Development of Health Monitoring Application using Machine Learning on Android Platform

With the increasing busy urban population rates, corpulence rates are expanding too but at a disturbing rate. Individuals need to control their daily calorie consumption to stay away from corpulence and keep their body slender and healthy. Within this paper, an efficient method is suggested to classify food objects and to measure the calorie intake by recognizing a fruit and vegetable using object recognition and deep learning neural networks. A CNN-based food classification and food detection model is proposed using TensorFlow to estimate the number of calories; in an image of food taken; based on the average calorie value of each detected category. This paper is attempting to give a progressively proficient method and to begin with, it requires the top sight and side sight pictures of the nourishment being dissected. At that point, it is going to utilize Faster R-CNN in order to recognize the nourishment and adjustment item. Given that the application system is developed and designed in the android studios, One of the Classification Algorithms, random forest calculation algorithm is utilized to analyse and detect the data in the frame to decide the nourishment's form. In the wake of evaluating the volume of nourishment, the creators can at long last gauge the measure of calories.