Using AI to predict hish risk worksites

Mar 2022

I lead a cross-functional team at FYLD that secured £560,000 of non-dilutive funding from the Office of Gas and Electricity Markets (OFGEM), as part of its inaugural Strategic Innovation Fund grants.

The project focused on predicting high risk worksites – the next step towards a ‘zero-harm’ vision for the utilities industry, powered by AI.

We laid the groundwork for FYLD’s Predictive Safety Interventions – a safety system dedicated to accurately predicting and mitigating safety incidents on site or out in the field. Using a combination of FYLD’s proprietary data and SGN’s safety incident information, we four key stages: identifying relevant data, applying machine learning, identifying key correlating factors, and showing that safety risk can be algorithmically predicted.

The ultimate goal is to achieve a ‘zero-harm’ outcome for companies using FYLD’s solution, by recording zero incidents out in the field. Using data, AI, and innovation, there is an opportunity to create a safer, more predictable, and lower risk working environment for every fieldworker, on every job. This technology enables field workers to return home safely every day after working in hazardous environments.

Read the full story on the FYLD website.