion rate.
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Campi, Tommaso, Silvano Cruciani, Francesca Maradei, and Mauro Feliziani. "Innovative Design of Drone Landing Gear Used as a Receiving Coil in Wireless Charging Application." Energies 12, no. 18 (September 10, 2019): 3483. http://dx.doi.org/10.3390/en12183483.
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A near-field wireless power transfer (WPT) technology is applied to recharge the battery of a small size drone. The WPT technology is an extremely attractive solution to build an autonomous base station where the drone can land to wirelessly charge the battery without any human intervention. The innovative WPT design is based on the use of a mechanical part of the drone, i.e., landing gear, as a portion of the electrical circuit, i.e., onboard secondary coil. To this aim, the landing gear is made with an adequately shaped aluminum pipe that, after suitable modifications, performs both structural and electrical functions. The proposed innovative solution has a very small impact on the drone aerodynamics and the additional weight onboard the drone is very limited. Once the design of the secondary coil has been defined, the configuration of the WPT primary coil mounted in a ground base station is optimized to get a good electrical performance, i.e., high values of transferred power and efficiency. The WPT design guidelines of primary and secondary coils are given. Finally, a demonstrator of the WPT system for a lightweight drone is designed, built, and tested.
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Yang, Guang You, Xiong Gan, Tuo Zheng, and Zhi Yan Ma. "A Study on Energy Consumption Optimization for Cooperative Beamforming in Wireless Sensor Networks." Key Engineering Materials 620 (August 2014): 625–31. http://dx.doi.org/10.4028/www.scientific.net/kem.620.625.
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In wireless sensor networks where the volume and energy of nodes are limited by batteries, which are difficult or prohibitively expensive to replace or recharge in the most of its application scenarios, so improving energy efficiency has very important significance.Cooperative beamforming forms virtual antenna arrays by multiple adjacent wireless sensor nodes, which improves the signal strength at the receiver and reduces the energy consumption of the transmitter by multiplexing gain and interference management.In this paper, the problem of energy consumption optimization for cooperative beamforming in wireless sensor networks was studied. First, considering both amplifier energy consumption and circuit energy consumption,energy consumption models for both broadcast phase and cooperative beamforming phase was presented.Then,we propose a two-step optimization to minimize the total energy consumption by optimizing the modulation parameter and the number of cooperative nodes.We simulate the total energy consumption for various transmission distances,modulation parameters , path losses and the number of cooperative nodes.The numerical results show that,for different system parameters, selecting the optimal modulation parameter and the optimal number of cooperative nodes can reduce total energy consumption and improve energy efficiency.
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Zhu, Kai, Yin Cheng Liang, and Xin Jun Xu. "An Energy-Saving Algorithm of Wireless Sensor Network for the Internet of Things." Applied Mechanics and Materials 701-702 (December 2014): 939–42. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.939.
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The internet of things (IoT) is developing very speedily. Wireless Sensor Networks (WSNs) are the perception foundation. It is inconvenience to recharge sensor batteries frequently and the sensor power resource is limited in the WSNs. Therefore, one of the most important problems about a WSN is to save energy. To overcome this challenge, a great deal of algorithms was developed in the last few years such as DYCTC. In this paper, we propose RD-LEACH algorithm. Data transmission depends on the residual energy and the distance between the nodes. It can reduce the number of data sent. It solves effectively the energy saving caused by the invalid send and avoids cluster heads concentrate in a small network. Tests show that this algorithm can save approximately 18% of the energy and prolong the network lifetime under the premise of the network connectivity.
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Manafi, Sara, and Hai Deng. "Design of a Small Modified Minkowski Fractal Antenna for Passive Deep Brain Stimulation Implants." International Journal of Antennas and Propagation 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/749043.
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A small planar modified Minkowski fractal antenna is designed and simulated in dual frequency bands (2.4 and 5.8 GHz) for wireless energy harvesting by deep brain stimulation (DBS) devices. The designed antenna, physically being confined inside a miniaturized structure, can efficiently convert the wireless signals in dual ISM frequency bands to the energy source to recharge the DBS battery or power the pulse generator directly. The performance metrics such as the return loss, the specific absorption rate (SAR), and the radiation pattern within skin and muscle-fat-skin tissues are evaluated for the designed antenna. The gain of the proposed antenna is 3.2 dBi at 2.4 GHz and 4.7 dBi at 5.8 GHz; also the averaged SAR of the antenna in human body tissue is found to be well below the legally allowed limit at both frequency bands. The link budget shows the received power at the distance of 25 cm at 2.4 GHz and 5.8 GHz are around 0.4 mW and 0.04 mW, which can empower the DBS implant. The large operational bandwidth, the physical compactness, and the efficiency in wireless signal reception make this antenna suitable in being used in implanted biomedical devices such as DBS pulse generators.
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Ijemaru, Gerald K., Kenneth Li-Minn Ang, and Jasmine Kah Phooi Seng. "Swarm Intelligence Techniques for Mobile Wireless Charging." Electronics 11, no. 3 (January 26, 2022): 371. http://dx.doi.org/10.3390/electronics11030371.
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This paper proposes energy-efficient swarm intelligence (SI)-based approaches for efficient mobile wireless charging in a distributed large-scale wireless sensor network (LS-WSN). This approach considers the use of special multiple mobile elements, which traverse the network for the purpose of energy replenishment. Recent techniques have shown the advantages inherent to the use of a single mobile charger (MC) which periodically visits the network to replenish the sensor-nodes. However, the single MC technique is currently limited and is not feasible for LS-WSN scenarios. Other approaches have overlooked the need to comprehensively discuss some critical tradeoffs associated with mobile wireless charging, which include: (1) determining the efficient coordination and charging strategies for the MCs, and (2) determining the optimal amount of energy available for the MCs, given the overall available network energy. These important tradeoffs are investigated in this study. Thus, this paper aims to investigate some of the critical issues affecting efficient mobile wireless charging for large-scale WSN scenarios; consequently, the network can then be operated without limitations. We first formulate the multiple charger recharge optimization problem (MCROP) and show that it is N-P hard. To solve the complex problem of scheduling multiple MCs in LS-WSN scenarios, we propose the node-partition algorithm based on cluster centroids, which adaptively partitions the whole network into several clusters and regions and distributes an MC to each region. Finally, we provide detailed simulation experiments using SI-based routing protocols. The results show the performance of the proposed scheme in terms of different evaluation metrics, where SI-based techniques are presented as a veritable state-of-the-art approach for improved energy-efficient mobile wireless charging to extend the network operational lifetime. The investigation also reveals the efficacy of the partial charging, over the full charging, strategies of the MCs.
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Al-shqeerat, Khalil. "An Integrated Approach for Constructing Cluster-based Virtual Backbone with Mobile Sink." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 01 (January 29, 2019): 53. http://dx.doi.org/10.3991/ijim.v13i01.9539.
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<p class="Abstract">In Wireless Sensor Networks, no physical backbone infrastructure used while all sensor nodes are energy constrained and impractical to recharge. The behavior of networks becomes unstable once the first node dies. The key challenge in such networks is how to reduce energy consumption to increase the network lifetime, especially with the different amount of energy in heterogeneity environments.</p><p class="Abstract">In this paper, the virtual backbone routing solution is suggested to reduce energy consumption in a wireless sensor network. An integrated approach combines both advantages of hierarchical cluster-based architecture and shortest spanning tree topology for constructing a virtual backbone with a mobile sink. The clustering solution is used to divide the network into clusters and reduces the number of nodes included in the communication. On the other hand, the shortest spanning tree technique is used to construct a backbone among all cluster heads and mobile sink every time the sink traverses to a new location. The proposed approach aims to construct an efficient data aggregation spanning tree used to send or receive data between the mobile sink and elected cluster heads in wireless sensor networks. It constructs an efficient virtual backbone to decrease the energy consumption and prolong the lifetime of the network.</p>Performance evaluation results demonstrate how the proposed approach prolongs the lifetime of wireless sensor networks compared to some conventional clustering protocols.
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Talib, Mohammed Saad. "Minimizing the Energy Consumption in Wireless Sensor Networks." JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences 26, no. 1 (December 19, 2017): 17–28. http://dx.doi.org/10.29196/jub.v26i1.349.
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Energy in Wireless Sensor networks (WSNs) represents an essential factor in designing, controlling and operating the sensor networks. Minimizing the consumed energy in WSNs application is a crucial issue for the network effectiveness and efficiency in terms of lifetime, cost and operation. Number of algorithms and protocols were proposed and implemented to decrease the energy consumption. Principally, WSNs operate with battery-powered sensors. Since Sensor's batteries have not been easily recharge. Therefore, prediction of the WSN represents a significant concern. Basically, the network failure occurs due to the inefficient sensor's energy. MAC protocols in WSNs achieved low duty-cycle by employing periodic sleep and wakeup. Predictive Wakeup MAC (PW-MAC) protocol was made use of the asynchronous duty cycling. It reduces the consumption of the node energy by allowing the senders to predict the receiver′s wakeup time. The WSN must be applied in an efficient manner to utilize the sensor nodes and their energy to ensure effective network throughput. To ensure energy efficiency the sensors' duty cycles must be adjusted appropriately to meet the network traffic demands. The energy consumed in each node due to its switching between the active and idle states was also estimated. The sensors are assumed to be randomly deployed. This paper aims to improve the randomly deployed network lifetime by scheduling the effects of transmission, reception and sleep states on the energy consumption of the sensor nodes. Results for these states with much performance metrics were also studied and discussed.
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Cheng, Rei-Heng, Tung-Kuang Wu, ChengJie Xu, and Jingjing Chen. "A Tier-Based Loading-Aware Charging Scheduling Algorithm for Wireless Rechargeable Sensor Networks." International Journal of Grid and High Performance Computing 14, no. 1 (January 20, 2023): 1–21. http://dx.doi.org/10.4018/ijghpc.316156.
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Charging scheduling is an important issue of wireless rechargeable sensor networks. Previous research proposed to optimize the scheduling sequence by considering factors such as distance and remaining working time. However, packets are transmitted to the base station hop by hop, so that the burden on each sensor is not the same. The unbalancing nature of loading should also be taken into account when dealing with charging requests scheduling. In this paper, the authors have found, both through theoretical analysis on hypothetical model and simulation in more realistic environments, that the communication loading of sensors impacts power consumption of sensors in different tiers relative to the base station significantly. Accordingly, the proposed charging scheduling algorithm takes the loading factor into consideration so that sensors closer to the base station may be given higher priority for recharge. The simulation results show that the proposed method can significantly improve the data delivery rate and achieve higher network availability when compared to previous research.
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Vamsi Krishna, M. Naga, N. Sai Harsha, K. V. D. Kiran, and Gandharba Swain. "Optimization of Energy Aware Path Routing Protocol in Wireless Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 3 (June 1, 2017): 1268. http://dx.doi.org/10.11591/ijece.v7i3.pp1268-1277.
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Strength conservation is one of the biggest challenges to the successful WSNs since the tiny very limited resource nodes such as energy, memory space| as well as communication and computation capabilities. the sensors are unattended Implemented and battery recharge is almost impossible. So many investigations have be done in redirecting energy efficient algorithms or protocols for WSNs. Our reasons behinds the study of number is based on the following three aspects. Initially of all First, we see That immediate transmittal is employed under small scale while multi-hop network transmittal network is employed under mass. All of us want to find the Which factors influence the transmittal manner. Second, it is Commonly That multi-hop agree transmitting more energy efficient than Usually transmitting When the average solitary source to destination distance is large. Yet ,}how to look for the optimal hop number in order That the overall energy consumption is nominal is not well tackled. Third, the hot location phenomenon the networking lifetime influences directly. After that all of us recommend to Optimization of energy aware routing path (OEAPR) algorithm, Which incorporate the overall routing mechanism With hop-based direction-finding nature During process in WSNs.
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Guimarães, Dayan Adionel, Edielson Prevato Frigieri, and Lucas Jun Sakai. "Influence of node mobility, recharge, and path loss on the optimized lifetime of wireless rechargeable sensor networks." Ad Hoc Networks 97 (February 2020): 102025. http://dx.doi.org/10.1016/j.adhoc.2019.102025.
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Pund, M. A., Shital Bahale, and Jaya Ingole. "Analysis of SCERP: A Cluster Based Routing Protocol for Energy Balancing in Wireless Sensor Network." IRA-International Journal of Technology & Engineering (ISSN 2455-4480) 7, no. 2 (S) (July 10, 2017): 1. http://dx.doi.org/10.21013/jte.icsesd201701.
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Prolonging lifetime of wireless sensor network is a most significant problem due to energy constraint nature of sensor nodes. It is difficult to recharge nodes during network lifetime, to increase application area of WSN there is a need to design energy efficient clustering protocol for WSN. In this article there is a discussion about problems in Leach protocol and propose an improvement on the Leach routing protocol to reduce energy consumption and to extend network lifetime. Proposed self organized cluster based energy balanced routing protocol (SCERP) selects a cluster head node by considering probability based on ratio of residual energy of the node and the average energy level of nodes in network, and the geometric distance between the candidate node to the BS as key parameters. The outcome of simulation shows that proposed protocol is better than Leach in terms of balancing energy consumption of nodes and extending WSN lifetime.
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Bevacqua, Martina T., Gennaro G. Bellizzi, and Massimo Merenda. "An Efficient Far-Field Wireless Power Transfer via Field Intensity Shaping Techniques." Electronics 10, no. 14 (July 6, 2021): 1609. http://dx.doi.org/10.3390/electronics10141609.
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Radiative (or far-field) energy replenishment for devices such as smartphones, laptops, robots, and small electric appliances paves the way to autonomous and continuous devices functioning, thus bypassing the need of operation interruptions, human maintenance activities, and replenishment by wired transformers. In this work, we investigate the feasibility of using a properly engineered antenna array able to deliver radiative power to devices in need of energy replenishment during their normal and unsupervised activity, whose locations are unknown. Both the case of single and multiple devices needing energy replenishment are addressed. A quantitative proof-of-concept study is carried out to validate the proposed approach. A 3D scenario is simulated to study the case of devices in need of energy replenishment within a standard office environment. Different antenna array configurations are investigated and the corresponding performances benchmarked against a standard installation of recharging antennas. Results confirm the outstanding capability of the proposed approach in terms of confinement and maximization of power transfer. Finally, in this framework, we also propose an efficient communication protocol that is able to manage multiple recharge demand given different operational rules.
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Alshawi, Imad S., Abdul-Kareem Y. Abdulla, and Asaad A. Alhijaj. "Fuzzy dstar-lite routing method for energy-efficient heterogeneous wireless sensor networks." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 2 (August 1, 2020): 906. http://dx.doi.org/10.11591/ijeecs.v19.i2.pp906-916.
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Sensor devices, in Wireless Sensor Networks (WSNs), are usually equipped with low-capacity batteries and scattered on areas that cannot be reached in most of the cases to recharge or replace these sensors. The available battery energy in the sensor nodes is barely sufficient to transmit a limited quantity of data packets. In this regard, most of the works are designed aiming at achieving high energy efficiency. Due to multiple-hop data transmission and many to one traffic connection, the Imbalanced Energy Depletion (IED) is an immanent issue in WSNs. Accordingly, this paper suggests an energy efficient routing protocol called Fuzzy Dstar-lite to produce an optimal pathway data routing for Heterogeneous WSNs (HWSNs). This protocol can also reuse the product path to keep the energy consumption fairly distributed over the nodes of a network. Interestingly, the proposed protocol is demonstrated to be more efficient in decreasing the transmission delay and balancing power consumption when compared with other protocols, i.e. chessboard clustering (CC), PEGASIS, and LEACH. The comparison also showed the proposed protocol has been increased the network lifetime approximately 15%, 40%, and 50% compare with CC, PEGASIS, and LEACH, respectively.
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Wang, Meihua, Wei-Chang Yeh, Ta-Chung Chu, Xianyong Zhang, Chia-Ling Huang, and Jun Yang. "Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm." Energies 11, no. 9 (September 10, 2018): 2385. http://dx.doi.org/10.3390/en11092385.
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Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.
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Moussaoui, Djilali, Mourad Hadjila, Sidi Mohammed Hadj Irid, and Sihem Souiki. "Clustered chain founded on ant colony optimization energy efficient routing scheme for under-water wireless sensor networks." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (December 1, 2021): 5197. http://dx.doi.org/10.11591/ijece.v11i6.pp5197-5205.
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One challenge in under-water wireless sensor networks (UWSN) is to find ways to improve the life duration of networks, since it is difficult to replace or recharge batteries in sensors by the solar energy. Thus, designing an energy-efficient protocol remains as a critical task. Many cluster-based routing protocols have been suggested with the goal of reducing overall energy consumption through data aggregation and balancing energy through cluster-head rotation. However, the majority of current protocols are concerned with load balancing within each cluster. In this paper we propose a clustered chain-based energy efficient routing algorithm called CCRA that can combine fuzzy c-means (FCM) and ant colony optimization (ACO) create and manage the data transmission in the network. Our analysis and results of simulations show a better energy management in the network.
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Ko, Seung-Woo, and Seong-Lyun Kim. "Impact of Node Speed on Energy-Constrained Opportunistic Internet-of-Things with Wireless Power Transfer." Sensors 18, no. 7 (July 23, 2018): 2398. http://dx.doi.org/10.3390/s18072398.
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Wireless power transfer (WPT) is a promising technology to realize the vision of Internet-of-Things (IoT) by powering energy-hungry IoT nodes by electromagnetic waves, overcoming the difficulty in battery recharging for massive numbers of nodes. Specifically, wireless charging stations (WCS) are deployed to transfer energy wirelessly to IoT nodes in the charging coverage. However, the coverage is restricted due to the limited hardware capability and safety issue, making mobile nodes have different battery charging patterns depending on their moving speeds. For example, slow moving nodes outside the coverage resort to waiting for energy charging from WCSs for a long time while those inside the coverage consistently recharge their batteries. On the other hand, fast moving nodes are able to receive energy within a relatively short waiting time. This paper investigates the above impact of node speed on energy provision and the resultant throughput of energy-constrained opportunistic IoT networks when data exchange between nodes are constrained by their intermittent connections as well as the levels of remaining energy. To this end, we design a two-dimensional Markov chain of which the state dimensions represent remaining energy and distance to the nearest WCS normalized by node speed, respectively. Solving this enables providing the following three insights. First, faster node speed makes the inter-meeting time between a node and a WCS shorter, leading to more frequent energy supply and higher throughput. Second, the above effect of node speed becomes marginal as the battery capacity increases. Finally, as nodes are more densely deployed, the throughput becomes scaling with the density ratio between mobiles and WCSs but independent of node speed, meaning that the throughput improvement from node speed disappears in dense networks. The results provide useful guidelines for IoT network provisioning and planning to achieve the maximum throughput performance given mobile environments.
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Mohiddin, Md Khaja, Rashi Kohli, V. B. S. Srilatha Indira Dutt, Priyanka Dixit, and Gregus Michal. "Energy-Efficient Enhancement for the Prediction-Based Scheduling Algorithm for the Improvement of Network Lifetime in WSNs." Wireless Communications and Mobile Computing 2021 (October 31, 2021): 1–12. http://dx.doi.org/10.1155/2021/9601078.
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In wireless sensor networks, due to the restricted battery capabilities of sensor nodes, the energy issue plays a critical role in network efficiency and lifespan. In our work, an upgraded long short-term memory is executed by the base station to frequently predict the forecast positions of the node with the help of load-adaptive beaconing scheduling algorithm. In recent years, new technologies for wireless charging have offered a feasible technique in overcoming the WSN energy dilemma. Researchers are deploying rechargeable wireless sensor networks that introduce high-capacity smartphone chargers for sensor nodes for charging. Nearly all R-WSN research has focused on charging static nodes with relativistic routes or mobile nodes. In this work, it is analysed how to charge nondeterministic mobility nodes in this work. In this scenario, a new mechanism is recommended, called predicting-based scheduling algorithm, to implement charging activities. In the suggested technique, it directs them to pursue the mobile charger and recharge the sensor, which is unique for the present work. The mobile charger will then choose a suitable node, utilizing a scheduling algorithm, as the charging object. A tracking algorithm based on the Kalman filter is preferred during energy transfer to determine the distance needed for charging between the destination node & mobile charger. Here, the collecting & processing of data are performed through the big data collection in WSNs. The R-WSN charging operations of nondeterministic mobility nodes will be accomplished using the proposed charging strategy.
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Hoseini, Sayed Amir, Jahan Hassan, Ayub Bokani, and Salil S. Kanhere. "In Situ MIMO-WPT Recharging of UAVs Using Intelligent Flying Energy Sources." Drones 5, no. 3 (September 5, 2021): 89. http://dx.doi.org/10.3390/drones5030089.
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Unmanned Aerial Vehicles (UAVs), used in civilian applications such as emergency medical deliveries, precision agriculture, wireless communication provisioning, etc., face the challenge of limited flight time due to their reliance on the on-board battery. Therefore, developing efficient mechanisms for in situ power transfer to recharge UAV batteries holds potential to extend their mission time. In this paper, we study the use of the far-field wireless power transfer (WPT) technique from specialized, transmitter UAVs (tUAVs) carrying Multiple Input Multiple Output (MIMO) antennas for transferring wireless power to receiver UAVs (rUAVs) in a mission. The tUAVs can fly and adjust their distance to the rUAVs to maximize energy transfer gain. The use of MIMO antennas further boosts the energy reception by narrowing the energy beam toward the rUAVs. The complexity of their dynamic operating environment increases with the growing number of tUAVs and rUAVs with varying levels of energy consumption and residual power. We propose an intelligent trajectory selection algorithm for the tUAVs based on a deep reinforcement learning model called Proximal Policy Optimization (PPO) to optimize the energy transfer gain. The simulation results demonstrate that the PPO-based system achieves about a tenfold increase in flight time for a set of realistic transmit power, distance, sub-band number and antenna numbers. Further, PPO outperforms the benchmark movement strategies of “Traveling Salesman Problem” and “Low Battery First” when used by the tUAVs.
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Carloni, Andrea, Federico Baronti, Roberto Di Rienzo, Roberto Roncella, and Roberto Saletti. "On the Sizing of the DC-Link Capacitor to Increase the Power Transfer in a Series-Series Inductive Resonant Wireless Charging Station." Energies 14, no. 3 (January 31, 2021): 743. http://dx.doi.org/10.3390/en14030743.
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Wireless inductive-coupled power transfer is a very appealing technique for the battery recharge of autonomous devices like surveillance drones. The charger design mainly focuses on lightness and fast-charging to improve the drone mission times and reduce the no-flight gaps. The charger secondary circuit mounted on the drone generally consists of a full-bridge rectifier and a second-order filter. The filter cut-off frequency is usually chosen to make the rectifier output voltage constant and so that the battery is charged with continuous quantities. Previous works showed that an increase in power transfer is achieved, if compared to the traditional case, when the second-order filter resonant frequency is close to the double of the wireless charger excitation and the filter works in resonance. This work demonstrates that the condition of resonance is necessary but not sufficient to achieve the power increment. The bridge rectifier diodes must work in discontinuous-mode to improve the power transfer. The paper also investigates the dependence of the power transfer increase on the wireless excitation frequency. It is found the minimum frequency value below which the power transfer gain is not possible. This frequency transition point is calculated, and it is shown that the gain in power transfer is obtained for any battery when its equivalent circuit parameters are known. LTSpice simulations demonstrate that the transferred power can be incremented of around 30%, if compared to the case in which the rectifier works in continuous mode. This achievement is obtained by following the design recommendations proposed at the end of the paper, which trade off the gain in power transfer and the amplitude of the oscillating components of the wireless charger output.