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Case Studies

Improving defect identification in pipelines

This pilot in collaboration with Phillips 66 sought to explore how machine learning technologies could improve the identification of defects in energy pipelines to reduce the likelihood of leaks and impact on the environment.

How can we enable engineers working with safety critical equipment to use predictive analytics?

Last week’s announcement of the partnership between Falkonry and Lloyd’s Register was a good illustration of how Safetytech Accelerator can promote market access and adoption for new technologies once it has selected crucial challenges that if solved could change markets.

Understanding decision-making on a ship through sensing.

This pilot sought to explore how sensing technologies could improve the understanding of unsafe human behaviours and mindsets on commercial ships, leading to better knowledge of why safety incidents occur.

Transforming food safety, assurance and compliance using AI technology

This pilot saw AuditXPRT curate and successfully trial their AI solution to improve automation of safety and compliance checks in the food industry.

Anonymising and desensitising health and safety data.

A major step to unlocking value and reducing accidents by automatically desensitising and anonymising over 1.5 million health and safety documents.

Startup deploys wireless sensors across ship’s cargo hold to predict fire.

This pilot project trialled wireless sensors to detect thermal temperature increases on the below deck of a cargo ship.

Startup improves safety using deep learning-based computer vision.

This pilot trialled NumberBoost’s computer vision inspection technology powered by deep learning, to build a real-time error detection and feedback solution, to automatically detect anomalies in photos of work done on critical infrastructure.

Discover the safetytech solution that can assess if a crew is fit for duty.

The pilot trialled Senseye’s Operational Risk Management solution on top of its existing Emotional Intelligence Engine a and computer vision-based pattern recognition to assess in real-time whether crew members were ‘fit for duty’ or not.

Transforming operational risk assessments to better inform personnel.

The industry-wide pilot trialled a digital safetytech solution to make risk assessment more dynamic and effective.

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