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How Can Natural Language Processing (NLP) Improve Safety at Sea?

Evan Palmejar by Evan Palmejar
8 months ago
Reading Time: 4 mins read
How Can Natural Language Processing (NLP) Improve Safety at Sea?

With artificial intelligence becoming more accessible to the masses, and with the volume of data continuously increasing in today’s digitally-driven world, the organisations that can harness their data are the ones that will be able to create a lasting impact in the industry. In the final part of our four article series on AI technologies in the maritime industry, we take a look at how natural language processing technology can optimise the way we work with maritime safety. 

NLP, or ‘Natural Language Processing’ is a subfield of artificial intelligence that deals with giving computers the ability to understand the text and spoken words in the same way that a human being can. 

Natural Language Processing or NLP combines a variety of concepts and technologies such as computational linguistics, where the human language is modelled based on certain rules, statistical models, and data-driven models. When these technologies are utilised together, they enable computer systems to process human language in the form of text or voice data and to interpret its meaning, intent, and/or sentiment. This form of AI technology has been used in the maritime industry such as in the preparation and processing of freight documents, and the optimised analysis of safety reports.

As the international trade association for the ship management industry, InterManager has been advocating for the best practices and procedures to promote the sustainability of the ship management practice since 1991. One of the organisation’s concerns focused on the area of lifeboat safety at sea. From this initiative, InterManager has been collecting data related to lifeboat incidents and fatalities several years ago, with the goal of identifying the main risk factors to help guide decision makers in the formulation of more effective policies. Currently, InterManager has the largest maritime industry database of lifeboat accidents.

For InterManager, the opportunity to utilise data and technology to address a challenging issue, such as lifeboat safety, came at the right time with the LR SafetyScanner, an artificial intelligence solution that was designed to identify the patterns, hotspots, and blindspots amongst a sea of raw and unstructured textual data. The technology was developed together with the support from organisations such as the UK government’s Health & Safety Executive, Glencore Marine and many others. 

The LR SafetyScanner’s machine learning algorithm includes natural language processing techniques that allow it to identify classified hazards, topics, incident severity and even root causes across the large data sets of raw and aggregated data from InterManager’s lifeboat accident database. The insights gathered include information on the main causes, hazards and trends surrounding lifeboat accidents. 

The interesting results from the LR SafetyScanner and InterManager’s database showed that human beings were not the primary cause for the accidents related to lifeboats, but were mostly related to issues with the equipment involved. The most common of these faulty mechanical issues were related to the release mechanism, the davit, and the wire/rope. These findings enable organisations like InterManager to help the maritime industry in guiding the policy development of regulators and shipping companies to create a safer environment at sea. 

The integration of artificial intelligence in these situations allows companies to recognise patterns that would have been difficult for humans to take note of. By using AI, the process becomes automated and the analysis of the raw data can be more thorough. This offers shipping companies a better perspective into what happens in these unfortunate incidents and allows us to focus on the areas that can truly make a difference. In this day and age, the ability of an organisation to take advantage of data and emerging technologies such as artificial intelligence is not just an option, but an imperative.

Download the full report here

ARTIFICIAL INTELLIGENCE SERIES

In collaboration with Lloyd’s Register, Thetius is delighted to present THE LEARNING CURVE, a report on the state of artificial intelligence in the maritime industry. Read by thousands of industry professionals across the globe, this report examines how Artificial Intelligence (AI) can allow maritime companies across the maritime asset value chain to not only get ahead of the market but accelerate their digital transformation and meet the challenges of the upcoming energy transition.

Over the coming weeks, we will be sharing a series of articles on Artificial Intelligence (AI) as a technology that will guide industry stakeholders in meeting the challenges of the evolving landscape of the maritime industry. Each article will look at an emerging form of artificial intelligence, discuss the opportunities that it can bring to improve an organisation’s competitive advantage, and present examples of innovative startups building upon this emerging technology. 

Download your copy for free @ THE LEARNING CURVE

Evan Palmejar

Evan Palmejar

Evan Palmejar is a Technology Analyst at Thetius and a marine engineer who has sailed onboard oil and chemical tankers. Evan holds a Bachelor’s degree in Marine Engineering and a Master’s degree in Maritime Management. In his free time, Evan likes to fix messy data, build dashboards, and work on his coding skills.

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