Optimum Piezo-Electric Based Energy Harvesting for Low-Power Wireless Networks with Power Complexity Considerations
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Published:2023-12
Issue:4
Volume:133
Page:2355-2377
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ISSN:0929-6212
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Container-title:Wireless Personal Communications
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language:en
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Short-container-title:Wireless Pers Commun
Author:
El-Bendary Mohsen A. M.ORCID, Haggag Ayman
Abstract
AbstractLow-power wireless sensing-based networks suffer from many constraints and challenges. In this research work, efficient power source has been designed to provide the need of energy for the Wireless Sensor Networks (WSNs) and Wireless Body Area Networks (WBANs). The energy sources are the main challenge and constraint these wireless networks applications. This paper discusses recent researcher’s works which considered the energy constraints of the WSN and WMSN with their proposed security techniques. The main idea of this presented work is the energy harvesting through extracting the electrical energy from the audio/acoustic signal/energy, this utilized audio/acoustic source in this scenario is the disk jockey. To maximize the produced power from the proposed acoustic energy harvesting Piezo-based several parameters is studied. The parameters are considered in this research work are the method of Piezo-transducers connections, the distance of sound source, the sound intensity variation and the sound concentrating tube length. These tubes are mounted on slim diaphragm two maximize the energy harvesting. The piezoelectric transducer array scenario is designed using four piezoelectric transducers utilizing different connect ion methods, series, parallel and in hybrid. Several practically experiments are performed on the presented different scenarios to evaluate the proposed energy harvesting efficiency. These experiments reveal that the superiority of the proposed acoustic energy harvesting technique with low power complexity wireless networks and suitable with the different presented scenarios.
Publisher
Springer Science and Business Media LLC
Reference82 articles.
1. El-Bendary, M. A. M. (2018). Wireless Personal Communications: Simulation and Complexity’. Springer. 2. El-Bendary, M. A. M., & Abou El-Azm, A. E. (2019). Complexity considerations: Efficient image transmission over mobile communications channels. Multimedia Tools and Applications, 78, 16633–16664. 3. Kasban, H., Nassar, S., & El-Bendary, M. A. M. (2021). Medical images transmission over Wireless Multimedia Sensor Networks with high data rate. Analog Integrated Circuits and Signal Processing, 108(1), 125–140. 4. El-Gohary, N. M., El-Bendary, M. A. M., Abd El-Samie, F. E., & Fouad, M. M. (2016). Performance evaluation of various erasures coding techniques in digital communication. Journal of Wireless Networking and Communications, 6(1), 10–20. 5. Khalil, A. A., Ibrahim, F. E., Abbass, M. Y., Haggag, N., Mahrous, Y., Sedik, A., Elsherbeeny, Z., Khalaf, A. A. M., Rihan, M., El-Shafai, W., El-Banby, G. M., Soltan, E., Soliman, N. F., Algarni, A. D., Al-Hanafy, W., El-Fishawy, A. S., El-Rabaie, E. S. M., Al-Nuaimy, W., Dessouky, M. I., … El-Samie. (2022). Efficient anomaly detection from medical signals and images with convolutional neural networks for Internet of medical things (IoMT) systems. International Journal for Numerical Methods in Biomedical Engineering, 38(1), 10–20.
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