YOLO algorithm for shipping waste discharges detection at Swedish waters based on fused satellite images with ship AIS data
Conference poster, 2025

The tank cleaning operations may pose a threat to the marine environment. Reports from the Swedish national audit office indicate that ships planning to clean sometimes deviate from routine routes, which suggest a role for analytics based on their navigation data e.g., AIS data and remote sensing data. By examining trajectories and their spatial and temporal attributes, it is possible to identify unusual movement patterns and flag potential non-compliant operations.
• Develop a feature engineered ML framework for anomaly detection
• Leverage image-processing algorithms on satellite images to cross-check detected anomalies

Author

Wengang Mao

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Ida-Maja Hassellöv

Chalmers, Mechanics and Maritime Sciences (M2), Transport, Energy and Environment

Selpi Selpi

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

Leif Eriksson

Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing

Chi Zhang

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

2025 AoA Transport All Research Day
Gothenburg, Sweden,

YOLO algorithm for shipping waste discharges detection at Swedish waters based on fused satellite images with ship AIS data

Chalmers Area of Advance Transport, 2025-01-01 -- 2026-12-31.

Driving Forces

Sustainable development

Areas of Advance

Transport

Subject Categories (SSIF 2025)

Transport Systems and Logistics

Marine Engineering

Infrastructure

Chalmers e-Commons (incl. C3SE, 2020-)

More information

Created

12/11/2025