Artificial Intelligence (AI) and the Internet of Things (IoT) are key drivers of today's digital transformation; therefore, engineering training programmes need practical learning tools that reflect these technologies. This paper presents the design and implementation of an electric fan control system that integrates AI-based speech recognition with IoT technology. The system uses an ESP32-S3 Yolo Uno board as the central controller, combined with a DHT20 temperature–humidity sensor, a light sensor, an I2C LCD and a relay module that switches the fan on and off. Sensor data are transmitted via the MQTT protocol to a cloud-based dashboard, allowing users to monitor the environment and turn the fan on and off remotely from a smartphone or computer. Functional tests on the prototype showed that 10 of 10 voice commands and 9 of 10 dashboard commands were executed correctly. Beyond its potential application in smart homes, the model also serves as a practical training kit for students of Electrical and Electronic Engineering, integrating sensors, embedded programming, electrical switching, IoT communication and applied artificial intelligence into learning activities. In this way, the model helps students develop the digital competencies that are widely applied in today's practice.