We worked with IoT technology providers Mindsett, to analyse real-time sensor data to forecast maintenance needs – predicting failures and preventing disruption.
From broken boilers to faulty deep fat fryers – unexpected asset failures cause disruption, and significant financial losses, to businesses around the world.
Mindsett, an IoT technology provider, wanted to expand their product offering to their clients in the retail and restaurant industries who suffer from asset failure. Mindsett approached ngenius.ai to incorporate real-time machine learning analysis of sensor data into their system to indentify usage patterns and predict asset failure.
To address the problem, ngenius.ai worked with Mindsett to analyse sensor data from stores. ngenius.ai, alongside the Mindsett technology teams, worked to design a data infrastructure to support the deployment of deep learning models in real-time and at scale across their client base.
We built intelligent maintenance schedules for assets using insights from usage, environment, and service history. The team also created a system to flag unusual measurements based on historic asset performance. The team developed, tested and deployed an AI framework which can correctly predict asset deterioration with over 86% accuracy.
If you’re interested to find out how AI technology could transform your business email email@example.com or use the contact form below.