Remote Predictive Home Monitoring
A first of its kind solution to monitor connected home boilers and anticipate faults before they happen.
By combining big data analysis and data science with industry leading cloud AI architectures we can analyse historic and real time datasets for customer boilers across more than 100 individual data points.
By accurately predicting specific at-risk boiler components and expected failure dates we allow engineers to proactively schedule a repair.
This minimises engineers’ time to identify problems and ensures that homeowners can avoid the cost and hassle of finding a last-minute engineer for an unexpected boiler repair.
By implementing best practice security along with robust and trusted tools such as Active Directory, we ensure that all customer data is stored securely and viewed only by authorised personnel.
Our expertise in Microsoft Azure cloud computing and AI allowed us to deliver an innovative and cost-effective global platform.
Using Azure’s advanced Machine Learning functionality allowed us to build, train and deploy a predictive model as an authenticated web service.
To meet security requirements, we used Azure Active Directory and a layered token exchange principal via Azure API Management to protect NWG internal systems. This combined with the use of Azure Hybrid Connection provides the end to end security needed by critical infrastructure companies.
The Analytics Platform provides real-time data from customer’s homes to authorised engineers, alerting them as soon as a fault is predicted.
An innovative web application, the platform has maximised the efficiency of engineers by reducing costly and unnecessary repairs while ensuring that customers around the globe are safe in the knowledge that the heart of their home is in safe hands.