Build and program IoT sensor stations to accurately measure and analyze environmental data such as temperature, humidity, air pressure, air quality, light, and noise levels.

Apply mathematical formulas and scientific principles (e.g., barometric formula, Steinhart-Hart equation) to interpret sensor data and create forecasts or indicators.

Design and implement IoT communication using protocols like MQTT to transmit data to online dashboards for real-time visualization and remote monitoring.

Integrate multimedia elements, such as webcams, into IoT systems for enhanced data representation and surveillance.

Develop and train artificial intelligence (AI) models by collecting labeled image data, running training processes on computers, and deploying trained models on embedded controllers.

Implement AI-powered object recognition systems to classify objects and control hardware outputs (LEDs, motors, barriers) based on AI inference results.

Apply AI and machine learning concepts in practical automation scenarios, such as intelligent barriers and sorting lines, to make autonomous decisions based on sensor input.

Program precise motor control and actuator management using encoder feedback for accurate movements in robotic systems.

Structure modular, clear, and maintainable programs using functions and event-driven programming techniques.

Evaluate AI system performance using statistical methods, including true/false positives and negatives, confidence levels, and reliability indicators, to improve model accuracy.

Design user-friendly interfaces and enable voice or remote control to facilitate intuitive interaction with IoT and robotic systems.

Integrate multiple technologies into cohesive, functional projects combining sensing, AI, communication, and actuation for real-world applications.

Develop problem-solving skills and technical knowledge that prepare students for further study or careers in robotics, AI, IoT, and automation engineering.