Vehicle to Vehicle Communication Using Image Processing and RF Technology

Abstract

This project presents a Vehicle-to-Vehicle (V2V)
communication system utilizing Image Processing
and RF technology to enhance road safety by
providing real-time vehicle recognition, alerts, and
distance management. The proposed system
leverages YOLO (You Only Look Once) for vehicle
detection and recognition using OpenCV, while an
Arduino Nano microcontroller facilitates control of
the embedded components. Vehicle communication
is achieved through 433MHz RF transmitter and
receiver modules, enabling effective data exchange
between vehicles. The system incorporates an
ultrasonic sensor for the detection of front vehicles
and provides collision warnings.
Information regarding detected vehicles and
warnings is displayed on an LCD display to alert the
driver promptly. By combining the AI-powered
YOLO framework for real-time image processing
and RF communication for data sharing, the solution
enhances vehicle safety by preventing accidents
through early alerts and vehicle recognition. In the
event of an accident (when Mems sensor is High),
the system sends an alert to surrounding vehicles,
ensuring immediate awareness among other drivers.
Additionally, in the case of a vehicle failure, an
emergency alert is broadcast to nearby vehicles. This
system provides a low-cost, efficient approach to
ensuring safer travel, particularly on highways and
in scenarios with high-speed vehicles, by employing
collaborative technologies to facilitate