The use of Wireless Sensor Networks (WSN) in smart agriculture has emerged in recent years. LoRaWAN (Long Range Wide Area Networks) is widely recognized as one of the most suitable technologies for this application, due to its capacity to transmit data over long distances while consuming little energy. Determining the number and location of gateways (GWs) in a production setting is one of the most challenging tasks of planning and building this type of network. Various solutions to the LoRaWAN gateway placement problem have been proposed in the literature, utilizing clustering algorithms; however, few works have compared the performance of various strategies. Considering all these facts, this paper proposes a strategy for planning the number and localization of LoRaWAN GWs, to cover a vast agricultural region. Four clustering algorithms were used to deploy the network GWs: K-Means and its three versions: Minibatch K-Means; Bisecting K-Means; and Fuzzy c-Means (FCM). As performance metrics, uplink delivery rate (ULDR) and energy consumption were used, to provide subsidies for the network designer and the client, with which to choose the best setup. A stochastic energy model was used to evaluate power consumption. Simulations were performed, considering two scenarios: Scenario 1 with lower-medium concurrence, and Scenario 2 with higher-medium concurrence. The simulations showed that the use of more than two GWs in Scenario 1 did not lead to significant improvements in ULDR and energy consumption, whereas, in Scenario 2, the suggested number of GWs was between 11 and 15. The results showed that for Scenario 1, the FCM algorithm was superior to all alternatives, regarding the ULDR and mean energy consumption, while the K-Means algorithm was superior with respect to maximum energy consumption. In relation to Scenario 2, K-Means caused the best ULDR and mean consumption, while FCM produced the lowest maximum consumption.

Precision Agriculture (PA) is a method for estimating, assessing and controlling agricultural practices. It emerged from the need for technologies to collect and transmitt data in agricultural areas. On the other hand, the evolution of wireless sensor nodes technology enabled the deployment of Wireless Sensor Networks (WSNs) in agricultural environments. The lack of path loss models for predicting attenuation in vineyard vegetation motivates the study of propagation in this kind of environment. Thus, the objective of this research is to assess signal propagation in a vineyard. In this paper, the impact of different propagation directions was assessed considering the angle between the transmission path and the crop rows (θ). From the experiments, it was possible to find the main attenuation factors of the plantation field and obtain a path loss prediction model that fits well to measurements.

Energy management in Wireless Sensor Networks (WSN) is a challenging problem that calls for careful modeling and analysis. It is shown in the paper that the problem can be more precisely characterized by calculating the probability distribution function (PDF) and the maximum and minimum values of the energy consumed by the network. As a result, this paper provides a novel approach for modeling and assessing the probability range of energy expended by WSN nodes. The steps that were taken for developing this project were: (1) an initial investigation into the power consumption of WSN devices; (2) the proposal of a stochastic model for consumption; (3) the collection of data using the LoRaWANSim simulator; and (4) the interpretation and comparison of simulation with theoretical results. The examination of the suggested method with a discrete-event simulator and the resulting mathematical expressions provide a deeper insight into the energy consumption patterns of WSNs.

Wireless sensor networks have been proposed as a solution to obtain soil and environment information in large distributed areas. The main economic activity of the São Francisco Valley region in the Northeast of Brazil is the irrigated fruit production. The region is one of the major agricultural regions of the country. Grape plantations receive large investments and provide good financial return. However, the region still lacks electronic sensing systems to extract adequate information from plantations. Considering these facts, this paper presents a study of path loss in grape plantations for a 2.4 GHz operating frequency. In order to determine the position of the sensor nodes, the research dealt with various environmental factors that influence the intensity of the received signal. It has been noticed that main plantation aisles favor the guided propagation, and the vegetation along the secondary plantation aisles compromises the propagation. Diffraction over the grape trees is the main propagation mechanism in the diagonal propagation path. Transmission carried out above the vineyard showed that reflection on the top of the trees is the main mechanism.

Wireless Sensor Networks (WSNs) can be used to monitor large agricultural areas, as the São Francisco Valley region in the northeast of Brazil. The main economic activity is grape growing for export which demands high quality production in order to attend the market requirements. This work presents an experimental study of path loss in grape plantations located in this region performed based on a measurement campaign. The research will aid the deployment of WSNs in São Francisco Valley region.