Health Buddy: An Interactive Healthcare Monitoring and Recommendation System Using Machine Learning and Real-Time Data Integration (KEY IJP************137)

• Munnangi Suma Reddy,Riya,Akhila M V,Dovina Maria White

Abstract

The growing emphasis on health and fitness has led to the rapid advancement of digital solutions aimed at improving personal well-being. This paper introduces Health Buddy, an interactive healthcare system designed to monitor and analyze health parameters using advanced technologies. The system integrates user data such as weight, height, age, and activity levels to calculate Body Mass Index (BMI) and provide customized fitness recommendations. It further incorporates features such as diet planning, exercise suggestions, and activity tracking through integration with Google Fit for real-time updates.The system leverages machine learning algorithms to analyze dietary habits using image-based food classification and predicts calorie intake, enabling users to make informed nutritional choices. Additionally, the dashboard offers visual insights through graphs and charts, providing an intuitive understanding of user progress.The Health Buddy platform ensures user-friendly interaction by incorporating login and signup functionalities, including Google authentication for seamless access. The integration of an intelligent recommendation engine and an interactive dashboard makes it a comprehensive solution for health monitoring and planning. The research focuses on the systems design, implementation, and performance evaluation, highlighting its potential to enhance personalized healthcare.