(untitled) (International Journal of Food and Nutritional Sciences, 2021)
The rapid advancements in Internet of Things (IoT) technology have opened new possibilities in healthcare, particularly in personalized nutrition management. This paper presents an IoT-based real-time nutritional monitoring and management system utilizing smart sensors to enhance dietary habits and overall health. The proposed system integrates wearable and non-wearable sensors to continuously track key nutritional parameters, such as calorie intake, macronutrient distribution, and hydration levels. These sensors, embedded in everyday objects like utensils, food containers, and wearable devices, transmit real-time data to a centralized platform where it is processed using advanced algorithms. The system provides users with personalized dietary recommendations based on their health goals, dietary restrictions, and real-time nutritional intake. Furthermore, the system incorporates machine learning models to predict and suggest optimal dietary choices, taking into account the user’s medical history, activity levels, and preferences. This proactive approach to nutrition management aims to prevent diet-related health issues, such as obesity, diabetes, and cardiovascular diseases, by promoting healthier eating habits. The real-time aspect of the system ensures that users receive immediate feedback and can make informed decisions about their diet throughout the day. Additionally, the integration of cloud computing allows for secure data storage and easy access to historical nutritional data, enabling users and healthcare providers to track progress and adjust dietary plans as needed. The proposed IoT-based system represents a significant step towards more personalized, data-driven nutrition management, offering the potential to improve public health outcomes through smarter, real-time dietary monitoring and management.