AQUAFAZE: AN AI-ENABLED FACE-IMAGE-BASED WATER REQUIREMENT PREDICTION

Abstract

Staying hydrated is essential for maintaining overall health and wellbeing. Water constitutes a significant percentage of body weight. Staying properly hydrated is important for various physiological functions and has a range of health benefits.  Therefore, it is important to consume an adequate amount of water daily. However, the specific needs of an individual may differ depending on the factors like age, gender, ethnicity, height, weight and the activity level. Even after knowing the importance of water intake, people do not take sufficient water, for which people suffer in dehydration where the body suffers from electrolytes imbalance and a reduction in blood volume. Dehydration, in severe cases, can also lead to heat exhaustion and heat stroke. Considering the importance of staying well hydrated, this work emphasizes on designing a Single face image-based Artificial Intelligence (AI) enabled water requirement prediction system, AQUAFAZE, where the user only needs to turn on his/ her device camera to predict the water requirement for that day. The proposed system can predict the age, gender, ethnicity, weight and height of an individual from the face image, and then using all these parameters, it predicts the hydration requirement of that person. In addition, the proposed system also predicts the excess water requirement for performing various activity for a certain duration. In absence of any such AI enabled single face image-based hydration prediction system, the performance of the proposed AQUAFAZE is compared with the conventional hydration prediction system, where a user needs to enter his/her age, gender, height and weight and based on that the system predicts some results. The comparative study also concludes that the proposed AQUAFAZE system can accurately predict the hydration requirement of a person from a single face image.