The problem Animo: A guide to Mental Health solves

"Animo" is the latin translation of mind and noticing the sync where mental health is the well being of one's mind, our main objective is to educate the population still oblivious to the issues regarding mental health.And provide a safe space for those who want to learn about what it is and whether they need help. We want to provide a platform to every individual who wishes to learn more about their mental health and the path to mindfulness. Our aim is to help as many people as we can suffering from degrading mental heath. Especially in times like these where there is nowhere to go and no one to talk to we want to be there for you.We aim at ensuring that all your questions are answered. The web app allows you to interact with the bot and ask as many questions as you like regarding your mental health starting from what it means to identifying symptoms of any possible underlying issues. You can have a proper conversation with our bot asking as many questions as you'd like without any fear of judgement. We also allow the users to look for the best solution for their problem. We use our bot to analyse the users current mental state and if based on the analysis we encounter patterns of troubled behaviour we provide them with a service which allows them to know about the nearest Psychiatrists or counsellors available all they need to do is to enter their pincode in the popup . Which in turn provides them with multiple links to nearest establishments by checking their loactions.The pincode allows the bot to connect their location.

Challenges we ran into

Any innovation is incomplete without hurdles. Facing multiple trials and errors is what makes the project succesful. In our process of making Animo we encountered several challenges in our path starting from data mining, then cleaning the dataset took a lot of time and effort. Designing the sequence to sequence model and then integerating the sentiment prediction was one of the biggest challenges. Waiting hours and hours for the model to train required alot of patience. Assigning the location based on the pincode was not an easy task since multiple times it gave wrong location outputs and also messed up the links. Facing several errors and solving multiple problems finally led us to the end of our project and left us quite content.