SKU: TH2196
UNIHIKER K10 AI Agent Coding Board is a STEM-focused AI learning platform built for beginners, students, and makers who want to explore computer science, TinyML, computer vision, and voice interaction on real hardware.
It combines an ESP32-S3 controller with a 2.8 inch 240×320 display, 2MP camera, microphone, speaker, RGB lights, and onboard sensors, making it easy to build interactive AI projects without assembling a large stack of external modules.
With pre-installed vision models and offline speech recognition, the board is well suited for face detection, image recognition, QR code projects, motion sensing, and custom voice command applications that can run locally.
The UNIHIKER K10 is a practical board for classroom demos, AI experiments, beginner coding lessons, and rapid prototyping. Students can move from simple sensor interactions to vision and voice projects on one board.
Typical use cases include face-aware displays, voice-controlled gadgets, QR scanners, interactive learning projects, motion-triggered devices, and entry-level edge AI experiments.
Technical details for DFRobot UNIHIKER K10 AI Agent Coding Board.
| Brand | DFRobot |
|---|---|
| Model | UNIHIKER K10 |
| MCU | ESP32-S3 Xtensa LX7 |
| SRAM | 512KB |
| Flash | 16MB |
| Wireless | Wi-Fi 2.4G, Bluetooth 5.0 |
| Display | 2.8 inch, 240×320 |
| Camera | 2MP |
| Sensors | Button, microphone, temperature sensor, humidity sensor, light sensor, accelerometer sensor |
| Actuators | RGB lights, speaker |
| Ports | USB Type-C, MicroSD, Gravity 3-pin & 4-pin port, 2-pin PH2.0 battery port, edge connector |
| Power Input | USB Type-C, battery port, edge connector |
| Dimensions | 51.6 × 83 × 11 mm |
Out of the box, the board includes ready-to-use AI features that help learners start quickly and focus on building projects instead of spending all their time on setup.
Note: package contents and additional accessories are not specified in the supplied product data.
It comes with pre-installed AI features including face detection, image recognition, cat/dog detection, QR code recognition, motion detection, local speech recognition, and custom voice commands. It is built for beginner-friendly STEM, AI, and TinyML projects.
Yes. The board supports local speech recognition and custom voice commands, so offline voice-based projects are supported without depending on cloud processing for those features.
It includes a 2MP camera, 2.8-inch 240x320 screen, microphone, speaker, RGB lights, buttons, and onboard sensors such as temperature, humidity, light, and accelerometer. This makes it suitable for interactive AI, vision, and sensor-based STEM builds.
The board offers Wi-Fi 2.4G and Bluetooth 5.0, along with USB Type-C, MicroSD, Gravity 3-pin and 4-pin ports, a 2-pin PH2.0 battery port, and an edge connector. These interfaces help with storage, power, and connecting external modules or peripherals.
It supports power input through USB Type-C, the battery port, or the edge connector. This gives flexibility for desktop learning setups as well as portable project use.
The board uses an ESP32-S3 Xtensa LX7 MCU with 512KB SRAM and 16MB flash. Its physical size is 51.6mm x 83mm x 11mm.
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