Sistema eletrônico e computacional baseado em internet das coisas para equipamentos de agropecuária de precisão

Abstract

The need for control and automation to create an intelligent farm through the integration of different systems with the Internet aims to create a precision agriculture (PA) environment. This action is an immediate necessity due to population growth and increasing demand for food production in a sustainable manner. The action is pointed out as a necessity for the future agricultural scenario according to the United Nations, the European Parliament, the Governments, the World Bank, and the National Development Banks. The Internet of Things (IoT) is a general term, where "things" means all that we can add a sensor to measure something and add an IP address to connect to the Internet. One of the fields of IoT application is to integrate farming systems and create an intelligent farm environment using a sensors network. Within the context of precision agriculture, these concepts are applied in the rope wick applicator known as Campo Limpo, developed by EMBRAPA, as a case study that aims at the precise and intelligent application of the herbicide, selecting only the target vegetation. For this to happen, different sensors repre senting the eyes, ears and other senses are needed, in some cases at levels beyond human capacity. The organization and processing of these data generates relevant information so that the productive process occurs in a sustainable, more competitive, and at the lowest cost way. In order for this set of information to be available and the controls to be effective, it is necessary to have standardization such as the use of the ISO 11783 (ISOBUS) for communication among devices. Thus, this work proposes, implements, and evaluatesin reduced-scale a system model based on ISOBUS that allows the implement to access sensors and actuators and perform the tasks necessary for its operation and integration to the tractor and the farm through the IoT, where the data generated by the sensors can create indicators related to the operation equipment, field quality, and improved herbicide use techniques, as well as mapping and using mappings generated by other smart farm systems.