The project aims to design and develop a small-scale, cost-effective VTOL (Vertical Take-Off and Landing) drone equipped with a machine learning-based fire detection system. The primary goal is to create a modular drone that can be easily upgraded with additional sensors and components in the future. Students will focus on integrating standard cameras and developing a machine learning model for fire detection, avoiding the high costs associated with thermal cameras. The project will also involve developing flight control software to ensure the drone's stability and maneuverability. This initiative provides an opportunity for students to apply their classroom knowledge in drone design, software development, and machine learning, while contributing to climate action through enhanced fire detection capabilities.

The project deliverables include a fully assembled and functional VTOL drone prototype, if feasible within the budget. Students will also provide a comprehensive codebase for the flight controller and fire detection system. Additionally, technical documentation detailing system design, implementation, and scalability will be produced. A project report and demonstration will summarize the results and showcase the drone's capabilities in real-time fire detection.