SriHealth: A Single Platform for Meal Plans, Workouts, Yoga Schedules Based on SriLankan Lifestyle

Abstract

Food is a fundamental piece of human existence. People have forgotten to follow good eating patterns and exercise goals because of today's fast-paced lifestyles, resulting in malnutrition, which has become one of the most serious public health issues in developing countries, including Sri Lanka. As a result, people are unable to adhere to a probable schedule to satisfy their desires intend for Sri Lankan cuisine. In this study, a mobile-based application named "SriHealth" is developed with an emphasis on Image Processing, Natural Language Processing (NLP), Classification and Regression in Machine Learning techniques. The results obtained show that for classification of food preferences identification produces high accuracy of 87% on Support Vector Machine (SVM) classifier, medical record breakdown comprises of 75% accuracy with Clustering through Logistic Regression, schedule provider consist of an 95% accuracy level in Naïve Bayes algorithm while the calorie counter provides an accuracy level of 73% in MobileNet. The proposed work would identify user food preferences and medical conditions, classify the user, provide the suitable meal plan, exercise and yoga plan schedule on their categorization, and measure the number of calories consumed while assisting them for a healthy life.