UNIT Pulsar C6 ESP32-C6 - UNIT Electronics

UNIT Pulsar C6 ESP32-C6

Proton AI Core Vision – ESP32-S3 Edge AI & Vision Board (3 Cards at Once) kit

$30.00
Availability: In stock
SKU
PDA11101P
Weight
100g
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3 Cards at Once Proton Ai Core Vision+

The ESP32-S3 based embedded AI development board is designed for edge AI, computer vision, voice processing, and motion detection applications. It features camera support, a built-in microphone, a 6-axis IMU, and external sensor expansion capabilities for rapid AI prototyping.

Proton AI Core is an embedded AI development board based on the ESP32-S3, designed for edge AI, computer vision, and multimode sensing applications. The board targets developers, manufacturers, and researchers who want to run AI workloads directly on the device without relying on cloud processing.

 

At its core, Proton AI Core is built around the ESP32s3 microcontroller, featuring dual-core processing and vector acceleration optimized for embedded AI inference. This makes it suitable for running lightweight neural networks directly on edge devices for tasks such as image classification, object detection, voice analysis, and sensor integration.

 

This board supports camera-based computer vision via a dedicated camera interface, enabling real-time image capture and processing for AI vision projects. In addition to vision capabilities, Proton AI Core also includes a built-in microphone, allowing developers to experiment with voice-based AI use cases such as wake-word detection, voice classification, and voice-triggered control.

 

To support motion and context-sensing applications, the board includes a 6-axis IMU (accelerometer + gyroscope). This enables use cases such as gesture recognition, motion tracking, orientation detection, and sensor fusion combined with image or audio data.

 

For extensibility, Proton AI Core provides external ports for additional sensors and peripherals, allowing developers to connect I²C-based sensors, external modules, and custom hardware. This makes the board flexible for rapid prototyping and testing in a wide variety of embedded AI scenarios.

 

Typical use cases include:

 

• Edge AI and computer vision experiments

 

• AI-powered IoT devices

 

• Robotics Projects in Schools or Educational Institutions

 

• Motion-sensing AI applications

 

• Voice-sensitive embedded systems

 

• Rapid prototyping of AI-powered hardware products

 

• Educational and research projects involving embedded machine learning

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