Considering the challenges posed by difficult-to-access regions and vast areas requiring monitoring, this EPICS in IEEE project from Universidad de La Sabana aims to develop a robust surveillance system based on an autonomous drone fleet. The primary objective is to create a cost-effective drone system capable of covering long distances, equipped with advanced cameras to capture crucial data for AI-driven algorithms that detect and identify livestock farming within the protected moorland areas. This initiative is developed as a proof of concept for more extensive future implementations.
A core element of the project is advanced artificial intelligence, which will optimize livestock detection and enable efficient path planning. AI will refine the image recognition algorithms, enhancing the precision of
livestock and environmental feature identification. Furthermore, the drones will coordinate as a fleet, effectively covering larger areas and transmitting real-time data to support immediate decision-making
processes.
This project was made possible by $5,750 in funding from the Instrumentation and Measurement Society (IMS), an EPICS in IEEE partner.