Dark Activity Identification via AIS Shutdown Analysis
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Solution Overview
Problem
Current methods for identifying dark maritime activities, such as sanctions evasion and illicit cargo transfers, are inadequate as they rely on manual screening and do not effectively utilize behavioral analysis or real-time data, leading to potential involvement in criminal activities and increased costs for compliance.
Innovation Solution
A method that analyzes shutdown events in vessel AIS transmissions to determine if a vessel had sufficient time to perform a dark activity by calculating the distance and time traveled, generating potential travel paths, and verifying these using images, thereby identifying potential maritime events like port calls or STS transfers with high confidence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual screening methods are used to identify dark maritime activities, then operational simplicity is maintained, but identification accuracy and timeliness deteriorate
Solution Approach 1:
The system segments the dark activity identification process into distinct functional modules: AIS signal monitoring module, shutdown event detection module, travel path generation module, image verification module, and time-distance calculation module. Each module handles a specific aspect of the analysis, transforming a complex manual screening task into automated, manageable segments that improve identification accuracy while maintaining operational clarity
Solution Approach 2:
The system introduces an intermediary automated analysis layer between raw AIS data and final dark activity identification. This intermediary processes location-reporting signals, generates potential travel paths, and performs time-distance calculations, acting as a mediator that enhances identification precision without requiring direct manual intervention in every step
2Loss of time
If behavioral analysis and real-time data processing are implemented, then identification timeliness is improved, but computational resource requirements increase
Solution Approach 1:
The system performs preliminary actions by continuously monitoring AIS signals and pre-processing location-reporting data in real-time. Shutdown events are detected immediately when signals cease, and potential travel paths are generated proactively using historic vessel behavior data. This preliminary processing enables rapid identification without requiring intensive computational resources at the moment of dark activity detection
Solution Approach 2:
The system applies partial action by focusing computational resources only on vessels exhibiting suspicious shutdown behavior rather than analyzing all maritime traffic continuously. By generating potential travel paths only for vessels with detected shutdown events and verifying them selectively using images, the system achieves timely identification while optimizing resource utilization through targeted rather than exhaustive analysis
3Productivity
If automated analysis of large maritime data sets is performed, then resource utilization is optimized, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically processing large maritime data sets without requiring manual configuration or intervention. The automated analysis engine continuously monitors AIS signals, detects shutdown events, generates travel paths using historic data, and verifies findings independently. This self-service capability maximizes resource utilization efficiency by eliminating manual screening while managing system complexity through automated decision-making algorithms
4Reliability
If potential travel paths are generated and verified using images, then identification reliability is improved, but processing time increases
Solution Approach 1:
The system applies partial verification by using image analysis selectively only for vessels where automated time-distance analysis indicates potential dark activities. Rather than verifying all vessel movements with images, the system focuses verification resources on high-probability cases, thereby improving identification reliability for suspicious activities while minimizing the time penalty associated with comprehensive image verification
Data Source
AI summary
A method, system and product comprising: obtaining location-reporting signals of a vessel indicating that the vessel was located at a first geographical position prior to a shutdown event and at a second geographical position after the shutdown event; determining a distance between the first and second geographical positions; determining an estimated time to travel the distance based on the location-reporting signals; comparing the estimated time to the duration of the shutdown event, to determine whether the vessel had sufficient time to perform a dark activity that is associated with a maritime event; generating a potential travel path from the first geographical position to the second geographical position, wherein the potential travel path comprises the maritime event; obtaining images that correspond to the duration of the shutdown event and to the potential travel path; and verifying that the maritime event occurred based on an analysis of the images.