New empirical path loss model for wireless sensor networks in mango greenhouses

FSPL and 2-Ray models are inaccurate to be used in conjugation with foliage models to predicted total path loss in vegetation environments and it has (38.20% and 65.74%) MPAE.The path loss model based COST235 and FSPL was the best performance to the empirical measurements, but it's still not optimum due to that the MAPE was 10.69%.New empirical path loss model (LRCFM) for mango greenhouse has MAPE about 2.75% as compared to other models. Signal propagation losses in protected environments are investigated using wireless sensor networks (WSNs) based on the IEEE 802.15.4 standard of operating frequency, 2.425GHz. In this research, various empirical measurements were conducted to examine the effects of each part of a tree on path loss using different transceiver heights. A new linear path loss regression curve-fitting model (LRCFM) was derived based on the regression technique of computing the total path loss inside the greenhouse environment. The greatest vegetation effects appear within 1.5m tree height; in this research, this height was adopted to study and analyse vegetation models in a mango greenhouse. This research proves that path loss prediction based on free space path loss (FSPL) and two-ray (2-Ray) propagation models is inaccurate in predicting loss in certain environments, as these approaches are simplistic and optimistic. Thus, most known foliage models used in conjugation with FSPL and 2-Ray are inaccurate in predicting the total path loss in a greenhouse environment. The analytical and empirical results prove that the new derived model, the LRCFM, is the best candidate compared to other foliage models. The mean absolute percentage error (MAPE) of the total path loss based on the new LRCFM model was 2.7% compared to the 10.69% of the well-known models.