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

Abstract

Extensive research has not been done on propagation modeling for natural short-and tall-grass 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 grass environments. The proposed models are compared with theoretical models to demonstrate their inaccuracy in predicting path loss between sensor nodes deployed in natural grass environments. Results show that theoretical models deviate from the proposed models by 12 to 42%. Also, results of the proposed models are compared with 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 previous studies and other terrain models such as those in dense tree environments. These comparisons show that there is significant difference in path loss and empirical models' 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.Index Terms-path loss model, RF propagation, short and tall natural grass, terrain, terrain factor, wireless sensor network, XBee radio.

Path-Loss Prediction for an Industrial Indoor Environment Based on Room Electromagnetics

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Holistic Approach for Characterizing the Performance of Wireless Sensor Networks

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