Inspiration

As a student traveling back and forth between school and home, we spend most of our travel time listening to podcasts. Unfortunately, we always had a hard time completing the podcast in one go as most podcasts we watched took longer than our travel time. Therefore, we developed dotCast to help us select podcasts that fit our travel time and hence, allow us to complete the entire podcast and get the key takeaways from the podcast completely.

What it does

dotCast helps you to generate a Spotify podcast playlist in which duration is within your travel time.

As most people in Singapore travel by MRT, dotCast allows you to select your source and destination MRT stations. dotCast will calculate the travel time between the 2 MRT stations and select podcasts you can complete before arriving at your destination.

How we built it

We built dotCast using Gradio. Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere!

Challenges we ran into

We had a hard time going through the API documentation. As there were a lot of fields and higher-level architecture that we needed to understand to develop the features. Moreover, there were issues we encountered with Login and Authentication through SSO. It was our first time working with this authentication method, and we had challenges figuring out the best practices to pass in authentication tokens.

Accomplishments that we're proud of

Completing product development from scratch, from the designing stage until the development stage. It was our first time doing product and project management from scratch.

What we learned

We learned new tech stacks, such as Vue and Flask on the first day of the hackathon.

What's next for dotCast

We would like to revamp and upgrade the UI for future development stages. We would also like to support other modes of transport beyond the MRT.

You may access our Figma Prototype for dotCast 2.0 here

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