Diabetes is the 6th leading cause of death in Canada, and affects over 3 million people; daily this number grows by 549 new cases. Diabetes patients often manage their condition via a combination of food intake and insulin. This method can cause blood glucose levels to fluctuate due to uncertainty in food portions consumed and can lead to severe illness. At Glucose Vision, our goal is to create a smartphone application capable of pre-evaluating diabetes patients’ meals before they consume themwith the snapof a picture. We are attempting to accomplish this goal by employing AI, machine learning as well as computer vision into our smartphone application. The first part of this project will be to assemble a dataset of foods tagged with nutritional informationthat can be used to train an image recognition algorithm. This will be the backend of the application allowing users to snap a photo of their meal and be displayed nutritional information such as a carbohydrate count based on their respective serving size. We will also require machine learning algorithms to make the meal information on specific foods such as homemade dishes more accurate and more personalized to the patient. By developing a model that uses these technologies, we believe we can create a smartphone application that will revolutionize how diabetes patients manage their condition and allow users to maintain consistent and healthier blood sugar levels.

Industry Partner(s):Glucose Vision

Academic Institution:Ryerson University

Academic Researcher: Khan, Naimul

Focus Areas: AI, Health

Platforms: Cloud, GPU