Experimental Study on Battery-Less Sensor Network Activated by Multi-Point Wireless Energy Transmission

Maehara, Daiki; Tran, Gia Khanh; Sakaguchi, Kei; Araki, Kiyomichi

doi:10.1587/transcom.2015ebp3318

Cited by 17 publications

(9 citation statements)

References 12 publications

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“…Strongly coupled magnetic resonance was used to realize the wireless power transfer [10]. Recently, the wireless power transfer technology has been applied to the practice [11,12]. The simplest circuit topology is shown in Figure 4(a).…”

Section: Biological Channel Wireless Power Transfer System Modelingmentioning

confidence: 99%

Research on the Key Issues in Power and Data Wireless Transmission of Implantable Medical Devices

Li¹,

Yang²,

Yu³

2018

PIER C

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Abstract-In order to solve a key issue about power and data wireless transmission of implantable medical devices, M-ary differentially-encoded amplitude and phase-shift Keying (MDAPSK) is employed to balance the frequency selective contradiction in this paper. Subsequently, bio-capacitor model and biological path loss model are introduced to improve the accuracy of conventional wireless power transmission efficiency model. Based on 16DAPSK modulation, biological channel error rate analysis model is set up. Compared with experiment data, accuracy of the model is proved. Error codes suppression and error codes correction methods are optimized, and the optimization results have been verified by experiments. Lastly, it can be found that the power and data synchronized wireless transmission scheme is feasible. This work provides a new solution and model reference for power and data wireless transmission of implantable medical devices.

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Section: Biological Channel Wireless Power Transfer System Modelingmentioning

confidence: 99%

Research on the Key Issues in Power and Data Wireless Transmission of Implantable Medical Devices

Li¹,

Yang²,

Yu³

2018

PIER C

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“…In this section, we review the research results [3][4][5][6][7][8][13][14][15][16][17] most related to our work. Kim et al [3] investigated various ambient energy-harvesting technologies using different power sources, such Energies 2016, 9, 696 3 of 22 as solar power, thermal power, piezoelectric power, and wireless RF power, in the aspect of their applicability for self-sustainable wireless sensor platforms.…”

Section: Related Workmentioning

confidence: 99%

“…, N. The proposed scheme is shown to be capable of mitigating power attenuation caused by the path loss effect and the standing-wave effect created by multipath and interference between multiple power transmitters so that the coverage of energy supply field is improved. Maehara et al [15] investigated the energy transmission coverage of the MPCSD scheme through theoretical discussions and practical experiments. It is shown that the MPCSD scheme can achieve 100% of coverage in an indoor environment for the sensor node duty factor of 1/100 (i.e., the sensor node is in the transmitting mode for the duration of 10 ms per second).…”

Section: Related Workmentioning

confidence: 99%

“…Many recent studies [4][5][6][7][8][9][10][11][12][13] focus on the WRSNs due to their sustainability. Some other studies [14][15][16][17][18][19][20] investigate battery-less or battery-free wireless sensor networks (WSNs) in which sensor nodes are powered by capacitors storing energy harvested through wireless power transmission (WPT), especially microwave power transmission (MPT). Without loss of generality, such WSNs are regarded as WRSNs in this paper.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Wireless Charger Deployment for Wireless Rechargeable Sensor Networks

Jiang

Liao

2016

Energies

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A wireless rechargeable sensor network (WRSN) consists of sensor nodes that can harvest energy emitted from wireless chargers for refilling their batteries so that the WRSN can operate sustainably. This paper assumes wireless chargers are equipped with directional antennas, and are deployed on grid points of a fixed height to propose two heuristic algorithms solving the following wireless charger deployment optimization (WCDO) problem: how to deploy as few as possible chargers to make the WRSN sustainable. Both algorithms model the charging space of chargers as a cone and calculate charging efficiency according power regression expressions complying with the Friis transmission equation. The two algorithms are the greedy cone covering (GCC) algorithm and the adaptive cone covering (ACC) algorithm. The GCC (respectively, ACC) algorithm greedily (respectively, adaptively) generates candidate cones to cover as many as possible sensor nodes. Both algorithms then greedily select the fewest number of candidate cones, each of which corresponds to the deployment of a charger, to have approximate solutions to the WCDO problem. We perform experiments, conduct simulations and do analyses for the algorithms to compare them in terms of the time complexity, the number of chargers deployed, and the execution time.

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“…It is suitable for office/home automation and can be easily installed in almost any environment without restriction. To deal with the poor detection probability of infrared sensors, we built a battery-less human detection network [18] [19], by which the sensors can be located anywhere in the space without restriction, so that they can be close to each user as much as possible, instead of being inflexibly embedded in walls or ceilings, which are far from detection objects. And a series of distributed sensors with overlapping coverage were deployed, instead of single sensor for one LED light and one area in conventional lighting control systems.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Lighting Control System Using Battery-Less Wireless Human Detection Sensor Networks

Tao

Kuki

Matsushita

et al. 2017

IEICE Trans. Commun.

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SUMMARYArtificial lighting is responsible for a large portion of total energy consumption and has great potential for energy saving. This paper designs an LED light control algorithm based on users' localization using multiple battery-less binary human detection sensors. The proposed lighting control system focuses on reducing office lighting energy consumption and satisfying users' illumination requirement. Most current lighting control systems use infrared human detection sensors, but the poor detection probability, especially for a static user, makes it difficult to realize comfortable and effective lighting control. To improve the detection probability of each sensor, we proposed to locate sensors as close to each user as possible by using a battery-less wireless sensor network, in which all sensors can be placed freely in the space with high energy stability. We also proposed to use a multi-sensor-based user localization algorithm to capture user's position more accurately and realize fine lighting control which works even with static users. The system is actually implemented in an indoor office environment in a pilot project. A verification experiment is conducted by measuring the practical illumination and power consumption. The performance agrees with design expectations. It shows that the proposed LED lighting control system reduces the energy consumption significantly, 57% compared to the batch control scheme, and satisfies user's illumination requirement with 100% probability. key words: proof-of-concept, energy saving, LED light control, battery-less wireless human detection sensor network, multi-sensor user localization

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Experimental Study on Battery-Less Sensor Network Activated by Multi-Point Wireless Energy Transmission

Cited by 17 publications

References 12 publications

Research on the Key Issues in Power and Data Wireless Transmission of Implantable Medical Devices

Research on the Key Issues in Power and Data Wireless Transmission of Implantable Medical Devices

Efficient Wireless Charger Deployment for Wireless Rechargeable Sensor Networks

Design and Implementation of Lighting Control System Using Battery-Less Wireless Human Detection Sensor Networks

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