Drone localisation with machine learning

With the upward trend in sales and ownership of recreational drones to the public consumers in both the global and local context. This give rise to possible privacy implications caused by malicious intent of drone owners. This project aims to develop a system that both identify and localizes drones within the desired monitoring vicinity enhanced with machine learning to improve identification accuracy. It presents an affordable and effective way to both identify and localize drones within detection range. The system helps users in protecting themselves from privacy implications caused by the presence of drones. Users will be more informed of the airspace within the detection range allowing for appropriate countermeasures to be taken. This report outlines the design and development process of the system. The main programming language used to create this project is Python, which handles all scripts in this project. The access point module from Python has aided the development of this project greatly, as it allows the interfacing with the operating system’s wireless card to be seamless. Hence, the primary purpose of the project has been created. The system itself has been tested and works properly with minor supervision from user due to the Machine learning aspect. Further implementations can be explored to further improve on the efficiency and effectiveness in identifying drones.Bachelor of Engineering (Electrical and Electronic Engineering