Personalized Food Systems: The “dine-on-demand” Sector


An open data driven solution will be will prototyped in order  to enhance transparency and better inform consumer choices in the “dine-on-demand” sector. Based on given food recipes, the application will acquire data by users and will exploit nutritional, environmental and other data available in open databases, in order to inform consumers about the nutritional value and environmental footprint of the meals they order. Moreover, additional historical data like: consumers’ purchasing behavior, demand trends and location-aware orders, will also be considered. Sentiment analysis will be conducted in order to assess the sentiment expressed regarding certain food trends and habits as they become evident in social media. Aggregated data will be used in order to inform better selection of food ingredients and menu development. This will help to more accurately forecast the demand and therefore make ingredients purchases more efficient by harmonizing the composition of menus offered with consumer purchasing patterns. This is expected to generate further benefits such as improvement of nutritional value, reduction of food miles and waste, reduction of costs and increase in labor efficiency.

The main users of this pilot are consumers, stakeholders in the food and hotel sector (i.e restaurants and hotels).