This project demonstrates currency recognition using ESP32-CAM and Edge Impulse. It covers dataset creation, image classification model training, and deployment on the ESP32-CAM for real-time note detection. The tutorial explains the complete TinyML workflow, from capturing currency images to running on-device inference, making it suitable for embedded vision and AI-based electronics projects. Read more : https://circuitdigest.com/microcontroller-projects/esp32-cam-currency-recognition-using-edge-impulse

2. ESP32-CAM Currency Recognition u
sing Edge Impulse
 how to build a currency
recognition system using the
ESP32-CAM and Edge Impulse.
 The ESP32-CAM captures images
of currency notes and runs a
trained machine learning vision
model to identify the
denomination.
 The entire recognition process
happens on the device, without
relying on cloud processing.

3. Why Currency Recognition?
 Manual identification of currency notes
can be slow and error-prone.
 By using computer vision and machine
learning, currency recognition
becomes faster and more reliable.
 This project shows how AI can run on
low-cost hardware, making it useful for
real-world embedded applications and
learning TinyML concepts.

4. Hardware & Software Used
 ESP32-CAM – Microcontroller with built-in
camera
 Edge Impulse – Platform for training and
deploying ML models
 Arduino IDE – Used to upload code to
ESP32-CAM
 Currency image dataset – Used for
training the model
The combination allows image capture,
processing, and classification on a single
device.

5. Dataset & Model Training
 Images of different currency
denominations are collected using
the ESP32-CAM.
 These images are uploaded to
Edge Impulse, where they are
labeled and used to train an
image classification model.
 The trained model learns visual
patterns like color, texture, and
symbols to identify currency notes
accurately.

6. Applications
 ESP32-CAM – Microcontroller with
built-in camera
 Edge Impulse – Platform for
training and deploying ML models
 Arduino IDE – Used to upload
code to ESP32-CAM
 Currency image dataset – Used
for training the model
 The combination allows image
capture, processing, and
classification on a single device.

7. For full Tutorial :
ESP32 CAM Currency Recognition: Complete Edg
e AI Arduino Tutorial
 www.circuitdigest.com
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