Avaliação da Tecnologia Lora em Cenários de IoT na Suplementação de Bovinos de Corte

Abstract

With the increase in demand for resources and food and in the face of problems such as climate change that impact production, Internet of Things (IoT) technologies, and low-power, long-distance wireless networks (LPWANs) have emerged as technological tools that may assist in addressing these demands. IoT devices have multiple applications in precision livestock: tracking, weight estimation, animal welfare, and feeding. Supplementation activity (part of livestock feeding activities) consists of providing feed supplements in addition to the forage available to the herd. Supplementation is a crucial activity to achieve quality and productivity goals. There are programmable automatic feeders (PAFs) that provide more assertive supplementation and with little human intervention. These machines have technological resources to distribute supplements, acquire, process, and send data. This master thesis presents a research work on network simulation on cattle supplementation scenarios in order to understand limitations of the technology and project its expansion in the future. The simulation was carried out using Network Simulator (NS-3) software to evaluate the performance and scalability of LoRaWAN technology, which is used in PAFs.