Systems and methods for food analysis, personalized recommendations and health management

A computer-implemented method, comprising:

• obtaining food-related data from a plurality of different sources, wherein at least a portion of the food-related data is obtained using one or more automated web-crawlers that are configured to search Internet sources in a continuous manner and update the food ontology substantially in real-time, wherein the food-related data from the plurality of different sources comprises unstructured data;
• abstracting information from the food-related data, at a hardware-based processor of a food analysis system, using one or more algorithms comprising at least one machine learning algorithm to develop a food ontology, wherein the one or more algorithms comprise at least one of (1) a computer vision algorithm that comprises artificial intelligence (AI) deep learning or optical character recognition (OCR) capabilities, and (2) a statistical model, wherein the one or more algorithms are configured to convert the unstructured data to structured data and further map the structured data onto the food ontology, and wherein the food ontology comprises a graphical representation depicting the information relating to the plurality of different foods;
• displaying the graphical representation of the food ontology via a user interface on an electronic display;
• accessing the food ontology, at an insights and recommendation engine, to generate, based on blood glucose levels of a user, a personal nutrition recommendation;
• and
• displaying a graphical representation of the personal nutrition recommendation via the user interface on the electronic display.