Edge AI Vision Module (Himax HX6538)

Bring powerful edge computer vision into your DIY projects — on battery power.
With Cortex-M55 and Ethos-U55, this module runs real AI inference on images and video locally, no cloud, no server.

• Battery-powered AI — deploy computer vision anywhere.
• Run CNN models optimized for Ethos-U55 — object detection, image classification, face recognition.
• Open-source ready — full SDK and examples to get started fast.
• Partner edition — designed by GRC, distributed by Elecrow, tuned for makers.

Connect a camera, run low-power vision, and wake up your project on events.

Key Features

• Visual Wake Word – reacts to people, animals, and vehicles

• Ultra-low power – runs for weeks on a single battery

• Pluggable camera support – with ToF sensor and microphone inputs

• Open-source SDK – with sample applications included

• Easy integration – works with Arduino and Edge Impulse

Use cases

• Smart security camera — detect people or vehicles locally.
• Wildlife photo trap — trigger captures only when animals appear.
• DIY vision robot — give your robot the power to see and recognize objects.
• Access control — offline face-based recognition system.

What Makers Get

• A fast start with built-in Visual Wake Word

• The ability to teach your project to see and react

• Ready-to-run demos — get results right after power-up

• A flexible platform for your own Edge AI experiments

Ready-to-Run Demos

Out of the box, the module comes with optimized demos.

Gate — Standalone ANPR Module for Gate & Barrier
A fully autonomous, battery-friendly module that opens your barrier or gate when it detects a recognized license plate.

Wild — autonomous long-term AI camera trap
Battery-powered AI camera trap for wildlife monitoring. Detects animal and bird species using onboard neural networks — no cloud or internet required.

Power Consumption and Battery Life

Sleep Mode:

• Base current consumption: 316 µA
• Applies when all peripherals are disabled (deep sleep)

Inference Mode (refers to detection & recognition networks):

• Active duration per inference: 130 ms + Himax startup time per inference 50 ms
• Current consumption during inference: ~30 mA
• Includes: activity of Himax HX6538 and Ethos-U55 NPU, including internal handling of camera and peripheral interfaces. External peripheral power consumption (camera, ToF sensor, mic, etc.) is not included.

Battery Life Example: Periodic Inference (2× per minute)

Assuming the device performs inference twice per minute, the average current is calculated as:

• Active time per minute: 0.36 s (2 × (130+50) ms)
• Sleep time per minute: 59.64 s
• Average current:

With a 2500 mAh battery, expected runtime:

 This makes the platform ideal for long-term deployments in battery-powered applications with periodic AI inference, such as remote sensors, monitoring systems, etc..

Power Consumption Data Available

When you purchase this module, we will also provide a detailed document outlining its power consumption in various operating modes — helping you accurately estimate energy usage in your final device.

Fast time to market

Use the module as a finished component — build your enclosure, add your model, and go to production.

• Open-source stack: Full firmware, Android app, and documentation available to accelerate development and customization.
• Ready-to-use platform: Includes camera interface, microphone array, uSD storage, ToF sensor, IMU, and Bluetooth — all pre-integrated.
• Free Support for Buyers

Open-source projects for rapid product development

An open-source object detection and classification project that you can customize for your specific use case

Ready-to-Use Software Ecosystem

The module comes with a complete open-source software stack, making it easy to start development and deploy real-world AI solutions without writing low-level code.

Supported Frameworks and Toolchains

• TensorFlow Lite Micro – for running quantized neural networks efficiently on MCUs

• CMSIS-NN – Arm-optimized neural network kernels

• Standard Arm toolchains – Compatible with Keil Studio, VSCode + PlatformIO

Everything is Open-Source:

• Preloaded firmware, example models, and full API documentation

• Android demo app with source code

• Easy model swap (replace pre-trained network with your own)

Example Projects & References:

• Visual Wake Word demo on Arm’s Corstone-320 MLEK:
  https://community.arm.com/arm-community-blogs/b/ml-ai/posts/ml-ek-vww

• Official Visual Wake Word dataset and benchmark:
  https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/person_detection/README.md

• Himax SDK and NPU documentation:
  https://www.himax.com.tw/products/ai-sensors/ai-accelerators/

Free Support for Buyers

When you purchase this module, you get free technical support and expert consultation to help you design and launch your own AI-powered solution.
Whether you're building a wildlife camera, smart gate, or custom embedded device — we're here to help from PoC to production.

End-to-End Development Workflow

Outcome: A ready-to-sell solution with low development costs and short time-to-market.

Subsystems & Their Functions

Under Himax control

• Image capture from camera module
• Audio acquisition from 4-microphone array
• Image processing using built-in hardware accelerators
• Image/audio processing using neural networks and Arm Ethos
• Data exchange with nRF52833 via SPI/I2C interfaces
• microSD card operations

Under nRF52833 control

• Himax communication via SPI and/or I2C interfaces
• Host communication via Bluetooth and/or USB-UART interfaces
• Power management and device configuration 
• (Himax, accelerometer, ToF sensor)
• Battery charging control and state monitoring
• LED control and button state reading

Hardware Components List

 1. Processing Units

• Main MCU: HiMax HX6538 – Handles primary tasks:
  • Neural network acceleration (Ethos-U55 NPU)
  • Camera interfacing (MIPI CSI-2)
  • Microphone array processing (PDM/PCM)
  • uSD card storage management

• Peripheral MCU: Nordic nRF52833 – Manages:
  • Bluetooth 5.2 Low Energy connectivity
  • Power management (battery/DC-in)
  • Time-of-Flight (ToF) sensor data acquisition
  • Inertial Measurement Unit (IMU) processing

2. Sensors & Peripherals

• Imaging:
  • Camera-In (MIPI interface) – Primary vision input
  • Camera-Out (Debug/auxiliary feed)
• Audio:
  • Dual PDM microphones – Beamforming-capable
• Environmental:
  • ToF sensor (VL53L5CX or equivalent)
  • 6-axis IMU (Accel + Gyro)

3. Storage

• uSD card slot – For high-capacity logging (video/audio)
• NOR Flash (64Mb+) – Firmware/ML model storage

From object detection to face recognition — start building your own computer vision projects today!

Additional links:

• Open-source object detection and classification project