ML enabled food recommendations for people with special dietary needs

Activity: Consultancy, spin-outs, CPD & licensingConsultancy & Services

Description

If you have either a food allergy and must avoid certain foods like cow's milk, egg or peanut, or have Coeliac disease and have to have a gluten-free diet, eating out in restaurants can be difficult. In the UK, Food Standards Agency research into the preferences of more than 500 food allergic or intolerant consumers when eating out of the home found that:
●56% of food allergic/intolerant consumers value conversations with staff that explore uncertainty, unfamiliarity and a lack of knowledge/information to maximise safety and minimise risk.
●Improved confidence in allergen information leads consumers to eat out more frequently and increases the likelihood of them returning.
●Consumers desire full ingredient information shown for each dish.

Restaurants struggle with meeting the needs for food allergies and intolerances as food ingredients used in food preparation can contain hidden allergens, and front of house staff often lack knowledge about food allergies and can miscommunicate orders to chefs.

Through an Innovate-funded project (Grant no 51865), Professor Clare Mills and Dr Sorrel Burden are working with a social impact start-up, Zess, to develop two digital products to help consumers eating out of the home and help restauranteurs meet special dietary requirements. This will be achieved by building
●A consumer app enabling people with food allergies, intolerances or specific dietary preferences to find and book suitable restaurants.
●Menu management software for restaurants that provides detailed ingredient information.


Period1 Oct 202030 Sep 2021
Work forZess.co, United Kingdom
Degree of RecognitionNational

Keywords

  • Food
  • Allergy
  • Machine Learning
  • Nutrition
  • Consumer choice
  • Eating-out

Research Beacons, Institutes and Platforms

  • Biotechnology