Machine Learning Based Platform and Recommendation System for Food Ordering Services within Premises

Normally, the long queues and crowd can be seen at the canteens/hotels whenever there is a lunch break in an organization or within a campus. This paper proposes a solution for eliminating the queue system and introduces the facility to remotely place food orders. Further, this paper proposes a real-time food recommendation system to suggest the dishes to users based on their past orders. The solution has been implemented through a mobile application built using Flutter. The mobile application has been empowered with a machine learning model for recommending the items that the user might like. The proposed method has been tested with 2 vendors catering to 60 customers successfully. The accuracy of the recommendation has been satisfactory.