Project Hub /Unmanned Aerial Vehicles (Drones)/Quadcopter / Multirotor Drones/AI Drone With Real Time Face Recognition, Traffic Monitoring

Intermediate

RASPBERRY PI

Project Specific

6 – 12 Hours

Partial Kit

AI Drone With Real Time Face Recognition, Traffic Monitoring

Build a low-cost AI-enabled F450 drone equipped with a Raspberry Pi and camera for real-time face recognition and monitoring.

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
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

We don't carry yet: EEPROM / Memory IC
Drone Parts (ESC / propeller / flight controller / BLDC)
LiPo Battery

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How It Works

This advanced quadcopter system integrates a robust F450 frame, four 1000kV motors, and electronic speed controllers (ESCs) managed by a KK2.2 flight controller to achieve stable aerial flight powered by a LiPo battery. At the core of the intelligent payload is a Raspberry Pi 4 Model B running Python and powered by libraries like OpenCV, numpy, and the face_recognition module. The Raspberry Pi Camera Module captures a live video feed during flight. As the drone navigates, the Raspberry Pi processes these video frames in real time, utilizing computer vision algorithms to detect faces or monitor traffic patterns below. If text-to-speech feedback is needed, the espeak synthesizer can process system alerts. The KK2.2 flight controller handles stabilization, user inputs, and motor throttle outputs via the ESCs, while the Raspberry Pi operates independently as an onboard companion computer for high-level image processing and AI tasks.

Why Build This

Develop practical undergraduate-level engineering experience by integrating embedded Linux computing platforms with multirotor flight hardware.

Implement real-world computer vision algorithms such as face recognition and traffic monitoring on resource-constrained edge hardware.

Master the complex system integration required to combine power distribution, motor control, sensor stabilization, and onboard software processing.

Real-World Application

Surveillance, suspect identification, locating missing persons, forest fire detection, and aerial traffic monitoring.

Skills You'll Learn

Computer vision programming

Edge AI implementation

Electronic speed controller configuration

Multirotor flight stabilization

Python scripting

Real-time video processing

Power distribution management

Safety Precautions

Ensure proper wiring and power regulation from the ESC to avoid damaging the Raspberry Pi or flight controller.

Technology Tags

RASPBERRY PI

F450 DRONE

KK2.2 FLIGHT CONTROLLER

FACE RECOGNITION

OPENCV

PYTHON

ARTIFICIAL INTELLIGENCE

IMAGE PROCESSING

BALENA FIN

Frequently Asked Questions

Can the Raspberry Pi directly control the drone's motors?

No, the Raspberry Pi handles high-level AI tasks and image processing, while the KK2.2 flight controller and ESCs are responsible for stabilizing and driving the 1000kV motors.

What power source is used for this project?

A high-capacity LiPo battery powers the propulsion system through the ESCs, and proper voltage regulation must be used to safely power the Raspberry Pi without damaging it.

Is internet connectivity required during flight for face recognition?

No, libraries like OpenCV and face_recognition run locally on the Raspberry Pi 4, allowing real-time processing to happen completely offline onboard the drone.

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.

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