Nourishment Recommendation Framework for Children Using Machine Learning and Matching Algorithm

Food plays an important role in daily life and is related to our core existence. The food that we eat supplies nutriments to the body. A balanced diet full of essential vitamins and minerals in adequate amount will help an individual reach their full growth potential especially children because a proper diet results in an increase in the learning ability, stamina and strength. It even has a positive impact on their behavior. To offer an efficient method regarding food intake, in this paper, we proposed a Nourishment Recommendation Framework (NRF) where we take user input from children, analyze the data and finally an output is generated that presents an improved diet plan. It aims to provide children from 8-13 years with healthy meals according to their age, growth, gender and health records.