@article {10.3844/ajassp.2022.78.83,
article_type = {journal},
title = {Rain Events Detection using Energy Variation of Commercial Microwave Links Attenuation},
author = {Ouedraogo, Wend Yam Serge Boris and Djibo, Moumouni and Doumounia, Ali and Sanou, Serge Roland and Sawadogo, Moumouni and Guira, Idrissa and Zougmoré, François},
volume = {19},
year = {2022},
month = {Aug},
pages = {78-83},
doi = {10.3844/ajassp.2022.78.83},
url = {https://thescipub.com/abstract/ajassp.2022.78.83},
abstract = {In this study, we propose a new method for detecting wet periods by using telecommunications Commercial Microwave Links (CML). The purpose of the study is to automatically find rain time slots. The attenuation of the microwave signal, propagating between a transmitting antenna and a receiving one, due to the variations of the climatic conditions over the link, is a non-stationary signal. When a rain event occurs over a CML, the attenuation signal level increases proportionally to the rain amount. This level decreases again at the end of the rain. These abrupt variations are exploited here to detect rainy time slots. The proposed method consists in splitting the attenuation signal into frames and computing the variation of the energy between consecutive frames. To determine whether the current frame corresponds to a wet period, the proposed method, named Energy Variation (EVA), compares the variation of the energy with a given threshold, while taking into account the status of the previous frame. Simulation results from real attenuation data of the mobile phone operator Telecel Faso SA (Burkina Faso) show that the proposed method allows the detection of 84.61% of rainy events. The Matthews Correlation Coefficient (MCC) is higher than 0.9, which demonstrates that EVA can discriminate between wet and dry periods with high accuracy.},
journal = {American Journal of Applied Sciences},
publisher = {Science Publications}
}