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Empirical Path Loss Models for Wireless Sensor Network Deployments in Short and Tall Natural Grass Environments

机译:短期和高温自然草环境中无线传感器网络部署的经验路径损耗模型

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Extensive research has not been done on propagation modeling for natural short- and tall-grassy environments for the purpose of wireless sensor deployment. This study is essential for efficiently deploying wireless sensors in different applications such as tracking the grazing habits of cows on the grass or monitoring sporting activities. This study proposes empirical path loss models for wireless sensor deployments in grassy environments. The proposed models are compared with the theoretical models to demonstrate their inaccuracy in predicting the path loss between sensor nodes deployed in natural grassy environments. The results show that the theoretical model values deviate from the proposed model values by 12%-42%. In addition, the results of the proposed models are compared with those of the experimental results obtained from similar natural grassy terrains at different locations resulting in similar outcomes. Finally, the results of the proposed models are compared with those of the previous studies and other terrain models such as those in dense tree environments. These comparisons show that there is a significant difference in path loss and empirical model parameters. The proposed models as well as the measured data can be used for efficient planning and future deployments of wireless sensor networks in similar grass terrains.
机译:出于无线传感器部署的目的,尚未针对自然短草和高草草环境的传播建模进行广泛的研究。这项研究对于有效地在不同应用中有效部署无线传感器至关重要,例如跟踪草地上奶牛的放牧习惯或监视体育活动。这项研究提出了在草地环境中无线传感器部署的经验路径损耗模型。将提出的模型与理论模型进行比较,以证明它们在预测自然草环境中部署的传感器节点之间的路径损耗方面的准确性。结果表明,理论模型值与建议的模型值相差12%-42%。另外,将所提出的模型的结果与从不同位置的类似天然草皮地形获得的实验结果进行比较,从而得到相似的结果。最后,将所提出的模型的结果与先前研究的结果以及其他地形模型(例如在茂密的树木环境中的模型)进行了比较。这些比较表明,路径损耗和经验模型参数存在显着差异。所提出的模型以及测得的数据可用于在类似草丛地形中有效规划和将来部署无线传感器网络。

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