METHODOLOGY FOR TEACHING COMPUTER VISION TECHNOLOGIES IN STEM-PROJECTS USING HARDWARE COMPUTING PLATFORMS

Abstract

In modern digital society, the development of digital competence plays a crucial role in preparing learners.One of the promising areas of its development is the use of computer vision technologies. This article explores the practical aspects of using computer vision through the development and programming of a self-guiding fan based on the ESP32CAM microcontroller, demonstrating an example of integrating intelligent systems into the educational process.The article analyzes the theoretical and practical aspects of creating automated control systems that utilize object and facial recognition methods via computer vision. The hardware components are examined, including the ESP32CAM microcontroller, servo motors, mounting systems, and power supply elements. Additionally, the software aspects are described, particularly image processing algorithms, the use of machine learning libraries, and optimization methods for improving recognition processes.Special attention is given to the integration of such technologies into the education system. The article suggests ways to incorporate computer vision-based educational projects into school, vocational, and higher education curricula. Examples are provided of how this project can be utilized within STEM education, programming and robotics courses, embedded systems studies, and the Internet of Things (IoT). Emphasis is placed on an interdisciplinary approach.Moreover, the article discusses the potential applications of such projects in scientific research, hackathons, and practical laboratory sessions in technical universities. The paper explores ways to improve computer vision algorithms to enhance object recognition accuracy, the use of deep neural networks, and the expansion of device functionality through cloud service integration for real-time data processing.