Case Study 05 · Verizon · US Patent 11,545,023

Designing a patented IoT user intelligence product from concept to granted patent.

Rad'r — an IoT-driven user behaviour intelligence platform at Verizon. From research through design to product concept and a granted US patent.

⬢ US Patent 11,545,023 · Granted January 2023
Role
UX Lead Designer
Company
Verizon
Patent
US 11,545,023
Year
2023
Focus
IoT, Data UX, Product Innovation

Not a brief. A question.

Unlike most projects that start with a brief, Rad'r started with a question: "What if we could understand user behaviour patterns in real environments to surface insights that improve decision-making?"

This was product innovation, not product refinement. There was no defined scope, no existing interface to iterate on, and no established user base. The design challenge was to take an open question and shape it into a coherent, valuable, and patentable product concept — from the first research session to the final IP filing.

Designer, researcher, prototype builder, and patent co-author.

This was one of the broadest-scope roles I've held — spanning early-stage research, UX design, data visualisation architecture, and ultimately the intellectual property process. Being a co-author on the granted patent reflects how deeply the design thinking shaped the product concept itself.

Product Design UX Research Data Visualisation Design Dashboard Architecture Prototype Development Innovation Strategy Patent Co-author

Five problems that defined the design direction.

01
Making IoT data meaningfulRaw sensor data is useless without the right abstraction layer for decision-makers. The design challenge was building that layer — translating telemetry into actionable intelligence.
02
Designing for multiple audiencesTechnical engineers and non-technical business users were looking at the same underlying data. The interface had to serve both without compromising either.
03
Real-time vs historicalUsers needed both live data for immediate decisions and trend analysis for strategic ones — ideally in the same interface, without cognitive overload.
04
Data density vs clarityIoT dashboards are notorious for overwhelming users with numbers. Finding the right density — enough to be useful, not so much to be paralysing — required extensive testing.
05
Trust in dataUsers wouldn't act on data they didn't understand or trust. Confidence indicators — showing the source, recency, and reliability of every insight — were critical design elements.

15 behaviour analysis sessions. Three insights that changed everything.

From 15 user behaviour analysis sessions, 15 key insights were uncovered. But three stood out as the most design-defining — reshaping the entire product concept and ultimately informing the patent filing.

01
Users didn't need more data — they needed fewer, better-curated insightsSurfaced at the right moment, a single well-timed insight was more valuable than a dashboard full of metrics. Curation, not comprehensiveness, was the product.
02
The most actionable insights were comparativeNot "usage is X" but "usage is X, which is 40% above baseline." Context and comparison transformed raw data into something people could act on immediately.
03
Decision-makers needed the "so what" before the "what"Lead with implication, not with data. The insight — and what it meant for a decision — had to come before the supporting evidence, not after.

Three principles to govern every design decision.

Principle 01
Insight Over Data
Every dashboard element exists to prompt a decision or action, not to display a number. If it doesn't lead somewhere, it doesn't belong.
Principle 02
Role-aware Views
Engineers see raw data; managers see trends and anomalies; executives see business impact. Same data, structured differently for each audience.
Principle 03
Confidence Visibility
Every insight shows its confidence level and data source so users can judge its reliability before acting. Trust must be earned at every data point.

Design thinking as protectable intellectual property.

The design work on Rad'r contributed directly to an intellectual property filing. The patent (US 11,545,023) covers the system's approach to user behaviour pattern detection and insight surfacing in IoT environments — a concept that emerged directly from the design and research process, not from engineering alone.

This was the first time design work I led contributed directly to a granted patent. It changed how I think about what design produces. Good design ideas — when they're novel, specific, and well-documented — are protectable. The discipline of design thinking, when applied rigorously to a hard problem, can generate intellectual property alongside user interfaces.

⬢ US Patent 11,545,023 · Granted January 2023

Being a co-author on the patent filing required me to articulate the design concepts at a level of specificity I'd never had to before. That process — translating design thinking into patent claims — was one of the most rigorous intellectual exercises of my career.

What IoT, data, and a patent process taught me about design.

Designing for IoT taught me that the challenge is always abstraction — how do you make sense of millions of data points for a human who needs to make one decision? The technology is rarely the bottleneck. The design layer — deciding what to show, when, and to whom — is where the real work happens.

Being involved in the patent process changed how I think about design fundamentally. Good design ideas are protectable. The specificity required to write a patent claim forced me to understand my own design decisions at a depth that made them stronger, not just documentable.

If I could revisit this project, I would have loved more time to test the insight-curation model with a wider range of user types. The three audiences we designed for represented the majority — but edge cases in data-intensive work often reveal the most interesting design opportunities.