Aplicação de Machine Learning em sistemas embarcados de borda: um estudo de caso

Abstract

The main premise of this project is to conduct a case study on the use of machine learning technology and edge computing in the development of a proof-of-concept prototype. The focus will be on implementing artificial intelligence in a device that utilizes computer vision to real-time identify the presence of moving obstacles during the reverse maneuver of a motor vehicle. Throughout the project, the methods and techniques used for this type of application will be evaluated, including the effectiveness and efficiency of different machine learning algorithms, computer vision techniques, and edge computing approaches. Additionally, cutting-edge technologies relevant to this field will be explored. Through this case study, the aim is to demonstrate the potential of machine learning and edge computing in enhancing the safety and efficiency of motor vehicle operations, particularly during challenging maneuvers such as reverse parking. The results and insights obtained from this project can contribute to further advancements in the field of intelligent transportation systems.