Easy City

Inspiration

The Alexa challenge and our research into accessibility opportunities inspired us to create a solution for an urgent problem: It is very hard to navigate through the city if you are disabled.

What it does

For people with disabilities who want to visit a city's attractions and businesses, our app filters their wishes according to their needs and suggests the quickest accessible route to their goal.

How we built it

Alexa skills + backend in python + data from cloud.accessibility + google maps api

Challenges we ran into

There is no source of data to plan routes for accessibility with an API. The only possible source was offered by google maps, which cannot be called programmatically. We also spent a lot of time researching possibilities into finding accessible places, what kind of accessibility is possible, planning routes for these places and comparing the efficiency of routes. We had to scrap multiple ideas because the data or a way to access it did not exist or the solution was not feasible due to requiring too much scraping (e.g. we could build the routes on our own, but then we must download all accessible stations in the city and also calculate routes between each one of them)

Accomplishments that we're proud of

We were able to download data from multiple sources, compare it with our algorithms and prepare it for Alexa. We hope this could also help our society.

What we learned

How to use Alexa Skills, which neither of us could. Improving our python knowledge. And most importantly, becoming aware of how hard it is to navigate if you require extra assistance.

What's next for Easy City

If there is interest in our idea, we could ask some data providers (mvg, sozialhelden, google maps team, etc.) to release more data for accessibility so we can improve the experience even more. We could integrate our results with existing route planning apps or Alexa.

Built With

• alexa
• alexaskills
• cloud.accessibility
• google-maps
• python
• skills