PowderPrep: Real-Time Gear Recommendation System for Ski Travel
Time frame: April 2025 – May 2025
Course: CS 394 Agile Software Engineering
Collaborators: Computer Science Major (x5)
Overview
PowderPrep is a mobile-first web application designed to help skiers and snowboarders prepare for trips by generating personalized packing recommendations based on real-time mountain weather conditions and a user’s existing gear inventory.
Developed as part of a multidisciplinary design studio, the project explored how environmental data, personal ownership constraints, and trip context could be translated into actionable decisions through software.
My Role
Software Engineering + System Design
- Developed wardrobe inventory workflows
- Integrated real-time resort weather APIs
- Implemented rule-based packing report generation
- Supported usability testing and iteration cycles
Understanding the User Problem
We began by modeling a typical college skier preparing for a trip under uncertainty. Early storyboarding sessions revealed that existing packing lists failed to account for two key realities:
- Dynamic weather conditions that could change rapidly and unpredictably.
- Personal gear inventories that varied widely in quality and warmth levels.
This reframed the project as an engineering challenge: translating environmental data into structured packing decisions tailored to individual users.
Early Prototype
Our first working prototype focused on validating whether resort weather data and wardrobe inventories could be combined into a functioning recommendation workflow. Users could:
Search ski resorts
View weather conditions
Manage a simplified wardrobe
Generate a rule-based packing list
While technically functional, recommendations remained generic and navigation workflows were unclear during early evaluations.
Engineering Development and Iteration
Following early testing, the team shifted toward a data-driven recommendation system capable of adapting to both environmental conditions and user-owned gear.
Real-Time Weather Integration
Integrated resort snowfall forecasts, wind chill, and temperature ranges so recommendations reflect actual slope conditions.
Wardrobe Personalization
Redesigned the wardrobe system to log owned gear by layering category and warmth level, with recommendations adjusting dynamically to inventory.
Interface Redesign
Simplified navigation with a persistent nav bar connecting search, wardrobe, and packing workflows into a single cohesive flow.
User Testing and Validation
We conducted structured testing sessions using realistic trip preparation scenarios. Pre- and post-test surveys captured confidence levels and perceived usefulness, with feedback directly informing interface refinements and report presentation.
Participants were asked to:
Search for a ski resort
Edit wardrobe inventory
Generate a packing report
Review recommendations
Key finding: users valued personalized recommendations but struggled with early navigation flows and checklist clarity.
Final System
The final system combined real-time resort conditions with wardrobe-aware recommendations to support confident trip preparation. The application reduced uncertainty by helping users pack efficiently while avoiding unnecessary baggage costs.
Users could:
Search resorts by location
Manage owned gear
Generate customized packing reports
Receive contextual recommendations based on forecast
Impact and Key Learnings
PowderPrep demonstrated how structured environmental data can support everyday decision-making through software design. The project strengthened my experience building systems that integrate external data sources, domain constraints, and user-centered workflows.
Engineering Feasibility
Balancing technical constraints with what users could intuitively understand and act on.
Data Translation
Turning complex weather and inventory data into clear, personalized recommendations.
Iterative Development
Rapidly refining the product through structured testing feedback across multiple demo cycles.