ML Enabled Food Recommendations For People With Special Dietary Needs

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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.