Tracking Illegal Fishing with AIS Data

Project Type: Neural Networks
Area/Sector: Fisheries, Marine Risk
Academic Institution: Dalhousie University
Lead Investigator: Dr. Stan Matwin
HQP’s: Gashin Ghazizadeh

Ship’s trajectory data, Automatic Identification System (AIS), provides automatic updates about the location and speed of vessels with every ship containing a unique ID. Researchers at the Institute for Big Data Analytics at Dalhousie University are using this data and the DeepSense platform to create a solution that could tackle illegal fishing.

Researchers are using ship movement and speed data combined with Deep Learning methods to create patterns that can determine whether a ship is fishing. Images of S-AIS data are extracted to show the paths which ships traverse when fishin or not. Extracted images are then used for the task of fishing detection with the help of deep convolutional networks. Each type of ship has a specific style of movement when fishing that CNNs can learn by looking at the paths. This problem is different from the normal image classification tasks that are done, so Transfer Learning cannot be used.

DeepSense’s computational and personnel resources are being utilized to tackle the huge amounts of data being analyzed. GPU and memory make storing and processing data quicker and easier. Researchers are also benefitting from DeepSense technical experts who are on hand to troubleshoot throughout the project.