Characteristics of UHF Propagation Channels Due to the Impact of Vegetation on WSN in The Tropical Forests
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Jan 27, 2025
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Abstract
The use of wireless communication in a wireless sensor network, especially in smart gardens, requires information about the amount of attenuation caused by vegetation. Therefore, measurements were made of the Received Signal Strength Indicator (RSSI) received by the XBee S2C device in the Bamboo Forest area, Surabaya, for several different lengths of vegetation depth and antenna height. From the measurement results, it is known that there is no significant difference between RSSI for antenna heights of 1 m and 2 m, while better RSSI is obtained for antennas with a height of 3 m. The antenna used is a vertical monopole antenna for the 2.4 GHz frequency. This is because, at an antenna height of 3 m, the number of vegetation that becomes obstacles is less than that of antennas of 1 m and 2 m. From the measurement results, it is also known that with this antenna height, data packets can be received up to a vegetation depth of 80 m. Then, the attenuation resulting from the calculation shows that the resulting trend is in accordance with the attenuation trend with the Weissberger, ITU-R, and FITU-R models but with higher values. Differences in measurement methods, locations, obstacles, and different climates and weather can cause this. To predict attenuation at a certain vegetation depth distance, based on the results of the attenuation calculation, a linear equation for calculating attenuation as a function of distance is created of the attenuation calculation, a linear equation for calculating attenuation as a function of distance is created.
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Kurniawati, I., Akbar, R., & Astomo, R. (2025). Characteristics of UHF Propagation Channels Due to the Impact of Vegetation on WSN in The Tropical Forests. Journal of Telecommunication Electronics and Control Engineering (JTECE), 7(1), 1-9. https://doi.org/10.20895/jtece.v7i1.1494
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References
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[3] J. A. Azevedo and F. E. Santos, “A model to estimate the path loss in areas with foliage of trees,” AEU - International Journal of Electronics and Communications, vol. 71, pp. 157–161, Jan. 2017, doi: 10.1016/j.aeue.2016.10.018.
[4] I. Kurniawati, G. Hendrantoro, Wirawan, and M. Taufik, “Statistical modeling of low-latitude long-distance HF ionospheric multi-mode channels,” Progress In Electromagnetics Research M, vol. 64, 2018.
[5] N. A. binti Masadan, M. H. Habaebi, and S. H. Yusoff, “Long range channel characteristics through foliage,” Bulletin of Electrical Engineering and Informatics, vol. 8, no. 3, pp. 941–950, Sep. 2019.
[6] J. R. Balbin, R. G. Garcia, F. L. Valiente, and Y. Hirota, “Detection and Localization for Buried and Alive Human Body After Mudslides Using Pulse Sensor and Force Sensing Resistor with XBee Technology and Global Positioning System to Support Rescue Operations,” in 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), Laoag: IEEE, Nov. 2019.
[7] R. Fitriani, “Kajian Kekuatan Sinyal Radio (Rssi) Xbee dalam Rangka Pemasangan Landslide Early Warning System (Lews) di Kabupaten Garut, Tasikmalaya dan Majalengka,” Alami, vol. 3, no. 2, Nov. 2019.
[8] S. Nathasa and S. M. Daud, “A Review on Computer Vision Technology for Monitoring Poultry Farm – Application, Hardware, and Software,” IEEE Access, vol. PP, no. 99, Dec. 2020.
[9] B. Gazal, K. Khateb, and K. Chahine, “A Poultry Farming Control System Using a ZigBee-based Wireless Sensor Network,” International Journal of Control and Automation, vol. 10, no. 9, pp. 191–198, Sep. 2017.
[10] T. Ojha, S. Misra, and N. S. Raghuwanshi, “Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges,” Comput Electron Agric, vol. 118, pp. 66–84, Oct. 2015.
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[12] J. Bauer and N. Aschenbruck, “Towards a Low-cost RSSI-based Crop Monitoring,” ACM Transactions on Internet of Things, vol. 1, no. 4, pp. 21–26, Jun. 2020.
[13] Z. Gao, W. Li, Y. Tian, F. Pang, W. Chao, and Ju. Ni, “Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks _ Enhanced Reader,” Sensors, vol. 18, no. 3116, pp. 1–18, Sep. 2018, Accessed: Aug. 07, 2023. [Online]. Available: https://www.mdpi.com/1424-8220/18/9/3116
[14] A. S. Adewumi and O. Olabisi, “Characterization and modeling of vegetation effects on UHF propagation through a long-forested channel,” Progress in Electromagnetics Research Letters, vol. 73, pp. 9–16, 2018, doi: 10.2528/pierl17092004.
[15] E. Dounias, “Rainforest, Tropical,” in The International Encyclopedia of Anthropology, vol. 1, H. Callan and S. Coleman, Eds., John Wiley and Son, 2018, pp. 1–3.
[16] S. Ozuomba, E. H. Johnson, and E. N. Udoiwod, “Application of Weissberger Model for Characterizing the Propagation Loss in a Gliricidia sepium Arboretum,” Universal Journal of Communications and Network, vol. 6, no. 2, pp. 18–23, Dec. 2018, doi: 10.13189/ujcn.2018.060202.
[17] Z. I. Rizman, K. Jusof, S. S. Rais, H. H. H. Bakar, and G. K. S. Nair, “Microwave Signal Propagation on Oil Palm tree: Measurements and Analysis,” International Journal on Smart Sensing and Intelligent Systems, vol. 4, no. 11, pp. 388–401, Aug. 2011.
[18] T. Ojha, S. Misra, and N. S. Raghuwanshi, “Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges,” Comput Electron Agric, vol. 118, pp. 66–84, Oct. 2015, doi: 10.1016/J.COMPAG.2015.08.011.
[19] N. T. Le and W. Benjapolakui, “Received signal strength data of ZigBee technology for on-street environment at 2.4 GHz band and the interruption of vehicle to link quality,” Data Brief, vol. 22, pp. 1036–1043, Feb. 2020.
[20] I. Magdalena, G. R. Andadari, and D. E. Reeve, “An integrated study of wave attenuation by vegetation,” Wave Motion, vol. 110, Mar. 2022.
[21] R. Prodanovic, D. Rancic, I. Vulic, and N. Zoric, “Wireless Sensor Network in Agriculture: Model of Cyber Security,” Sensors, vol. 20, no. 23, Dec. 2020.
[22] Digi International, “Signal strength and the RSSI pin,” https://www.digi.com/resources/documentation/Digidocs/90001456-13/concepts/c_rssi_pin_and_signal_strength.htm.
[23] W. Stallings, Komunikasi dan Jaringan Nirkabel , 2nd ed. Jakarta: Erlangga, 2005.
[24] M. A. Weissberger, “An Initial Critical Summary of models for Predicting the attenuation of radio waves by trees,” Electromagnetic Compatibility Analysis Centre, vol. Report ESD-TR, pp. 81–101, Jun. 1982.
[25] H. Maisarah Rahim, C. Yen Leow, and T. Abd Rahman, “Millimeter Wave Propagation Through Foliage: Comparison of Models,” in 2015 IEEE 12th Malaysia International Conference on Communications (MICC), Kuching, 2015, pp. 236–240. Accessed: Sep. 29, 2022. [Online]. Available: https://ieeexplore.ieee.org/document/7725440
[26] D. Kuramoto, T. Tokunou, and T. Hamasaki, “Vegetation Effect in Paddy Field for A Wireless Sensor Network,” in 2018 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), 2018. Accessed: Nov. 20, 2022. [Online]. Available: 10.1109/USNC-URSI.2018.8602773
[27] ITU-R, “Method for the prediction of the performance of HF circuits,” vol. 12, p. 8, 2012, doi: ITU-R P.533-12.
[28] M. S. H. Al Salameh, “Lateral ITU-R Foliage and Maximum attenuation models Combined with Relevant Propagation Models for Forest at the VHF and UHF bands,” Journal: International Journal of Networking and Communication, vol. 1, p. 55, Jul. 2014, doi: DOI: 01.IJNC.2014.1.7.