ABOUT ACCELERATE
Explore how our project advances UAV applications for sustainable environmental practices. Join us in discovering the transformative impact of our research and collaboration.
OBJECTIVES
Advance UAV-based environmental monitoring by integrating AI and remote sensing technologies across diverse ecosystems.
Overcome technological and operational bottlenecks in UAV deployments through targeted research on sensor optimization, BVLOS operation, and data processing scalability.
Foster the development of open-source, interoperable tools and platforms for AI-driven UAV data analysis, visualization, and decision support.
Promote community-driven innovation and multi-stakeholder engagement in environmental governance through demonstrators and real-world use cases.
Support EU policy goals for sustainability, digital transformation, and resilience by informing climate-neutral strategies with UAV-derived insights.
Opportunities & Support
At our project, we are committed to advancing the understanding and application of UAV technology for environmental sustainability. Our mission is to bridge innovative research with practical solutions, ensuring our findings positively impact ecological initiatives.
We focus on integrating cutting-edge AI and evolving the role of UAVs across diverse environmental contexts, fostering collaboration among multidisciplinary scientific communities. Through our efforts, we strive to drive meaningful change that supports EU sustainability goals and promotes research excellence.
TECHNOLOGIES
Perform technological advancements in the field of UAVs in both hardware and software domains.
Develop new protocols and methodological pipelines in using UAVs in each use case, testing and demonstrating in parallel the technological advancements developed in Pillar I.
Develop methodological pipelines to perform multi-faceted sustainability impact assessment using UAV technology in selected disciplines and applications.
USE CASES
Coastline Litter Pollution
UAVs assess coastal litter with RGB/NIR/Thermal sensors and AI models (RF, SVM, CNN). Challenges include remote access and BVLOS integration.
Crop Monitoring & Health
Use UAVs for crop detection and health assessment with ML/DL, sensor calibration, and open-source visual tools for scalable agriculture analytics.
Urban Air Quality
Monitor PMs, RH, and temperature using UAVs with low-cost sensors and DL models (CNN, LSTM) to detect pollution patterns and sources.
