Facial Recognition in Embedded Systems

This work explores how facial interaction technologies can be integrated with embedded systems to create responsive, intelligent control interfaces that connect image recognition with electromechanical actions. The use of multiple biosignal modalities demonstrates the relevance of FICS in human-computer interaction, IoT, and assistive technology. The system manages LEDs, relays, motors, and displays, showing adaptability to different actuators and applications. The theoretical section reviews facial recognition technologies, covering computer vision, machine learning, and HCI principles, while tracing the evolution of FICS in automation and assistive contexts. The practical section presents the Vision-Activated Control System, which employs an ESP8266 microcontroller to process facial expressions, gaze, and blinks in real time. By integrating open-source vision and speech libraries with a wireless microcontroller, the system demonstrates how everyday devices can be operated through intuitive, hands-free inputs.

Autorentext
Natalia Anfilova earned a BA in Oriental Studies at St. Petersburg State University, Russia, with training in Indonesia and Germany. The author later obtained a degree in Electromechanical Engineering at the University of Petrosani, Romania, complemented by academic activities in Turkey, Belgium, and France.