ML Enabled Food Recommendations For People With Special Dietary Needs

为有特殊饮食需求的人提供基于机器学习的食物推荐

• 批准号: 51865
• 金额: $ 20.48万
• 依托单位: HUMANITY V2 LTD
• 依托单位国家: 英国
• 项目类别: Study
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=51865
• 关键词: ML; Enabled; Food; Recommendations; People

The World Health Organisation (WHO) estimates 3%-7% suffer from a food allergy globally which translates to 220-500 million people. This project aims to aid food allergic, intolerant and people with special dietary preferences in deciding what to eat when eating out by applying machine learning techniques to a domain-specific knowledge graph. In collaboration with The University of Manchester, this project will create disruptive technology to support decision making for people with special dietary needs, along with increasing transparency, trust and reducing food safety risk at food outlets. The outputs of the project will help to test the 'feasibility' of the solution and de-risk early-stage R&D by co-designing, building and testing the technology with the target demographic. Acting as a catalyst for future research and investment for the partners involved. The long-term potential will have a significant impact on the UK economy by improving health and wellbeing through personalised nutrition and behaviour change, via cloud, mobile and IoT technologies. Additionally, exporting the technology to a global scale from significant investment from impact-driven venture capital firms.

世界卫生组织（WHO）估计，全球有3%-7%的人患有食物过敏，相当于2.2亿至5亿人。该项目旨在通过将机器学习技术应用于特定领域的知识图谱，帮助食物过敏，不耐受和有特殊饮食偏好的人决定外出就餐时吃什么。该项目将与曼彻斯特大学合作，创造颠覆性技术，以支持有特殊饮食需求的人的决策，沿着增加透明度，信任和降低食品店的食品安全风险。该项目的产出将有助于测试解决方案的“可行性”，并通过与目标人群共同设计、构建和测试技术来降低早期研发的风险。为有关合作伙伴的未来研究和投资提供催化剂。长期潜力将对英国经济产生重大影响，通过云、移动的和物联网技术，通过个性化营养和行为改变改善健康和福祉。此外，通过影响力驱动的风险投资公司的大量投资，将技术出口到全球范围。