Battery-Powered Edge AI Module on Himax HX6538 with Cortex-M55 & Ethos-U55 | Open-Source Platform

Build smarter, energy-efficient devices with local AI that sees and reacts — without the cloud, without latency, and without constant power draw.

Visual Wake Word: just like a smart speaker listens for a voice cue, this module “wakes up” when it sees a human, vehicle, animal or another oblect you choose.

Autonomous operation, long battery life, and instant response — ideal for 

• Smart Doorbells: Instantly detect a person at the door and trigger alerts — no cloud or Wi-Fi required.

• Retail People Counter: Low-power presence detection and classification to track footfall and store occupancy.

• Wireless Security Node: Battery-powered edge device with visual wake-up; sends notifications when a person or vehicle is detected.

• Access Control System: Local AI detects authorized personnel or license plates, triggering gate or door mechanisms.

• Smart Bird Feeder / Wildlife Monitor: Recognizes specific species and logs sightings autonomously in the field.

• Construction Site Monitoring: Detect unauthorized human presence or restricted zone entries in low-power mode.

Ready-to-use Example Applications

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.

What can you do with it?

With this module, you can:

• Run neural networks for object detection and classification (e.g., animals, vehicles, license plates);
• Capture and process audio and video directly on the device;
• Develop fully autonomous systems that run on batteries or rechargeable power;
• Integrate it as a drop-in component into your final product.

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
• Current consumption during inference: ~3.02 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: 0.26 s (2 × 130 ms)
• Sleep time per minute: 59.74 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

1. Platform Evaluation

• You have a pre-configured dev kit 
  (hardware + firmware + pre-trained model)
• Run out-of-the-box demo (e.g., animal detection) to test:
  • Inference performance (FPS, accuracy)
  • API integration (REST/gRPC/edge SDK)
  • Hardware compatibility (CPU/GPU/NPU utilization)
• Review the API specification and model compatibility guidelines via the pre-built demo

2. Custom Model Integration

Swap the default demo neural network for a task-specific model 

(e.g., ANPR for local license plates) via:

• DIY path: adapt existing models;
• White-glove service: Grovety delivers a custom model (optimized for target hardware).

3. Prototype to Production

• Modify the open-source board firmware to implement custom business logic;
• Enhance the mobile app with required features and UI/UX changes;
• Finalize the hardware: uses existing enclosure or develops custom hardware.

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

Additional links:

Open-source object detection and classification project