Desenvolvimento de um back-end usando django e um broker MQTT para monitoramento de dados agrícolas

Abstract

Modern agricultural activity requires the use of new technologies to improve production and the working environment in the field. One example of these technologies is the Internet of Things (IoT), in which a network of sensors can collect various data from the field and monitoring and management platforms can help in decision-making about planting. Recent studies have attempted to develop agricultural IoT solutions with the Jaguaribe Valley region in mind, where the basic idea is to have embedded platforms equipped with sensors that capture data from the field and make this data available on an MQTT broker. In this sense, this work implemented a back-end system that connects to an MQTT broker for agricultural monitoring. Initially, the functional and non-functional requirements of the system and their level of priority were defined. Based on these requirements, the MTV architecture was chosen, used by the Django and Django REST frameworks, in which the application was developed. To improve the system visualization, a sequence of UML diagrams was developed. The use case diagram shows the general interactions that users will have with the system functionalities; the sequence diagrams demonstrate the data flow and function calls of the main functionalities; and the class diagram shows the main classes, defined methods and their relationships. To validate the application, a test plan was prepared that includes the hardware and software used, the definition of the failure level and the specification of the test cases, with their origins and guidelines for the tests performed. Based on the results obtained, difficulties during development were identified, such as establishing communication between the application and the MQTT broker, which was only resolved after a series of tests. The results also show the ease of developing more basic functionalities. The development of this application offers a simple and easy-to-configure tool that will contribute to improving agricultural production monitoring.