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

基于人工智能的食物垃圾区分，用于家庭堆肥营养成分估算

• 批准号: 576912-2022
• 负责人: Wang, GuanghuiG
• 金额: $ 2.19万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749760
• 关键词: AI; enabled; food; waste; differentiation

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.

加拿大是世界上最大的食物垃圾产生国之一，每年人均浪费或丢失食物约396公斤。在家中将厨余垃圾直接转化为有机堆肥，是解决厨余危机的绝佳方式。该项目的主要目标是使用家用堆肥机将家庭中的食物垃圾数字化，以实现可持续的未来。通过探索人工智能的最新发展，该项目将开发专门的机器学习算法来检测、分割和分类厨房产生的各种食物垃圾，使每个人都可以使用简单的移动应用程序立即估计产生的堆肥的质量和营养。该项目将与致力于为食物垃圾问题提供可持续解决方案的清洁技术公司VCycene Inc.合作。除了现金贡献，VCycene还承诺为该项目提供大量实物捐助，包括数据收集和注释团队以及模型部署和移动App开发团队。他们将利用他们的关系和专业知识来提供支持，并保证这个项目的成功。拟议的解决方案在技术上是新颖的，专门设计用于解决食物垃圾的检测、分割和分类问题。该项目将为餐厨垃圾处理提供更方便、更经济的解决方案。如果成功，它将产生重大的社会影响，改变目前食物垃圾管理的做法，显著减少我们的碳排放，实现加拿大在《巴黎协定》中的目标。