  Unmanned Aerial Vehicles (UAVs) have become pivotal in domains spanning
military, agriculture, surveillance, and logistics, revolutionizing data
collection and environmental interaction. With the advancement in drone
technology, there is a compelling need to develop a holistic methodology for
designing UAVs. This research focuses on establishing a procedure encompassing
conceptual design, use of composite materials, weight optimization, stability
analysis, avionics integration, advanced manufacturing, and incorporation of
autonomous payload delivery through object detection models tailored to satisfy
specific applications while maintaining cost efficiency. The study conducts a
comparative assessment of potential composite materials and various quadcopter
frame configurations. The novel features include a payload-dropping mechanism,
a unibody arm fixture, and the utilization of carbon-fibre-balsa composites. A
quadcopter is designed and analyzed using the proposed methodology, followed by
its fabrication using additive manufacturing and vacuum bagging techniques. A
computer vision-based deep learning model enables precise delivery of payloads
by autonomously detecting targets.
