Introduction
Effective management and maintenance of critical infrastructure is essential, both to ensure that the infrastructure can perform its function, but also to ensure it does so in a safe manner. With advances in AI and data science, the role of digital technologies is becoming key, and in some instances the data itself is becoming part of the asset requiring appropriate management. In the UK, there are 13 critical infrastructure sectors, which all feed into the universal goal of supporting the functioning of society.
This project, in collaboration with University of Strathclyde and Lloyd’s Register Foundation, provides a deep dive into the datasets, information sources, and analytics methods that are crucial for enhancing safety protocols, risk mitigation, and operational efficiency associated with the management of critical infrastructure.
Explaining the science
Lloyd's Register Foundation recently commissioned a report addressing the question of: "How do we ensure the future safety of the complex critical infrastructure on which modern society relies?". A key outcome of this report was the recommendation that a deep dive review be performed to understand what data can be harnessed most effectively to deliver safe and reliable critical infrastructure to support a functioning society, and how AI and data science could be used to effectively support and manage this.
By bringing together the broad sectors (which don't normally interact), we will identify commonalities and gaps, as well as best practice, resulting in the optimal utilisation of data science and AI to ensuring safety and resilience across all the critical infrastructure sectors. By surfacing the common challenges and approaches, this will allow the complex interdependencies between the various sectors, and the need for underlying unifying data and knowledge exchange architectures, to be identified.
Project aims
This project aims to produce a report containing a clear and actionable set of recommendations which will provide the necessary evidence for targeted investment in appropriate digital technologies. Importantly this will provide a trusted, independent assessment of the opportunities for improving safety in critical infrastructure through digital technologies, AI and data science for use by policy makers, asset owners, the supply chain and academia.
Ultimately, this research could extend the lifetime of critical infrastructure, increase the reliability of critical services, improve retention of asset management knowledge and expertise, and reduce the cost of maintaining publicly owned critical infrastructure.
Get involved
Interested in hearing more and contributing to this research project, register your interest here.
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