Smart Hydration Planning Based on Workout and Weather Data

Pina, Rebecca Santana De (2025) Smart Hydration Planning Based on Workout and Weather Data. Masters thesis, Dublin, National College of Ireland.

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Abstract

Hydration is essential for the proper functioning of the human body and essential for recreational athletes during physical exercise. However, many of these athletes lack access to personalized hydration strategies before and during workouts. While some smartwatches offer water intake reminders, these are often generic and not tied to workouts or individual physiological history. This project aims to fill the hydration gap for recreational athletes by developing a hydration assistant that provides personalized recommendations based on planned workouts, the user’s physical attributes (e.g., age, weight, gender), exercise duration, intensity, and weather data such as temperature. Unlike current solutions, which rely on smartwatches with expensive monthly subscriptions, this assistant uses machine models trained on a public and private exercise dataset, combined with sweat loss formulas and environmental information to estimate the athlete’s water needs. The system then provides recommendations through a web interface. This solution is suitable for beginner athletes who want to improve performance and avoid dehydration without the need for high-end smartwatches.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Chikkankod, Arjun UNSPECIFIED
Uncontrolled Keywords:	Hydration; Machine Learning; Fitness Technology; Exercise Planning
Subjects:	Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine > Personal Health and Hygiene
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	26 Aug 2026 10:24
Last Modified:	26 Aug 2026 10:24
URI:	https://norma.ncirl.ie/id/eprint/9656

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