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Education & Toys
SketchSense
AI Smart Drawing Board based on ESP32-S2
LCD drawing tablet that recognizes hand-drawn shapes and provides stroke correction guidance for children learning to write.
Shape Recognition
94%
Pressure Levels
4096
SketchSense
Client
An educational technology company creating a digital drawing tablet for children that provides real-time feedback on handwriting and drawing skills.
Challenge
Achieving low-latency handwriting recognition and shape classification on-device for children aged 3-8, supporting both free drawing and structured tracing exercises.
Product Concept & Architecture
The ESP32-S2 with USB OTG reads a Wacom EMR digitizer (4096 pressure levels) over SPI. A 10.5-inch monochrome LCD provides a paper-like drawing experience.
Engineering Solution
We implemented a real-time stroke processing pipeline: raw pen coordinates (200Hz) → Douglas-Peucker simplification → stroke classification (TinyML CNN, 30KB). In trace mode, the system compares the child's stroke to the template using Dynamic Time Warping and provides visual correction cues.
Result
<30ms pen-to-display latency. 94% shape recognition accuracy. Used in 200+ occupational therapy practices.
Deep Tech FAQ
What makes the AI Smart Drawing Board based on ESP32-S2 unique?+
The AI Smart Drawing Board based on ESP32-S2 leverages custom hardware and edge AI to deliver industry-leading performance and efficiency.
What are the core technical benefits?+
Key benefits include low power consumption, real-time processing, robust connectivity, and a compact form factor tailored for deployment.
Can this architecture be adapted for other use cases?+
Absolutely. The underlying methodology is modular and can be retargeted for various applications with minimal redesign.
Project Profile
Services Delivered
Hardware DesignEmbedded Software
Core Technologies
Wi-Fi/BluetoothTinyMLRTOS
Silicon & Vendors
EspressifWacom
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