UX Case Study · IoT & wellbeing · Newcastle University

LeafLink

Most people kill their houseplants — not from neglect, but from picking the wrong plant for the room. As UX lead on a five-person “Technologies for HCI” team, I helped build LeafLink: a sensor device and app that read a room's light, humidity, temperature, and air quality, then recommend plants that'll actually thrive there. After a four-week sprint, 85% of the people we demoed it to felt more confident choosing and caring for plants.

Role
UX lead — team of 5
Domain
IoT · indoor wellbeing
Timeline
4 weeks · 2024
Platform
Mobile + web app · physical device
Methods
Lit review · competitive analysis · personas · prototyping
Context
“Technologies for HCI” · Newcastle University
85%
felt more confident choosing plants
92%
said it simplified plant care
65%
wanted to grow their indoor garden
78%
interested in similar smart devices

Demo-day responses from end-of-semester panellists and visitors — encouraging signal, not a controlled study.

01 — Context

A device that reads the room

LeafLink pairs a smart sensor device with an app to help people choose houseplants that suit their space. It was the project I led for my “Technologies for HCI” course at Newcastle University, guiding a team of five from concept through to a working prototype.

As UX lead I owned the experience mapping and turned our findings into design decisions, ran an iterative loop across both the digital and physical prototypes, shaped the overall form of the device alongside teammates on electronics and aesthetics, and kept the plan on track with clear ownership. The thread throughout: keep it user-centred while wrangling real hardware constraints.

Fig 01 · Context
LeafLink device and app
LeafLink — a sensor device and companion app that turn a room’s conditions into the right plant for the space.
02 — The challenge

Why people keep killing their plants

People struggle to choose and keep houseplants alive — and failure is discouraging. The root issue is a lack of accessible, personalised information about what a plant needs and whether it fits a particular indoor environment.

The brief we were set

Design a social and technical intervention that helps users meaningfully and responsibly collect data from other people and/or their local environment, for the purpose of living well together.

01

Not knowing what a plant needs

Most people don't have a clear sense of a plant's needs for light, humidity, and temperature — making it hard to pick one that will thrive in their particular space.
02

No way to read the room

Without the right tools, people can't accurately assess or track the conditions in their home — so placement and care end up being guesswork.
03

Too many plants to choose from

The sheer variety of houseplants is overwhelming, turning a simple choice into a time-consuming, confusing one.

What we set out to do

  • Build an intuitive solution to the houseplant-selection problem.
  • Use data and digital tools to give useful insights and recommendations.
  • Encourage healthier living spaces through informed selection and care.
  • Turn complex information into clear, actionable recommendations.
  • Grow users' understanding of their indoor environment and its effect on plant — and personal — health.
03 — Approach

Five people, four weeks

With a small team and a tight timeline, we ran a clear, sequential method to get from a blank page to a working build.

  1. Propose. The team brainstormed a range of solutions to houseplant-care challenges.
  2. Vote. We converged on the most promising concept together.
  3. Explore. Investigated the required technology and feasibility, and built initial prototypes.
  4. Allocate. Split the work by expertise — hardware, software, and UI design — so everyone owned a clear piece.
04 — Research

Learning from plants and products

Literature review

We started with a literature review across academic papers and online sources on indoor plant care, environmental sensing, and smart-home technology. It grounded us in the science of plant growth and where technology could realistically help.

Fig 02 · Research
Literature review
Literature review — the science of plant growth and environmental sensing that underpinned the concept.

Competitive analysis

We then examined existing plant-care apps, smart planters, and environmental monitors — their features, interfaces, and user feedback. That surfaced clear gaps: personalised recommendations, friendlier ways to present environmental data, and integrated care guidance.

Fig 03 · Research
Competitive analysis
Competitive analysis — mapping existing products to find the gaps LeafLink could fill.
05 — The process

Narrowing to wellbeing at home

In the Define phase we focused the project on improving health and wellbeing at home through plants, and sharpened the problem into a single guiding question.

How might we enhance indoor spaces that promote better health and wellbeing through the use of plants?
Fig 04 · Process
Define phase
Defining and reframing the problem before committing to a direction.
Fig 05 · Process
User persona
The persona we designed for — someone who wants plants but lacks the confidence to keep them alive.
Fig 06 · Process
User journey and storyboard
Journey and storyboard — how a user would go from an uncertain room to a confident plant choice.
06 — The solution

Sensors, app, and a plant that lives

LeafLink came together as three connected pieces: a sensing device, a clear app, and the pipeline that links them.

01

A data-driven selection device

The LeafLink device measures air quality, humidity, temperature, and light in a room, then suggests plants that will grow best in that space — taking the guesswork out of plant shopping and teaching people how their home affects what they grow.
SensingRecommendations
Fig 07 · Solution
The LeafLink device
The device that reads the room and turns its conditions into plant recommendations.
02

A friendly mobile app

The app works with the device across three screens — Home (a quick look at all your LeafLinks), Insights (room conditions in real time, with charts), and Suggestions (recommended plants and care tips). The simple design helps people read the data and act on it.
MobileData viz
Fig 08 · Solution
Mobile app overview
The companion app — Home, Insights, and Suggestions.
03

Hardware and software, joined up

Sensors collect room data; a Raspberry Pi processes it and sends it securely to a server; the app fetches the results and shows them. The result is a seamless flow from real-world conditions to a plant recommendation on your phone.
Raspberry PiCloud
Fig 09 · Solution
Hardware and software
The end-to-end pipeline from sensors to recommendations.
07 — Impact

What the demo told us

We put a working device and app in front of people at the end of a four-week sprint — and the response was strongly positive.
  • 85% felt more confident selecting and caring for houseplants after using LeafLink, and 65% wanted to expand their indoor gardens.
  • 92% agreed the technology simplified their plant-care routine, and 78% were interested in similar smart devices for other parts of home management.
Reading these honestly

These figures come from the panellists and visitors present at the prototype demonstration, based on responses gathered on the day. It's encouraging signal from a real demo — not a controlled study — and I'd frame it that way to a stakeholder.

08 — Future scope

Where LeafLink could grow

With custom electronics, LeafLink could capture metrics more precisely and stand on its own as a product. A few directions stood out:

  • Smart-home integration. Work with Alexa or Google Home, so people can check plant data or get care reminders by voice.
  • AI plant-health monitoring. Use machine learning on leaf images to catch early signs of disease or pests.
  • Community features. Let people share tips, show off their plants, and compete in friendly “greenest home” challenges.
09 — Reflection

What leading this taught me

Bridging the design–development gap

Some of our UI concepts simply weren't feasible to build, which forced late changes. I learned to involve developers from the start and design for what's technically possible — fewer last-minute reworks, better end results, and a smoother handoff.

Clear team communication

Gaps in communication caused problems sourcing the right components and inconsistencies in the designs. Regular check-ins and a shared project glossary pulled the team into alignment and kept execution tight.

Technical knowledge beyond UX

Uneven understanding of the backend led to designs that didn't match what the system could do. I pushed myself to learn the technical side, then shared those constraints with the team — fewer redesign cycles, more realistic designs.

Innovating within constraints

Limited components, thanks to procurement issues, taught me to be flexible and resourceful — finding good solutions inside real limits, which is closer to how design works outside the classroom than ideal conditions ever are.

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