PYC Basic II

AIoT programming introductory equipment for training IoT and data science and machine learning

Realization of training with one board composed of high-performance, low-power ARM quad-core processor modules and various I/O devices optimized for training to collect and analyze sensor data  and forecast  them through the model definition in real time at AIoT environment

To enhance the understanding of embedded interface, various input devices such as GPIO-controlling button, ultrasound, ADC-based distance measurement, illumination, noise level, movement sensing,  I2C-based proximity, ambient illumination, color, gesture, temperature and humidity are provided

To support the visualization of analyzed or forecast sensor data, various output devices such as basic LED, OLED that can output texts or brief graphics,  RGB-type 16×16 Pixel Display accompanied with colorful lighting effects are provided 

Gigabit Ethernet, dual-band Wi-Fi (2.4GHz, 5GHz) and Bluetooth 5.0 are provided to make the remote-control of the equipment possible with smartphone or tablet in the IoT connectivity environment

Web browser-based dedicated learning environment that supports Python 3 and C11/C++17 based on interpreter of European Institute of Particle Physics  and Blockly: the Google block coding platform is provided to enhance the expediency of AIoT programming

Soda OS where  Debian Linux is optimized for training of ARM-based IoT, data science, and machine learning and Pop library where supports reliable hardware abstraction are provided

Supports the open integrated development environment based on Visual Studio Code for professional application development

Dedicated learning contents required for realizing IoT, data science, and machine learning are provided