This project will integrate wearable-derived data on sleep, activity, and nutrition into an AI-powered adolescent health risk model. The system will detect early metabolic risk factors, such as insulin resistance, and deliver tailored school-based interventions supported by teachers, parents, and health professionals. Social determinants, family environment, and digital media use will be factored into personalised recommendations. The project will involve partnerships with schools, public health agencies, and technology providers to ensure national reach. Outputs include a validated risk prediction algorithm, a digital school health dashboard, and evidence-based recommendations for national adolescent health guidelines. 

Call for Partnerships:
We welcome partnerships with universities, health services, primary care networks, technology providers, government agencies, and community health organisations to provide data access, clinical expertise, digital health capacity, and co-funding for large-scale trials.