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SAFETY4SEA

Partners to use AI to unlock insight from vast amounts of incident data

by The Editorial Team
September 3, 2020
in Smart, Smart Parent
marlink bureau veritas

Credit: Shutterstock / Photo by: Italyan

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Lloyd’s Register has partnered with STC Global to use AI to unlock insight from the vast amounts of incident data captured by HSE functions but left untapped.

The partnership will integrate Natural Language Processing AI and root cause analysis technologies for the first time.

The outputs from the partnership will help HSE professionals to better identify and understand the underlying causes of HSE trends, patterns, systemic problems, and latent dangers. By developing a tool that provides a holistic, end to end view of incidents – past, present, and potential – HSE professionals will gain a comprehensive understanding of the key hazards associated with each incident in real time.

Once deployed, HSE professionals will be able to gain deep insight into the where and why of safety issues, ensuring each can be addressed more efficiently and effectively than ever before.

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As part of the development of its digital HSE programme for clients, Lloyd’s Register will leverage its artificial intelligence solution LR SafetyScanner built to ingest large amounts of data and then cluster them.

STC Global will apply COMET, one of the best and most progressive solutions in the field of Incident Investigation and Root Cause Analysis.

Some of the key benefits of combining the two technologies will include the ability to capture recurring systemic root causes and commonly occurring root cause clusters, map out hazard ‘hot spots’ and emerging trends to focus improvement strategies and prevent incidents in the future, to create safer more profitable work environments.

STC Global Managing Director Mark Rushton stated:

Our first joint venture product will deliver a suite of incident prevention solutions which particularly excites us as it sees our COMET platform utilise machine learning for the first time

Tags: AIdigitalizationLRmaritime data

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