IoT's Role in Personalized Dietary Support for Mental Health using RNN Model
S. Subha, N. Mohankumar, Allanki Sanyasi Rao, A. Ayub Khan, Ishwarya M. V, S. Murugan
Abstract
Rapid developments in Internet of Things (IoT) technology have spawned new ways of thinking about the very important field of mental health and wellbeing. This abstract explores "Personalized Dietary Support," a new paradigm powered by the Internet of Things that aims to improve mental health outcomes by providing individualized dietary counseling. Individuals may get real-time insights into the dynamic interaction between their food choices, lifestyle, and mental well-being using data from IoT devices, such as wearables, nutritional trackers, and physiological sensors. Incorporating nutrient intake, meal timing, and dietary behaviors favorable to enhanced mental health, machine learning algorithms evaluate this data to provide tailored dietary recommendations. The IoT ecosystem also encourages user engagement through gamification and constant progress monitoring, which helps to keep users committed to their new eating habits over time. Working with medical experts, patients may care for their mental health from every angle. Recognizing the important importance of diet on mental health, this abstract investigates the possibility of IoT-driven Personalized Dietary Support to equip people with implementable methods. Data privacy and security are emphasized, as are patient autonomy and systemic approaches to healthcare.