Develops surveillance applications to protect no-fly zones from the intrusion of malicious drones. Implements a sound-based solution to complement GPS and wireless detection co-developed with the security team. Delivers a proof-of-concept in less than 3 months applying Scrum methodology. Provides extended documentation and annotated bibliography on classification and detection methods.


  • Implemented Python tools for real-time signal processing and sound recognition using machine-learning algorithms.
  • Improved the classification and recognition of acoustic patterns with a prediction rate superior to 90%.
  • Tested prototype detecting the sound emitted by drones in a range up to 75 meters in natural environment.


Programming Python, Scikit Learn, Tensor Flow, Matlab.
DevOps JIRA, Gitlab, Make, Docker.
Documentation Confluence, Jupyter, Markdown, Latex.