This is Mara, and her pet dog Zoey. Mara often takes Zoey on walks around her neighbourhood. However, she begins to feel bored of seeing the same old scenery everyday. Concrete, brick, and unpaved roads. She doesn’t know where else to walk and the activity meant to clear her mind soon begins to clutter it.
She starts dreading 5 pm strolls and her dog has to deal with the effects.
The younger generation is more sedentary than ever seen before, and no one wants to get out of their comfortable homes.
As a citizen of this generation, we faced this issue too; the modernization of living areas makes walking less enjoyable, safe, and no one feels motivated to go on them anymore. I mean, who wants to constantly walk through noisy construction zones and grey pavements.
Intentional walking for at least 30 minutes a day is proven to improve their mental, cognitive, and physical states by a significant margin and n a survey taken at Spur Hacks, over 75% of participants knew that walking could greatly improve their lives, but, it wasn’t something they did often, — because they felt unmotivated, unsafe, and unaware of how to properly go on walks.
What it does
This is why we created Roami: an app equipped with features that will change going on walks forever. Roami takes the inputs of our users’ allocated time, distance range, step targets, and preferred environment — like scenic, urban, or quiet paths, and generates the perfect walking route using Machine Learning, and GPS data.
Roami is designed for those who need to build lasting, healthy habits through walking, as well as for frequent walkers who want to explore new, personalized routes that keep them motivated. A university student with 30 minutes between classes wants a calming scenic walk. Roami maps it all out for them.
How we built it
We used HTML, CSS and Java script for our front end and we used json for our back end.
Challenges we ran into
We were trying to use the Google Geolocation API key to activate our map, but we couldn't make it work and we also didn't figure out the MongoDB database. We also had problem connect the model we trained for identifying the map to our web app.
Accomplishments that we're proud of
This is our first time doing things related to machine learning and we are very proud that we
What we learned
We learned the basics of machine learning and how to train a model
What's next for Roami
We are thinking about adding a feature that allows disabled people who can't walk well, to find people who can't walk well, to find a more easy route to take like with less hills and other factors to make it more accessible for them to experience nature
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