
Oceanic Plastic Waste Detection with AI and Remote Sensing
From Satellite Data to Sustainable Cleanup: AI for Marine Plastic Detection
Skills you will gain:
About Workshop:
Oceanic Plastic Waste Detection with AI and Remote Sensing is a 3-day advanced workshop focused on using satellite imagery, machine learning, and predictive modeling to identify, track, and optimize cleanup strategies for marine plastic pollution. Participants will gain hands-on experience with computer vision, drift forecasting, and AI-based environmental monitoring tools through guided Colab sessions.
Aim: To enable participants to apply AI and remote sensing techniques for detecting, tracking, and optimizing responses to oceanic plastic pollution.
Workshop Objectives:
- Understand satellite-based detection of ocean plastic.
- Apply AI models for debris identification and segmentation.
- Develop predictive models for plastic drift tracking.
- Explore optimization techniques for cleanup planning.
- Gain hands-on implementation experience.
What you will learn?
🛰️ Day 1 — Detection from Orbit
- Floating Plastic Index (FPI) using Sentinel-2 SWIR bands
- Multi-scale detection with satellite and UAV imagery (Super-Resolution GANs)
- Debris segmentation using U-Net and DeepLabV3+
- Hands-on: Build a spectral classifier for plastic identification
🛰️ Day 2 — Movement & Drift Prediction
- Ocean transport modeling: Eulerian vs. Lagrangian approaches
- RNN-based drift forecasting for marine debris
- ConvLSTM heatmap prediction for debris accumulation zones
- Hands-on: Develop a 72-hour plastic trajectory predictor
🛰️ Day 3 — Cleanup Strategy Optimization
- Reinforcement learning for autonomous vessel routing
- YOLO-based waste classification
- Drone swarm coordination for debris scouting
- Hands-on: Implement an AI-based cleanup path optimizer
Mentor Profile
Fee Plan
Important Dates
26 Feb 2026 Indian Standard Timing 4 : 30 PM
26 Feb 2026 to 28 Feb 2026 Indian Standard Timing 5 : 30 PM
Get an e-Certificate of Participation!

Intended For :
- Postgraduate students, Ph.D. scholars, researchers, and academicians in relevant fields
- Industry professionals working in sustainability, climate tech, or geospatial analytics
- Basic knowledge of Python and machine learning is recommended
- Familiarity with remote sensing or satellite data is beneficial but not mandatory
Career Supporting Skills
Workshop Outcomes
- Analyze satellite data for marine plastic detection.
- Develop AI models for debris identification and drift prediction.
- Apply optimization methods for cleanup planning.
- Implement practical AI workflows for ocean monitoring.
