This paper presents EstacionaTEC, an innovative educational project that bridges theory and practice by engaging engineering students in developing a smart parking system based on IoT and AI. The project's core objective is aligned with Sustainable Development Goal (SDG) 11, aiming to make cities more sustainable by tackling parking inefficiencies on university campuses, thereby reducing vehicular emissions and optimizing resource use. The methodology involved a hands-on, project-based approach where students designed and integrated a network of sensors (ultrasonic, NFC, environmental) with NodeMCU ESP8266 microcontrollers, an Oracle database, and a real-time dashboard using Oracle APEX. A key innovative component was the implementation of Google's Gemini AI for visual validation of fire alerts, enhancing system intelligence. The results successfully demonstrate a functional prototype that provides real-time parking occupancy, automated access control, and environmental monitoring. This project serves as a model for how experiential learning in IoT and AI can produce tangible solutions for campus sustainability, proving its potential to decrease search time, lower CO2 emissions, and provide a scalable smart parking framework.
