AIoT Home

Product Name : AIoT Home

Model: LA-AIoT-01

Equipment Description:
• AI and IoT convergence training equipment using 2D model of living room of home
• Main module supporting AI acceleration calculation, multimedia and various IoT sensors are integrated into the base board
• The main module is selectable between a 128-core GPU supercomputer for edge devices or a Cortex-A72 quad-core processor
with tensor processor unit
• 5 inch TFT LCD with 800×480 resolution and 8M pixel high resolution camera
• Provides Gigabit Ethernet, dual band Wi-Fi(2.4GHz, 5GHz) and Bluetooth 4.2 or 5.0
• Digital microphones and speakers support cloud-based speech recognition and audio playback
• 4 dedicated expansion interfaces support various IoT sensor modules
• Positioning sensors and actuators by creating 2D models of living rooms in real homes to increase attention
• Soda OS, the exclusive AIoT operating system, and Pop library
• Interpreter-based C/C++ development environments optimized for beginners to program including Python 3
• A dedicated web browser-based learning environment for training Python 3 and C/C++ simultaneously on PCs and tablets
• mDNS/DNS-SD based distributed name resolution, network service publishing and discovery support
• Open Integrated development environment based on Visual Studio Code for professional application development
• Educational contents for IoT sensor control, multimedia and AI
• AIoT Home Plus provides 8 types of IoT sensor modules connected to a dedicated expansion interface
• AIoT Home PrimeX contains a supercomputer up to 21TOPS supporting all AI frameworks

Training Centers :


Configuration and Practice Environment of AIoT Home
Python and Linux 101
IoT Application Technology


File and DB-Based Data Persistence
Audio Recording and Playback
Google Text-to-Speech Converter
Google Assistant and User Device Actions
Camera and Sensor Application

 

 AI Technology :
Numpy for Fast Multidimensional Matrix Operations
Pandas for Time Series and Tabular Data Analysis
Matplotlib for Data Visualization
Supervised and Unsupervised Learning
Theory & Practice for Pop.AI-based Linear and Logistic Regression Algorithm
Theory & Practice for Pop.AI-based Perceptron
Theory & Practice for Pop.AI-based ANN, DNN, and CNN
Theory & Practice for Pop.AI & OpenAI DQN-based Reinforcement Learning
Understanding Tensorflow

Product Configaretion :

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