Diabetes is becoming a major health problem all over the world. Diabetes is a long-life disease that leads to many complications such as kidney failure, high blood pressure, high cholesterol, heart diseases, blindness, stroke, and even death. Diabetic patients need to manage their disease to stay healthy by eating healthier, taking medicine as directed, taking care of their body, reducing stress, being active, and checking the blood sugar daily by using on body and/or home monitoring devices. Thus, to avoid diabetes complications, diabetic patients need to be early diagnosed, monitored, and assisted. This can be achieved by building a general, user friendly, smart, and reliable system. This paper presents a general semantic system relying on a modular ontology annotating the daily activities, food, symptoms, and diabetes patients in order to monitor the parameters related to diabetes patients and assist him/her to avoid medical crisis. This modular ontology is conceived using OWL language and inference engine (Pellet reasoner) in order to fill the gap between diabetic patients, medical staff, and daily life activities systems. Pre-evaluation scenarios are discussed to prove the efficiency of the proposed ontologies