AI-enabled food waste differentiation for at-home compost nutrients estimation

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Canada is one of the top food waste generators in the world, with about 396 kilograms of food wasted or lost per capita every year. Turning food waste directly into organic compost at home is an excellent way to solve the food waste crisis. The main goal of this project is to digitalize food waste at home for a sustainable future using at-home composters. By exploring state-of-the-art development of artificial intelligence, the project will develop dedicated machine learning algorithms to detect, segment, and classify various food waste generated in the kitchen, making it possible for everyone to immediately estimate the quality and nutrients of the generated compost using a simple mobile App.The project will collaborate with VCycene Inc., a cleantech company dedicated to providing sustainable solutions to the food-waste problem. In addition to the cash contribution, VCycene has committed substantial in-kind contributions to this project, including a team for data collection and annotation and a team for model deployment and mobile App development. They will use their connection and expertise to provide support and guarantee the success of this project.The proposed solution is technically novel and specifically designed to solve the problem of food waste detection, segmentation, and classification. The project will provide a more convenient and economical solution for food waste processing. If successful, it will make substantial societal impacts and change the current practice of food waste management, significantly cutting down our carbon emissions and meeting Canada's goals for the Paris Agreement.