Since the introduction of AIS almost 20 years ago and more recently Satellite AIS, activity in the maritime environment has become more transparent. An AIS based industry has been spawned including satellite and terrestrial AIS providers, tracking companies and analysts. Shipowners can now track their fleets across oceans and, with the right analytical capabilities, generate efficiencies in their operational plans. Many other operators including cargo owners, logistic companies, insurers, marine service providers, commodity traders, terminal operators and charterers all benefit from AIS. And regulators have an additional tool to use in their quest to spot illegal practices at sea such as sanction busting, illegal fishing, marine pollution and smuggling, as long as the perpetrators comply in using AIS as it was intended.
AIS is inconsistent. Indeed, the information given by the AIS can be inaccurate and incomplete. Worse still, AIS can be switched off. Therefore, recipients of AIS data need to be aware of the system’s limitations and be able to verify the data they are presented with.
A recent (May 2020) Global Advisory by OFAC (the US Office of Foreign Assets Control) highlights the importance of good AIS discipline and encourages Flag Registries, maritime insurance companies, financial institutions, ship owners and many others to become better aware of the activities of their vessels. Some might choose to outsource this. The result will be that vessels are less likely to engage in illegal activities and, importantly, the ‘noise’ of inaccurate AIS signals from vessels going about legitimate activities will decrease, thereby reducing the ability of a sanction breaker, and others, to hide.
The SiriusInsight.AI platform fuses data from numerous sources such as AIS, other trackers, Satellite EO data, terrestrial data and many other sources. The data is then verified and fused and the operator presented with a picture that is not the product of just one, potentially unreliable source. SiriusInsight.AI then goes further by detecting unusual behaviour through automatic alerts and analysing the pattern of life behaviour.