The value of intelligent lifestyle intervention for T2D and its complications has been initially explored, but evidence-based support for the effectiveness of related AI risk prediction models and intervention models remains to be confirmed. The primary objective of this study is to verify the effectiveness of an AI model for predicting the risk of T2D complications based on phenotype, laboratory indicators and wearable device indicators, and to explore the effect and applicability of an intelligent lifestyle intervention model combining wearable devices and smartphones in preventing T2D complications.

Inclusion Criteria:

1. Confirmed diagnosis of Type 2 Diabetes;
2. Aged ≥ 18 years;
3. Able to accept the diabetes management model with AI-assisted management and wearable device monitoring;
4. Able to provide complete lifestyle records, including medical history, medication status, diet, exercise, etc.;
5. Fully understand the purpose, nature, and methods of the study, voluntarily participate in this study, accept a 3-month follow-up, and sign the informed consent form.

Exclusion Criteria:

1. Having severe mental illness or language barriers;
2. Suffering from malignant tumors;
3. Pregnant or lactating women;
4. Suspected active infections (such as active pulmonary tuberculosis, pneumonia, etc.);
5. Severe hepatic and renal insufficiency (alanine transaminase and/or aspartate transaminase > 3 times the upper limit of normal; estimated glomerular filtration rate < 15 mL/min/1.73 m²);
6. A history of definite major adverse cardiovascular events and/or revascularization and/or intravenous thrombolysis and/or endovascular thrombectomy;
7. Uncontrolled hyperthyroidism or hypothyroidism, pituitary-adrenal dysfunction, or other endocrine diseases;
8. Alcoholism or drug addiction;
9. Receiving insulin therapy;
10. Unable to accept new comprehensive intervention technologies for various reasons (such as personal beliefs, economic factors, etc.).