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.

In recent decades, expansion in urban areas has faced issues such as management of public waste, noise, mobility, and air quality, among others. In this scenario, Internet of Things (IoT) and Wireless Sensor Network (WSN) scenarios are being considered for Smart Cities solutions based on the deployment of wireless remote sensor nodes to monitor large urban areas. However, as the number of nodes increases, the amount of data to be routed increases significantly as well, meaning that the choice of the data routing process has great importance in terms of the energy consumption and lifetime of the network. In this work, we describe and evaluate the energy consumption of routing protocols for WSN-based Smart Cities applications in LoRa-based mesh networks, then propose a novel energy-saving radio power adjustment (RPA) routing protocol. The Cupcarbon network simulator was used to evaluate the performance of different routing protocols in terms of their data package delivery rate, average end-to-end delay, average jitter, throughput, and load consumption of battery charge. Additionally, a novel tool for determining the range of nodes based on the Egli propagation model was designed and integrated into Cupcarbon. The routing protocols used in this work are Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Distance Vector Routing (DVR). Our simulation results show that AODV presents the best overall performance, DSR achieves the best results for power consumption, and DVR is the best protocol in terms of latency. Finally, the proposed RPA routing protocol presents power savings of 11.32% compared to the original DSR protocol.

Spectrum scarcity and the inefficient use of the electromagnetic spectrum motivated the development of Cognitive Radio (CR), which aims to extend the spectral efficiency, with opportunistic access to the available frequency bands. Energy Detection (ED) is the most adopted spectrum sensing technique for cognitive radio applications due to its simplicity. However, fading effects are usually simplified or discarded when evaluating the energy detector performance in spectrum sensing. This paper presents the performance evaluation of cognitive spectrum sensing, based on energy detector, for fading channels. The objective is to analyze how the use of various fading models affect the spectral detection in cognitive networks. Rayleigh, Rice, Nakagami-m and Lognormal fading channels are considered, and the results favor the use of ED when the channel is subject to Lognormal fading.

Cognitive Radio (CR) is extending the applications of wireless communications worldwide. Cognitive radio verifies the electromagnetic spectrum availability and permits the modification of the transmission parameters using the interaction with the environment. The goal is to opportunistically occupy spectral bands with minimum interference to other users or applications. Cognitive radio for Vehicular Ad hoc Networks (CRVs or CR-VANETs) is a new trend in the automotive market. Recent and future vehicles will offer functionalities for the transmission of intra-vehicular commands and dynamic access to wireless services, while the car is in transit. This paper describes the cognitive radio technology and its signal processing perspectives for the automotive market

This article presents the development of a data acquisition system that uses a hybrid communication network based on long-range (LoRa) modules. This system aims to provide the gathered information over long distances. The proposed hybrid structure minimizes the costs involved in using LoRa transmitters, deploying a wired network to interconnect the sensors and actuators in the vicinity of the transmission point. This structure is compatible with the main existing industrial communication protocols, which facilitates the connection with preinstalled networks. A hydraulic plant was used to test the system having its instrumentation as a form to optimize the water distribution system (WDS) monitoring, where a mean of measurement error of 0.78% was obtained. Moreover, the performance of LoRa modules was evaluated in terms of the quality of data transmission over long distances. A noise analysis was also conducted to evaluate the influence caused on industrial sensors and the interference generated by elements in the environments that affect the considered system. The results demonstrate the viability of the proposed solution for remote and local monitoring of WDSs.

Vegetation encroachment alongside power lines in urban and rural areas are a common cause of interruption in power energy supply. A system based on Wireless Sensor Network (WSN) is proposed to support in the control of the vegetation growth. Sensors modules can be installed sequentially in transmission lines to monitor the vegetation encroachment in transmission lines. Embedded devices containing microprocessors and radio communication modules were used in practical experiments to prove it effectiveness in the detection of the vegetation in this scenario. The experimental results demonstrated that the system meets the requirements of the proposal, being a viable and reduced cost option for the monitoring of transmission lines.