Precision Nutrition through Smart Wearable Technology Tailored Solutions for Personalized Health Enhancement

The increasing prevalence of obesity and sedentary lifestyles has become a pressing global health issue, prompting the need for effective interventions to promote healthier habits. In response, there has been a growing emphasis on utilizing technology-driven approaches, as demonstrated by the introduction of the NutriWear system. This innovative system aims to provide personalized recommendations for dietary plans by analysing data from smartwatches and pathological insights. Through the integration of wearable devices, web application, and data storage, NutriWear offers tailored guidance and insights to improve overall health and well-being. Employing various machine learning algorithms such as Random Forest, Decision Tree, Gaussian Naive Bayes, K-Means Clustering, and K-Nearest Neighbors, the system initially assesses their accuracy in generating precise and individualized dietary recommendations. Subsequently, based on the evaluation, NutriWear selects K-Nearest Neighbors (KNN) for its superior accuracy performance. By implementing KNN, the system ensures optimal health outcomes and addresses the challenges of obesity and sedentary lifestyles. Evaluation measures demonstrate the effectiveness of NutriWear in offering personalized dietary suggestions. In summary, NutriWear represents a notable advancement in personalized health management, providing practical strategies for enhancing health outcomes and addressing the challenges of obesity and sedentary lifestyles.