The equipment for these labs includes different microcontroller boards like Raspberry Pi, Arduino, and ESP32, many types of sensors for measuring temperature, motion, light, and more, as well as devices that can act on commands.
Communication tools like Wi-Fi, Bluetooth, and LoRaWAN are also needed. High-performance computers, sometimes with special graphics processors for AI work, are essential.
Access to cloud AI platforms such as AWS, Google Cloud AI, and Azure ML, along with software tools like TensorFlow and PyTorch, is important for building and training AI models.
Other tools like breadboards, multimeters, and data collection devices help students design, build, test, and use smart connected projects.