Image Processing and Machine Learning Based Nutrition and Fitness Journaling System

People tend to lead a busy and stressful lifestyle with several responsibilities which makes them no time to be concerned about leading a healthy lifestyle which had led to most of the most common and serious non-communicable diseases including diabetes, cardiovascular diseases, and obesity worldwide with an increase in mortality rates. A lack of an easy and proper system to monitor and manage health has become a threat to the people in Sri Lanka. This had also affected the youth population with the rise of pandemic situations worldwide. Due to these reasons, there is a great demand for a proper nutrition and fitness journaling system especially during the pandemic situation that could be used without any physical meetups. The use of image processing and advanced machine learning algorithms for these systems are not very prominent which causes an enhanced urge for these systems. Four major components have been used in the proposed system to address this issue. These components include image processing with object detection to obtain body measurements which reduce the human errors caused by traditional methods where Waist to Hip ratio obtained from the body measurements is used to provide the health risk level to the users comparing the standard set of values which is an efficient method to identify the health conditions of the user, personalized workout recommendation system, personalized nutrient plan system and progress tracking and analysis system to track the progress of the users when using the system.