About the project

A real-time object detection system aimed to enhance the capabilities of drone by integrating CV algorithms for automated object detection and tracking which is suitable for a wide range of applications, including surveillance, search, rescue, and environmental monitoring.
Integrated DJITellopy, a Python library for controlling DJI Tello drones, to establish communication with the drone and receive live video feed from its onboard camera.

Tech Stack

In today's rapidly evolving technological landscape, innovation plays a pivotal role in addressing various challenges across industries. One such challenge lies in ensuring the safety and efficiency of drone operations, particularly in environments where real-time object detection is crucial. The inspiration behind developing a drone object detection system stems from the intersection of safety concerns, technological advancement, and the need for enhanced operational capabilities. Safety is paramount in any drone operation, whether it involves surveillance, search and rescue missions, or infrastructure inspection. Traditional drone operations often rely on manual piloting or pre-programmed flight paths, which may not adequately account for dynamically changing environments or unforeseen obstacles. By integrating object detection capabilities into drones, operators can identify and avoid obstacles in real-time, significantly reducing the risk of collisions and ensuring the safety of both the drone and surrounding assets or personnel.