Radar UI
R&d, User research, UI/UX Design
Overview
Platform
Web
Background
Transmission Dynamics design and build rail monitoring systems that allow engineers to spot signs of deterioration and proactively plan maintenance to their infrastructure. Their Radar project was made up of a suite of five AI-powered anomaly detection capabilities. While invaluable for engineers, they faced the problem of having to sift through the vast amount of data the monitoring system produced.
The agency I worked for took on a funded R&D project to improve the hierarchy of information fed back to engineers through an AI-driven user interface.
I ran an empathy mapping session with Transmission Dynamics to get an idea of who their users were and their needs. I also had the chance to interview a small number of engineers from network rail directly.
There were a few distinct groups of users with different interests but what they all had in common was needing to get to the information that was relevant to them as quickly as possible, instead of having to look through multiple dashboards.
I did a lot of research into data visualisation and most effective ways to plainly communicate complex data. I produced multiple concepts and basic prototypes to explore this.
The chosen idea was a dashboard featuring a ‘digest’ of events for the user to look through. These would be presented in order of severity, with the ability to mark the event as an issue to raise, leave for the moment, or mark as dealt with.
The dashboard also contains analytical insight relevant to the user from data trends over time and the ability to ask questions about what’s going on in their area using a large language model.
The dashboard was eventually scaled down to a conversational widget that lived within Transmission Dynamics’ existing system, with role-based alerts drawn from the live monitoring data. It was built and demoed as a working prototype.
