Real-time food analysis using deep learning for Diabetes Self -Monitoring

Our proposed research is to create an algorithm capable of pre-evaluating diabetes patients’ meals before they consume them with the snap of a picture. We are attempting to accomplish this goal by employing AI, machine learning as well as computer vision for real-time analysis. Our goal is to analyse a users meal to return an accurate carb count and offer portion size adjustments to reduce their blood sugar fluctuations. By developing a model that uses these technologies, we believe we can create an algorithm that will revolutionize how diabetes patients manage their condition and allow users to maintain consistent and healthier blood sugar levels. This research will greatly benefit the partner organization as it will help accelerate the growth of development heavily on the technology side to bring this to a level where it can be commercialized to generate revenue and used by others.

Faculty Supervisor:

Naimul Khan


Liam Bell;Osama Muhammad;Muhammed Ashad Khan


Glucose Vision


Engineering - biomedical


Health care and social assistance


Ryerson University


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