# Path Loss Determination Using Linear and Cubic Regression Inside a Classic Tomato Greenhouse
## 4 Conclusions  
In the present work, a complete study of the propagation models for tomatoes greenhouses was carried out. The characteristics of tomato plantation caused an attenuation due to vegetation, and to the height, so by means of this study it has been possible to see if the theoretical propagation models adjust well to the conditions that exist in the plantations of tomatoes. With the novel mathematical models of propagation of radio waves developed, a better estimation of its attenuation can be obtained for this specific environment. In this way, the results of this study allow planning the deployment of WSN in terms of maximum distances between nodes and consequently in the number of nodes that would be used. It is recommended to place the omnidirectional antenna at a height to half a meter above ground level because greater coverage between two nodes in the deployment can be reached. By optimizing the number of nodes required to monitoring and/or automatizing the greenhouse crop, we could reduce the cost of investment, redistributing the economic savings to reinvest it on their crops. With this height, the classical models diverge up to an error percentage of 42.84%, with the Weissberger and two-rays models being the closest empirical measurement after our proposed model. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**\% Error**} & \multicolumn{8}{c}{**Distance (m)**} \\ \cline{2-10}  & **2.6** & **4.4** & **6.2** & **8** & **9.8** & **11.6** & **13.4** & **15.2** & **17.0** & **18.8** & **20.6** & **22.4** & **24.2** \\ \hline FSPL & 40.64 & 42.84 & 38.30 & 32.21 & 31.30 & 25.04 & 18.81 & 13.46 & 7.92 & 6.94 & 4.95 & 4.52 & 17.52 \\ Two-Ray & 20.44 & 6.44 & 9.57 & 7.41 & 10.75 & 6.27 & 1.52 & 0.65 & 3.91 & 3.44 & 4.25 & 13.27 & 26.25 \\ Weissberger + Two Ray & 17.99 & 9.24 & 12.99 & 11.56 & 15.34 & 11.66 & 7.76 & 9.15 & 5.25 & 5.93 & 5.43 & 2.51 & 13.99 \\ Linear Regression & 8.81 & 1.25 & 0.68 & 1.62 & 3.85 & 1.73 & 0.06 & 0.61 & 1.31 & 2.82 & 5.53 & 0.89 & 6.77 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Percentage of error in the 2.4 GHz band with propagation models in the presence of vegetation when the Tx and Rx nodes were 0.5 m above the ground. Figure 8: Linear and cubic regression for measurement at 0.5 m and 1.5 m respectively along with its deviation. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**\% Error**} & \multicolumn{8}{c}{**Distance (m)**} \\ \cline{2-10}  & **2.6** & **4.4** & **6.2** & **8** & **9.8** & **11.6** & **13.4** & **15.2** & **17.0** & **18.8** & **20.6** & **22.4** & **24.2** \\ \hline FSPL & 40.64 & 42.84 & 38.30 & 32.21 & 31.30 & 25.04 & 18.81 & 13.46 & 7.92 & 6.94 & 4.95 & 4.52 & 17.52 \\ Two-Ray & 20.44 & 6.44 & 9.57 & 7.41 & 10.75 & 6.27 & 1.52 & 0.65 & 3.91 & 3.44 & 4.25 & 13.27 & 26.25 \\ Weissberger + Two Ray & 17.99 & 9.24 & 12.99 & 11.56 & 15.34 & 11.66 & 7.76 & 9.15 & 5.25 & 5.93 & 5.43 & 2.51 & 13.99 \\ Linear Regression & 8.81 & 1.25 & 0.68 & 1.62 & 3.85 & 1.73 & 0.06 & 0.61 & 1.31 & 2.82 & 5.53 & 0.89 & 6.77 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Percentage of error in the 2.4 GHz band with propagation models in the presence of vegetation when the Tx and Rx nodes were 1.5 m above the ground. The lowest coverage was obtained at 1.5 m, and the models that most closely approximate the empirical values were those of ITU-R, ITU-R, and FSPL that can diverge on average up to an error rate of 30%. The two models that we have developed have percentages of error lower than 9% when the nodes are at a height of less than one and a half meters, and less than 3% with a half meter of separation with the ground. Our models are replicable and help more accurately to plan, predict coverage, and optimize the number of nodes in a network of wireless sensors operating in the 2.4 GHz band in a tomato greenhouse. Future work could examine how to generalize the model to other types of greenhouse crops.