Optimizing a food wastage stream at the consumer level of the Food Supply Chain through Machine Learning and the Internet-of-Things.

Across the world, one-third of all the food produced yearly—¬¬¬worth $400 billion—is wasted (Bharucha,2017). This project aims to research and develop the accuracy of a machine learning algorithm in order to assess its efficiency in reducing food wastage and making restaurants more profitable.

Faculty Supervisor:

Cheng Li

Student:

Johan Alexander Arcos Mendez;Ramin Shabani

Partner:

InVerte Portion Control Ltd

Discipline:

Engineering

Sector:

Manufacturing

University:

Memorial University of Newfoundland

Program:

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