Introduction
The UNIHIKER K10 + M10 bundle includes two powerful educational tools designed to provide a comprehensive AI and IoT learning experience. The UNIHIKER K10 serves as an entry-level AI learning device with pre-installed vision models and TinyML capabilities, while the UNIHIKER M10 offers advanced computational power and IoT integration for complex projects. Together, they enable users to transition seamlessly from foundational AI concepts to advanced applications.
Differentiated Learning Pathways
UNIHIKER K10: AI Literacy Accelerator
Ideal for: Grade 3+, Elementary STEM Clubs | Homeschool Foundations
Instant AI Validation: Pre-loaded models deliver quick wins (QR code scanning → classroom attendance systems)
Failure-Proof Coding: Drag-and-drop AI blocks generate MicroPython for tactile learners
Classroom-Ready: 10+ plug-and-play sensors enable 45-min lesson plans
UNIHIKER M10: Production-Grade Sandbox
Essential for: Grade 6+, High School Robotics | College Prototyping
Enterprise Tech Stack: Debian OS + VSCode mirrors industry environments
Model Iteration Workflow: Train MobileNet models on M10 → deploy to K10 via edge computing
IoT Scaling: Local SIoT server handles 50+ device networks (smart campus simulations)
Figure: UNIHIKER - AI, IoT, and Python Coding Learning Devices
Figure: UNIHIKER Supports AI for Vision, Voice, and Sensors
Scalable IoT Project Integration
K10: Collects sensor data (temperature, light, motion) and transmits via Wi-Fi/Bluetooth for simple IoT setups, visualized on its 2.8-inch screen.
M10: Expands to large-scale IoT systems with built-in Jupyter Notebook, SIoT service (local MQTT data storage), and Python-driven API integration for cloud connectivity.
Figure: UNIHIKER built-in and expandable sensors for comprehensive data collection
Figure: UNIHIKER Supports the Internet of Things
Unified Hardware & Software Ecosystem
K10: Simplified block coding (Mind+) and MicroPython for rapid prototyping.
M10: Professional tools (VS Code, Thonny) and Debian OS for Python scripting, Git workflows, and multi-device control.
Shared Expandability: Both devices support Gravity sensors, motors, and third-party modules, enabling projects from smart homes to robotics.
Figure: UNIHIKER Supports Code-based Programming and Visual Programming
Figure: UNIHIKER K10 and UNIHIKER M10 Overview
Specification
UNIHIKER K10:
MCU: ESP32-S3 Xtensa LX7
SRAM: 512KB
Flash: 16MB
Wi-Fi: 2.4G
BT: Bluetooth 5.0
Screen: 2.8 inch, 240x320
Camera: 2MP
Sensor: Button, Microphone, Temperature Sensor, Humidity Sensor, Light Sensor, Accelerometer Sensor
Actuator: RGB Lights, Speaker
Pre-Installed AI models:
Face Detection
Image Recognition
Cat/Dog Detection
QR Code Recognition
Motion Detection
Local Speech Recognition
Custom Voice Commands
Port: USB Type-C, MicroSD, Gravity 3pin & 4pin port, 2pin ph2.0 battery port, Edge connector
Power: USB Type-C, Battery Port, Edge Connector
Size: 51.6mm x 83mm x 11mm
UNIHIKER M10:
CPU: Quad-Core ARM Cortex-A35, up to 1.2GHz
RAM: 512MB
Flash: 16GB
OS: Debian
Wi-Fi: 2.4G
BT: Bluetooth 4.0
Screen: 2.8inch, 240×320, Touch Screen
MCU: GD32VF103
Sensor: Button, Microphone, Light Sensor, Accelerometer Sensor, Gyroscope Sensor
Actuator: Led, Buzzer
Port: USB Type-C, USB-A, Gravity 3pin & 4pin port, Edge connector
Power: 5V 2A for USB Type-C
Size: 51.6mm x 83mm x 13mm
Shipping List
UNIHIKER K10:
UNIHIKER K10 x1
Type-C USB cable x1
UNIHIKER M10:
UNIHIKER M10 Single Board Computer x1
Type-C USB cable x1
Double Sided PH2.0-3P white 20cm silicone wire x4
Double Sided PH2.0-4P white 20cm silicone wire x2
Documents
UNIHIKER K10 Documentation
UNIHIKER M10 Documentation
UNIHIKER Projects
UNIHIKER Tutorials
Applications
Education: K12 AI curriculum alignment (CSTA, NGSS), bridging block coding (K10) to Python/ML (M10).
Prototyping: Rapid development of AIoT systems, from voice-controlled devices (K10) to cloud-connected dashboards (M10).
Research: Collect sensor data via K10 and analyze trends using M10’s computational power for environmental or robotics projects.