BOUNCE – A Habit and Mood Tracker using Time-Series Analysis
Swathi S, S and Bharathi, A. (2026) BOUNCE – A Habit and Mood Tracker using Time-Series Analysis. JOURNAL OF ADVANCE AND FUTURE RESEARCH, 4 (5). pp. 875-887. ISSN 2984-889X
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Abstract
This project presents a Habit and Mood Tracking System designed to help users build consistency, improve
self-awareness, and monitor personal growth over time. The application has three main components: a habit
tracker, a mood tracker, and a daily reflection system. Users can create and manage habits, track daily
performance with status indicators like complete, fail, skip, and freeze, and visualize progress through
dynamic charts. Along with habit tracking, the system includes a mood analysis feature where users log daily
emotions using rating scales and categorized emotional tags. The application processes this data to show
monthly and yearly mood trends, as well as dominant emotional patterns. Additional features such as streak
tracking, freeze limits, analytics dashboards, notes, and a to-do list boost productivity and engagement. Built
with web technologies like HTML, CSS, JavaScript, and Chart.js, along with backend integration for
managing habit data, the system offers an intuitive and interactive user experience. The project aims to
combine productivity tracking with emotional awareness, providing a useful tool for personal development.
areas separately, resulting in a fragmented approach to self-improvement. This project aims to bridge that
gap by developing an integrated Habit and Mood Tracking Web Application that combines productivity
management with emotional analysis in a single platform.
The habit tracking component of the system is designed to help users build consistency and accountability
in their daily routines. It provides an interactive calendar interface where users can record the status of each
day for a selected habit. Each day can be categorized as completed, failed, skipped, or frozen, allowing
flexibility while still encouraging discipline. The system also incorporates advanced features such as streak
tracking, maximum streak records, and freeze limits, which motivate users to maintain long-term consistency.
Visual analytics, including bar charts, provide insights into performance by summarizing completed, failed,
and skipped days.In addition to habit tracking, the application includes a comprehensive mood tracking module that focuses
on emotional well-being. Users can log their daily mood using an intuitive emoji-based scale, supported by
selectable positive and negative emotional descriptors. This dual-layer input system allows for both quick logging and deeper emotional reflection. In the modern digital era, individuals are constantly striving to
improve productivity while also maintaining their mental and emotional well-being.
| Item Type: | Article |
|---|---|
| Subjects: | Computer Science Engineering > Data Science |
| Domains: | Computer Applications |
| Depositing User: | Mr IR Admin |
| Date Deposited: | 10 May 2026 12:01 |
| Last Modified: | 10 May 2026 12:01 |
| URI: | https://ir.vistas.ac.in/id/eprint/13770 |
