Enabling Underwater Wireless Power Transfer towards Sixth Generation (6G) Wireless Networks: Opportunities, Recent Advances, and Technical Challenges

Mohsan, Syed Agha Hassnain; Khan, Muhammad Asghar; Mazinani, Alireza; Alsharif, Mohammed H.; Cho, Ho-Shin

doi:10.3390/jmse10091282

Cited by 32 publications

(26 citation statements)

References 128 publications

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“…Other fields that utilize WPT include underwater sensor networks, and SHM. The far-field radiative power transfer has limited energy transmission efficiency in the underwater, as such inductive wireless power transfer (IWPT) is more common in the underwater [42]- [44]. The underwater environment however does not closely resemble the UG environment.…”

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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“…Despite significant evolution in providing Sub-Saharan Africa with energy access over the last decade, the coronavirus disease-19 (COVID-19) crisis has shattered the graph. With the energy shortage, it is predicted that there will still be around 560 million people in Sub-Saharan Africa in the year 2030 [2]. From a technical perspective, the transmission system has already moved to High-Voltage Direct Current (HVDC) transmission to overcome the transmission losses in the AC transmission system.…”

Section: Introductionmentioning

confidence: 99%

Solar-Powered LVDC Nano-Grid with Smart FPGA-based Residential Power Switching Algorithm

Shanmugam

Balasubramaniam²,

Shnain

et al. 2024

IEEE Access

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A Low Voltage Direct Current (LVDC) nano-grid opens new potentials for the electrification of isolated rural settlements, urban residential structures, and the existing grid infrastructure. This study introduces and examines the Power-Sharing Control (PSC) of a solar Photovoltaic (PV) system connected to a low-voltage DC nano-grid. Effective control and power management between the components of a planned LVDC nano-grid system are presented, as is the use of a PSC algorithm implemented on a Field Programmable Gate Array (FPGA). General simulation investigations are tested to analyse the system's performance using the recommended controller. The proposed LVDC nano-grid idea is developed, and its hardware is assessed. The results of the hardware under different settings are shown and discussed. The proposed nano-grid model is implemented in matrix laboratory (MATLAB)-Simulink and has an FPGAbased Maximum Power Point Tracking (MPPT) controller and a central PSC algorithm; simulation studies are performed, and results are achieved. 100 W nano-grid hardware is set up and tested. Quantitative costbenefit analyses of the LVDC nano-grid of the proposed controller are given.

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“…For ROV, losing balance may cause the cables to wrap around the ROV, which reduces the movement distance [ 5 ]. For AUV, losing balance causes the AUV to spend more power on adjusting its attitude, which further reduces the endurance time [ 6 ]. Besides, for ROV and AUV, the loss of orientation and balance not only makes it difficult to accomplish underwater tasks but also causes them to be swept away by the flow, which is a huge economic loss [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Thermal Tactile Sensor Based on Micro Thermoelectric Generator for Underwater Flow Direction Perception

Liu

Chen

Xing

et al. 2023

Sensors

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Underwater vehicles can operate independently in the exploitation of marine resources. However, water flow disturbance is one of the challenges underwater vehicles must face. The underwater flow direction sensing method is a feasible way to overcome the challenges but faces difficulties such as integrating the existing sensors with underwater vehicles and high-cost maintenance fees. In this research, an underwater flow direction sensing method based on the thermal tactility of the micro thermoelectric generator (MTEG) is proposed, with the theoretical model established. To verify the model, a flow direction sensing prototype is fabricated to carry out experiments under three typical working conditions. The three typical flow direction conditions are: condition No. 1, in which the flow direction is parallel to the x-axis; condition No. 2, in which the flow direction is at an angle of 45° to the x-axis; and condition No. 3, which is a variable flow direction condition based on condition No. 1 and condition No. 2. According to the experimental data, the variations and orders of the prototype output voltages under three conditions fit the theoretical model, which means the prototype can identify the flow direction of three conditions. Besides, experimental data show that in the flow velocity range of 0~5 m/s and the flow direction variation range of 0~90°, the prototype can accurately identify the flow direction in 0~2 s. The first time utilizing MTEG on underwater flow direction perception, the underwater flow direction sensing method proposed in this research is cheaper and easier to be applied on the underwater vehicles than traditional underwater flow direction sensing methods, which means it has great application prospects in underwater vehicles. Besides, the MTEG can utilize the waste heat of the underwater vehicle battery as the energy source to achieve self-powered work, which greatly enhances its practical value.

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Enabling Underwater Wireless Power Transfer towards Sixth Generation (6G) Wireless Networks: Opportunities, Recent Advances, and Technical Challenges

Cited by 32 publications

References 128 publications

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

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

Solar-Powered LVDC Nano-Grid with Smart FPGA-based Residential Power Switching Algorithm

A Novel Thermal Tactile Sensor Based on Micro Thermoelectric Generator for Underwater Flow Direction Perception

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