Project Hub /Artificial Intelligence & Edge ML/License Plate Recognition (ANPR)/How to use ESP32 CAM for Automatic Number Plate Recognition (ANPR)

Intermediate

ESP32

₹1,500 – ₹5,000

3 – 6 Hours

Complete Kit

How to use ESP32 CAM for Automatic Number Plate Recognition (ANPR)

Learn how to use an ESP32-CAM to capture vehicle images and send them to a cloud API for automatic number plate recognition, displaying the results on an OLED screen.

Originally published on CircuitDigest

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

ESP32 CAM WiFi Module Bluetooth with OV2640 Camera Rs. 1,483.00
0.96 Inch I2C/IIC 4pin OLED Display Module White Rs. 349.00
2-Slot 18650 Holder with Protective Cover and On/Off Switch – Case Rs. 109.00
10pcs - 220 ohm 1/4 W Resistor Set Rs. 39.00
USB to UART/ESP8266 Adapter Programmer for ESP-01 WiFi Modules with CH340G Chip Rs. 99.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

This list includes a generic resistor set as a placeholder — it is not matched to the exact value or part number this circuit needs. The correct one is specified on the original source page linked above; check it before buying.

Browse all components

How It Works

This edge-AI system operates by using an ESP32-CAM module to capture high-resolution images of vehicle license plates when triggered. The core of the circuit centers around the ESP32-CAM, which integrates an OV2640 camera sensor and onboard Wi-Fi capabilities. When a user presses the tactile push button connected via a 10K pull-down resistor circuit, it signals the ESP32 microcontroller to take a snapshot. Once the image is captured, the microcontroller connects to a local wireless network using its built-in Wi-Fi library and uploads the image data to an external cloud API configured for optical character recognition and Automatic Number Plate Recognition (ANPR). After processing the image, the cloud API returns the recognized alphanumeric plate text back to the ESP32 over the internet connection. The microcontroller then communicates with a 0.96-inch OLED display using the I2C protocol via the Wire library to render and present the processed license plate data visually to the user. A USB to UART converter is utilized initially during the prototyping phase on a breadboard to program the ESP32-CAM and transmit debug messages via serial communication using jumper wires for interconnections.

Why Build This

Develop practical undergraduate-level experience in integrating edge microcontrollers with cloud-based computer vision APIs.

Implement real-world smart city applications such as automated toll collection and secure vehicle access control systems.

Gain hands-on hardware prototyping skills by wiring image sensors, communication displays, and manual input controls on a breadboard.

Real-World Application

Automated toll gates, smart parking systems, vehicle access control, and traffic monitoring.

Skills You'll Learn

I2C communication

Wi-Fi network interfacing

microcontroller programming

serial UART debugging

cloud API integration

Safety Precautions

No specific precautions noted for this build — always follow general electronics safety practices.

Technology Tags

ESP32-CAM

OCR

CLOUD API

COMPUTER VISION

WI-FI

OLED DISPLAY

IMAGE PROCESSING

HTTPS

Frequently Asked Questions

Why do I need a USB to UART converter if the ESP32-CAM has a microcontroller?

Unlike standard development boards, the ESP32-CAM typically lacks an onboard USB-to-serial chip to keep its footprint small and cost low, requiring an external adapter to upload code from the Arduino IDE.

How does the OLED display communicate with the ESP32-CAM?

The 0.96-inch OLED display communicates using the I2C protocol, which requires connecting just the SDA and SCL lines alongside power and ground, managed in software via the Wire library.

Can this system perform license plate recognition completely offline?

No, the heavy computational lifting of Automatic Number Plate Recognition (ANPR) is offloaded to a cloud API, meaning the ESP32-CAM requires an active Wi-Fi connection to transmit the image and receive the text result.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

Kitkraft Project Hub — curated from the maker community, credited at the source.

PRJ-01122