Deep Learning-based Implementation of Food Nutritional intake Tracking System using Convolution Neural Network Algorithm

Deep Learning-based Implementation of Food Nutritional intake Tracking System using Convolution Neural Network Algorithm.

Shobana¹, Vinayakam Dhilip Kumar².

• Assistant Professor, Department of CSE, Adhiyamaan College of Engineering, Hosur
• UG Scholar, Department of CSE, Adhiyamaan College of Engineering, Hosur

ABSTRACT- Nutrition is an important basis for the development of the human body. Malnutrition can lead to a weakening of the immune system, an increased risk of various diseases, and the development of poor physical and mental health. This project based on an in-depth study will automatically detect nutritious foods and create an accurate system in which we find that nutritional levels in the diet increase the level of nutritional or poor nutrition. Monitor nutrition in their diet and maintain daily health records. The quality of the nutrition is maintained on the website. The level of the elements should be compared to the site using the convolution neural network (CNN) algorithm. Collected databases should be reviewed after 7 days when food levels are healthy or nutritious. If the level of healthy eating is not good the methods try to eat more protein and fat and light sugars and walk or engage in less activity to stimulate your appetite. It is about building a healthy and balanced diet and is essential for a healthy lifestyle. The technology is useful in developing a daily diet plan aimed at recommending the most popular foods for the user, which can be eaten as soon as possible, and to satisfy one's daily nutritional needs

Keywords: Food nutrition detection, CNN algorithm.