Project Details
Description
The moorlands in Colombia, covering just 2% of the territory, are vital for water regulation, supplying 70% of the population. These unique ecosystems act as natural water reservoirs and are home to rich biodiversity, including many endemic species. Nevertheless, their conservation is increasingly threatened by expanding cattle grazing. The moorlands' natural grasslands attract livestock, leading to overgrazing that degrades soil, disrupts native vegetation, and diminishes water storage and purification capacities. Cattle waste contaminates water with nitrogen and phosphorus, raising nitrate levels by 30% above safe limits. Moreover, converting moorland into pastures alters the hydrological cycle, reducing water retention and
increasing flood risks. These threats pose significant challenges to preserving these critical ecosystems.
Considering the challenges mentioned above, our project focuses on developing a robust surveillance system designed to cover vast areas and regions that are difficult for humans to access. We believe the most effective solution to this problem is the deployment of an autonomous drone fleet system. Our primary objective is to create a cost-effective drone capable of traveling long distances, equipped with advanced
cameras to capture crucial data for an AI-driven algorithm that detects and identifies livestock farming within the boundaries of moorland areas, all this as a proof of concept.
increasing flood risks. These threats pose significant challenges to preserving these critical ecosystems.
Considering the challenges mentioned above, our project focuses on developing a robust surveillance system designed to cover vast areas and regions that are difficult for humans to access. We believe the most effective solution to this problem is the deployment of an autonomous drone fleet system. Our primary objective is to create a cost-effective drone capable of traveling long distances, equipped with advanced
cameras to capture crucial data for an AI-driven algorithm that detects and identifies livestock farming within the boundaries of moorland areas, all this as a proof of concept.
| Short title | EPICS_2_ING2025 |
|---|---|
| Status | Finished |
| Effective start/end date | 2/06/25 → 1/06/26 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
-
SDG 11 Sustainable Cities and Communities
-
SDG 13 Climate Action
Strategic Focuses
- Bioeconomía, Energías renovables y Sostenibilidad (BEES)
- Sociedad Digital y Competitividad (SocietalIA)
Project Status
- Execution
Relation Academy- enterprises
- No
Training for research
- No
Interdisciplinary
- No
Collaborative project between research groups
- No
- Yes
Project with potential for technological development susceptible to intellectual property protection.
- Yes
Area of knowledge (OECD)
- 2. ENGINEERING AND TECHNOLOGY. 2.B. Electrical, Electronics and Computer Engineering
Rol Sabana
- Executor
Geographic reach
- Regional – Central Sabana
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.