A healthy lifestyle hinges on the fusion of a balanced diet and regular physical activity. This powerful combination is crucial not only for weight management but also for reducing the risk of chronic diseases like heart disease and cancer. Proper nutrition, rich in essential nutrients, serves as the foundation for the body’s optimal performance. Caloric intake, representing the energy stored within foods, is a key measure in maintaining energy levels. On average, individuals need around 2,000 calories a day to maintain their weight, although this varies with factors such as age, gender, and activity level.
With the onset of the COVID-19 pandemic, significant changes in daily routines have occurred, including irregular working hours and increased physical and mental stress. To address these disruptions, we propose a machine learning-driven platform designed to provide personalized recommendations for a healthy diet and yoga poses, customized based on an individual’s Body Mass Index (BMI).
Our Arogya system will leverage Decision Tree and Naive Bayes machine learning algorithms to generate tailored diet plans and yoga poses, helping individuals maintain physical and mental well-being. By inputting their height and weight, users can calculate their BMI, and the platform will deliver personalized recommendations through a web-based interface.
Watch the Arogya system in action! See how it generates personalized recommendations for diet and yoga poses based on user input.