Roadio

An all-encompassing mobility platform to reduce CO2 footprint by offering carpools between your home and office.

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✨ Inspiration

Instead of switching between multiple navigation apps for different purposes, we offer a convenient one-stop solution to access all types of navigation services to save time and effort. Introducing: Roadio, an all-encompassing mobility platform developed for Vitesco's Work Smarter & Sustainable challenge.

❓ What it does

  • Our app offers seamless transitions between driving directions, walking routes, public transit information, cycling paths, and more.
  • Users can access real-time traffic updates, estimated arrival times, alternative routes, and public transportation schedules to choose the best path based on their preferences.
  • Roadio provides personalized features tailored to individual preferences where users can save personalized addresses, collect sustainability points, and rank up the leaderboard.
  • Users can carpool using a fellow co-worker's vehicle on their way to the office or offer a ride and earn sustainability points.

💻 How we built it

  • Technologies: AWS, Docker, Streamlit, React, Figma, Hostinger, and of course, StackOverflow
  • Datasets: Vitesco's sample dataset, OpenStreetMap's API, and World CO2 emissions dataset
  • Languages: Python, JavaScript, HTML/CSS

Go to http://34.255.207.2:8501/ to access our working prototype and log in as our (fake) user persona:

Username: brad_pettis Password: 1234

Alternatively, you can access it through our very long AWS link by clicking here.

⚔️ Challenges we ran into

  • Since we need to send requests regularly to the OpenStreetMap API, we faced a timeout error after reaching the maximum number of calls. We solved this by deploying the app to AWS with Docker :)

🏅 Accomplishments that we're proud of

  • We successfully created a working prototype with an interactive user interface and deployed it throughout the hackathon! 🥳
  • Miraculously, some of us managed to sleep.
  • We also developed a solid business plan and a beautiful landing page for Roadio which you can see on https://roadio.cloud/.

📚 What we learned

  • How to integrate Streamlit with Docker and Amazon Web Services.
  • Methods of utilizing AI - particularly Graph Neural Networks (GNNs) - to calculate the shortest path between two addresses.
  • Different visualization techniques contribute to enhancing the user experience, so it's vital to always test your application and use it from the perspective.

🔮 What's next for Roadio

Further integrations with other mobility companies or public transportation apps would significantly boost Roadio's efficiency. We can also incorporate emerging technologies such as AR, voice assistants, and smart home integrations to elevate the user experience. Moreover, although the provided dataset is perfect to test our models and algorithms, it would also be interesting to see how far our application could scale using a more global dataset :)

🤗 Meet our team!

  • Tayfun Bönsch (Germany)
  • Marvin Lederer (Germany)
  • Sohangkumar Patel (India)
  • Hari Kesavan (India)
  • Nathanya Queby (Indonesia)
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