Development of an Artificial Intelligence Integrated into an Embedded Sensor System for Air Quality Monitoring

My work focuses on the development of an intelligent embedded system for air quality monitoring. I design PCB board integrating gas sensors and microcontrollers (ESP32), and I work on data acquisition and analysis of environmental signals such as NO₂, CO₂, and NH₃. In addition, I develop machine learning models to process sensor data, focusing on improving selectivity, drift compensation, and robustness to environmental variations.