Helix

The problem

Maintenance engineers operating CT scanner infrastructure at busy airport terminals were working against tools that were never designed for them. Legacy command-line interfaces demanded deep institutional knowledge to operate, made fault identification slow and error-prone, and created systemic risk whenever experienced personnel turned over.

The challenge was not simply a UI problem. It was an organizational one: how do you build a diagnostic system that transfers expertise into the interface itself, so that any qualified technician can operate at the level of your best one?

Design leadership and strategic direction

Leading the design of Helix meant defining not just how the product looked, but how it should think. The core strategic decision was to treat spatial reasoning as the primary diagnostic model.

Rather than surfacing raw data in tables or logs, the platform was built around a 2.5D isometric visualization system that let technicians reason through physical scanner infrastructure the same way they would on the floor. That decision shaped every layer of the product, from information architecture to component-level data visualization.

A progressive disclosure framework governed the entire experience. Technicians should never be confronted with more than the level of information they need at that moment. The system was designed across two primary views, each with a distinct and purposeful scope.

• 2.5D Isometric visualization system
• Government security compliant
• MATLAB, D3.js & multi-OS compatible

Level I: Site view

The site view is the command layer. A 2.5D isometric layout maps every CT scanner across a multi-terminal environment in real time, with each unit color-coded by operational status: green for operational, amber for degraded, red for outage.

Ten scanners across Terminal A, B, and C are visible simultaneously, giving technicians immediate spatial orientation across the full site. A Nodes toggle, Zoom slider, and Locate search bar give operators precise control over what they are looking at and how.

Below the visualization, individual scanner cards display arc-gauge health percentages for each unit. The right panel adds operational context: a Network Efficiency chart tracks throughput trends across hourly intervals, a System Capacity bar shows relative load by terminal, and a Downtime breakdown identifies failure types by category: hardware at 46%, network at 27%, service at 15%, and other at 12%.

A Time Range slider scopes all panel data to a relevant window. A technician can assess the health of an entire site and identify where to act next without leaving a single screen.

Level II: Scanner view

Drilling into a specific unit drops the technician into a detailed isometric model of the scanner itself. Each major component is labeled directly on the 3D form with callout annotations: Detector Array, X-Ray Emitter, Gantry Ring, Power Supply Unit, and Conveyor Belt.

The physical model and the diagnostic data below it are in direct correspondence. What technicians see in the visualization maps exactly to what they diagnose.

Each component has its own dedicated module, with a data format matched to the nature of that component. The Detector Array renders as a radar chart showing multi-axis signal distribution. The X-Ray Emitter displays a temperature gauge trending into the amber range. The PSU surfaces a ring indicator with HV, Logic, and Cooling status. The Gantry Ring tracks rotational activity as an area chart. The Conveyor Belt presents time-series throughput counts scoped by minute.

This component-level diagnostic language was designed as a reusable system, consistent across scanner types and extensible to future hardware without redesign.

Outcome

Helix shifted the diagnostic workflow from a process that depended on who was in the room to one that lived in the product itself.

The platform is compliant with government security standards and compatible with MATLAB, D3.js, and multiple operating systems. Design decisions were grounded in data visualization principles, human factors research, and eye tracking studies, ensuring the interface performed not just in ideal conditions, but in the high-pressure, time-sensitive environment it was actually built for.