CliniQ

NTU HACKATHON

Problem statement

Crowd information from nearby clinic to visit the least crowded one
Old people can’t wait long
Small clinic’s cannot afford to have in-house database
Effective planning in the clinic, based on the crowd.

Solution Outline

An AI face detector to detect the faces in the clinic waiting area, to find the crowd capacity in the clinic. The crowd capacity is updated realtime to the cloud storage and fetched using a Python Rest API to return to the users based on their current location.

code Outline (repo's)

face detect is the code for face detection using opencv which updates the firebase with the number of people information
python server is a flask server, acts as a REST API
Ionic app is the front end application.