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...

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Bibliographic Details
Published in2021 2nd Global Conference for Advancement in Technology (GCAT) pp. 1 - 8
Main Authors Aditya, G M, Hoode, Aditya, Anvesh Rai, K, Biradar, Gangadhar, Ajay Kumara, M.A, Manoj Kumar, M V, Prashanth, B S, Sneha, H R, Shivadarshan, S L
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2021
Subjects
Employment
Food Recommendation System
Industries
Machine learning
Matrix Factorization
Mobile applications
Organizations
Real-time systems
Recommendation
User experience
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Summary: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.
DOI:10.1109/GCAT52182.2021.9587601