Current technology makes possible the collection of a large amount of data about shipping vessels, from automatic identification signals, radio transmissions, satellite imagery etc. While it would seem that this makes it difficult for vessels to evade monitoring, the perception is an inaccurate one. Identification signals can be disabled or spoofed with remarkable ease, radio transmissions are difficult to monitor at scale, and commercial satellite imagery either does not have the required resolution to identify illicit behaviour or is prohibitively expensive. 

In the ADVISER project, we leverage the use of artificial intelligence (AI) for large-scale data analysis, combining information from different modalities, and making use of gaps in information to help identify anomalies for further investigation. This allows authorities to better monitor maritime services by providing timely analysis and an estimated likelihood of anomalous behaviour.