This project demonstrates a cost-effective and versatile system for object selection and tracking using a Raspberry Pi 4 paired with a Pi Camera, Arduino Uno, and a servo motor. The system is designed to identify and follow a specified object in real-time. The Raspberry Pi 4 serves as the central processing unit, leveraging the Pi Camera to capture video feed. Computer vision algorithms are implemented to detect and track the object of interest based on color or shape. The detected object's position is then communicated to the Arduino Uno via serial communication. The Arduino Uno processes this data to control the servo motor, which adjusts its position to keep the object centered in the camera's field of view. This integration enables dynamic and accurate tracking of moving objects, showcasing a practical application of low-cost hardware and open-source software in robotics and automation. The project highlights the feasibility of using affordable components to achieve sophisticated object tracking tasks, with potential applications in surveillance, robotics, and interactive systems.

 

The main objectives of the project are:

• Object Detection and Tracking: Develop and implement a robust system that can reliably detect and track an object using a Raspberry Pi 4 and a Pi Camera. The system should be capable of identifying objects based on visual characteristics such as color or shape.
• Real-time Processing: Achieve real-time processing of video data to ensure that the object tracking is responsive and accurate. This involves efficient image processing algorithms and timely communication between the Raspberry Pi and the Arduino Uno.

The major building blocks of this project are:

1. Arduino UNO.
2. Raspberry Pi.
3. Servo Motor.
4. Pi Camera.

Software’s used:

1. Arduino UNO compiling and dumping code into Microcontroller
2. Express SCH for Circuit design.

   

   

     

 

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