Inspiration
Patient who are having normal disease like fever, cold are not getting proper treatment. So we developed an application that helps patients to communicate with doctors and having personal rooms where they can share their problems.
What it does
It creates a real time chatting application in which patients and doctor will be running client side application and server will give them fumctionality to connect using socket.io
How we built it
We built from scratch using HTML, CSS, Reat, Node.js and socket.io
Challenges we ran into
Initially, we had a plan in mind with what API's we wanted to utilize in order to process the images of the user and the queries from the patients. This second API had very confusing documentation and caused us to lose a relatively significant amount of time that could have been better spent on other productive means. Due to this roadblock in progress, we were effectively forced to resort to node js for the database and express for connecting the frontend and backend.
Accomplishments that we're proud of
There are two main accomplishments that our team is proud of. Our user interface in particular, turned out to be very successful in being both clean, atheistically pleasing, practical, and easy to both use and navigate. As a key component in our project, getting the React App and Express to function properly with the application is another accomplishment that we are very proud of.
What we learned
As it was over first hackathon, we learn many new things such as dealing with React js app, express and nodeJs. Moreover, we also learned about the APIs and CORS (cross origin recourses sharing).There were a number of things that our team learned from the process. The most notable thing that we learned was that time management and organisation are subtle but key factors when it comes to working on an application (especially in the short time span of a hackathon).
What's next for Doctors Chat Application
The application is under development process, so next we will be focusing on setting integrated Alarm for elderly patient and additionally, medicine recognition using deep learning. And integrating the authentication using SAWO labs.
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