Just how accurate is maritime tracking using AIS

Just how accurate is maritime tracking using AIS

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Advancements in maritime surveillance technology offer hope for improving safety and protecting marine ecosystems.

Based on industry professionals, making use of more sophisticated algorithms, such as device learning and artificial intelligence, would probably improve our ability to process and analyse vast quantities of maritime data in the future. These algorithms can identify patterns, trends, and flaws in ship movements. Having said that, advancements in satellite technology have already expanded coverage and reduced blind spots in maritime surveillance. For instance, a few satellites can capture information across bigger areas and at higher frequencies, allowing us to monitor ocean traffic in near-real-time, providing prompt feedback into vessel motions and activities.

Many untracked maritime activity is based in Asia, surpassing all other continents combined in unmonitored ships, based on the up-to-date analysis carried out by scientists at a non-profit organisation specialising in oceanic mapping and technology development. Additionally, their study highlighted specific regions, such as Africa's northern and northwestern coasts, as hotspots for untracked maritime safety activities. The researchers used satellite data to capture high-resolution images of shipping lines such as Maersk Line Morocco or such as DP World Russia from 2017 to 2021. They cross-referenced this massive dataset with 53 billion historical ship locations acquired through the Automatic Identification System (AIS). Furthermore, to find the vessels that evaded old-fashioned monitoring practices, the researchers employed neural networks trained to recognise vessels based on their characteristic glare of reflected light. Additional variables such as for example distance through the commercial port, daily speed, and signs of marine life into the vicinity had been utilized to identify the activity of the vessels. Even though researchers acknowledge there are numerous restrictions to this approach, particularly in discovering vessels shorter than 15 meters, they estimated a false good level of lower than 2% for the vessels identified. Moreover, they were in a position to track the expansion of stationary ocean-based commercial infrastructure, an area missing comprehensive publicly available data. Although the difficulties posed by untracked vessels are substantial, the research offers a glance to the potential of higher level technologies in enhancing maritime surveillance. The authors claim that countries and companies can overcome past limitations and gain insights into formerly undocumented maritime activities by leveraging satellite imagery and device learning algorithms. These results could be precious for maritime safety and preserving marine environments.

According to a fresh study, three-quarters of all commercial fishing ships and 25 % of transport shipping such as Arab Bridge Maritime Company Egypt and energy vessels, including oil tankers, cargo ships, passenger vessels, and help vessels, have been overlooked of previous tallies of maritime activity at sea. The research's findings highlight a substantial gap in present mapping techniques for tracking seafaring activities. Much of the public mapping of maritime activities relies on the Automatic Identification System (AIS), which necessitates vessels to broadcast their place, identity, and activities to land receivers. Nevertheless, the coverage given by AIS is patchy, leaving lots of vessels undocumented and unaccounted for.