Published Paper Details:

The sea has various restricted areas, including maybe some exclusive economic zones and dangerous zones where a lot of marine boats may accidentally or purposely stray. Additionally, a lack of real-time vessel position data contributes to a high number of collisions in the sea. Without a precise vessel's position, rescue attempts are exceedingly challenging. Numerous studies have been conducted to estimate the location of vessels in the sea to help rescue personnel assist the stranded vessels. Extended time-interval forecast of ship position is needed in light of both efficient ship allocation by shipping corporations based on worldwide freight demand and maritime situational awareness (MSA). At various information levels, decision-making and action planning can be aided if a ship's position is predicted. In order to detect vessels in the water, our present research attempted to conduct thorough as well as crucial analysis of around 70 pertinent prior works that were published in academic journals throughout a twenty-two-year period (2000-2022). The following themes received particular attention: (I) the machine learning algorithms utilized and their suitability in this domain;(II) the factors and hypotheses influencing the location also the source of study; and (III) The relevant measures for error and accuracy used in the location predicting process. We conclude by summarizing the difficulties and prospects for more study on this topic.