Inspiration

Everyone's life is a cycling routine. Some people's routines are more sporadic than others who follow a strict daily/weekly plan but in the large scope of things, everyone lives inside a certain pattern and there is no app that helps you maintain/enhance it based on personalized data. While it helps make your routine life more dynamic by suggesting enhancements, for people who move to new cities/environments on a regular basis, you need to be able to stabilize your schedule. There is no app that helps maintain your same lifestyle patterns across different cities. We want to not only make these routine maintenance/enhancement feature but make it a social experience.

What it does

The app recommends activities or potential routines based on the location and types of activities you engage in. You are also able to search through categories of activities/routines/places which you can add to your weekly schedule. There is also a newsfeed that shows all the activities/routines that those who you are following are engaging in. Lastly, there is a feature in which when you change your current address to a new address, meaning you've moved into a new place, the app automagically generates a routine that is adapted into the new place while maintaining the feel/pattern of the routine from the previous location.

How I built it

We built the interface/UI using Java and Android studios. We built the back-end via using JSON objects obtained from querying bing, yelp and google maps api.

Challenges I ran into

Bing API issues and limitations as well as complications with data transfer/storage.

Accomplishments that I'm proud of

Having produced a working app that can serve a purpose and meets some of our many ideas that we had.

What I learned

By looking into a variety of features, learned a lot of different things ranging from simple Java/Android to Speech Recognition and Location.

What's next for HackathonProject

Machine Learning! While this was a 36 hour hack, by building a more comprehensive machine learning algorithm, we would be able to make a more interesting and meaningful routine recommendation. We were also looking into Speech Recognition accessibility feature that could answer questions like "How is my son doing?" "At what restaurants does Jennifer eat out the most at?" that could gather the right information and speak it back out to the user. This would be useful for military personnels, veterans and visually impaired for whom the app has a lot of use case because they move between cities frequently.

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