Spiend Tech

Your personal space friend.

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Inspiration

With the advent of commercial space travel, the need for applications to keep health check-in space is only going to become more important. We want to help astronauts, and maybe one day, even normal people as they embark on their space travel journey. It can get lonely in space, and it's easy to neglect one's health due to a variety of different reasons. Therefore, we came up with a platform where users can take care of their health while also chatting with an intelligent AI if they require company.

What it does

  • Predicts heart rate level as a measure of health: an abnormal heart rate in space can cause hearing loss, brain edema, and deformation of the eye. [2]
  • Suggests exercises that one could do in space, based on their current health condition
  • Suggests a suitable amount of time to spend on the treadmill to reduce calf muscle loss; calf muscle loss leads to weakness and inability to do work. [3]
  • Has a GPT3 powered chatbot to combat loneliness and provide users with company in space [1]
  • It's connected to Twilio Whatsapp API so users can interact with the chatbot not only through the site, but also through Whatsapp. This will enable the users to more conveniently access the chatbot and strike up a conversation with it.

It drastically improves the quality of life for the people who are on a space journey. After all, Spiend stands for Space + Friend, and that’s what it achieves - we provide people with a companion to accompany and take care of them.

How we built it

We used Flask as the backend to run functions for our chatbot and ML models.

We used HTML, CSS and JS for the frontend.

We used the GPT3 natural language processing model by OpenAI and integrated Twilio for the chatbot.

Lastly, we used the Sk-learn library and datasets from NASA to train 3 ML models that recommend exercises in space.

Challenges we ran into

  • We were unable to integrate Twilio with the bot at first; but we managed to do it in the end.
  • Making everything work together. However, we enjoyed it and learnt a lot in the process.

Accomplishments that we're proud of

  • Building an MVP in 24 hours!
  • Integrating ML with Flask
  • Making a good chatbot and a nice-looking frontend

What we learned

  • How to use the Twilio API
  • How to make a chatbot
  • How to integrate ML models in flask and connect everything together

What's next for Spiend Tech

We plan to add more ML models to make the predictions better.

We also want to add an exercise tracker so that people in space have a personalized health experience.

Citations

1) https://blogs.scientificamerican.com/guest-blog/mental-health-in-outer-space/

2) https://www.nasa.gov/mission_pages/station/research/station-science-101/cardiovascular-health-in-microgravity/

3) https://www.nasa.gov/pdf/64249main_ffs_factsheets_hbp_atrophy.pdf

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