From Pixels to Protection: Real-Time AI for Earth’s Alarms
Eyes in the Sky” is a concise, hands-on workshop on using drones, satellites, and AI for real-time environmental monitoring. Through the Silvanet & Silvaguard case study, you’ll see how remote sensing and ML fuse to detect deforestation and wildfires, track air quality, and estimate emissions and vegetation carbon stocks—while addressing real-world hurdles like data gaps, accuracy, and scaling in low-resource regions.
To equip participants to design, evaluate, and deploy AI-driven, real-time environmental monitoring pipelines that fuse drone and satellite imagery for rapid detection of deforestation, wildfires, and air-quality issues—grounded in the Silvanet & Silvaguard (Germany) case study—and to develop practical strategies for overcoming data gaps, accuracy limits, and scalability challenges in low-resource settings.
Introduce core concepts of AI-enabled remote sensing for real-time monitoring.
Demonstrate ingestion & preprocessing of satellite, drone, and sensor data.
Apply change detection and early-warning models for deforestation and wildfires.
Fuse multi-resolution data (UAV + EO + IoT) for robust signal detection.
Estimate air-quality proxies (e.g., AOD) and vegetation carbon stocks.
Evaluate model performance (IoU/F1/PR) and calibrate alert thresholds.
Explore the Silvanet & Silvaguard case to derive deployable design patterns.
Address data gaps, accuracy limits, and scaling in low-resource contexts.
Prototype a minimal alerting workflow and web map/dashboard for decision support.
📅 Day 1 – Platforms, Sensors & Mission Design
📅 Day 2 – Analytics & Fusion
📅 Day 3 – Hands-On: End-to-End AOI Build (single lab)
Environmental & forestry professionals, wildfire/disaster management teams
Remote sensing & GIS analysts (QGIS/ArcGIS/Google Earth Engine users)
Data scientists & ML engineers working with geospatial data
Air-quality, climate, and sustainability researchers/practitioners
UAV/drone operators and Earth-observation startups
Government agencies, utilities, and NGOs involved in monitoring & response
Graduate students and faculty in Environmental Science, Geography, CS/AI
Build a real-time EO pipeline (satellite + drones + sensors).
Train models for deforestation change & early wildfire signals.
Fuse multi-resolution data; detect smoke/thermal anomalies.
Estimate air-quality (AOD) and vegetation carbon stocks.
Evaluate (IoU/F1), tune thresholds to cut false alarms.
Deliver: alerting workflow, mini dashboard, and a one-page rollout for low-resource settings.
₹2,499
$50
The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.
Through recorded video lectures from the original live workshop, with the study material. Watch at your own pace, any time.
365 days from your registration, on your NanoSchool dashboard.
Yes, an e-certificate after completion, with a QR code anyone can verify and an "Add to LinkedIn" button.
By card, UPI or PayPal on the payment page; international bank transfer is also available there.
See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy
Registration open
Live, mentor-led and certified. Dates and times in IST.
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