This repository implements a simple YOLO algorithm for detection of birds and other aerial obstacles for drones to avoid collision during flight.

Given a fleet of drones, a list of customer orders, and availability of the individual products in warehouses, schedule the drone operations so that the orders are completed as soon as possible.

A simulation project that merges Autonomous Vehicle (AV) car-sharing with drone deliveries to optimize out-of-range deliveries.

Optimal drone aeronautical route calculation for making emergency delivery system using drones.

MedicAir, an event driven REST API to manage a fleet of medication delivery drones, with a chatbot interface for real-time interaction and monitoring via MQTT

Solving the Flying Sidekick Traveling Salesman Problem (FSTSP) using Mixed-Integer Linear Programming (MILP) with Python & Gurobi. Optimizes hybrid truck-and-drone delivery routes.

DJI Phantom 2 / Naza-M V2 Arduino program for load drop servo mechanism

The future of aviation is here! Supersonic flights in 3 hours, electric & hydrogen aircraft, flying taxis, vertiports, space tourism, and the end of kerosene. Aviation 2040 — welcome to the skies of tomorrow.

RISE: dRone InfraStructure tokEnisation

This contract enables users to request drone deliveries, operators to register and manage their drone fleets, and automated payment processing with platform commission splitting. The system includes rating mechanisms, earnings tracking, and comprehensive error handling.

Wings of Relief is a drone delivery system designed to transport medical supplies to remote areas. Using the APM 2.8 flight controller and real-time telemetry, it ensures efficient, autonomous deliveries. The project overcomes healthcare logistics challenges by automating delivery routes, offering a reliable solution for medical emergencies

Discrete-Event Simulation of a last-mile drone delivery hub in Accra, Ghana. Built with SimPy to find the minimum fleet (drones + chargers) achieving 95% on-time delivery within 120 minutes. 1,440 experiment runs across 48 fleet configurations with seasonal wind sensitivity analysis.

This project combines Answer Set Programming for optimal drone delivery route planning with temporal logic verification of flight maneuvers. It balances distance and energy costs while formally verifying safety properties, providing mathematical guarantees for autonomous drone operations