Sistema de monitoramento de animais usando dispositivo IOT com integração mobile

Abstract

This study aims to develop and validate an animal monitoring system using sensors connected to an IoT device, integrated with a mobile application. The system was designed to collect and transmit real-time data on animal location and movement through GPS and accelerometer (ADXL345) sensors. These data are sent to an API developed using Django REST Framework, stored in a database, and made available to the end user via an application built with the Ionic framework. The adopted methodology was based on Design Science Research (DSR), including stages such as design, development, controlled environment testing, and field evaluation with sheep. The tests demonstrated the technical feasibility of the solution and its ability to capture relevant data, even with interference caused by the animals themselves. Furthermore, the system structure allows scalability, integration with machine learning algorithms, and future automation of analysis and report generation. It is concluded that the application presents practical potential to support animal management, promoting improved welfare and efficiency in monitoring.