Objectif
The increase in food safety information quantity (e.g. through online sources) and diversity (e.g. information from social networks vs. structured surveillance programmes), results into a need to adequately discover and display information about food threats in a way that is customized to the user’s specific context and environment, in a highly usable and integrated format. Foodakai would like to take advantage of the identified business opportunity by harmonizing and making more user-friendly the discovery of information on foodborne diseases, food alerts, outbreaks and recalls. We aim to innovate the way information is discovered today, by combining and harmonizing food product recall and foodborne disease data from various, heterogeneous and dynamic online sources. We plan to apply text and data mining techniques, as well as forecasting and other analytical models, so that Foodakai provides tailored tracking, alerting and warning capabilities to its users. It will also be designed in a way that can allow users to adapt and customise the presented information so that it matches their preferences and information needs in a highly professional way - which contrasts this app from previous one-size-fits-all solutions.
Champ scientifique
- engineering and technologyindustrial biotechnologybiomaterialsbioplasticspolylactic acid
- natural sciencescomputer and information sciencesdata sciencenatural language processing
- natural sciencescomputer and information sciencesdata sciencedata mining
- social scienceseconomics and businessbusiness and managementbusiness models
- engineering and technologyother engineering and technologiesfood technologyfood safety
Programme(s)
Régime de financement
SME-1 - SME instrument phase 1Coordinateur
3001 Heverlee Leuven
Belgique
L’entreprise s’est définie comme une PME (petite et moyenne entreprise) au moment de la signature de la convention de subvention.