Project Hub /Artificial Intelligence & Edge ML/License Plate Recognition (ANPR)/Automatic Camera Based Boom Barrier Better Than The IR Based

Intermediate

RASPBERRY PI

Project Specific

3 – 6 Hours

Partial Kit

Automatic Camera Based Boom Barrier Better Than The IR Based

An automated camera-based boom barrier system that uses license plate recognition and an ultrasonic sensor to control vehicle access without requiring IR tags.

Originally published on ElectronicsForU

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.

Raspberry Pi 3 - Model B+ 1.4Ghz 64-bit quad-core Processor with 1 GB Ram (Original) Rs. 9,810.00
Ultrasonic Sensor Module HC-SR04 Rs. 89.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

We don't carry yet: Speaker / Audio Amplifier

Browse all components

How It Works

The Automatic Camera-Based Boom Barrier system leverages computer vision and edge machine learning on a Raspberry Pi 4 Model B to manage vehicle entry without relying on traditional infrared tags. When a vehicle approaches the gate, the Raspberry Pi camera captures a live video feed of the car. The integrated Python software processes these image frames to perform Automatic Number Plate Recognition (ANPR), extracting the license plate text. Simultaneously, an HC-SR04 ultrasonic sensor measures the distance to the incoming vehicle to confirm its exact positioning relative to the barrier gate. Once a valid license plate is identified and proper vehicle positioning is verified by the ultrasonic sensor, the Raspberry Pi signals the mechanical boom barrier to open. To enhance user interaction and provide immediate feedback, the system utilizes an espeak voice synthesizer paired with a speaker to announce vehicle status or welcome messages audibly. Operators can monitor the entire access control process locally using the connected 7-inch touchscreen display. Power is reliably delivered to the entire setup using a dedicated 5V 2A DC power supply.

Why Build This

Implement an advanced computer vision and edge AI pipeline suitable for real-world undergraduate engineering deployment in corporate or residential parking management.

Gain practical experience integrating optical sensor hardware like the Raspberry Pi camera with distance-measuring ultrasonic modules for automated physical access control.

Develop software engineering skills by combining Python programming, speech synthesis libraries, and image processing frameworks on a single-board computer platform.

Real-World Application

Vehicle access control at corporate offices, residential societies, parking lots, shopping malls, and hotels.

Skills You'll Learn

Computer vision and image processing

Optical character recognition implementation

Ultrasonic distance measurement

Audio synthesis integration

Touchscreen GUI interfacing

Python hardware control

Safety Precautions

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

Technology Tags

RASPBERRY PI

CAMERA

ULTRASONIC SENSOR

IMAGE PROCESSING

LICENSE PLATE RECOGNITION

AUTOMATION

PYTHON

Frequently Asked Questions

Can I use a Raspberry Pi 3 instead of a Pi 4?

Yes, the project data notes that either a Raspberry Pi 3 or Pi 4 with 4GB or 8GB of RAM can be used, though the Pi 4 will offer faster image processing speeds for license plate recognition.

What is the purpose of the HC-SR04 ultrasonic sensor if the camera is already reading plates?

The ultrasonic sensor accurately measures the vehicle's physical distance from the barrier, ensuring the gate only opens when a car is correctly positioned right in front of the barrier.

How does the system provide audio feedback to drivers?

The system uses the espeak voice synthesizer running on the Raspberry Pi combined with an attached speaker to generate spoken audio alerts and status updates.

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-00772