10 Practical Applications For The Microcontroller AI Boards Like the Cyberpunk Board

Introduction

Are you ready to unlock the potential of edge AI with a microcontroller that’s as powerful as it is stylish? In just 60 days, Botshop’s Cyberpunk series will launch a groundbreaking AI board, designed in South Africa and built for both learning and deployment. This modular masterpiece—featuring the ESP32-S3, Neural processor  Kendryte K210 plug-in module, and a suite of sensors—empowers students and developers to create practical projects that bring intelligence to the edge. From gesture-controlled robots to voice-activated smart devices, let’s explore the exciting possibilities awaiting you with boards like the Cyberpunk AI board!

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What is edge AI?

Edge AI refers to the deployment of artificial intelligence (AI) algorithms and models directly on edge devices—such as microcontrollers, sensors, or IoT gadgets—rather than relying solely on centralised cloud servers for processing. This approach brings computation closer to the data source, enabling real-time analysis, decision-making, and action without requiring constant internet connectivity. By leveraging hardware such as the ESP32-S3 or Kendryte K210 on a board like Botshop’s Cyberpunk series AI board, edge AI minimises latency, reduces bandwidth usage, and enhances privacy by keeping sensitive data local. Applications range from gesture-controlled smart home devices and voice-activated security monitors to autonomous robots with crash detection, making it a transformative technology for industries and education, particularly in resource-constrained or remote environments.

Why the Cyberpunk AI Board Stands Out


The Cyberpunk AI board is more than just hardware—it’s a platform for innovation. With its neon-green and purple cyberpunk aesthetic, pulsing RGB LEDs, and compact 60x60 mm design, it combines style with substance. 

Powered by the ESP32-S3 for connectivity and control via MicroPython, and enhanced by the K210 for AI processing with MaixPy, this board supports a modular ecosystem. It is also compatible with popular programming languages like Python and C++, making it easy for developers to get started. Added onboard is the ICM-42670-P IMU for motion detection, INMP441 microphone for voice input, MAX98357A amplifier for audio output, ILI9341 TFT LCD (or OLED display) for vibrant displays, and OV2640 camera for vision. Whether you’re a student in a 5-hour workshop or a developer racing to market, this board supercharges your journey from idea to deployment.

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Practical Project Examples

Here are ten hands-on projects to inspire you, showcasing the board’s versatility for education and industry. From simple educational exercises to complex industry applications, this board is designed to meet your needs and exceed your expectations.

  1. Gesture-Controlled Smart Home Hub
    • What You’ll Do: Use the ICM-42670-P’s APEX engine to detect hand gestures (e.g., wave to turn on lights, tilt to adjust volume) and control smart devices via the ESP32-S3’s Wi-Fi. Display status on the ILI9341.
    • Skills Gained: Gesture recognition, IoT connectivity, MicroPython programming.
    • Application: A stylish, hands-free home automation system.
  2. Voice-Activated Security Monitor
    • What You’ll Do: Leverage the INMP441 microphone and K210 module for voice commands (e.g., “activate camera”), paired with the OV2640 for real-time video feed on the ILI9341. Use the MAX98357A to play alerts.
    • Skills Gained: Voice recognition, edge AI with MaixPy (a framework for edge AI), and video processing.
    • Application: A compact security solution for homes or small businesses.
  3. Robot Crash Detection S​ystem
    • What You’ll Do: Program the ICM-42670-P to detect impacts with reinforcement learning (RL) on the K210, triggering a visual alert on the ILI9341 and audio warning via MAX98357A. Use ESP32-S3 for data logging.
    • Skills Gained: Motion detection, RL, edge computing.
    • Application: Safety monitoring for autonomous robots or drones.
  4. Interactive Smart Mirror
    • What You’ll Do: Combine the OV2640 for face detection with the K210, display info on the ILI9341 (e.g., weather, time), and use the INMP441 for voice queries. Add gesture control with ICM-42670-P.
    • Skills Gained: Vision AI, multimodal interfaces, project integration.
    • Application: A futuristic mirror for smart homes or retail.
  5. Portable IoT Environmental Sensor
    • What You’ll Do: Connect external sensors to the ESP32-S3, process data with the K210 (e.g., air quality analysis), and display results on the ILI9341. Use MAX98357A for audio feedback. Include with a prediction module to predict possible outcomes.
    • Skills Gained: Sensor integration, edge data processing, MicroPython.
    • Application: Environmental monitoring for industrial or personal use.
  6. Gesture-Based Gaming Controller
    • What You’ll Do: Use the ICM-42670-P to detect dynamic gestures (e.g., swipe to move, tilt to jump) and send commands via the ESP32-S3’s Bluetooth to a game on a PC or mobile device. Display scores on the ILI9341.
    • Skills Gained: Gesture mapping, Bluetooth communication, and game development.
    • Application: A custom controller for educational games or casual gaming.
  7. Voice-Commanded Personal Assistant
    • What You’ll Do: Train the K210 with MaixPy to recognise custom voice commands (e.g., “set alarm,” “check time”) using the INMP441, with responses displayed on the ILI9341 and audio output via MAX98357A.
    • Skills Gained: Voice recognition training, edge AI deployment, audio integration.
    • Application: A portable assistant for personal or educational use.
  8. Autonomous Navigation Robot
    • What You’ll Do: Utilise the OV2640 and K210 for object detection to enable navigation of a robot, with the ICM-42670-P detecting obstacles or falls. The ESP32-S3 handles motor control, and ILI9341 shows the path.
    • Skills Gained: Vision-based navigation, real-time processing, robotics.
    • Application: Autonomous delivery or exploration bots.
  9. Smart Wearable Health Monitor
    • What You’ll Do: Connect a heart rate sensor (via Grove) to the ESP32-S3, process data with the K210 for anomaly detection, display results on the ILI9341, and use MAX98357A for audio alerts.
    • Skills Gained: Sensor data analysis, health tech, edge ML.
    • Application: Medical and wearable devices for fitness or medical monitoring.
  10. Interactive Art Installation
    • What You’ll Do: Combine the OV2640 for motion tracking, ICM-42670-P for gesture input, and K210 for real-time visual effects displayed on the ILI9341. Use MAX98357A for ambient soundscapes.
    • Skills Gained: Multimedia integration, creative coding, edge AI art.
    • Application: Public art exhibits or educational displays.

These projects leverage the board’s modular design, allowing you to start with the ESP32-S3 for basic tasks and add the K210 for advanced AI, all simplified with the CyberpunkAI library. 

Have more ideas? Tell us in the comments.

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