MBTA & Role Playing Game with Solana Blockchain

A real-time MBTA planner where Pokémon GO meets Maps—gamifying fares and leveling up your commute.

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MBTA Transit Helper & RPG Game with Solana Blockchain

About the Project

We built an MBTA transit planner that doubles as a playful RPG-style game. Our goal: make trip planning less stressful and add game-like motivation to everyday commuting. Joshua brought prior mapping and front-end experience, pushing us to build a robust, interactive map; Rohan’s fintech background helped add a Solana blockchain rewards layer to incentivize fare compliance.

Key Features:

  • Transit Mode – Plan multi-leg MBTA trips in real time with:

    • Intelligent transfer routing: Origin → Transfer → Destination
    • Live arrival predictions and auto-refreshing data (every 30 seconds)
    • Walking time estimation and transfer confidence scoring based on timing and distance
    • Interactive map with MBTA line colors, routes, and station markers
    • Easy, validated station selection with dropdowns grouped by subway line

  • Game Mode – Overlay an RPG system on top of everyday trips:

    • Unlock by uploading a ticket; earns points and tracks journeys
    • Progression via XP, levels, and achievements for distance and tasks
    • AI-generated “quests,” gamified event reporting, and a collection of badges

  • Blockchain Integration:

    • Each journey and achievement is recorded on-chain (Solana, via Memo)
    • Micro-rewards (SOL) are distributed for validated journeys
    • Phantom or Solflare wallet connection for transparent, real-time rewards

From live trip planning to RPG questing and verifiable blockchain rewards, we aimed to turn the MBTA commute into a rewarding experience—both practically and playfully.

What We Learned

We learned how to integrate live transit data with a React front end, and how to design two distinct experiences in one product without losing coherence. We also learned how to use AI responsibly in coding to move faster under a tight deadline—leaning on it to draft structure, explore approaches, and debug faster while we kept control of product decisions and implementation details. This was especially helpful with the hackathon's limited time.

How We Built It

We built the web app in React + Vite, using the MBTA V3 API for routes, stops, predictions, and vehicles. Transit Mode focuses on trip planning and transfer confidence. Game Mode layers in XP, quests, achievements, and event reporting on top of the same transit system.

A good mental model for our build was:

experience = transit utility + engagement loop

Challenges We Faced

  • Aligning real MBTA stop and route data with consistent map rendering
  • Keeping the UI cohesive across two very different modes
  • Balancing depth vs. scope under time pressure
  • Validating complex flows quickly enough to ship
  • Making a meaningful game layer without overwhelming core transit features

We are glad we were able to submit and be here—this is Joshua's first hackathon, and finishing something complete on time was a huge win.

Tech Stack

GitHub

GitHub made collaboration and version control smooth. Using branches and PRs kept us organized while iterating quickly. We appreciated how reliable it is under fast-moving hackathon conditions.

Vite

The dev server speed was excellent. Hot reloads stayed consistent even as the project grew, which made iteration much faster.

MBTA V3 API

The API was rich and well-documented, and the data quality was strong. The main friction was making sure stop IDs and route patterns aligned with how we wanted to visualize trips, but once we understood the data model the integration was very workable.

AI Tooling for Coding

AI was useful for accelerating boilerplate, ideation, and debugging. The big lesson was to treat it as a collaborator that speeds up thinking rather than a replacement for product judgment.

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