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The use of wireless sensor networks (WSN) for monitoring variables in agricultural environments and natural forests has been increasing in recent years. However, the sizing of these systems is affected by the inaccuracy of the radio wave propagation models used, leading to possible increased costs and measurement errors. This systematic literature review (SLR) aims to identify propagation models widely used in WSN deployments in agricultural or naturally vegetated environments and their effectiveness in estimating signal losses. We also identified today’s wireless technologies most used in precision agriculture (PA) system implementations. In addition, the results of studies focused on the development of new propagation models for different environments are evaluated. Scientific and technical analysis is presented based on articles consulted in different specialized databases, which were selected according to different combinations of criteria. The results show that, in most of the application cases, vegetative models present high error values when estimating attenuation.

The growing global demand for food and the environmental impact caused by agriculture have made this activity increasingly dependent on electronics, information technology, and telecommunications technologies. In Colombia, agriculture is of great importance not only as a commercial activity, but also as a source of food and employment. However, the concept of smart agriculture has not been widely applied in this country, resulting in the high production of various types of crops due to the planting of large areas of land, rather than optimization of the processes involved in the activity. Due to its technical characteristics and the radio spectrum considered in its deployment, 5G can be seen as one of the technologies that could generate the greatest benefits for the Colombian agricultural sector, especially in the most remote rural areas, which currently lack mobile network coverage. This article provides an overview of the current 5G technology landscape in Colombia and presents examples of possible 5G/IoT applications that could be developed in Colombian fields. The results show that 5G could facilitate the implementation of the smart farm in Colombia, improving current production and efficiency. It is useful when designing 5G implementation plans and strategies, since it categorizes crops by regions and products. This is based on budget availability, population density, and regional development plans, among others., AUIP (Iberoamerican University Association for Postgraduate Studies), Spanish Government PGC2018-098813-B-C33, UAL-FEDER 2020 UAL2020-TIC-A2080

En este artículo se evalúan tres modelos de propagación: COST-231 HATA, Walfisch Ikegami e Interino de la Universidad de Stanford para un escenario suburbano. Los datos fueron recolectados en un drive test en la banda de 1900 MHz, para lo cual se eligió un sector de la ciudad de Barranquilla, Colombia. Como método de evaluación, se utilizó el cálculo del error de predicción y relativo de cada modelo con respecto a las mediciones.Los resultados obtenidos muestran que el modelo Interino de la Universidad de Stanford presentó niveles de error más bajos en relación a los obtenidos con el modelo COST-231 HATA y el Walfisch Ikegami.Los altos valores de error permiten concluir que los modelos analizados no representan las mediciones en el escenario estudiado, lo cual hace necesario procesos de ajuste a fin de mejorar los resultados, además de ampliar la campaña de medición para validar los hallazgos.