Footfall Tracker and Predictor
Predicting footfall in hostel canteen for a given menu.
Supervisors: Dr. Rajesh Kumar
Our aim was to save food wastage. The hostel mess prepares food for the students enrolled in the mess dining program. However, it is not the case that all the students shall dine at the mess. Hence, the prepared food is then sent for waste management. Prastut, Fenil and I decided to solve this problem by predicting the number of students that would turn up for lunch/dinner on a given day(menu).
As part of this project, we developed a real-time embedded system that would capture the students entering the mess. This solved our data collection process. We then predicted the number of students that would turn up for a given menu and day. We used linear regression for Weibull distribution(since our data fit this dist).