Selected Work by Paul Tomanpos

Adventure Finder

Inspiring Outdoor Adventures Through User-Centered Design

Introduction

This case study highlights the design and development of the AdventureFinder mobile application. The app was created to solve the challenges of finding and planning outdoor adventures. By focusing on user-centered design principles, a scalable, intuitive, and robust solution for outdoor enthusiasts was developed. The design process included low-fidelity prototyping using wireframes for the home screens and an Atomic Design approach for the UI.

Project Overview

  • Goal: To create a mobile app that inspires users to discover and plan outdoor adventures, such as hiking, biking, and kayaking.
  • Target Users: The primary users include tech-savvy solo hikers, leisurely hikers with families, and busy parents seeking family-friendly trails. (Personas: Aisha Sharma, David Chen, and Maria Rodriguez)
  • Problems Solved: The app addresses the difficulty in finding trails tailored to user preferences, the lack of real-time information about trail conditions, and limited ability to track and share adventure progress.
  • Design Philosophy: Prioritize clarity, accessibility, and responsiveness to ensure a seamless user experience.
  • Tools: Figma for prototyping; Atomic Design principles to structure the UI.

Key Features

  • Home/Dashboard View: This serves as the central hub, offering a personalized overview with quick access to key features. It includes:
    • Featured trails or activities
    • A quick search bar
    • Weather updates
    • Recent activity highlights
    • User review summary
  • Map View: Displays location-based data with interactive pins or markers, enhanced with:
    • Trail overlays
    • Difficulty level indicators
    • Live conditions
    • Route recommendations
    • Real-time trail status (open, closed, partially blocked)
  • Detail View: Provides a deep dive into a specific trail or activity. This includes:
    • Trail description
    • Photos
    • Difficulty rating
    • Gear recommendations
    • User reviews
    • Accessibility information (e.g., wheelchair accessibility)
  • List/Grid View: An alternative browsing method using infinite scrolling, card-based layouts, and intelligent sorting and filtering:
    • Trail categories
    • Recent searches
    • Bookmarked trails
  • AI Chatbot Interface (Adventure Guide AI): Provides personalized assistance and recommendations:
    • Input field
    • Suggested questions (e.g., “What trails are good for beginners?”)
    • Real-time conversational responses with gear recommendations
  • Reports/Data Screen (Adventure Insights): Presents insights with interactive charts, visualizations, and dynamic filtering:
    • Heatmaps of trail usage
    • Performance metrics
    • Cumulative activity stats
    • User review summaries
  • User Reviews and Ratings: Enables users to submit reviews and ratings of activities and trails.
  • Accessibility Information: Includes data on accessibility features, such as wheelchair accessibility or stroller-friendly paths.

Design Highlights

  • Dynamic Content: The app uses dynamic content, adaptive layouts, and modular components to ensure scalability.
  • Interactive Map: Features dynamic trail overlays, live updates, and geospatial analysis to highlight the best routes.
  • AI-Driven Recommendations: The AI Chatbot utilizes machine learning to recommend activities based on preferences, skill levels, and real-time weather data.
  • Comprehensive Information: Detailed gear recommendations based on the trail, and safety tips for different activities.
  • User Feedback: Enables users to submit reviews and ratings of activities and trails to assist other users in making their decisions.

Design System and Workflow

  • Atomic Design: The design system was built using Atomic Design principles, allowing for the creation of scalable and consistent user interfaces.
  • Low-Fidelity Prototyping: Wireframes were used for the home screen to establish layouts and workflows before moving to higher fidelity designs.

Conclusion

The AdventureFinder app demonstrates a commitment to user-centered design and problem-solving efficacy. By leveraging AI-driven features, robust reporting, and intuitive interfaces, the app provides a modern solution for outdoor enthusiasts. The use of an Atomic Design system ensures scalability, and the data structures support more detailed information. The app is designed to enhance the user experience for all kinds of outdoor adventurers.