Big Lifestyle Data Analytics
Our Big Lifestyle Data (aka wellness) project aims to build an application that could track, gather and analyse users’ lifestyle data, comprising of what they eat, their exercise routines, and self-recording medical records. The key research topics include deep learning models for food image recognition; analysis of physical and cyber activities of users to derive users’ exercise habits and wellness profiles; construction of food, disease and wellness knowledge graphs, and deep lifestyle analytics. The data will be used to infer risks towards critical illnesses, and will be used as basis to recommend and influence users towards healthy lifestyle.
There are four key research tasks to be explored in this project.
1)Automated food recognition.
2)Development of knowledge graph linking food ingredients to nutrition and diseases, as well as their interactions.
3)Extraction of activities from users’ physical and cyber data.
4)Validation and deployment with core interest groups.