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<div>Workshop<br>
AI4Nature@AVSS2026<br>
<a href="https://www.ai4nature.tech/">https://www.ai4nature.tech</a></div>
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Computer Vision and AI for Environmental Monitoring, Biodiversity Analysis, and Ecosystem Restoration<br>
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The global climate and biodiversity crises demand a paradigm shift in how we monitor, analyze, and protect our natural world. This workshop, AI4Nature, explores the transformative role of advanced visual and signal-based systems in addressing these challenges.
In alignment with AVSS 2026's theme of "Expanding Horizons," we move beyond traditional security and surveillance to focus on ecological and environmental applications. The workshop will showcase cutting-edge research in computer vision, deep learning, and
multi-modal sensor fusion for the automated monitoring of biodiversity (e.g., species identification, population counting, behavioral analysis), the detection of environmental threats (e.g., pollution, poaching, wildfire, invasive species), and the assessment
of ecosystem health. By bringing together computer vision researchers, ecologists, and environmental scientists, AI4Nature aims to foster interdisciplinary collaboration and chart a roadmap for a new generation of intelligent, autonomous systems dedicated
to the sustainability and restoration of our planet's ecosystems.<br>
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Topics<br>
The workshop will focus on, but is not limited to, the following topics:<br>
1. Computer Vision for Biodiversity Analysis:<br>
- AI-driven species identification, counting, and tracking from camera traps, baited remote underwater video systems (Bruvs), drones, and underwater vehicles.<br>
- Individual animal re-identification using biometrics (e.g., fur patterns, scars, fin shapes) for population studies.<br>
- Automated analysis of animal behavior and social interactions in the wild.<br>
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2. Multi-Modal Environmental Monitoring:<br>
- Sensor fusion for ecological surveillance, combining video, audio (bioacoustics), thermal, LiDAR, and eDNA data.<br>
- Anomaly detection (and early-warning systems) for environmental threats such as poaching, illegal logging, pollution events (e.g., oil spills, microplastics), invasive species, and wildfire ignition.<br>
- Multimodal foundation models for understanding complex ecosystem dynamics, linking visual data with climatic and chemical parameters.<br>
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3. Autonomous Systems for Ecology: <br>
-UAV/drone-based monitoring of remote or inaccessible habitats (forests, coastlines, marine protected areas).<br>
- Autonomous surface and underwater vehicles for marine biodiversity assessment and seafloor habitat mapping.<br>
- Edge AI for real-time, in-situ analysis on robotic platforms, enabling adaptive mission planning.<br>
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4. AI for Ecosystem Health and Restoration:<br>
- Habitat change detection using high-resolution satellite and aerial imagery.<br>
- Assessment of restoration interventions through automated vegetation and geomorphological analysis.<br>
- Digital twins of ecosystems for predictive modeling and scenario analysis to support evidence-based conservation interventions and policy.<br>
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This workshop is highly timely as the European Union's Green Deal, Biodiversity Strategy 2030, and Nature Restoration Law create an urgent demand for the scalable, accurate, and cost-effective monitoring technologies that our community can provide<br>
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Submission https://cmt3.research.microsoft.com/AIforNATURE2026<br>
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Important dates<br>
Paper submission deadline May 20, 2026<br>
Notification of acceptance June 10, 2026<br>
Camera ready deadline July 1, 2026<br>
Workshop date August 31, 2026<br>
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Organizing Committee<br>
Concetto Spampinato, University of Catania, Italy<br>
Marco Milazzo, University of Palermo, Italy<br>
Cosimo Distante, CNR, Italy<br>
Paolo Spagnolo, CNR, Italy<br>
Ilyes Benaissa, CNR, Italy</div>
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