The objective of this project is to design and develop a small-scale, cost-effective VTOL drone equipped with a flight controller and a fire detection system using machine learning (ML). The drone should be designed with modularity in mind, allowing for future sensor and component upgrades. Given budget constraints, the project will focus on using standard cameras and ML-based fire detection instead of expensive thermal cameras.

Students will be responsible for developing the drone’s software, integrating sensors, and implementing the ML-based fire detection system while ensuring the design is scalable for larger applications.

Project Outcomes and Deliverables:

VTOL Drone Design & Development:

• Design a small, affordable VTOL drone with core flight capabilities.
• Develop and integrate a flight controller with essential navigation and stabilization features.
• Ensure modularity for future upgrades, including additional sensors.

Fire Detection System Using ML:

• Train and implement a machine learning model capable of detecting fire from standard camera footage.
• Test the system for accuracy and real-time performance.
• Optimize the model for deployment on resource-constrained hardware.

Software Development & Integration:

• Develop flight control software, ensuring stability and maneuverability.
• Integrate ML-based fire detection with the drone’s onboard processing system.
• Implement communication protocols for remote monitoring and alerts.

Final Deliverables:

• Fully Assembled and Functional VTOL Drone Prototype (if feasible within the budget).
• Codebase for the flight controller and fire detection system.
• Technical Documentation detailing system design, implementation, and future scalability.
• Project Report & Demonstration summarizing the results and showcasing the drone’s capabilities.