A Paradigm Shift in Maritime Security

Currently, one-third of the world’s fish stocks are being harvested at unsustainable levels, disrupting marine habitats and negatively influencing the livelihoods of legitimate fishers.  The estimations show that IUU fishing causes annual losses of $10– 23.5 billion.

IUU fishing primarily operates through unauthorized vessel entry into restricted maritime zones, undermining national sovereignty in Exclusive Economic Zones and hindering conservation in Marine Protected Areas.

Unauthorized vessel entry is not limited to fishing zones but also poses significant security risks in other restricted maritime areas. Such zones, including Maritime Exclusion Zones, Danger Zones, and Naval Operations Areas, are established to control or prohibit public access for safety and security purposes. These areas may be used for hazardous operations such as target practice or missile testing, or they may be established to protect government property or military assets.

When vessels not having Long-Range Identification and Tracking onboard intentionally disable their Automatic Identification Systems (AIS), they become virtually invisible to conventional and publicly available monitoring, creating a critical blind spot in today’s maritime surveillance.

To effectively combat illegal, unreported, and unregulated fishing, a comprehensive and coordinated global response is required. Relying on AIS has proven insufficient; thus, future efforts must utilize advanced technologies.  A recent study found that relying on AIS data alone missed almost 90% of illegal fishing vessel detections compared to a more advanced monitoring approach. The use of satellite imagery, together with artificial intelligence, represents an innovative option for real-time dark vessels detection, process automation, which allows for immediate threat response.

Limited ship tracking methods:  When AIS is disabled on a vessel, several other methods may be used to track it, though they are often more complex, costly, or provide less continuous data than AIS.

Latency:  The current monitoring options are not incompatible with time-sensitive activities that require near or real-time information from the area of interest.

Costs:  In time-sensitive use cases, late data delivery results in higher collateral expenditures.

Effectivity:  Increased latency, higher costs, and a lack of data processing automation reduce the overall dark vessel detection effectiveness.

Deployed directly on satellites, SKAISEN performs real-time image analysis in orbit, autonomously detecting changes and anomalies and instantly propagating such information in existing data lakes or directly to end users. This innovative approach delivers actionable insights to end-users within minutes, enabling rapid responses in both military and civil contexts on Earth.

The SKAISEN system allows for continuous, autonomous monitoring, enabling immediate alerts for anomalies, such as unauthorized vessel detection.

SKAISEN, an AI-based onboard vessels screening system that uses machine learning algorithms to analyze imagery, detect, and categorize pre-defined objects. By prioritizing relevant data for transmission, SKAISEN reduces communication overhead, enhances response times, and supports rapid decision-making for applications in environmental protection, security, and public safety. By turning raw information into actionable insights, edge computing facilitates faster decision-making and more effective responses, providing a critical advantage in complex operational environments. The system allows sending an actionable insight to the end user within 10 minutes from the time the anomaly is detected.

By processing the data from a camera by AI onboard a satellite a real-time warning messages (actionable insights) can be created and transmitted to the data lake for data fusion or directly to the end user. Such early detection and notification allow for a more efficient and targeted deployment of patrol efforts, saving both manpower and money while strengthening overall enforcement and control.