Revolutionising Maritime Surveillance with ESA IOD REMIS
Traditional vessel tracking heavily relies on Automatic Identification Systems (AIS), but there's a significant gap in identifying "dark vessels" that operate without AIS, posing risks such as piracy, illegal fishing, and human trafficking.
Background
Imagine the vast expanse of the world's oceans, where countless ships sail, carrying goods, people, and sometimes hidden dangers. In today's maritime industry, the urgency for real-time ship detection is paramount, spanning concerns from government security agencies to offshore asset owners and insurance providers. While traditional vessel tracking relies heavily on Automatic Identification Systems (AIS), a critical blind spot persists—the elusive "dark vessels" that operate without AIS. These dark vessels pose serious threats, including piracy, illegal fishing, and human trafficking. Bridging this gap, S[&]T has partnered with ESA to develop a groundbreaking solution utilising machine learning for real-time ship detection from orbit, revolutionising maritime security and safety protocols.
The Problem
Current vessel tracking systems are limited in accurately detecting dark vessels - those operating with their Automatic Identification Systems (AIS) switched off. Common traditional surveillance methods, such as Synthetic Aperture Radar (SAR), are very effective. However, they are too complex and not suitable for real-time analysis. Additionally, current satellite image analysis processes often suffer from substantial delays caused by extensive data preprocessing and ground-based analysis, resulting in significant latency issues when delivering actionable insights to stakeholders. These limitations underscore an urgent necessity need for a novel approach that can overcome these hurdles and provide actionable intelligence swiftly and reliably.
The Solution
Our solution proposes the development of a machine learning-based real-time ship detection system deployed in orbit. This system leverages optical image sensors and on-board processing to enable immediate ship detection without the need for ground-based preprocessing. By utilising machine learning algorithms, the system can identify dark vessels and provide real-time insights to stakeholders, enhancing maritime surveillance capabilities significantly.
The creation of a machine learning-based real-time ship detection system represents a transformative solution for maritime surveillance challenges. This innovative technology empowers stakeholders such as government agencies, offshore asset owners, and ship insurance companies to swiftly identify elusive "dark vessels," significantly enhancing safety, security, and regulatory compliance within the maritime domain.
S[&]T's Role
As a leading high-tech solutions provider, we have contributed significantly to the design, development, and deployment of the proposed real time ship detection. Leveraging our deep background in machine learning, image processing and satellite technology, we were able to deliver our expertise in sensor pre-launch adaptation, detection model training, on-board image equalisation, detection application, and in model fine tuning in post launch. This successful project underpins our ongoing mission to generate cutting-edge solutions that provide real value to maritime industry partners through actionable insights.
Conclusion
The success of this project positions our company at the forefront of providing cutting-edge software and hardware solutions for on-board object detection in optical imagery. This achievement not only opens doors to exciting opportunities within ESA, national agencies, and commercial ventures but also underscores our commitment to advancing technological frontiers and making substantial contributions to the evolution of maritime surveillance.