BigO aims to redefine the way existing obesity-related policy strategies are designed and deployed in the European societies. It is envisioned as a valuable tool for the local Public Health Authorities by acting as an open platform for:
The collection of Big Data (e.g., accelerometry, geolocation, food pictures) from school aged children about their behavioural patterns. The BigO data pool will be analysed and combined with various online data (e.g., maps, registries and GIS) in order to extract information on the local environment of the children.
The creation of comprehensive models of the obesity prevalence dependence matrix through the association of the local environment, community behavioural patterns and local obesity prevalences.
The real-time visualisation of the system outcomes allowing evaluation of behavioural risk factor profiles and comparison with other individuals and populations.
The Public Health Authorities to evaluate their communities based on their stratified obesity prevalence risk, to plan health policies against obesity, to predict their efficiency in specific communities.