SLEEP QUALITY AND WELLNESS TRACKER USING PYTHON AND DATA SCIENCE

Fiza Fathima, M and jebathangam, j (2026) SLEEP QUALITY AND WELLNESS TRACKER USING PYTHON AND DATA SCIENCE. International Journal of Engineering Technology Research & Management (IJETRM), 10 (4). pp. 654-659. ISSN 2456-9348

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Abstract

Sleep is a vital component of overall health and well-being, influencing physical functioning, cognitive
performance, and emotional stability. However, modern lifestyle factors such as irregular schedules, increased
screen exposure, and elevated stress levels often lead to poor sleep quality and related health concerns. This
Sleep Quality & Wellness Journal is designed as a structured and systematic tool to monitor and evaluate
individual sleep patterns alongside daily lifestyle habits and mental and physical health indicators. The journal
enables users to record essential aspects of sleep, including duration, timing, interruptions, and perceived
quality, while also capturing influencing factors such as diet, physical activity, screen time, and pre-sleep
routines. In addition, it incorporates the assessment of emotional states, stress levels, energy, and overall
physical condition to provide a comprehensive understanding of how sleep interacts with daily wellness.
Through consistent daily entries, as well as weekly and monthly reviews, the journal facilitates the identification
of patterns, trends, and potential causes of sleep disturbances. By promoting self-awareness, reflection, and
disciplined tracking, this journal supports individuals in making informed lifestyle adjustments to improve sleep
quality and overall health. Although it relies on self-reported data and does not replace professional medical
guidance, it serves as an effective personal tool for fostering healthier habits, enhancing productivity, and
achieving long-term well-being.

Item Type: Article
Subjects: Computer Science Engineering > Computer Network
Domains: Computer Applications
Depositing User: Mr IR Admin
Date Deposited: 13 May 2026 02:36
Last Modified: 13 May 2026 02:36
URI: https://ir.vistas.ac.in/id/eprint/19247

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