STYLE
FORECAST
A weather-powered fashion discovery platform that combines real-time weather conditions with curated clothing recommendations, helping users plan outfits and build personalised style inspiration collections.
PROJECT TYPE
Individual Academic Project
TIMELINE
2 Months
October – November 2025
TEAM
Individual
MY ROLE
UX Design · UI Design · Frontend Development · API Integration
TOOLS
Blazor · C# · ASP.NET Core · HTML · CSS · Visual Studio
APIS
OpenWeather API · ASOS API (RapidAPI)
Problem-solving in daily life.
For an assignment, we were tasked with the job of creating a website which would help us solve a problem we face in our daily lives. Style Forecast was developed as an individual academic project between October and November 2025. The goal was to combine real-time weather information with fashion recommendations to simplify outfit planning.
By integrating external APIs and designing a clean editorial interface, the platform transforms weather forecasts into personalised style inspiration.
Weather is not data — it’s daily context.
The core idea emerged from observing how people mentally translate weather into clothing decisions. Instead of reading forecasts logically, users interpret them emotionally: “it feels cold”, “I’ll probably need layers”, “this looks like a coat day.”
This revealed an opportunity: bridge structured meteorological data with intuitive fashion reasoning, turning forecasts into a styling system rather than a static report.
“The goal wasn’t to predict weather — it was to translate it into something wearable.”
Editorial clarity over algorithmic overload.
The interface was intentionally designed to feel more like a curated fashion editorial than a utility dashboard. This reduced cognitive load and reframed recommendations as inspiration rather than automated output.
Each weather result is structured into a hierarchy: temperature → mood → outfit direction → product selection.
- Minimal UI density to reduce decision fatigue
- Large imagery to prioritise visual styling cues
- Soft hierarchy between weather and fashion layers
Turning forecasts into fashion recommendations.
Users can search for any location, retrieve live weather data, and receive curated clothing recommendations tailored to current conditions.
Built with API integration at its core.
The application was developed using Blazor Server and ASP.NET Core. OpenWeather powers the live weather functionality while the ASOS API provides product recommendations based on forecast conditions.
A complete weather-powered styling assistant.
The final platform enables users to discover weather-aware outfits, browse fashion recommendations, and save favourite products to a personal lookbook.
The project successfully demonstrated API integration, responsive design, and user-focused fashion discovery within a single web application.
End-to-end ownership across design and implementation.
I led the UX design, UI system, and full frontend implementation of the application. This included designing the information architecture, building responsive layouts, and integrating external APIs into a cohesive user experience.
A key challenge was mapping structured weather data into meaningful fashion recommendations without overwhelming the user with technical detail.