Development of A Wireless Power Transmission System for Agriculture Sensor Devices

Robinson, Charles Alexander; Nieman, Brandon T.; Craven, Robert; Bima, Muhammad; Neste, C. W. Van

doi:10.1109/bigdata50022.2020.9377855

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…Measurements and experiments were performed for the designed rectenna and the overall tile system in a laboratory test bed [39]. Other studies, such as [40], demonstrated WPT through soil using current conduction, whereas [41] experimented on the possibility of increasing the efficiency of energy collection by combining RFEH and thermoelectric energy. Other fields that utilize WPT include underwater sensor networks, and SHM.…”

Section: Related Workmentioning

confidence: 99%

Radio Frequency Energy Harvesting for Underground Sensor Nodes: Possibilities and Challenges

Mahenge,

Sinde,

Dida

et al. 2024

IEEE Access

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Radio frequency energy harvesting (RFEH) is considered an optimal and environmentally friendly solution for energizing sensor devices and prolonging the lifetime of wireless sensor networks (WSNs). Despite being studied and experimented in several environments where WSNs are used, studies and experiments related to RFEH in underground wireless systems are limited to near-field wireless power transfer (WPT), measurement of received signal strength, and current conduction. The goal of this study is to examine the possibilities and challenges of actualizing RFEH in wireless underground sensor networks (WUSNs). A radio-frequency (RF) spectral survey was conducted, and a comparison was performed with similar surveys conducted worldwide to determine the generally available ambient RF energy. Using the aboveground to underground (AG2UG) RF communication model, the signal path loss was analyzed under varying conditions. By relating the ambient RF power and AG2UG signal path loss, it was found nearly impossible to harvest ambient RF energy with the harvesting antenna buried within the soil, as the best-case environment will require a rectenna with sensitivity of at least -62.75dBm. However ambient RF energy can be harvested when the harvesting antenna is in free space, while the other components are underground and will require a high sensitivity of at least -40 dBm. Another possibility for underground RFEH is the use of a dedicated WPT device located 1m above the ground, transmitting at 20 dBm with the RF energy harvester 30 cm below the soil surface with a sensitivity of at least -30 dBm.INDEX TERMS Internet of Underground Things (IoUT), Radio frequency energy harvesting (RFEH), wireless power transfer (WPT), wireless underground sensor networks (WUSNs).

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Section: Related Workmentioning

confidence: 99%

Radio Frequency Energy Harvesting for Underground Sensor Nodes: Possibilities and Challenges

Mahenge,

Sinde,

Dida

et al. 2024

IEEE Access

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“…Unlike traditional contact-based power transmission methods, WPT is free from the constraints of wires and offers significant advantages such as enhanced safety [2][3], flexibility, and reliability [4]. This technology is suitable for a wide range of applications including transportation [7], implantable medical devices [8], and consumer electronics industries [9][10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Coil Array Compensation Structure Design with High-Misalignment Tolerance for UAV-Enable WPT system

Rong,

Chang,

Liu

et al. 2024

Preprint

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The problem of charging unmanned aerial vehicles (UAVs) is an important application area for wireless power transmission (WPT). However, the flight characteristics of UAVs make it difficult for the traditional single-coil coupling mechanism to ensure alignment between the transmitting and receiving ends. It also has poor anti-skewing performance and a cumbersome optimization process, which ultimately decreases the efficiency of charging UAVs. To address this problem, this paper takes the 2×2 square coil array as research object, analyzes the distribution characteristics of the axial magnetic field at a specific height, proposes a "cross" compensation structure, and adopts genetic algorithm to optimize the side length and turns of the compensation coil. The goal is to significantly improve the axial magnetic field uniformity in the charging area and reduce the degree of magnetic field leakage. Finally, the effectiveness and superiority of the proposed "crossover" compensation structure and its optimization method are demonstrated through the construction and testing of the system experimental platform, which significantly improves the anti-offset performance and transmission efficiency of the WPT system.

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“…Generators, transformers, power lines, circuit breakers and other electrical equipment are important components of ubiquitous power IoT [1][2][3][4][5][6][7]. With the improvement of information level at present, the power IoT uses wireless sensors as sensing units to build a sensing system for electrical equipment state, which is used for network fault handling or other advanced applications [8][9][10][11][12][13][14][15]. In a large number of measurement signals collected by actual wireless sensor networks, it is inevitable that there will be sudden signal changes caused by signal transmission or storage failures.…”

Section: Introductionmentioning

confidence: 99%

Research on State Detection Method of Electrical Equipment Based on Wireless Sensor Network Signal Processing

Liang¹,

Ding²,

Jin-fa³

et al. 2022

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False alarms and omissions of key measurement signals may even affect the reliability of decision-making in power IoT system, lead to safety accidents and bring huge economic losses. In order to improve the reliability of system operation and the information management level of electrical equipment, it is necessary to identify and extract suddenly changed signals from massive measurement signals collected by wireless sensor networks, and to detect the working state of electrical equipment by judging the source of signals. Therefore, this article studies the state detection method of electrical equipment based on wireless sensor network signal processing. In the second chapter, a cluster splitting and merging method is designed to solve the problem that the existing detection methods tend to ignore the imbalance of cluster size. In the third chapter, according to the data characteristics of measurement signals collected by wireless sensor networks, a similarity measurement criterion for composite time series of measurement signals is proposed, and the corresponding distance matrix is generated based on this criterion. In the fourth chapter, wavelet decomposition is used to decompose the initial measurement signals collected by wireless sensor networks, and then the signals are compressed twice based on compressed sensing. Then the abnormal signal data information is imported into support vector machine for training to realize the real-time detection of abnormal signals of electrical equipment state. Experimental results verify the effectiveness of the proposed algorithm.

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Development of A Wireless Power Transmission System for Agriculture Sensor Devices

Cited by 6 publications

References 4 publications

Radio Frequency Energy Harvesting for Underground Sensor Nodes: Possibilities and Challenges

Radio Frequency Energy Harvesting for Underground Sensor Nodes: Possibilities and Challenges

A Novel Coil Array Compensation Structure Design with High-Misalignment Tolerance for UAV-Enable WPT system

Research on State Detection Method of Electrical Equipment Based on Wireless Sensor Network Signal Processing

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