The problem Caress solves

The app can be used in the following manner -
1- The user can keep a track of his/her health realted datas like heart rate, step count, systolic and diastolic blood pressures, oxygen content along with a smart stress prediction which uses the same to predict it, The app fetches data from a wearable device like Android Smart Watch which uses Google Fit API to provide the above described data.
2- This can be used by stressed people to inform their loved ones or guardians whenever they are in any state of stress or a hike in stress level.
3- This app too produces alert to stop current using app which creates a sudden hike in his/her anxiety level. Thus it too is valuable app for the people in anxiety.
4- The app has a special feature of self assesment which has sets of questionare for 5 different categories like anxiety, depression, post traumatic sleep disorder(PTSD), schizophrenia and addiction. Thus it too provides a good user interaction which makes user to test his state of mind by answering some questions being present over different categories.
5- This app also provides one special feature of calling over his guardian or friend whenver there is a hike in his heart rate. We too have provided a different page which renders the helpline numbers with their respective websites of some renowned organisations.
6- This app has a page which too renders all news and articles related to mental health for the whole last month from present. This can also be considered as a news or current affair app for articles and information related to mental health.

Challenges we ran into

Some of the challenges we faced during this entire hackathon were -

1. Implementation and training of ML model was one of the most difficult phase of this project. We were not getting correctly predicted data at first but finally after spending hours on a single bug , we were finally able to solve the problem.

2. Initially we took hours to fetch the smart watch data using google fit. It took us some hours to explore the way of fetching this data.

3. Deployment of Flask Backend on Render.com also created a minor issue in the overall development phase.