Empirical Model of Radio Wave Propagation in the Presence of Vegetation inside Greenhouses Using Regularized Regressions

Abstract

Spain is Europe’s leading exporter of tomatoes harvested in greenhouses. The production of tomatoes should be kept and increased, supported by precision agriculture to meet food and commercial demand. The wireless sensor network (WSN) has demonstrated to be a tool to provide farmers with useful information on the state of their plantations due to its practical deployment. However, in order to measure its deployment within a crop, it is necessary to know the communication coverage of the nodes that make up the network. The multipath propagation of radio waves between the transceivers of the WSN nodes inside a greenhouse is degraded and attenuated by the intricate complex of stems, branches, leaf twigs, and fruits, all randomly oriented, that block the line of sight, consequently generating a signal power loss as the distance increases. Although the COST235 (European Cooperation in Science and Technology - COST), ITU-R (International Telecommunications Union—Radiocommunication Sector), FITU-R (Fitted ITU-R), and Weisbberger models provide an explanation of the radio wave propagation in the presence of vegetation in the 2.4 GHz ICM band, some significant discrepancies were found when they are applied to field tests with tomato greenhouses. In this paper, a novel method is proposed for determining an empirical model of radio wave attenuation for vegetation in the 2.4 GHz band, which includes the vegetation height as a parameter in addition to the distance between transceivers of WNS nodes. The empirical attenuation model was obtained applying regularized regressions with a multiparametric equation using experimental signal RSSI measurements achieved by our own RSSI measurement system for our field tests in four plantations. The evaluation parameters gave 0.948 for R2, 0.946 for R2 Adj considering 5th grade polynomial (20 parameters), and 0.942 for R2, and 0.940 for R2 Adj when a reduction of parameters was applied using the cross validation (15 parameters). These results verify the rationality and reliability of the empirical model. Finally, the model was validated considering experimental data from other plantations, reaching similar results to our proposed model.

Modeling Radio Wave Propagation for Wireless Sensor Networks in Vegetated Environments: A Systematic Literature Review

“…Like ITU-R and COST-235, the Weissberger model is derived from the MED and has been widely used in the work that is part of this SLR. Equation (4) describes the losses of this model [ 47 ]: …”

Path loss model based on exponential water cycle algorithm for wireless sensor network

“…In this application, the radio wave propagation model is framed using the linear and cubic regression 13 and regularized regression. 14 But the problem is that the regression condition is not satisfied, and the error in the model is high. In the case of an outdoor environment, the propagation modeling is even tough due to real-time obstructions.…”

“…Many studies bring the efficient modeling of path loss for indoor applications such as tomato greenhouses. In this application, the radio wave propagation model is framed using the linear and cubic regression 13 and regularized regression 14 . But the problem is that the regression condition is not satisfied, and the error in the model is high.…”

A Multiwall Path-Loss Prediction Model Using 433 MHz LoRa-WAN Frequency to Characterize Foliage’s Influence in a Malaysian Palm Oil Plantation Environment

“…Palm oil is the main cash crop of Malaysia, and most of the farmland in Malaysia is devoted to palm oil plantations. The use of LoRa-IoT applications in palm oil plantations can bring a revolutionary improvement in the palm oil industry through smart farming activities; however, LoRa data transmission is vulnerable due to the foliage blockage [ 4 ] caused by vegetation canopies [ 5 ]. Palm oil plantations are covered by oil palm trees, which are planted in rows.…”